No retraction, correction or concern found when last checked on Oct 20, 2026.
The glycosylation in SARS-CoV-2 and its receptor ACE2
Yanqiu Gong, Suideng Qin, Lunzhi Dai and 1 more
Signal Transduction and Targeted Therapy · 2021 · Review · CC BY
doi:10.1038/s41392-021-00809-8
Abstract
Coronavirus disease 2019 (COVID-19), a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected more than 235 million individuals and led to more than 4.8 million deaths worldwide as of October 5 2021. Cryo-electron microscopy and topology show that the SARS-CoV-2 genome encodes lots of highly glycosylated proteins, such as spike ( S ), envelope ( E ), membrane ( M ), and ORF3a proteins, which are responsible for host recognition, penetration, binding, recycling and pathogenesis. Here we reviewed the detections, substrates, biological functions of the glycosylation in SARS-CoV-2 proteins as well as the human receptor ACE2, and also summarized the approved and undergoing SARS-CoV-2 therapeutics associated with glycosylation. This review may not only broad the understanding of viral glycobiology, but also provide key clues for the development of new preventive and therapeutic methodologies against SARS-CoV-2 and its variants.
Full text
From PubMed Central, U.S. National Library of Medicine, as current on Oct 20, 2026. Paragraph numbers are ours, so an answer can point at one.
Introduction
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus causing the coronavirus disease 2019 (COVID-19), which threatens human health and public safety.– SARS-CoV-2 virus is genetically closely related to SARS-CoV,– less deadly but far more transmissible.– It usually causes a lower respiratory tract infection, and the most common symptoms include fever, malaise, dry cough and shortness of breath, which can progress to severe acute respiratory syndrome and even multiple organ failure.– Epidemiology data show that the SARS-CoV-2 pandemic has resulted in more than 235 million confirmed infected cases and more than 4.8 million deaths worldwide as of October 5 2021 (https://covid19.who.int/), urgently calling for effective prevention and intervention therapeutics.– In-depth studies on viral infection and pathogenic mechanisms will help to find potential cures for COVID-19.–
Protein glycosylation is a process of post-translational or co-translational covalent attachment of glycans to the amino acid side chains of proteins.– Glycans, being linear or branched chains of monosaccharides, often have high solubility and conformational entropy, which regulates the protein folding, structures, and functions.– The SARS-CoV-2 is decorated by a large number of highly glycosylated proteins, and its glycosylation (both N-linked and O-linked) extensively affects host recognition,,, penetration, binding, recycling, and pathogenesis.– In this review, we have systematically introduced the methods for characterizing protein glycosylation, summarized the reported glycosylome of SARS-CoV-2 proteins and its receptor protein ACE2, described the potential biological functions of the glycosylation in SARS-CoV-2, and presented the approved and potential SARS-CoV-2 prevention and treatment theraputics associated with glycosylation.
Overview of protein glycosylation
Glycosylation is the most common protein post-translational modification (PTM) in virus.– Glycosylation not only promotes viral protein folding and subsequent trafficking,,, but also modulates their interactions with receptors and the following innate and adaptive immune response,– which affects the host recognition, viral replication, and infectivity.– The viruses choose the host cell biosynthetic pathway to produce their genetic and structural materials, and thus the glycosylation of viral proteins greatly depends on the host organelles and enzymes.,,, As the evolution of viruses, their glycosylome changes, which may cause huge impacts on the survival and transmissibility of the viruses.
N-glycosylation refers to the glycans attached to asparagine (Asn) residue., The glycan precursor (Glc3Man9GlcNAc2) containing three glucose (Glc), nine mannose (Man), and two N-acetylglucosamine (GlcNAc) is first synthesized in the membrane of endoplasmatic reticulum (ER)., Then, the glycan precursor is transported to the ER lumen for processing by adding monosaccharides. When the glycan is matured, it is added to Asn residue by the oligosaccharyltransferase (OST), and the nascent protein is formed. Next, other enzymes like mannosidases, glucosidases, sialyl-, fucosyl-, or galactosyl-transferases located at the ER-Golgi apparatus decorate the protein., N-linked glycans mainly simplifies into three types based on the structures, including oligomannose (2HexNAc), hybrid (3HexNAc), and complex-type (with more than 3HexNAc) N-glycan structures, (Fig. 1a).
O-glycosylation usually occurs on serine (Ser), threonine (Thr), and tyrosine (Tyr) residues,, and mucin-type O-glycosylation (N-acetylgalactosamine (GalNAc)-type) is most common in virus.,, In the O-glycosylation process, GalNAc monosaccharide is first transferred by GalNAc-transferases to Ser, Thr, or Tyr residue in the Golgi apparatus., The glycosyltransferases then decorate the O-linked glycans, of which eight core structures have been described (Fig. 1b). Core 1-4 are four common O-GalNAc glycan core structures in mammals,, while Core 1 and Core 2 prefer to exist in virus.–
Methods to characterize protein glycosylation
Mass spectrometry (MS)-based N-glycoproteomics has been widely adopted for both site- and structure-specific characterization of glycosylation.,,– Sample preparation, chromatographic separation, LC-MS/MS analysis and bioinformatics data analysis are the four key pipeline steps.–
Sample preparation (Fig. 2, left). Glycosylation analysis usually includes the characterization of glycan,– intact glycopeptide,– glycosite-containing peptide,, as well as intact glycoprotein.– During the sample preparation, glycan releasing enzymes (such as PNGase F for N-glycans),– protease (such as trypsin),– both glycan releasing and protease,, or no enzymatic approaches may be adopted.– Glycans usually need to be enriched by hydrophilic materials, such as porous graphitized carbon (PGC),, before MS analysis,– while intact glycopeptides can be analyzed by MS with or without enrichment, although the enrichment step is beneficial for deep characterization of glycopeptides with low stoichiometry.– Historically, chemical enrichment methods were adopted for both glycans and glycopeptides such as hydrazide chemistry,– boronic acid,,– etc. Hydrophilic interaction liquid chromatography (HILIC),,– lectin affinity chromatography,,, and graphitized carbon chromatography are the most widely adopted methods for enrichment of glycopeptides.,–
LC-MS/MS analysis (Fig. 2, middle). Before tandem MS/MS analysis, chromatographic separation can simplify the composition of glycans and glycopeptides. The underivatized native glycans are hydrophilic and usually separated by PGC columns,– while the permethylated glycans are hydrophobic and often separated by reversed-phase C18 chromatography., For the separation of glycosite-containing peptides and intact glycopeptides, the reversed-phase C18 chromatography,,– HILIC,– and PGC are also widely used., Moreover, cation-exchange chromatography (CEX),, size-exclusion chromatography (SEC),– and capillary electrophoresis (CE) are also applied to the separation step.–
The separated glycans or glycopeptides are then analyzed by tandem MS/MS with various dissociation methods,– (Fig. 2, middle). Because of the possible appearance of multiple putative glycosites on a single peptide and the frequent presence of structural isomers in glycans,, glycosite localization and glycan structure identification are the two major challenges in MS/MS analysis of both N- and O- glycosylation. A general workflow for the MS/MS analysis of intact glycopeptides are shown in Fig. 3 (note that this workflow is a stereotyped summarize of schemes for the identification of intact glycopeptides, which means many studies will not strictly follow this workflow). The N-glycosites can be localized by site-determining fragment ions from MS2 spectra, and structural isomers are distinguished with structure-diagnostic fragment ions of the N-glycan moieties. While O-glycosites, due to the frequent existence of three target amino acids (S/T/Y) and densely glycosylated adjacent sites, are much more difficult to be determined than N-glycosites.–
N-glycosites rigorously follow the motif rule of N-X-S/T/C (X represents any amino acid except proline),, and several other peculiar motif rules have been reported.,– Therefore, the methods for acquiring evident MS2 signals and the algorithms of parsing the MS2 data are necessary.–
A precise site-determination method for N-glycosites is to use paired b*/y* ions in the MS2 spectrum, where b* and y* ions respectively refer to peptide b and y ions with a connected GlcNAc residue (Fig. 3b). These b* and y* ions often appear with moderate abundance after the cleavage of glycopeptide precursor ions. Several detected b* or y* ions can narrow the possible area of N-glycan moiety and make it covers only one putative site so that the real N-glycosite can be determined.,,
Collision-based dissociation, such as collision induced dissociation (CID) and higher energy collisional dissociation (HCD), can cause peptide fragmentation (either glycosite-containing peptides or intact glycopeptides) and produce abundant b/y fragment ions. Electron-based dissociation, such as electron capture dissociation (ECD) and electron transfer dissociation (ETD), has the advantage of causing “gentle” dissociation of the peptide backbone without neutral loss of the N-glycan moiety, generating c/z ions. Ultraviolet photodissociation (UVPD), simultaneously including the features of both collision- and electron-based dissociation, provides comprehensive types of fragment ions. Selective fragmentation of either the peptide backbone or the N-glycan moiety can be achieved with the combination of different dissociation methods (such as ETD + CID) or different energies of the same dissociation method (such as high and low normalized collision energies of HCD).– In addition, combinatory dissociation methods such as combined EThcD and ETciD on Orbitrap mass spectrometers have also been applied.,
N-glycans on N-glycoproteins contain hundreds of compositions and more than ten thousand different structures in mammals. N-glycosylation occurring on an identical site of glycoprotein may have thoroughly different biological processes because of distinct monosaccharide compositions.– Even N-glycans sharing the same monosaccharide composition may have different functions due to the glycan structures,, indicating that the significant roles of N-glycan structures in regulating the functions of N-glycoproteins. Therefore, structure-specific characterization of N-glycans is urgently needed at both aspects of chemistry and biology. In general, tandem MS/MS analysis of intact N-glycopeptides is able to precisely identify peptide backbone sequences, N-glycosites as well as N-glycan compositions and structures., However, due to the limitation of MS analytical discernibility, some monosaccharide isomers are unable to be distinguished. For example mannose, galactose, and glucose are interpreted as hexoses in glycan compositions. Moreover, N-glycans with the same monosaccharide composition may as well form different structures with different amount of antenna and serial numbers of linked carbon atoms (β-1,2 or β-1,4 at α-1,3 core mannose, etc.).,,
To unambiguously discriminate the structural isomers, a pivotal series of fragment ions in MS2, herein named structure-diagnostic ions are required. This kind of ions are in fact the fragmented N-glycan A/B/C/X/Y/Z ions which can independently distinguish a specific structure from the structural isomers., N-glycan structures can be discriminate by detecting theoretical structure-diagnostic ions which are generated in silico relying on the theoretical N-glycan structure database created by the retrosynthetic strategy, and structures of intact N-glycopeptides are figured out by assigning N-glycan structures to peptide backbones.
Bioinformatics analysis (Fig. 2, right). For identifying intact glycopeptides from LC-MS data, two strategies of MS data acquisition have currently been adopted: data-dependent acquisition (DDA) and data-independent acquisition (DIA).– Most of the software and platforms for analyzing intact glycopeptides are designed to search against the spectra generated from DDA.– DDA focuses on the precursors with high intensity and specifically isolates them to form fragments and generate MS2 spectra.– Based on the DDA data, the method for identifying intact N- and O-glycopeptides, which consists of the following steps (the order of these steps may be rearranged in several platforms or software): (1) deducing peptide backbone by peptide fragment ions, (2) determining glycan mass by calculating the mass difference between deduced peptide backbone and intact glycopeptide precursor, (3) localizing glycosite by matching specific glycosite-containing ions, and (4) characterizing glycan composition or structure using glycan or glycan-containing fragment ions, is adopted by most of the software such as Byonic, pGlyco,, GPQuest, GPSeeker, O-pair Search in MetaMorpheus, MSFragger-Glyco, and StrucGP. In-silico digested theoretical peptide database or customized experimental peptide spectra library is used for the identification of peptide backbone of intact glycopeptide.
The characterization of glycans (especially N-glycans) by DDA can be achieved by several strategies (Fig. 3a), including (1) parsing N-glycan compositions using theoretical glycan composition database (for instance Byonic,,– which calculates the precise masses of glycans constructed by proper combinations of monosaccharides, giving the number of Hex, HexNAc, etc). These compositions together with their masses are then stored in the composition database and the exact masses of relevant theoretical fragment ions are also calculated and matched in the MS2 spectra for further characterization; (2) parsing N-glycan structures using theoretical structure database built by retrosynthesis rules (for instance GPSeeker), and (3) parsing N-glycan structures using de novo algorithm (for instance StrucGP). The first strategy only offers the information of monosaccharide composition, while the second and third strategies can provide N-glycan structure information. In particular, the second strategy uses structure-diagnostic ions to distinguish different theoretical structures from the same monosaccharide composition and provides the entire structure of each characterized N-glycan. In contrast, the third strategy sequentially matches a series of Y ions and complementary B ions to form an intact N-glycan structure (that is, de novo algorithm), and shows structures with high accuracy regardless of theoretical database. However, the third strategy may ambiguously distinguish symmetrical structures in some applications. StrucGP is the first search engine that adopts de novo algorithm to conduct structure-specific identification of intact glycopeptides.
The application of DIA to identify intact glycopeptides is still very young., Compared with the DDA strategy, DIA does not select specific precursors based on MS1 peak intensities. Instead, DIA collects all ions acquired in MS1 based on retention time and fragments these ions to generate MS2 spectra,, suggesting that LC-MS/MS data from DIA contains complete information of the sample rather than DDA data which only contains the information of peptides with high abundance. However, interpreting DIA data remains a challenge and needs more advanced algorithms such as machine learning., The techniques adopted to analyzing DIA data includes pre-building corresponding DDA data library and many other methods.,, As for the identification of intact glycopeptide using DIA strategy, SWATH-MS workflow has also been adopted, and the characterization of glycosylation has been achieved at the molecular levels of intact glycopeptide and glycan.,
Glycosylation of SARS-CoV-2 proteins
The aforementioned high-throughput detection and analysis of the structure and localization of protein glycans is a prerequisite for discovering and studying the function of glycosylation,,, which will lead to a better understanding of glycoprotein functions and the molecular mechanisms of infectious disease.,,–
SARS-CoV-2 is a positive-sense single-stranded RNA virus., Sequence analysis of SARS-CoV-2 isolates shows that the 30 kb genome at least encodes 29 proteins, including 4 structural proteins, 16 non-structural proteins (NSP1-NSP16), and 9 accessory factors (ORF3a, ORF3b, ORF6, ORF7a, ORF7b, ORF8, ORF9b, ORF9c, ORF10)., The NSPs involve in virus processing and replication,– while the structural proteins including spike (S), envelope (E), membrane (M), and nucleocapsid (N) are responsible for host recognition, binding, recycling, and pathogenesis.,–, According to the in silico topology, the majority of the encoded proteins are glycoproteins, although only four of them have been reported with their exact glycosites to date.
S protein
Among the structural proteins, S protein in SARS-CoV-2 is the only one with sequence variability >20% when compared with SARS-CoV. It is a trimeric transmembrane protein that composes of two functional subunits S1 and S2., The S1 subunit is responsible for host cell receptor binding, while S2 subunit is for membrane fusion., The total length of S protein is 1273 amino acids, and the receptor binding domain (RBD) is located in the region from amino acid 319 to 541 in S1 subunit. The receptor binding motif (RBM) that mediates the contact with the angiotensin-converting enzyme 2 (ACE2) receptor locates in the RBD from amino acid 437 to 507.,, The S protein can recognize and bind to ACE2 receptor as the primary host cell infection route. Therefore, S protein determines the infectivity and transmissibility of SARS-CoV-2 and is the major antigen and target of vaccination.,
S protein is a well-known glycoprotein, and the modified glycans shield about 40% of the protein surface of the S trimer, which functions as camouflage to humoral and cellular components of the host innate immune system. Compared with Middle East respiratory syndrome coronavirus (MERS-CoV) and SARS-CoV, the S protein of SARS-CoV-2 has a lower glycosylation density,,, indicating the S protein surface is more exposed and it is more effective in eliciting humoral immunity. Since the first report of 16 N-linked glycosites by cryo-electron microscopy (cryo-EM), the characterization of glycosylation of S protein becomes a hotspot.,,,,,– In total, 23 N-linked glycosites with high occupancy (mostly >95%) have been reported (Fig. 4).,,,,– In contrast, among all the O-linked glycosites, only two sites show relative high occupancy (Table 1).,,,,,,,– The S1 subunit has 13 putative N-glycosites (N17, N61, N74, N122, N149, N165, N234, N282, N331, N343, N603, N616, and N657) with the N-X-S/T (X ≠ P) sequon, one putative N-glycosite (N334) with the N-X-C (X ≠ P) sequon and two putative O-glycosites (T323 and S325), of which T323, S325, N331, N334, and N343 are located on RBD. The S2 subunit has 9 putative N-glycosites (N709, N717, N801, N1074, N1098, N1134, N1158, N1173, and N1194) with the N-X-S/T (X ≠ P) sequon.
Although the N-glycosites of S protein identified by different teams in different expressed systems are almost same, the glycan compositions and structures as well as their occupancy are distinct (Fig. 4). MS-based characterization of recombinant S protein expressed in human cells including human embryonic kidney (HEK) 293F cells and HEK 293 cells shows that the glycans on N234 and N709 are mainly oligomannose-type.,,,, Complex-type glycans can be predominantly found at N17, N74, N149, N165, N282, N331, N343, N616, N657, N1098, N1134, N1158, N1173, and N1194 residues, while six positions including N61, N122, N603, N717, N801, and N1074 are modified by a mixture of oligomannose- and complex-type glycans. Notably, the most common oligomannose-type glycan is Man5GlcNAc2. More than half of these N-linked glycans are fucosylated, and highly processed sialylated complex-type glycans can be predominantly found on the residues of N165, N282, N801, N1074, and N1098, (Fig. 5). By using energy-optimized LC–MS/MS method, glycoforms including the LacdiNAc and polyLacNAc structural motifs have been revealed on N-glycans of S protein expressed in the HEK293 expression system., Moreover, a recent quantitative N-glycan analysis on protein of S1 subunit purified from SARS-CoV-2 infected Calu-3 cells by immunoaffinity purification showed that the complex-type N-glycans (79%) with 21% oligomannose and/or hybrid structures predominate. In addition to the diverse N-linked glycans of S protein identified by MS, the N-linked glycan structures of RBD of S glycoprotein expressed in human HEK293F cells have been characterized by nuclear magnetic resonance (NMR) spectroscopy, which avoids sample digestion and derivatization. A lot of glycan structures missed in MS-based approaches have been disclosed. Besides the expected N-acetyllactosamine (LacNAc), 3′SLN (3′SLacNAc), and 6′SLN (6′SLacNAc) terminal moieties at the glycans of N331 and N343, the unprecedented structures such as LeX (LewisX), LDNF (LeX and fucosylated lacdiNAc), and 6′SLDN (6’SLacdiNAc) were also identified.
The distinct types of N-linked glycans of S protein in different expression systems are proposed to be determined by the differential processing of N-glycans among different species, rather than the location of glycosites., Different from that in human cell expression system (Fig. 4a),,,,,–, the N-linked glycans of recombinant S protein obtained from insect cell expression system are most high mannose-type,,, (Fig. 4b). It is worth noting that besides the N331 and N343 in the RBD, glycosylation at N334 has also been detected in recombinant S protein expressed from Spodoptera frugiperda (Sf9) cells with low occupancy, which is consistent with the report of an N-X-C motif exhibiting substantial N-glycosylation (Fig. 4b). Interestingly, compared with the recombinant S protein in insect cells, native S protein has lower levels of oligomannose-type glycans and high levels of complex-type glycans (Fig. 4c). These studies collectively generated a comprehensive N-glycosylation map of the S protein, and all the identified structures are plotted in Fig. 5.,,,,,,–,,,–,
The N-linked glycosites of S protein have diverse functions (Fig. 6). N165 and N234 are located near the RBD., N-linked glycosylation at N234 is largely accessible to α-1,2-mannosidases and can regulate the conformational dynamics of RBD. Deletion of the glycans through N165A and N234A mutations significantly changed the RBD conformational shift towards to the “down” state (presenting a receptor-inaccessible state) and reduced the binding to ACE2, which suggests that the glycosylation at N165 and N234 may promote host recognition. Moreover, N282, N331, and N343 are also proximal glycosites that shield the receptor binding sites of S protein, especially the RBD in the “down” state.,,, Besides the involvement of these glycosites in the binding of SARS-CoV-2 to the receptor, these glycosites also affect the sensitivity of viruses to neutralizing antibodies. For example, N234Q mutation can significantly decrease the sensitivity to neutralizing antibodies, whereas N165Q and N709Q mutations increase the sensitivity. In addition, N149Q, N331Q, and N1173Q mutations also dramatically increase the sensitivity to convalescent sera,,, indicating the influence of glycans in epitopes targeted by neutralizing antibodies (Fig. 6). The glycosylation is also important for virus virulence and viral infection. When the glycosylation at N122, N331 with N343, N717, N801, and N1074 of S protein are inhibited by mutations, the viral infectivity of SARS-CoV-2 is significantly reduced, (Fig. 6). The polybasic cleavage site (RRAR) at the junction of S1 and S2 subunits is one notable feature of SARS-CoV-2, which is not observed in SARS-CoV., The RRAR can be cleaved by furin or other proteases and play important roles in determining viral fusion, entry and pathogenesis.,, The N-glycosylation at N61, N603 and N657 is proximal to the furin-site and able to increase the steric hindrance for cleavage, which seems to be beneficial to SARS-CoV-2 entry (Fig. 6). Different from being cleaved by proteases, computational saturation mutagenesis of N616 and N1134 residues increases the stability of S protein, which may be associated with glycosylation; however this phenotype needs experimental confirmation (Fig. 6). 3D structural modeling of glycosylated SARS-CoV-2 trimmer S protein disclosed the micro-heterogeneity of N-glycosites. The glycans at N74 and N165 residues of S protein interact with ACE2 receptor glycan at N546 residue and thus modulate Spike-ACE2 interactions, suggesting that the changes of glycans occupancy may affect the affinity and alter the infectivity (Fig. 6).
Besides the N-glycosites, a large number of putative O-glycosites have also been found in S protein (Table 1). Among them, the levels of O-glycosylation at T323 and S325 are relative higher, while the glycosylation of other O-glycosites are in low occupancy.,,,,,– The O-glycans identified on O-glycosites of S protein and RBD from human cells as well as deduced O-glycan structures were summarized,,,,,,–,– (Table 2, Table 3). O-linked glycans such as Core-1, disialylated Core-1, Core-2, mucin-type, and sialylated mucin type are reported on the recombinant S protein.
Although various O-glycosites have been identified, their functions remain largely unknown. Similar to N-glycosylation, the functions of O-glycosylation of S protein are also very important. More than 60% O-glycosites located close to N-glycosites may suggest the possible complementary functions of O-glycans in immune shielding. The furin cleavage site is unique to the SARS-CoV-2 S protein compared to SARS-CoV. The O-glycosylation at T678, adjacent to the polybasic furin cleavage site, carries Core-1 and Core-2 structures capped primarily with α2–3 sialic acid, which may suggest that cleavage is potentially regulated by the nearby O-glycans., Mutation of N616 abolished the O-glycosylation at T618 indicates that N-glycosylation at N616 is the prerequisite of N-sequon-related O-glycosylation, which obeys an “O-Follow-N rule”. T323 and S325 residues are two conserved O-glycosites in the RBD of S1 subunit, which may play important roles in mediating Spike-ACE2 binding.,, Compared with SARS-CoV, S494 is one of the six mutations on the RBD of S protein encoded by SARS-CoV-2. Attachment of the O-glycans to S494 can increase the binding affinity of virus to ACE2. The predicted O-linked glycosylation residues at S673, T678 and S686 are near the RRAR position,, implying their potential functions in virus penetration.,,
E protein
E protein is a small integral membrane protein of 8–12 kDa in SARS-CoV-2, and functions in viral assembly, release and pathogenesis.– It comprises of three domains, including a short hydrophilic N-terminus domain, a hydrophobic transmembrane domain and long hydrophilic C terminal region., Previous studies showed that E proteins in many coronaviruses can form pentameric structures exhibiting cation selective channel activity,– which is critical for viral infectivity, and Ca2+ conductivity in the ER-Golgi intermediate compartment. Based on the sequence prediction, two putative N-linked glycosites may exist in the transmembrane segment of E protein at positions N48 and N66 (Fig. 7a). Probably due to the proximity of the residue to the membrane, residue N48 is difficult to be glycosylated. In contrast, N66 is found to be modified with oligomannose-type glycans. Mutation of residue N66 can promote the resembling of dimers and trimers of E protein which is required for virion assembly, while the monomer may function in disruption of the host secretory pathway.
M protein
M protein is the most abundant envelope protein of SARS-CoV-2 that contains 222 amino acids., It comprises of three N-terminal transmembrane domains, and is essential for the assembly of virus particles by interacting with other three structural proteins of SARS-CoV-2.– Similar to E protein, the glycosylation of M protein has not yet been extensively studied and characterized. In silico computation and simulation has revealed the topology of M proteins from different coronaviruses and predicted eight N-glycosites including N5, N21, N41, N43, N117, N121, N203, and N216 were predicted (Fig. 7b). The functions of these N-linked glycosylation remain to be studied.
ORF3a protein
The non-structural proteins of human coronaviruses are indispensable for viral replication and transcription., ORF3a is a non-structural protein of SARS-CoV-2 localized at the surface. It is the largest accessory factor that contains 274 amino acids, and shows broad functions,, such as enhancing viral entry within the host, regulating the pro-inflammatory cytokine and chemokine production, participating in ion channel formation as well as modulating release of virus from the host cell. According to the hydrophobicity analyses and topology studies, there may be four O-linked glycosites at S27, T28, T32 and T34 residues,, with higher O-glycosylation occupancy at T28 and T32 residues; N-glycosylation is absent in ORF3a protein (Fig. 7c). The functions of these O-linked glycosylation remain to be investigated.
Glycosylation of human target protein ACE2
The severity of SARS-CoV-2 infection varies greatly among individuals. One possible reason may be due to the different expression of SARS-CoV-2 receptor. ACE2 is the main human receptor of SARS-CoV-2., It is expressed on the membrane of cells located in many organs (such as heart, kidney, and intestines) and is a promising drug target., Besides expression difference, glycosylation on ACE2 also affects the SARS-CoV-2 entry and infectivity. In the recombinant ACE2 protein from HEK293 cells, 7 N-glycosites and 2 O-glycosites have been identified (Fig. 8). The majority of glycans at N53, N90, N103, N322, N432, N546, and N690 residues of ACE2 are of complex-type, always with >75% occupancy, and the sialic acid linkage always exist in the glycans.,, The sialic acid was previously identified to serve as an attachment factor for a number of coronaviruses including MERS-CoV, transmissible gastroenteritis virus, human coronavirus (HCoV)-OC43, and HCoV-HKU1., The sialic acids present on ACE2 substantially block infection of SARS-CoV; however, the block effect is much smaller in the case of SARS-CoV-2. In particular, N-glycosylation at residues N90, N322, and N546 of ACE2 play critical roles in the binding of ACE2 with RBD of S protein. Mutation of N90 residue increases the binding affinity to S protein, indicating N90 glycosylation can protect host cells against viral infection. Atomistic molecular dynamics (MD) simulations show that N322 glycan binds to the core region of RBD of S protein from amino acid 369 to 378., The interaction between RBD and N322 residue of ACE2 is much stronger than that between RBD and N90 residue of ACE2. Besides, the antibody (CR3022) obtained from SARS-CoV infected patients has a binding site that overlaps remarkably with that of the N322 glycan, suggesting the N322 glycosylation may affect viral infection. Moreover, MD simulations show that N546 residue involves in the glycan-glycan interactions with S protein at N74 and N165. Of the two identified O-glycosites of ACE2, the stoichiometry of glycosylation at S155 is extremely low, and the function remains elusive. T730 residue is distal to the binding interface between S protein and ACE2, and the Core-1 mucin type O-glycan GalNAcGalNeuAc2 is the predominant glycan on it. It is speculated that the massive hydrophilic glycosylation at T730 in the juxtamembrane region outside the cell membrane may affect the dimerization and the presentation of ACE2 on the cell surface.
Therapeutic strategies for COVID-19 associated with glycosylation
As of 5 April 2021, there are 216 vaccines and 506 therapeutic drugs at different development stages for COVID-19. Among them, 92 vaccines and 419 therapeutic drugs are undergoing clinical trials, and 122 vaccines and 87 therapeutic drugs are in preclinical development (https://biorender.com/covid-vaccine-tracker). Influence of site- and structure-specific glycosylation on infectivity and immune escape is one of the key factors for vaccine development.,, The efficacy of some vaccines and therapeutic drugs may be closely associated with glycosylation (Table 4).
Neutralizing antibodies
The neutralizing antibodies are one the most important specific defense against viral infection.,, Antibodies that specifically target viral proteins can block the interaction between the virus and the host cell, thereby preventing the virus entry for replication., By high-throughput single-cell sequencing of COVID-19 patients’ B cells, potential SARS-CoV-2 neutralizing antibodies have been found from convalescent patients such BD23-Fab. Glycosylation at the N165 of S protein can facilitate the binding of BD23-Fab to the RBD. S protein has highly conserved glycosylation patterns between SARS-CoV and SARS-CoV-2, the antibodies bound to glycopeptide epitopes of SARS-CoV are critical for the screening of monoclonal antibody (Mab) to treat SARS-CoV-2, such as MAb S309 that has been isolated from SARS-CoV patient targeting an epitope containing a glycan at N343.,, Notably, the antibodies isolated from patients recovering from SARS-CoV, such as the monoclonal antibodies VIR-7831 (Phase II clinical trial), VIR-7832 (Phase I/II clinical trial) and their parent antibody (S309), can also effectively neutralize SARS-CoV-2 in vivo and in vitro.– Besides the antibodies from the recovered patients, natural antibodies formed spontaneously without specific immunization may also be very useful for SARS-CoV-2 treatment., GalNAc-O-Ser/Thr (Tn antigen) and Gal-GalNAc-O-Ser/Thr (T antigen) are well-known natural antigens and associated with the pathogenesis of many diseases.– Compared to non-infected individuals, the anti-Tn antibodies level in COVID-19 patients are significantly lower, suggesting that natural anti-Tn antibodies may be protective against COVID-19. In addition, the HIV-1 Env Fab-dimerized glycan (FDG)-reactive antibodies are an anti-glycan antibody that recognize high mannose glycans of SARS-CoV-2, indicating the potential prospects of these natural antibodies in SARS-CoV-2 treatment.
Vaccines
Vaccination is the most effective long-term strategy for the prevention and control of COVID-19., Vaccines, such as inactivated vaccines,– DNA plasmid vaccines,, adenovirus-vectored vaccines,, RNA vaccines,, protein subunit vaccines,, and virus-like particle vaccines,, have been developed. In the protein subunit vaccines, the RBD of S glycoprotein is an ideal immunogen.,, Because of the existence of glycosites in the immunogenic epitope of the virus, the immunogenic epitopes masked by glycosylation may not be recognized by the host, thus leading to immune escape of the virus. By mapping the glycosites on the complex structure of the RBD bound to ACE2, it is found that most glycosites are located in the RBD core subdomain and distant from the bound ACE2, indicating that glycans on RBD may not affect receptor recognition and/or binding. In addition, the viral glycans are also important immunogens., The complex N-glycans such as GlcNAc2-4-Man3-GlcNAc2-Asn in N74, N149, N282, N801, N1074, and N1098 of S protein,,, as well as oligomannose-type glycan Man5-GlcNAc2 in N234 may be suitable immunogens for developing vaccines.,,,,
Other drugs
Lectins are carbohydrate-binding proteins binding to sugar groups, and have potent antiviral properties through preventing the attachment of virus to host cell.,, FRIL is a lectin isolated from hyacinth beans and serves as an antiviral agent by blocking the complex-type N-glycans against SARS-CoV-2. Griffithsin, a red-alga-derived lectin, is in phase I clinical trial for the treatment HIV infection and also is promising for the treatment of COVID-19 by binding to the oligosaccharides on the surface of viral glycoproteins.– Other lectins such as Clec4g and CD209c can also bind to the N-glycans of S protein and interfere the Spike-ACE2 interaction and reduce SARS-CoV-2 infection. Notably, Lentil lectin derived from Lens culinaris can bind specifically to oligomannose-type glycans and GlcNAc at the non-reducing end terminus of S protein, thus block the binding of ACE2 to S trimer, showing the strongly inhibit infection of SARS-COV-2, including epidemic variants B.1.1.7, B.1.351, and P.1.
The major cause of death by SARS-CoV-2 refers to the “cytokine storm”,,– which is featured as excess release of inflammatory cytokines, such as interleukin (IL)-1, tumor necrosis factor α (TNF-α), and IL-6. Galectin-3 (Gal-3), a member of β-galactoside-binding lectins that preferentially binds to N-acetyllactosamine moieties on glycoconjugates, showed a dramatic increase with cytokine storm., Inhibition of Gal-3 can reduce the releases of IL-1, TNF-α, and IL-6 from macrophages, suggesting Gal-3 inhibitor as a promising agent for COVID-19 treatment., Currently, the Gal-3 inhibitor TD139 is undergoing clinical trials for the treatment of COVID-19,, and other Gal-3 inhibitor such as GB1107,, belapectin (also called GR-MD-02) are under investigation.
Iminosugars, also called iminosaccharides, are the analogs of common sugars where an oxygen atom is replaced by a nitrogen atom in the ring of the structure. They are known to interfere with the N-linked glycosylation by inhibiting the α-glucosidase I and II enzymes on the ER,, thus affecting the interaction between viral glycoproteins and host receptor. Iminosugars such as Celgosivir, Castanospermine and the monocyclic UV-4 have been reported to prevent SARS-CoV-2-induced cell death and reduce viral replication, while Miglustat can lead to a dramatically decrease of the viral Spike protein of SARS-CoV-2. Other potential inhibitors with similar structures such as α-mannosidase inhibitors Kifunensine also show similar roles in reducing SARS-CoV-2 entry.,
DAS181 is a kind of inhaled bacterial sialidase that functions by removing sialic acid from the surface of epithelial cells, thus preventing attachment and subsequent infection by respiratory viruses., The sialic acid linkage always existed in the glycans of ACE2,,, suggesting the potential therapeutic effect of DAS181 in COVID-19 treatment. Currently, DAS181 is in phase III clinic trial for patients with severe COVID-19.
Perspectives
It is well-known that virus may alter the glycan coat on the viral surface to enhance the infectivity and affect immune recognition., With the rapid development of techniques for characterizing the glycans and the glycoproteins,, the biological functions and significance of glycans and glycoproteins of virus are disclosed, which broads the understanding of virus biology.,, As described above, both SARS-CoV-2 proteins (especially S and N proteins) and their receptor (ACE2) are densely glycosylated. The glycan masses on S protein, N protein and ACE2 are about 80 kDa, 13 kDa, and 30 kDa, respectively; the average mass of a single glycan is about 4 kDa, indicating that these proteins are glycosylated simultaneously on multiple sites, although other modifications, such as phosphorylation, may also contribute to the extra masses on the basis of the protein sequence. Characterization of glycosylation at the intact N-glycopeptide level with the assistance of state-of-the-art enrichment will deliver comprehensive glycosylation information (glycosite, glycan composition and structure) for single sites, the cross-talk between different glycosites as well as other PTMs previously missed., Adoption of protein enzymes (such as Glu-C, Asp-N other than trypsin or chymotrypsin) cutting less frequently occurring amino acids to produce larger and longer peptides, or no enzyme at all (i.e, the top-down method) may be an optional choice. However, delicate selective dissociation of peptide backbones and glycan moieties as well as versatile bioinformatics tools supporting interpretation of multiple modifications at a time needs to be developed in the future.
The evolution of SARS-CoV-2 is fast within the human population by gaining fitness-enhancing mutations, which may alter viral infectivity and disease severity, and escape the host immunity even in individuals who have been vaccinated. For example, mutation of D to G at the residue 614 (D614G) of S protein moderately increases the infectivity and transmissibility.,– Following the D614G mutation, N439K and Y453F mutations within the RBM of S protein appears in SARS-CoV-2 variants. These mutations not only enhance the binding affinity for the ACE2 receptor, but also reduce the therapeutic efficacy of neutralizing antibodies., SARS-CoV-2 Delta variant, also known as lineage B.1.617.2, is a variant of lineage B.1.617 of SARS-CoV-2. It has three mutations on S protein including T478K, P681R and L452R, which dramatically increases transmission and leads to antibody escape.– However, despite many SARS-CoV-2 variants appear, whether the mutations of SARS-CoV-2 variants would affect the glycosylation profile of SARS-CoV-2 is still less understood. Given the critical roles of glycosylation in host recognition, penetration, binding, recycling and pathogenesis, uncovering the glycosylome of SARS-CoV-2 variants may help to increase the understanding of viral biology and develop more effective vaccines and drugs for SARS-CoV-2 variants.
References 477
- 1.
Wang D, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. Jama. 2020;323:1061-1069.
Not in our library10.1001/jama.2020.1585
- 2.
Li Q, et al. The impact of mutations in SARS-CoV-2 spike on viral infectivity and antigenicity. Cell. 2020;182:1284-1294.e1289.
Not in our library10.1016/j.cell.2020.07.012
- 3.
Tay MZ, et al. The trinity of COVID-19: immunity, inflammation and intervention. Nat. Rev. Immunol. 2020;20:363-374.
Not in our library10.1038/s41577-020-0311-8
- 4.
Udugama B, et al. Diagnosing COVID-19: the disease and tools for detection. ACS Nano. 2020;14:3822-3835.
Not in our library10.1021/acsnano.0c02624
- 5.
Rajendran DK, et al. Systematic literature review on novel corona virus SARS-CoV-2: a threat to human era. Virusdisease. 2020;31:161-173.
Not in our library10.1007/s13337-020-00604-z
- 6.
Hu B, Guo H, Zhou P, Shi ZL. Characteristics of SARS-CoV-2 and COVID-19. Nat. Rev. Microbiol. 2021;19:141-154.
Not in our library10.1038/s41579-020-00459-7
- 7.
Rabaan AA, et al. SARS-CoV-2, SARS-CoV, and MERS-COV: a comparative overview. Infez. Med. 2020;28:174-184.
Not in our library
- 8.
Petrosillo N, et al. COVID-19, SARS and MERS: are they closely related? Clin. Microbiol. Infect. 2020;26:729-734.
Not in our library10.1016/j.cmi.2020.03.026
- 9.
Petersen E, et al. Comparing SARS-CoV-2 with SARS-CoV and influenza pandemics. Lancet Infect. Dis. 2020;20:e238-e244.
Not in our library10.1016/s1473-3099(20)30484-9
- 10.
Gates B. Responding to Covid-19 - a once-in-a-century pandemic? New Engl. J. Med. 2020;382:1677-1679.
Not in our library10.1056/nejmp2003762
- 11.
- 12.
Yang X, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir. Med. 2020;8:475-481.
Not in our library10.1016/s2213-2600(20)30079-5
- 13.
Lv, M. et al. Coronavirus disease (COVID-19): a scoping review. Euro Surveill. 25, 2000125 (2020).
Not in our library10.2807/1560-7917.es.2020.25.15.2000125
- 14.
Wu Z, McGoogan JM. Characteristics of and important lessons from the Coronavirus Disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the chinese center for disease control and prevention. JAMA. 2020;323:1239-1242.
Not in our library10.1001/jama.2020.2648
- 15.
Xu X, et al. Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2. Eur. J. Nucl. Med. Mol. Imaging. 2020;47:1275-1280.
Not in our library10.1007/s00259-020-04735-9
- 16.
Li LQ, et al. COVID-19 patients’ clinical characteristics, discharge rate, and fatality rate of meta-analysis. J. Med. Virol. 2020;92:577-583.
Not in our library10.1002/jmv.25757
- 17.
Huang C, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497-506.
Not in our library10.1016/s0140-6736(20)30183-5
- 18.
V’Kovski P, et al. Coronavirus biology and replication: implications for SARS-CoV-2. Nat. Rev. Microbiol. 2021;19:155-170.
Not in our library10.1038/s41579-020-00468-6
- 19.
Amanat F, Krammer F. SARS-CoV-2 vaccines: status report. Immunity. 2020;52:583-589.
Not in our library10.1016/j.immuni.2020.03.007
- 20.
- 21.
Mari, A. et al. Reply to Nikolaos Grivas, Sanchia Goonewardene, Wouter Everaerts, Nikolaos Kalampokis’s Letter to the Editor re: Andrea Mari, Riccardo Tellini, Francesco Porpiglia, et al. Perioperative and mid-term oncological and functional outcomes after partial nephrectomy for complex (PADUA Score ≥10) renal tumors: a prospective multicenter observational study (the RECORD2, Project). Eur Urol Focus. In press. 10.1016/j.euf.2020.07.004. Eur Urol Focus S2405-4569, 30306 (2020).
Not in our library
- 22.
- 23.
- 24.
Wenjie, L. et al. The mechanism of glycosylation in SARS-CoV-2 infection and application in drug development. Prog. Chem. 33, 524 (2020).
Not in our library
- 25.
Spiro RG. Protein glycosylation: nature, distribution, enzymatic formation, and disease implications of glycopeptide bonds. Glycobiology. 2002;12:43r-56r.
Not in our library10.1093/glycob/12.4.43r
- 26.
Spiro RG. Glycoproteins. Adv. Protein Chem. 1973;27:349-467.
Not in our library10.1016/s0065-3233(08)60451-9
- 27.
Hart, G. W. Glycosylation. Curr. Opin. Cell Biol.4, 1017–1023 (1992).
Not in our library10.1016/0955-0674(92)90134-x
- 28.
Pinho SS, Reis CA. Glycosylation in cancer: mechanisms and clinical implications. Nat. Rev. Cancer. 2015;15:540-555.
Not in our library10.1038/nrc3982
- 29.
Reily C, Stewart TJ, Renfrow MB, Novak J. Glycosylation in health and disease. Nat. Rev. Nephrol. 2019;15:346-366.
Not in our library10.1038/s41581-019-0129-4
- 30.
Shental-Bechor D, Levy Y. Effect of glycosylation on protein folding: a close look at thermodynamic stabilization. Proc. Natl Acad. Sci. USA. 2008;105:8256-8261.
Not in our library10.1073/pnas.0801340105
- 31.
Zhao X, Chen H, Wang H. Glycans of SARS-CoV-2 spike protein in virus infection and antibody production. Front Mol. Biosci. 2021;8:629873.
Not in our library10.3389/fmolb.2021.629873
- 32.
Chatterjee, S. K. & Saha, S. Biotechnology to Combat COVID-19 (IntechOpen, 2021).
Not in our library
- 33.
Shajahan, A. et al. Glycosylation of SARS-CoV-2: structural and functional insights. Anal. Bioanal. Chem. 1–15, 10.1007/s00216-021-03499-x (2021).
Not in our library10.1007/s00216-021-03499-x
- 34.
Casalino L, et al. Beyond shielding: the roles of glycans in the SARS-CoV-2 spike protein. ACS Cent. Sci. 2020;6:1722-1734.
Not in our library10.1021/acscentsci.0c01056
- 35.
- 36.
- 37.
Jennings BC, Kornfeld S, Doray B. A weak COPI binding motif in the cytoplasmic tail of SARS-CoV-2 spike glycoprotein is necessary for its cleavage, glycosylation, and localization. FEBS Lett. 2021;595:1758-1767.
Not in our library10.1002/1873-3468.14109
- 38.
Ramírez Hernández E, et al. The role of the SARS-CoV-2 S-protein glycosylation in the interaction of SARS-CoV-2/ACE2 and immunological responses. Viral Immunol. 2021;34:165-173.
Not in our library10.1089/vim.2020.0174
- 39.
Wang L, Wang L, Zhuang H. Profiling and characterization of SARS-CoV-2 mutants’ infectivity and antigenicity. Signal Transduct. Target Ther. 2020;5:185.
Not in our library10.1038/s41392-020-00302-8
- 40.
Zhao P, et al. Virus-receptor interactions of glycosylated SARS-CoV-2 spike and human ACE2 receptor. Cell Host Microbe. 2020;28:586-601.e586.
Not in our library10.1016/j.chom.2020.08.004
- 41.
Reis CA, Tauber R, Blanchard V. Glycosylation is a key in SARS-CoV-2 infection. J. Mol. Med. 2021;99:1023-1031.
Not in our library10.1007/s00109-021-02092-0
- 42.
Nunes-Santos CJ, Kuehn HS, Rosenzweig SD. N-glycan modification in Covid-19 pathophysiology: in vitro structural changes with limited functional effects. J. Clin. Immunol. 2021;41:335-344.
Not in our library10.1007/s10875-020-00905-4
- 43.
Schjoldager KT, Narimatsu Y, Joshi HJ, Clausen H. Global view of human protein glycosylation pathways and functions. Nat. Rev. Mol. Cell Biol. 2020;21:729-749.
Not in our library10.1038/s41580-020-00294-x
- 44.
Mariño K, Bones J, Kattla JJ, Rudd PM. A systematic approach to protein glycosylation analysis: a path through the maze. Nat. Chem. Biol. 2010;6:713-723.
Not in our library10.1038/nchembio.437
- 45.
Vigerust DJ, Shepherd VL. Virus glycosylation: role in virulence and immune interactions. Trends Microbiol. 2007;15:211-218.
Not in our library10.1016/j.tim.2007.03.003
- 46.
Sugrue RJ. Viruses and glycosylation: an overview. Methods Mol. Biol. 2007;379:1-13.
Not in our library10.1007/978-1-59745-393-6_1
- 47.
Carbaugh, D. L. & Lazear, H. M. Flavivirus envelope protein glycosylation: impacts on viral infection and pathogenesis. J. Virol. 94, e00104–20 (2020).
Not in our library10.1128/jvi.00104-20
- 48.
Tannous A, Pisoni GB, Hebert DN, Molinari M. N-linked sugar-regulated protein folding and quality control in the ER. Semin. Cell Dev. Biol. 2015;41:79-89.
Not in our library10.1016/j.semcdb.2014.12.001
- 49.
Sacks D, et al. Multisociety consensus quality improvement revised consensus statement for endovascular therapy of acute ischemic stroke. Int. J. Stroke. 2018;13:612-632.
Not in our library10.1177/1747493018778713
- 50.
- 51.
- 52.
- 53.
Bagdonaite I, Wandall HH. Global aspects of viral glycosylation. Glycobiology. 2018;28:443-467.
Not in our library10.1093/glycob/cwy021
- 54.
Rudd PM, et al. Glycosylation and the immune system. Science. 2001;291:2370-2376.
Not in our library10.1126/science.291.5512.2370
- 55.
- 56.
Cipollo JF, Parsons LM. Glycomics and glycoproteomics of viruses: Mass spectrometry applications and insights toward structure-function relationships. Mass Spectrom. Rev. 2020;39:371-409.
Not in our library10.1002/mas.21629
- 57.
- 58.
Stanley, P. et al. The Consortium of Glycobiology. 99–111 (Cold Spring Harbor Laboratory Press Copyright 2015–2017, 2015).
Not in our library
- 59.
Nascimento da Silva LC, et al. Exploring lectin-glycan interactions to combat COVID-19: lessons acquired from other enveloped viruses. Glycobiology. 2021;31:358-371.
Not in our library10.1093/glycob/cwaa099
- 60.
Hargett AA, Renfrow MB. Glycosylation of viral surface proteins probed by mass spectrometry. Curr. Opin. Virol. 2019;36:56-66.
Not in our library10.1016/j.coviro.2019.05.003
- 61.
- 62.
Zhang Y, et al. Site-specific N-glycosylation characterization of recombinant SARS-CoV-2 spike proteins. Mol. Cell. Proteomics. 2020;20:100058.
Not in our library10.1074/mcp.ra120.002295
- 63.
- 64.
Wadzinski TJ, et al. Rapid phenolic O-glycosylation of small molecules and complex unprotected peptides in aqueous solvent. Nat. Chem. 2018;10:644-652.
Not in our library10.1038/s41557-018-0041-8
- 65.
Mayr J, et al. Unravelling the role of O-glycans in influenza A virus infection. Sci. Rep. 2018;8:16382.
Not in our library10.1038/s41598-018-34175-3
- 66.
Chen N, Kong X, Zhao S, Xiaofeng W. Post-translational modification of baculovirus-encoded proteins. Virus Res. 2020;279:197865.
Not in our library10.1016/j.virusres.2020.197865
- 67.
Brockhausen, I. et al. The Consortium of Glycobiology (Cold Spring Harbor Laboratory Press Copyright, 2009).
Not in our library
- 68.
Brockhausen, I. & Stanley, P. in Essentials of Glycobiology (eds. A. Varki et al.) 113–123 (Cold Spring Harbor Laboratory Press, 2015).
Not in our library
- 69.
Bagdonaite I, et al. Global mapping of O-glycosylation of varicella zoster virus, human cytomegalovirus, and Epstein-Barr virus. J. Biol. Chem. 2016;291:12014-12028.
Not in our library10.1074/jbc.m116.721746
- 70.
Shajahan A, Supekar NT, Gleinich AS, Azadi P. Deducing the N- and O-glycosylation profile of the spike protein of novel coronavirus SARS-CoV-2. Glycobiology. 2020;30:981-988.
Not in our library10.1093/glycob/cwaa042
- 71.
Bagdonaite I, et al. A strategy for O-glycoproteomics of enveloped viruses-the O-glycoproteome of herpes simplex virus type 1. PLoS Pathog. 2015;11:e1004784.
Not in our library10.1371/journal.ppat.1004784
- 72.
Xiao KJ, Tian ZX. GPSeeker enables quantitative structural N-glycoproteomics for site- and structure-specific characterization of differentially expressed N-glycosylation in hepatocellular carcinoma. J. Proteome Res. 2019;18:2885-2895.
Not in our library10.1021/acs.jproteome.9b00191
- 73.
Wang Y, Tian ZX. New energy setup strategy for intact N-glycopeptides characterization using higher-energy collisional dissociation. J. Am. Soc. Mass Spectrom. 2020;31:651-657.
Not in our library10.1021/jasms.9b00089
- 74.
Wang Y, Xiao K, Tian Z. Quantitative N-glycoproteomics using stable isotopic diethyl labeling. Talanta. 2020;219:121359.
Not in our library10.1016/j.talanta.2020.121359
- 75.
Rosenbalm KE, et al. Glycomics-informed glycoproteomic analysis of site-specific glycosylation for SARS-CoV-2 spike protein. STAR Protoc. 2020;1:100214.
Not in our library10.1016/j.xpro.2020.100214
- 76.
Zhou D, Xiao K, Tian Z. Separation and detection of minimal length glycopeptide neoantigen epitopes centering the GSTA region of MUC1 by liquid chromatography/mass spectrometry. Rapid Commun. Mass Spectrom. 2020;34:e8622.
Not in our library10.1002/rcm.8622
- 77.
Xue B, Xiao K, Wang Y, Tian Z. Site- and structure-specific quantitative N-glycoproteomics study of differential N-glycosylation in MCF-7 cancer cells. J. Proteom. 2020;212:103594.
Not in our library10.1016/j.jprot.2019.103594
- 78.
Shen Y, Xiao K, Tian Z. Site- and structure-specific characterization of the human urinary N-glycoproteome with site-determining and structure-diagnostic product ions. Rapid Commun. Mass Spectrom. 2021;35:e8952.
Not in our library10.1002/rcm.8952
- 79.
Xu F, et al. Quantitative site- and structure-specific N-glycoproteomics characterization of differential N-glycosylation in MCF-7/ADR cancer stem cells. Clin. Proteom. 2020;17:3.
Not in our library10.1186/s12014-020-9268-7
- 80.
Tian, W. et al. O-glycosylation pattern of the SARS-CoV-2 spike protein reveals an “O-Follow-N” rule. Cell Res.31, 1123–1125 (2021).
Not in our library10.1038/s41422-021-00545-2
- 81.
Dang L, et al. Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry. Trends Anal. Chem. 2019;114:143-150.
Not in our library10.1016/j.trac.2019.02.009
- 82.
Hu H, et al. A review of methods for interpretation of glycopeptide tandem mass spectral data. Glycoconj. J. 2016;33:285-296.
Not in our library10.1007/s10719-015-9633-3
- 83.
Yu A, et al. Advances in mass spectrometry-based glycoproteomics. Electrophoresis. 2018;39:3104-3122.
Not in our library10.1002/elps.201800272
- 84.
Gaunitz S, Nagy G, Pohl NL, Novotny MV. Recent advances in the analysis of complex glycoproteins. Anal. Chem. 2017;89:389-413.
Not in our library10.1021/acs.analchem.6b04343
- 85.
Li, X. et al. Databases and bioinformatic tools for glycobiology and glycoproteomics. Int. J. Mol. Sci. 21, 6727 (2020).
Not in our library10.3390/ijms21186727
- 86.
Abrahams JL, et al. Recent advances in glycoinformatic platforms for glycomics and glycoproteomics. Curr. Opin. Struct. Biol. 2020;62:56-69.
Not in our library10.1016/j.sbi.2019.11.009
- 87.
Ruhaak LR, et al. Mass spectrometry approaches to glycomic and glycoproteomic analyses. Chem. Rev. 2018;118:7886-7930.
Not in our library10.1021/acs.chemrev.7b00732
- 88.
Lisacek F, et al. Databases and associated tools for glycomics and glycoproteomics. Methods Mol. Biol. 2017;1503:235-264.
Not in our library10.1007/978-1-4939-6493-2_18
- 89.
Peng, W. et al. MS-based glycomics and glycoproteomics methods enabling isomeric characterization. Mass Spectrom. Rev. 10.1002/mas.21713 (2021).
Not in our library10.1002/mas.21713
- 90.
Thaysen-Andersen M, Packer NH. Advances in LC-MS/MS-based glycoproteomics: getting closer to system-wide site-specific mapping of the N- and O-glycoproteome. Biochim. Biophys. Acta. 2014;1844:1437-1452.
Not in our library10.1016/j.bbapap.2014.05.002
- 91.
- 92.
Pujić, I. & Perreault, H. Recent advancements in glycoproteomic studies: Glycopeptide enrichment and derivatization, characterization of glycosylation in SARS CoV2, and interacting glycoproteins. Mass Spectrom. Rev. 10.1002/mas.21679 (2021).
Not in our library10.1002/mas.21679
- 93.
Domann PJ, et al. Separation-based glycoprofiling approaches using fluorescent labels. Proteomics. 2007;7:70-76.
Not in our library10.1002/pmic.200700640
- 94.
Tharmalingam T, et al. Strategies for the profiling, characterisation and detailed structural analysis of N-linked oligosaccharides. Glycoconj. J. 2013;30:137-146.
Not in our library10.1007/s10719-012-9443-9
- 95.
Pabst M, Altmann F. Glycan analysis by modern instrumental methods. Proteomics. 2011;11:631-643.
Not in our library10.1002/pmic.201000517
- 96.
Kolli V, Schumacher KN, Dodds ED. Engaging challenges in glycoproteomics: recent advances in MS-based glycopeptide analysis. Bioanalysis. 2015;7:113-131.
Not in our library10.4155/bio.14.272
- 97.
Wuhrer M, Catalina MI, Deelder AM, Hokke CH. Glycoproteomics based on tandem mass spectrometry of glycopeptides. J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 2007;849:115-128.
Not in our library10.1016/j.jchromb.2006.09.041
- 98.
Desaire H. Glycopeptide analysis, recent developments and applications. Mol. Cell. Proteom. 2013;12:893-901.
Not in our library10.1074/mcp.r112.026567
- 99.
Sun S, Zhang H. Identification and validation of atypical N-glycosylation sites. Anal. Chem. 2015;87:11948-11951.
Not in our library10.1021/acs.analchem.5b03886
- 100.
Sun S, et al. Comprehensive analysis of protein glycosylation by solid-phase extraction of N-linked glycans and glycosite-containing peptides. Nat. Biotechnol. 2016;34:84-88.
Not in our library10.1038/nbt.3403
- 101.
Jacobs JF, Wevers RA, Lefeber DJ, van Scherpenzeel M. Fast, robust and high-resolution glycosylation profiling of intact monoclonal IgG antibodies using nanoLC-chip-QTOF. Clin. Chim. Acta. 2016;461:90-97.
Not in our library10.1016/j.cca.2016.07.015
- 102.
Haselberg R, de Jong GJ, Somsen GW. CE-MS for the analysis of intact proteins 2010-2012. Electrophoresis. 2013;34:99-112.
Not in our library10.1002/elps.201200439
- 103.
Unione L, et al. Glycoprofile analysis of an intact glycoprotein as inferred by NMR spectroscopy. ACS Cent. Sci. 2019;5:1554-1561.
Not in our library10.1021/acscentsci.9b00540
- 104.
Balaguer E, Neusüss C. Glycoprotein characterization combining intact protein and glycan analysis by capillary electrophoresis-electrospray ionization-mass spectrometry. Anal. Chem. 2006;78:5384-5393.
Not in our library10.1021/ac060376g
- 105.
Baerenfaenger M, Meyer B. Intact human alpha-acid glycoprotein analyzed by ESI-qTOF-MS: simultaneous determination of the glycan composition of multiple glycosylation sites. J. Proteome Res. 2018;17:3693-3703.
Not in our library10.1021/acs.jproteome.8b00309
- 106.
Grunow D, Blanchard V. Enzymatic release of glycoprotein N-glycans and fluorescent labeling. Methods Mol. Biol. 2019;1934:43-49.
Not in our library10.1007/978-1-4939-9055-9_4
- 107.
Tayi VS, Butler M. Isolation and quantification of N-glycans from immunoglobulin G antibodies for quantitative glycosylation analysis. J. Biol. Methods. 2015;2:e19.
Not in our library
- 108.
Mamedov, T. et al. A plant-produced in vivo deglycosylated full-length Pfs48/45 as a transmission-blocking vaccine candidate against malaria. Sci. Rep. 9, 1–12 (2019).
Not in our library10.1038/s41598-019-46375-6
- 109.
Sakayama K, et al. Glycosylation of lipoprotein lipase in human subcutaneous and omental adipose tissues. Biochim. Biophys. Acta. 1992;1127:153-156.
Not in our library10.1016/0005-2760(92)90271-v
- 110.
Morio, A. et al. Expression, purification, and characterization of highly active endo-α-N-acetylgalactosaminidases expressed by silkworm-baculovirus expression system. J. Asia Pac. Entomol.22, 404–408 (2019).
Not in our library
- 111.
Koutsioulis D, Landry D, Guthrie EPJG. Novel endo-α-N-acetylgalactosaminidases with broader substrate specificity. Glycobiology. 2008;18:799-805.
Not in our library10.1093/glycob/cwn069
- 112.
Pralow A, et al. Improvement of the glycoproteomic toolbox with the discovery of a unique C-terminal cleavage specificity of flavastacin for N-glycosylated asparagine. Sci. Rep. 2017;7:11419.
Not in our library10.1038/s41598-017-11668-1
- 113.
Chaze, T. et al. O-glycosylation of the N-terminal region of the serine-rich adhesin Srr1 of Streptococcus agalactiae explored by mass spectrometry. Mol. Cell. Proteomics13, 2168–2182 (2014).
Not in our library10.1074/mcp.m114.038075
- 114.
Bejugam M, Maltman BA, Flitsch SLJTA. Synthesis of N-linked glycopeptides on solid support and their evaluation as protease substrates. Tetrahedron Asymmetry. 2005;16:21-24.
Not in our library10.1016/j.tetasy.2004.11.031
- 115.
Vakhrushev, S. Y. et al. Enhanced mass spectrometric mapping of the human GalNAc-type O-glycoproteome with SimpleCells. Mol. Cell. Proteomics12, 932–944 (2013).
Not in our library10.1074/mcp.o112.021972
- 116.
Van Rooijen JJ, Voskamp AF, Kamerling JP, Vliegenthart JFJG. Glycosylation sites and site-specific glycosylation in human Tamm-Horsfall glycoprotein. Glycobiology. 1999;9:21-30.
Not in our library10.1093/glycob/9.1.21
- 117.
Bongers J, et al. Characterization of glycosylation sites for a recombinant IgG1 monoclonal antibody and a CTLA4-Ig fusion protein by liquid chromatography–mass spectrometry peptide mapping. J. Chromatogr. A. 2011;1218:8140-8149.
Not in our library10.1016/j.chroma.2011.08.089
- 118.
Tumurbaatar O, Yoshida T. Enzymatic digestion and mass spectroscopies of N-linked glycans in lacquer stellacyanin from Rhus vernicifera. Int. J. Polym. Sci. 2015;2015:547907-547909.
Not in our library
- 119.
van der Post S, Thomsson KA, Hansson GC. Multiple enzyme approach for the characterization of glycan modifications on the C-terminus of the intestinal MUC2mucin. J. Proteome Res. 2014;13:6013-6023.
Not in our library10.1021/pr500874f
- 120.
Keating CL, et al. Spontaneous glycan reattachment following N-glycanase treatment of influenza and HIV vaccine antigens. J. Proteome Res. 2020;19:733-743.
Not in our library10.1021/acs.jproteome.9b00620
- 121.
Zielinska DF, Gnad F, Wiśniewski JR, Mann M. Precision mapping of an in vivo N-glycoproteome reveals rigid topological and sequence constraints. Cell. 2010;141:897-907.
Not in our library10.1016/j.cell.2010.04.012
- 122.
Lopez Aguilar A, et al. Tools for studying glycans: recent advances in chemoenzymatic glycan labeling. ACS Chem. Biol. 2017;12:611-621.
Not in our library10.1021/acschembio.6b01089
- 123.
Yang S, et al. Deciphering protein O-glycosylation: solid-phase chemoenzymatic cleavage and enrichment. Anal. Chem. 2018;90:8261-8269.
Not in our library10.1021/acs.analchem.8b01834
- 124.
Stavenhagen K, Kolarich D, Wuhrer M. Clinical glycomics employing graphitized carbon liquid chromatography-mass spectrometry. Chromatographia. 2015;78:307-320.
Not in our library10.1007/s10337-014-2813-7
- 125.
She YM, et al. Resolving isomeric structures of native glycans by nanoflow porous graphitized carbon chromatography-mass spectrometry. Anal. Chem. 2020;92:14038-14046.
Not in our library10.1021/acs.analchem.0c02951
- 126.
Qing, G. et al. Recent advances in hydrophilic interaction liquid interaction chromatography materials for glycopeptide enrichment and glycan separation. TrAC Trends Anal. Chem.124, 115570 (2019).
Not in our library
- 127.
Chen L, et al. Hydrophilic interaction/cation-exchange chromatography for glycopeptide enrichment by using a modified strong-cation exchange material. Anal. Methods. 2013;5:6919-6924.
Not in our library
- 128.
Lewandrowski U, et al. Glycosylation site analysis of human platelets by electrostatic repulsion hydrophilic interaction chromatography. Clin. Proteom. 2008;4:25-36.
Not in our library
- 129.
Zhu R, et al. Glycoprotein enrichment analytical techniques: advantages and disadvantages. Methods Enzymol. 2017;585:397-429.
Not in our library10.1016/bs.mie.2016.11.009
- 130.
Zhu R, et al. Glycoproteins enrichment and LC-MS/MS glycoproteomics in central nervous system applications. Methods Mol. Biol. 2017;1598:213-227.
Not in our library10.1007/978-1-4939-6952-4_9
- 131.
Palmisano G, Larsen MR, Packer NH, Thaysen-Andersen M. Structural analysis of glycoprotein sialylation – part II: LC-MS based detection. RSC Adv. 2013;3:22706-22726.
Not in our library
- 132.
Hägglund P, et al. A new strategy for identification of N-glycosylated proteins and unambiguous assignment of their glycosylation sites using HILIC enrichment and partial deglycosylation. J. Proteome Res. 2004;3:556-566.
Not in our library10.1021/pr034112b
- 133.
Merkle RK, Cummings RD. Lectin affinity chromatography of glycopeptides. Methods Enzymol. 1987;138:232-259.
Not in our library10.1016/0076-6879(87)38020-6
- 134.
Lee WC, Lee KH. Applications of affinity chromatography in proteomics. Anal. Biochem. 2004;324:1-10.
Not in our library10.1016/j.ab.2003.08.031
- 135.
Chen CC, et al. Interaction modes and approaches to glycopeptide and glycoprotein enrichment. Analyst. 2014;139:688-704.
Not in our library10.1039/c3an01813j
- 136.
Deeb SJ, Cox J, Schmidt-Supprian M, Mann M. N-linked glycosylation enrichment for in-depth cell surface proteomics of diffuse large B-cell lymphoma subtypes. Mol. Cell. Proteom. 2014;13:240-251.
Not in our library10.1074/mcp.m113.033977
- 137.
Wiśniewski JR, Zielinska DF, Mann M. Comparison of ultrafiltration units for proteomic and N-glycoproteomic analysis by the filter-aided sample preparation method. Anal. Biochem. 2011;410:307-309.
Not in our library10.1016/j.ab.2010.12.004
- 138.
Qiu R, Regnier FE. Use of multidimensional lectin affinity chromatography in differential glycoproteomics. Anal. Chem. 2005;77:2802-2809.
Not in our library10.1021/ac048751x
- 139.
Jandera P. Stationary and mobile phases in hydrophilic interaction chromatography: a review. Anal. Chim. Acta. 2011;692:1-25.
Not in our library10.1016/j.aca.2011.02.047
- 140.
Lastovickova M, Strouhalova D, Bobalova J. Use of lectin-based affinity techniques in breast cancer glycoproteomics: a review. J. Proteome Res. 2020;19:1885-1899.
Not in our library10.1021/acs.jproteome.9b00818
- 141.
Zeng Z, et al. A proteomics platform combining depletion, multi-lectin affinity chromatography (M-LAC), and isoelectric focusing to study the breast cancer proteome. Anal. Chem. 2011;83:4845-4854.
Not in our library10.1021/ac2002802
- 142.
Xu Y, Zhang L, Lu H. Use of boronic acid nanoparticles in glycoprotein enrichment. Methods Mol. Biol. 2013;951:45-55.
Not in our library10.1007/978-1-62703-146-2_4
- 143.
Mysling S, Palmisano G, Højrup P, Thaysen-Andersen M. Utilizing ion-pairing hydrophilic interaction chromatography solid phase extraction for efficient glycopeptide enrichment in glycoproteomics. Anal. Chem. 2010;82:5598-5609.
Not in our library10.1021/ac100530w
- 144.
Sun N, et al. Advances in hydrophilic nanomaterials for glycoproteomics. Chem. Commun. 2019;55:10359-10375.
Not in our library10.1039/c9cc04124a
- 145.
Huang, J. et al. Simultaneous enrichment and separation of neutral and sialyl glycopeptides of SARS-CoV-2 spike protein enabled by dual-functionalized Ti-IMAC material. Anal. Bioanal. Chem. 1–9, 10.1007/s00216-021-03433-1 (2021).
Not in our library10.1007/s00216-021-03433-1
- 146.
Nilsson J, et al. Enrichment of glycopeptides for glycan structure and attachment site identification. Nat. Methods. 2009;6:809-811.
Not in our library10.1038/nmeth.1392
- 147.
Huang T, Armbruster MR, Coulton JB, Edwards JL. Chemical tagging in mass spectrometry for systems biology. Anal. Chem. 2019;91:109-125.
Not in our library10.1021/acs.analchem.8b04951
- 148.
Taga Y, Kusubata M, Ogawa-Goto K, Hattori S. Development of a novel method for analyzing collagen O-glycosylations by hydrazide chemistry. Mol. Cell. Proteom. 2012;11:M111.010397.
Not in our library10.1074/mcp.m111.010397
- 149.
Zhang H, Li XJ, Martin DB, Aebersold R. Identification and quantification of N-linked glycoproteins using hydrazide chemistry, stable isotope labeling and mass spectrometry. Nat. Biotechnol. 2003;21:660-666.
Not in our library10.1038/nbt827
- 150.
- 151.
Bull SD, et al. Exploiting the reversible covalent bonding of boronic acids: recognition, sensing, and assembly. Acc. Chem. Res. 2013;46:312-326.
Not in our library10.1021/ar300130w
- 152.
Wang X, Xia N, Liu L. Boronic Acid-based approach for separation and immobilization of glycoproteins and its application in sensing. Int. J. Mol. Sci. 2013;14:20890-20912.
Not in our library10.3390/ijms141020890
- 153.
Selman MH, Hemayatkar M, Deelder AM, Wuhrer M. Cotton HILIC SPE microtips for microscale purification and enrichment of glycans and glycopeptides. Anal. Chem. 2011;83:2492-2499.
Not in our library10.1021/ac1027116
- 154.
Qing, G. et al. Recent advances in hydrophilic interaction liquid interaction chromatography materials for glycopeptide enrichment and glycan separation. TrAC Trends Analyt. Chem.124, 115570 (2020).
Not in our library
- 155.
Zhang C, et al. Evaluation of different N-glycopeptide enrichment methods for N-glycosylation sites mapping in mouse brain. J. Proteome Res. 2016;15:2960-2968.
Not in our library10.1021/acs.jproteome.6b00098
- 156.
- 157.
Ongay S, Boichenko A, Govorukhina N, Bischoff RJJ. Glycopeptide enrichment and separation for protein glycosylation analysis. J. Sep. Sci. 2012;35:2341-2372.
Not in our library10.1002/jssc.201200434
- 158.
Neue K, Mormann M, Peter-Katalinić J, Pohlentz G. Elucidation of glycoprotein structures by unspecific proteolysis and direct nanoESI mass spectrometric analysis of ZIC-HILIC-enriched glycopeptides. J. Proteome Res. 2011;10:2248-2260.
Not in our library10.1021/pr101082c
- 159.
Takegawa Y, et al. Simple separation of isomeric sialylated N-glycopeptides by a zwitterionic type of hydrophilic interaction chromatography. J. Sep. Sci. 2006;29:2533-2540.
Not in our library10.1002/jssc.200600133
- 160.
Morelle W, Michalski JC. Analysis of protein glycosylation by mass spectrometry. Nat. Protoc. 2007;2:1585-1602.
Not in our library10.1038/nprot.2007.227
- 161.
Stavenhagen K, Plomp R, Wuhrer M. Site-specific protein N- and O-glycosylation analysis by a C18-porous graphitized carbon-liquid chromatography-electrospray ionization mass spectrometry approach using pronase treated glycopeptides. Anal. Chem. 2015;87:11691-11699.
Not in our library10.1021/acs.analchem.5b02366
- 162.
Issaq HJ, et al. Separation, detection and quantitation of peptides by liquid chromatography and capillary electrochromatography. J. Chromatogr. A. 2009;1216:1825-1837.
Not in our library10.1016/j.chroma.2008.12.052
- 163.
Young C, et al. In-house packed porous graphitic carbon columns for liquid chromatography-mass spectrometry analysis of N-glycans. Front. Chem. 2021;9:653959.
Not in our library10.3389/fchem.2021.653959
- 164.
Mechref Y, et al. Quantitative glycomics strategies. Mol. Cell. Proteom. 2013;12:874-884.
Not in our library10.1074/mcp.r112.026310
- 165.
Veillon L, et al. Characterization of isomeric glycan structures by LC-MS/MS. Electrophoresis. 2017;38:2100-2114.
Not in our library10.1002/elps.201700042
- 166.
Vreeker GC, Wuhrer M. Reversed-phase separation methods for glycan analysis. Anal. Bioanal. Chem. 2017;409:359-378.
Not in our library10.1007/s00216-016-0073-0
- 167.
Gutierrez Reyes CD, et al. Glycomics and glycoproteomics: approaches to address isomeric separation of glycans and glycopeptides. J. Sep Sci. 2021;44:403-425.
Not in our library10.1002/jssc.202000878
- 168.
Ji ES, et al. Isomer separation of sialylated O- and N-linked glycopeptides using reversed-phase LC-MS/MS at high temperature. J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 2019;1110:101-107.
Not in our library10.1016/j.jchromb.2019.02.015
- 169.
Hage, D. S. et al. in Liquid Chromatography(Second Edition) (eds Salvatore Fanali, Paul R. Haddad, Colin F. Poole, & Marja-Liisa Riekkola) 319–341 (Elsevier, 2017).
Not in our library
- 170.
Chirita RI, et al. Investigations on the chromatographic behaviour of zwitterionic stationary phases used in hydrophilic interaction chromatography. J. Chromatogr. A. 2011;1218:5939-5963.
Not in our library10.1016/j.chroma.2011.04.002
- 171.
Zauner G, Koeleman CA, Deelder AM, Wuhrer M. Protein glycosylation analysis by HILIC-LC-MS of Proteinase K-generated N- and O-glycopeptides. J. Sep. Sci. 2010;33:903-910.
Not in our library10.1002/jssc.200900850
- 172.
- 173.
Kozlik P, Goldman R, Sanda M. Hydrophilic interaction liquid chromatography in the separation of glycopeptides and their isomers. Anal. Bioanal. Chem. 2018;410:5001-5008.
Not in our library10.1007/s00216-018-1150-3
- 174.
Royle L, et al. HPLC-based analysis of serum N-glycans on a 96-well plate platform with dedicated database software. Anal. Biochem. 2008;376:1-12.
Not in our library10.1016/j.ab.2007.12.012
- 175.
Guile GR, et al. A rapid high-resolution high-performance liquid chromatographic method for separating glycan mixtures and analyzing oligosaccharide profiles. Anal. Biochem. 1996;240:210-226.
Not in our library10.1006/abio.1996.0351
- 176.
Molnarova, K. & Kozlík, P. J. M. Comparison of different HILIC stationary phases in the separation of hemopexin and immunoglobulin G glycopeptides and their isomers. Molecules25, 4655 (2020).
Not in our library10.3390/molecules25204655
- 177.
Balog, C. I. et al. N-glycosylation of colorectal cancer tissues: a liquid chromatography and mass spectrometry-based investigation. Mol. Cell. Proteomics11, 571–585 (2012).
Not in our library10.1074/mcp.m111.011601
- 178.
Reiding, K. R. et al. High-throughput serum N-glycomics: method comparison and application to study rheumatoid arthritis and pregnancy-associated changes*[S]. Mol. Cell. Proteomics18, 3–15 (2019).
Not in our library10.1074/mcp.ra117.000454
- 179.
Zhu R, et al. Isomeric separation of N-glycopeptides derived from glycoproteins by porous graphitic carbon (PGC) LC-MS/MS. Anal. Chem. 2020;92:9556-9565.
Not in our library10.1021/acs.analchem.0c00668
- 180.
Stavenhagen, K. et al. N- and O-glycosylation analysis of human C1-inhibitor reveals extensive mucin-type O-glycosylation. Mol. Cell. Proteomics17, 1225–1238 (2018).
Not in our library10.1074/mcp.ra117.000240
- 181.
Lohrig K, Sickmann A, Lewandrowski U. Strong cation exchange chromatography for analysis of sialylated glycopeptides. Methods Mol. Biol. 2011;753:299-308.
Not in our library10.1007/978-1-61779-148-2_20
- 182.
Zhao Y, et al. Online coupling of hydrophilic interaction/strong cation exchange/reversed-phase liquid chromatography with porous graphitic carbon liquid chromatography for simultaneous proteomics and N-glycomics analysis. J. Chromatogr. A. 2015;1415:57-66.
Not in our library10.1016/j.chroma.2015.08.017
- 183.
Cai W, et al. Top-down proteomics of large proteins up to 223 kDa enabled by serial size exclusion chromatography strategy. Anal. Chem. 2017;89:5467-5475.
Not in our library10.1021/acs.analchem.7b00380
- 184.
Saraswat, M., Garapati, K., Mun, D. G. & Pandey, A. Extensive heterogeneity of glycopeptides in plasma revealed by deep glycoproteomic analysis using size-exclusion chromatography. Mol. Omics. 10.1039/d1mo00132a (2021).
Not in our library10.1039/d1mo00132a
- 185.
Alvarez-Manilla G, et al. Tools for glycoproteomic analysis: size exclusion chromatography facilitates identification of tryptic glycopeptides with N-linked glycosylation sites. J. Proteome Res. 2006;5:701-708.
Not in our library10.1021/pr050275j
- 186.
Kammeijer GS, et al. Dopant enriched nitrogen gas combined with sheathless capillary electrophoresis-electrospray ionization-mass spectrometry for improved sensitivity and repeatability in glycopeptide analysis. Anal. Chem. 2016;88:5849-5856.
Not in our library10.1021/acs.analchem.6b00479
- 187.
Amon S, Zamfir AD, Rizzi A. Glycosylation analysis of glycoproteins and proteoglycans using capillary electrophoresis-mass spectrometry strategies. Electrophoresis. 2008;29:2485-2507.
Not in our library10.1002/elps.200800105
- 188.
Khatri K, et al. Microfluidic capillary electrophoresis-mass spectrometry for analysis of monosaccharides, oligosaccharides, and glycopeptides. Anal. Chem. 2017;89:6645-6655.
Not in our library10.1021/acs.analchem.7b00875
- 189.
An HJ, Lebrilla CB. Structure elucidation of native N- and O-linked glycans by tandem mass spectrometry (tutorial). Mass Spectrom. Rev. 2011;30:560-578.
Not in our library10.1002/mas.20283
- 190.
Scott, N. E. et al. Simultaneous glycan-peptide characterization using hydrophilic interaction chromatography and parallel fragmentation by CID, higher energy collisional dissociation, and electron transfer dissociation MS applied to the N-linked glycoproteome of Campylobacter jejuni. Mol. Cell. Proteomics10, S1–S18 (2011).
Not in our library10.1074/mcp.m000031-mcp201
- 191.
Riley, N. M., Malaker, S. A., Driessen, M. D. & Bertozzi, C. R. Optimal dissociation methods differ for N- and O-glycopeptides. J. Proteome Res.19, 3286–3301 (2020).
Not in our library10.1021/acs.jproteome.0c00218
- 192.
Yin, X. et al. Glycoproteomic analysis of the secretome of human endothelial cells. Mol. Cell. Proteomics12, 956–978 (2013).
Not in our library10.1074/mcp.m112.024018
- 193.
Prien JM, et al. Differentiating N-linked glycan structural isomers in metastatic and nonmetastatic tumor cells using sequential mass spectrometry. Glycobiology. 2008;18:353-366.
Not in our library10.1093/glycob/cwn010
- 194.
Shao W, Lam H. Tandem mass spectral libraries of peptides and their roles in proteomics research. Mass Spectrom. Rev. 2017;36:634-648.
Not in our library10.1002/mas.21512
- 195.
Mechref Y, Kang P, Novotny MV. Differentiating structural isomers of sialylated glycans by matrix-assisted laser desorption/ionization time-of-flight/time-of-flight tandem mass spectrometry. Rapid Commun. Mass Spectrom. 2006;20:1381-1389.
Not in our library10.1002/rcm.2445
- 196.
Levery SB, et al. Advances in mass spectrometry driven O-glycoproteomics. Biochim. Biophys. Acta. 2015;1850:33-42.
Not in our library10.1016/j.bbagen.2014.09.026
- 197.
Khoo KH. Advances toward mapping the full extent of protein site-specific O-GalNAc glycosylation that better reflects underlying glycomic complexity. Curr. Opin. Struct. Biol. 2019;56:146-154.
Not in our library10.1016/j.sbi.2019.02.007
- 198.
Darula Z, Medzihradszky KF. Analysis of mammalian O-glycopeptides-we have made a good start, but there is a long way to go. Mol. Cell. Proteom. 2018;17:2-17.
Not in our library10.1074/mcp.mr117.000126
- 199.
Seo Y, Park GM, Oh MJ, An HJ. Investigation of O-glycosylation heterogeneity of recombinant coagulation factor IX using LC-MS/MS. Bioanalysis. 2017;9:1361-1372.
Not in our library10.4155/bio-2017-0086
- 200.
Hashii N, Suzuki J. Site-specific O-glycosylation analysis by liquid chromatography-mass spectrometry with electron-transfer/higher-energy collisional dissociation. Methods Mol. Biol. 2021;2271:169-178.
Not in our library10.1007/978-1-0716-1241-5_12
- 201.
Wells L, et al. Mapping sites of O-GlcNAc modification using affinity tags for serine and threonine post-translational modifications. Mol. Cell. Proteom. 2002;1:791-804.
Not in our library10.1074/mcp.m200048-mcp200
- 202.
- 203.
Hashii N, Ishii-Watabe A. [Site-specific O-glycosylation analysis of therapeutic Fc-fusion protein by mass spectrometry]. Yakugaku Zasshi. 2018;138:1483-1494.
Not in our library10.1248/yakushi.18-00020-2
- 204.
Aebi M. N-linked protein glycosylation in the ER. Biochim. Biophys. Acta. 2013;1833:2430-2437.
Not in our library10.1016/j.bbamcr.2013.04.001
- 205.
Pasing Y, Sickmann A, Lewandrowski U. N-glycoproteomics: mass spectrometry-based glycosylation site annotation. Biol. Chem. 2012;393:249-258.
Not in our library10.1515/hsz-2011-0245
- 206.
Furmanek A, Hofsteenge J. Protein C-mannosylation: facts and questions. Acta Biochim. Pol. 2000;47:781-789.
Not in our library
- 207.
Maynard JC, Burlingame AL, Medzihradszky KF. Cysteine S-linked N-acetylglucosamine (S-GlcNAcylation), a new post-translational modification in mammals. Mol. Cell. Proteom. 2016;15:3405-3411.
Not in our library10.1074/mcp.m116.061549
- 208.
Hofsteenge J, et al. New type of linkage between a carbohydrate and a protein: C-glycosylation of a specific tryptophan residue in human RNase Us. Biochemistry. 1994;33:13524-13530.
Not in our library10.1021/bi00250a003
- 209.
- 210.
Kolarich D, Jensen PH, Altmann F, Packer NH. Determination of site-specific glycan heterogeneity on glycoproteins. Nat. Protoc. 2012;7:1285-1298.
Not in our library10.1038/nprot.2012.062
- 211.
Qin H, et al. Proteomics analysis of site-specific glycoforms by a virtual multistage mass spectrometry method. Anal. Chim. Acta. 2019;1070:60-68.
Not in our library10.1016/j.aca.2019.04.025
- 212.
Liu M, et al. Efficient and accurate glycopeptide identification pipeline for high-throughput site-specific N-glycosylation analysis. J. Proteome Res. 2014;13:3121-3129.
Not in our library10.1021/pr500238v
- 213.
Kim, U. et al. MS-based technologies for the study of site-specific glycosylation. Mass Spectrom. Lett.8, 69–78 (2017).
Not in our library
- 214.
Xiao K, Shen Y, Li S, Tian Z. Accurate phosphorylation site localization using phospho-brackets. Anal. Chim. Acta. 2017;996:38-47.
Not in our library10.1016/j.aca.2017.09.043
- 215.
Harrison AG. To b or not to b: the ongoing saga of peptide b ions. Mass Spectrom. Rev. 2009;28:640-654.
Not in our library10.1002/mas.20228
- 216.
Reid GE, Stephenson JL, McLuckey SA. Tandem mass spectrometry of ribonuclease A and B: N-linked glycosylation site analysis of whole protein ions. Anal. Chem. 2002;74:577-583.
Not in our library10.1021/ac015618l
- 217.
- 218.
Zhang W, et al. Large-scale assignment of N-glycosylation sites using complementary enzymatic deglycosylation. Talanta. 2011;85:499-505.
Not in our library10.1016/j.talanta.2011.04.019
- 219.
Olsen JV, et al. Higher-energy C-trap dissociation for peptide modification analysis. Nat. Methods. 2007;4:709-712.
Not in our library10.1038/nmeth1060
- 220.
Wolff JJ, et al. Electron capture dissociation, electron detachment dissociation and infrared multiphoton dissociation of sucrose octasulfate. Eur. J. Mass Spectrom. 2009;15:275-281.
Not in our library10.1255/ejms.951
- 221.
Syka JE, et al. Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry. Proc. Natl Acad. Sci. USA. 2004;101:9528-9533.
Not in our library10.1073/pnas.0402700101
- 222.
Warnke S, et al. Photodissociation of conformer-selected ubiquitin ions reveals site-specific cis/trans isomerization of proline peptide bonds. J. Am. Chem. Soc. 2014;136:10308-10314.
Not in our library10.1021/ja502994b
- 223.
Nilsson J. Liquid chromatography-tandem mass spectrometry-based fragmentation analysis of glycopeptides. Glycoconj. J. 2016;33:261-272.
Not in our library10.1007/s10719-016-9649-3
- 224.
Yang Y, Franc V, Heck AJR. Glycoproteomics: a balance between high-throughput and in-depth analysis. Trends Biotechnol. 2017;35:598-609.
Not in our library10.1016/j.tibtech.2017.04.010
- 225.
Sanda M, Benicky J, Goldman R. Low collision energy fragmentation in structure-specific glycoproteomics analysis. Anal. Chem. 2020;92:8262-8267.
Not in our library10.1021/acs.analchem.0c00519
- 226.
Zhao P, et al. Combining high-energy C-trap dissociation and electron transfer dissociation for protein O-GlcNAc modification site assignment. J. Proteome Res. 2011;10:4088-4104.
Not in our library10.1021/pr2002726
- 227.
Reiding KR, Bondt A, Franc V, Heck AJR. The benefits of hybrid fragmentation methods for glycoproteomics. TrAC Trends Anal. Chem. 2018;108:260-268.
Not in our library
- 228.
Swaney DL, et al. Supplemental activation method for high-efficiency electron-transfer dissociation of doubly protonated peptide precursors. Anal. Chem. 2007;79:477-485.
Not in our library10.1021/ac061457f
- 229.
Frese CK, et al. Toward full peptide sequence coverage by dual fragmentation combining electron-transfer and higher-energy collision dissociation tandem mass spectrometry. Anal. Chem. 2012;84:9668-9673.
Not in our library10.1021/ac3025366
- 230.
Kronewitter SR, et al. The development of retrosynthetic glycan libraries to profile and classify the human serum N-linked glycome. Proteomics. 2009;9:2986-2994.
Not in our library10.1002/pmic.200800760
- 231.
Solá RJ, Griebenow K. Effects of glycosylation on the stability of protein pharmaceuticals. J. Pharm. Sci. 2009;98:1223-1245.
Not in our library10.1002/jps.21504
- 232.
Haltiwanger RS, Lowe JB. Role of glycosylation in development. Annu. Rev. Biochem. 2004;73:491-537.
Not in our library10.1146/annurev.biochem.73.011303.074043
- 233.
Moremen KW, Tiemeyer M, Nairn AV. Vertebrate protein glycosylation: diversity, synthesis and function. Nat. Rev. Mol. Cell Biol. 2012;13:448-462.
Not in our library10.1038/nrm3383
- 234.
Chandler KB, Costello CE. Glycomics and glycoproteomics of membrane proteins and cell-surface receptors: Present trends and future opportunities. Electrophoresis. 2016;37:1407-1419.
Not in our library10.1002/elps.201500552
- 235.
Čaval T, Heck AJR, Reiding KR. Meta-heterogeneity: evaluating and describing the diversity in glycosylation between sites on the same glycoprotein. Mol. Cell. Proteom. 2020;20:100010.
Not in our library10.1074/mcp.r120.002093
- 236.
Khatri K, et al. Integrated omics and computational glycobiology reveal structural basis for influenza a virus glycan microheterogeneity and host interactions. Mol. Cell. Proteom. 2016;15:1895-1912.
Not in our library10.1074/mcp.m116.058016
- 237.
Dennis JW, et al. Beta 1-6 branching of Asn-linked oligosaccharides is directly associated with metastasis. Science. 1987;236:582-585.
Not in our library10.1126/science.2953071
- 238.
Gabius HJ, et al. From lectin structure to functional glycomics: principles of the sugar code. Trends Biochem. Sci. 2011;36:298-313.
Not in our library10.1016/j.tibs.2011.01.005
- 239.
Freeze HH. Understanding human glycosylation disorders: biochemistry leads the charge. J. Biol. Chem. 2013;288:6936-6945.
Not in our library10.1074/jbc.r112.429274
- 240.
- 241.
Croci DO, et al. Glycosylation-dependent lectin-receptor interactions preserve angiogenesis in anti-VEGF refractory tumors. Cell. 2014;156:744-758.
Not in our library10.1016/j.cell.2014.01.043
- 242.
Ardejani, M. S., Noodleman, L., Powers, E. T. & Kelly, J. W. Stereoelectronic effects in stabilizing protein–N-glycan interactions revealed by experiment and machine learning. Nat. Chem. 13, 480–487 (2021).
Not in our library10.1038/s41557-021-00646-w
- 243.
Park JJ, Lee M. Increasing the α 2, 6 sialylation of glycoproteins may contribute to metastatic spread and therapeutic resistance in colorectal cancer. Gut Liver. 2013;7:629-641.
Not in our library10.5009/gnl.2013.7.6.629
- 244.
Strasser R. Biological significance of complex N-glycans in plants and their impact on plant physiology. Front. Plant Sci. 2014;5:363.
Not in our library10.3389/fpls.2014.00363
- 245.
- 246.
Liew CY, et al. Structural identification of N-glycan isomers using logically derived sequence tandem mass spectrometry. Commun. Chem. 2021;4:92.
Not in our library10.1038/s42004-021-00532-z
- 247.
Chernykh A, Kawahara R, Thaysen-Andersen M. Towards structure-focused glycoproteomics. Biochem. Soc. Trans. 2021;49:161-186.
Not in our library10.1042/bst20200222
- 248.
Shen J, et al. StrucGP: de novo structural sequencing of site-specific N-glycan on glycoproteins using a modularization strategy. Nat. Methods. 2021;18:921-929.
Not in our library10.1038/s41592-021-01209-0
- 249.
Gindzienska-Sieskiewicz E, et al. The changes in monosaccharide composition of immunoglobulin G in the course of rheumatoid arthritis. Clin. Rheumatol. 2007;26:685-690.
Not in our library10.1007/s10067-006-0370-7
- 250.
Stanley P. A method to the madness of N-glycan complexity? Cell. 2007;129:27-29.
Not in our library10.1016/j.cell.2007.03.022
- 251.
Cai X, et al. The importance of N-glycosylation on β(3) integrin ligand binding and conformational regulation. Sci. Rep. 2017;7:4656.
Not in our library10.1038/s41598-017-04844-w
- 252.
Xiao K, et al. Large-scale identification and visualization of N-glycans with primary structures using GlySeeker. Rapid Commun. Mass Spectrom. 2018;32:142-148.
Not in our library10.1002/rcm.8023
- 253.
Maass K, et al. “Glyco-peakfinder”-de novo composition analysis of glycoconjugates. Proteomics. 2007;7:4435-4444.
Not in our library10.1002/pmic.200700253
- 254.
Haslam, S. M. et al. Glycoinformatics for Structural Glycomics. Glyco-Bioinformatics-Bits “n” Bytes of Sugars (ISBN: 978-3-8325-2719-8). Chapter 1 (2011).
Not in our library
- 255.
Xiao K, Tian Z. Site- and structure-specific quantitative N-glycoproteomics using RPLC-pentaHILIC separation and the intact N-glycopeptide search engine GPSeeker. Curr. Protoc. Protein Sci. 2019;97:e94.
Not in our library10.1002/cpps.94
- 256.
Pan KT, Chen CC, Urlaub H, Khoo KH. Adapting data-independent acquisition for mass spectrometry-based protein site-specific N-glycosylation analysis. Anal. Chem. 2017;89:4532-4539.
Not in our library10.1021/acs.analchem.6b04996
- 257.
Cao L, et al. Global site-specific analysis of glycoprotein N-glycan processing. Nat. Protoc. 2018;13:1196-1212.
Not in our library10.1038/nprot.2018.024
- 258.
- 259.
Pompach P, et al. Semi-automated identification of N-Glycopeptides by hydrophilic interaction chromatography, nano-reverse-phase LC-MS/MS, and glycan database search. J. Proteome Res. 2012;11:1728-1740.
Not in our library10.1021/pr201183w
- 260.
Choo MS, Wan C, Rudd PM, Nguyen-Khuong T. GlycopeptideGraphMS: improved glycopeptide detection and identification by exploiting graph theoretical patterns in mass and retention time. Anal. Chem. 2019;91:7236-7244.
Not in our library10.1021/acs.analchem.9b00594
- 261.
Woodin CL, et al. GlycoPep grader: a web-based utility for assigning the composition of N-linked glycopeptides. Anal. Chem. 2012;84:4821-4829.
Not in our library10.1021/ac300393t
- 262.
Liang SY, et al. An adaptive workflow coupled with Random Forest algorithm to identify intact N-glycopeptides detected from mass spectrometry. Bioinformatics. 2014;30:1908-1916.
Not in our library10.1093/bioinformatics/btu139
- 263.
Lynn KS, et al. MAGIC: an automated N-linked glycoprotein identification tool using a Y1-ion pattern matching algorithm and in silico MS² approach. Anal. Chem. 2015;87:2466-2473.
Not in our library10.1021/ac5044829
- 264.
Park GW, et al. Integrated GlycoProteome Analyzer (I-GPA) for automated identification and quantitation of site-specific N-glycosylation. Sci. Rep. 2016;6:21175.
Not in our library10.1038/srep21175
- 265.
Cao L, et al. Characterization of intact N- and O-linked glycopeptides using higher energy collisional dissociation. Anal. Biochem. 2014;452:96-102.
Not in our library10.1016/j.ab.2014.01.003
- 266.
Mao J, et al. A new searching strategy for the identification of O-linked glycopeptides. Anal. Chem. 2019;91:3852-3859.
Not in our library10.1021/acs.analchem.8b04184
- 267.
Schulze, S. et al. SugarPy facilitates the universal, discovery-driven analysis of intact glycopeptides. Bioinformaticsbtaa1042, 10.1093/bioinformatics/btaa1042 (2020).
Not in our library10.1093/bioinformatics/btaa1042
- 268.
Campbell MP, et al. UniCarbKB: putting the pieces together for glycomics research. Proteomics. 2011;11:4117-4121.
Not in our library10.1002/pmic.201100302
- 269.
Lütteke T, et al. GLYCOSCIENCES.de: an Internet portal to support glycomics and glycobiology research. Glycobiology. 2006;16:71r-81r.
Not in our library10.1093/glycob/cwj049
- 270.
Cooper CA, Harrison MJ, Wilkins MR, Packer NH. GlycoSuiteDB: a new curated relational database of glycoprotein glycan structures and their biological sources. Nucleic Acids Res. 2001;29:332-335.
Not in our library10.1093/nar/29.1.332
- 271.
Cooper CA, et al. GlycoSuiteDB: a curated relational database of glycoprotein glycan structures and their biological sources. 2003 update. Nucleic Acids Res. 2003;31:511-513.
Not in our library10.1093/nar/gkg099
- 272.
Campbell MP, Packer NH. UniCarbKB: new database features for integrating glycan structure abundance, compositional glycoproteomics data, and disease associations. Biochim. Biophys. Acta. 2016;1860:1669-1675.
Not in our library10.1016/j.bbagen.2016.02.016
- 273.
Campbell MP, et al. UniCarbKB: building a knowledge platform for glycoproteomics. Nucleic Acids Res. 2014;42:D215-D221.
Not in our library10.1093/nar/gkt1128
- 274.
von der Lieth CW, et al. EUROCarbDB: an open-access platform for glycoinformatics. Glycobiology. 2011;21:493-502.
Not in our library10.1093/glycob/cwq188
- 275.
Ahmad Izaham AR, Scott NE. Open database searching enables the identification and comparison of bacterial glycoproteomes without defining glycan compositions prior to searching. Mol. Cell. Proteom. 2020;19:1561-1574.
Not in our library10.1074/mcp.tir120.002100
- 276.
Zhao S, et al. GlycoStore: a database of retention properties for glycan analysis. Bioinformatics. 2018;34:3231-3232.
Not in our library10.1093/bioinformatics/bty319
- 277.
Aoki-Kinoshita K, et al. GlyTouCan 1.0-The international glycan structure repository. Nucleic Acids Res. 2016;44:D1237-D1242.
Not in our library10.1093/nar/gkv1041
- 278.
Damerell D, et al. The GlycanBuilder and GlycoWorkbench glycoinformatics tools: updates and new developments. Biol. Chem. 2012;393:1357-1362.
Not in our library10.1515/hsz-2012-0135
- 279.
Zhu Z, et al. GlycoPep Detector: a tool for assigning mass spectrometry data of N-linked glycopeptides on the basis of their electron transfer dissociation spectra. Anal. Chem. 2013;85:5023-5032.
Not in our library10.1021/ac400287n
- 280.
Go EP, et al. GlycoPep DB: a tool for glycopeptide analysis using a “Smart Search”. Anal. Chem. 2007;79:1708-1713.
Not in our library10.1021/ac061548c
- 281.
Chang, D. & Zaia, J. Methods to improve quantitative glycoprotein coverage from bottom-up LC-MS data. Mass Spectrom. Rev.10.1002/mas.21692 (2021).
Not in our library10.1002/mas.21692
- 282.
Riley NM, Malaker SA, Driessen MD, Bertozzi CR. Optimal dissociation methods differ for N- and O-glycopeptides. J. Proteome Res. 2020;19:3286-3301.
Not in our library10.1021/acs.jproteome.0c00218
- 283.
- 284.
Bern M, Cai Y, Goldberg D. Lookup peaks: a hybrid of de novo sequencing and database search for protein identification by tandem mass spectrometry. Anal. Chem. 2007;79:1393-1400.
Not in our library10.1021/ac0617013
- 285.
Zeng WF, et al. pGlyco: a pipeline for the identification of intact N-glycopeptides by using HCD- and CID-MS/MS and MS3. Sci. Rep. 2016;6:25102.
Not in our library10.1038/srep25102
- 286.
- 287.
Toghi Eshghi S, et al. GPQuest: a spectral library matching algorithm for site-specific assignment of tandem mass spectra to intact N-glycopeptides. Anal. Chem. 2015;87:5181-5188.
Not in our library10.1021/acs.analchem.5b00024
- 288.
Lu L, et al. O-pair search with MetaMorpheus for O-glycopeptide characterization. Nat. Methods. 2020;17:1133-1138.
Not in our library10.1038/s41592-020-00985-5
- 289.
Polasky DA, Yu F, Teo GC, Nesvizhskii AI. Fast and comprehensive N- and O-glycoproteomics analysis with MSFragger-Glyco. Nat. Methods. 2020;17:1125-1132.
Not in our library10.1038/s41592-020-0967-9
- 290.
Pai PJ, Hu Y, Lam H. Direct glycan structure determination of intact N-linked glycopeptides by low-energy collision-induced dissociation tandem mass spectrometry and predicted spectral library searching. Anal. Chim. Acta. 2016;934:152-162.
Not in our library10.1016/j.aca.2016.05.049
- 291.
Zhu J, et al. Differential quantitative determination of site-specific intact N-glycopeptides in serum haptoglobin between hepatocellular carcinoma and cirrhosis using LC-EThcD-MS/MS. J. Proteome Res. 2019;18:359-371.
Not in our library10.1021/acs.jproteome.8b00654
- 292.
Giménez E, Gay M, Vilaseca M. Automatic and rapid identification of glycopeptides by nano-UPLC-LTQ-FT-MS and proteomic search engine. J. Proteom. 2017;152:236-242.
Not in our library10.1016/j.jprot.2016.11.010
- 293.
Yu Z, et al. Sequential fragment ion filtering and endoglycosidase-assisted identification of intact glycopeptides. Anal. Bioanal. Chem. 2017;409:3077-3087.
Not in our library10.1007/s00216-017-0195-z
- 294.
Bern M, Kil YJ, Becker C. Byonic: advanced peptide and protein identification software. Curr. Protoc. Bioinform. 2012;Chapter 13:Unit13.20.
Not in our library10.1002/0471250953.bi1320s40
- 295.
Ye Z, Vakhrushev SY. The role of data-independent acquisition for glycoproteomics. Mol. Cell Proteom. 2021;20:100042.
Not in our library10.1074/mcp.r120.002204
- 296.
Ye Z, Mao Y, Clausen H, Vakhrushev SY. Glyco-DIA: a method for quantitative O-glycoproteomics with in silico-boosted glycopeptide libraries. Nat. Methods. 2019;16:902-910.
Not in our library10.1038/s41592-019-0504-x
- 297.
- 298.
Xu LL, Young A, Zhou A, Röst HL. Machine learning in mass spectrometric analysis of DIA data. Proteomics. 2020;20:e1900352.
Not in our library10.1002/pmic.201900352
- 299.
Lin CH, Krisp C, Packer NH, Molloy MP. Development of a data independent acquisition mass spectrometry workflow to enable glycopeptide analysis without predefined glycan compositional knowledge. J. Proteom. 2018;172:68-75.
Not in our library10.1016/j.jprot.2017.10.011
- 300.
Phung TK, Zacchi LF, Schulz BL. DIALib: an automated ion library generator for data independent acquisition mass spectrometry analysis of peptides and glycopeptides. Mol. Omics. 2020;16:100-112.
Not in our library10.1039/c9mo00125e
- 301.
Yang X, et al. Proteome-wide analysis of N-glycosylation stoichiometry using SWATH technology. J. Proteome Res. 2017;16:3830-3840.
Not in our library10.1021/acs.jproteome.7b00480
- 302.
Yuan W, et al. Quantitative analysis of immunoglobulin subclasses and subclass specific glycosylation by LC-MS-MRM in liver disease. J. Proteom. 2015;116:24-33.
Not in our library10.1016/j.jprot.2014.12.020
- 303.
Zacchi LF, Schulz BL. SWATH-MS glycoproteomics reveals consequences of defects in the glycosylation machinery. Mol. Cell. Proteom. 2016;15:2435-2447.
Not in our library10.1074/mcp.m115.056366
- 304.
Roth Z, Yehezkel G, Khalaila I. Identification and quantification of protein glycosylation. Int. J. Carbohydr. Chem. 2012;2012:640923.
Not in our library
- 305.
Dimitrov DS. Virus entry: molecular mechanisms and biomedical applications. Nat. Rev. Microbiol. 2004;2:109-122.
Not in our library10.1038/nrmicro817
- 306.
- 307.
- 308.
- 309.
Malik YA. Properties of Coronavirus and SARS-CoV-2. Malays. J. Pathol. 2020;42:3-11.
Not in our library
- 310.
Kim D, et al. The architecture of SARS-CoV-2 transcriptome. Cell. 2020;181:914-921.e910.
Not in our library10.1016/j.cell.2020.04.011
- 311.
Gordon DE, et al. A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature. 2020;583:459-468.
Not in our library10.1038/s41586-020-2286-9
- 312.
Fehr AR, Perlman S. Coronaviruses: an overview of their replication and pathogenesis. Methods Mol. Biol. 2015;1282:1-23.
Not in our library10.1007/978-1-4939-2438-7_1
- 313.
- 314.
- 315.
Kumar, S., Nyodu, R., Maurya, V. K. & Saxena, S. K. J. C. D. Morphology, genome organization, replication, and pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronavirus Disease 2019 (COVID-19)23 (2020).
Not in our library
- 316.
- 317.
Xu X, et al. Evolution of the novel coronavirus from the ongoing Wuhan outbreak and modeling of its spike protein for risk of human transmission. Sci. China Life Sci. 2020;63:457-460.
Not in our library10.1007/s11427-020-1637-5
- 318.
Archambault AN, et al. Cumulative burden of colorectal cancer-associated genetic variants is more strongly associated with early-onset vs late-onset cancer. Gastroenterology. 2020;158:1274-1286.e1212.
Not in our library10.1053/j.gastro.2019.12.012
- 319.
Zhang Y, Kutateladze TG. Molecular structure analyses suggest strategies to therapeutically target SARS-CoV-2. Nat. Commun. 2020;11:2920.
Not in our library10.1038/s41467-020-16779-4
- 320.
Walls AC, et al. Structure, function, and antigenicity of the SARS-CoV-2 spike glycoprotein. Cell. 2020;181:281-292.e286.
Not in our library10.1016/j.cell.2020.02.058
- 321.
Hoffmann M, et al. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell. 2020;181:271-280.e278.
Not in our library10.1016/j.cell.2020.02.052
- 322.
Huang Y, et al. Structural and functional properties of SARS-CoV-2 spike protein: potential antivirus drug development for COVID-19. Acta Pharmacol. Sin. 2020;41:1141-1149.
Not in our library10.1038/s41401-020-0485-4
- 323.
Shang J, et al. Structural basis of receptor recognition by SARS-CoV-2. Nature. 2020;581:221-224.
Not in our library10.1038/s41586-020-2179-y
- 324.
Zhang H, et al. Expression of the SARS-CoV-2 ACE2 Receptor in the human airway epithelium. Am. J. Respir. Crit. Care Med. 2020;202:219-229.
Not in our library10.1164/rccm.202003-0541oc
- 325.
- 326.
Samrat SK, Tharappel AM, Li Z, Li H. Prospect of SARS-CoV-2 spike protein: Potential role in vaccine and therapeutic development. Virus Res. 2020;288:198141.
Not in our library10.1016/j.virusres.2020.198141
- 327.
Walls AC, et al. Unexpected receptor functional mimicry elucidates activation of coronavirus fusion. Cell. 2019;176:1026-1039.e1015.
Not in our library10.1016/j.cell.2018.12.028
- 328.
Antonopoulos A, et al. Site-specific characterization of SARS-CoV-2 spike glycoprotein receptor-binding domain. Glycobiology. 2021;31:181-187.
Not in our library10.1093/glycob/cwaa085
- 329.
Wang D, et al. Comprehensive analysis of the glycan complement of SARS-CoV-2 spike proteins using signature ions-triggered electron-transfer/higher-energy collisional dissociation (EThcD) mass spectrometry. Anal. Chem. 2020;92:14730-14739.
Not in our library10.1021/acs.analchem.0c03301
- 330.
Lenza MP, et al. Structural characterization of n-linked glycans in the receptor binding domain of the SARS-CoV-2 spike protein and their interactions with human lectins. Angew. Chem. Int. Ed. Engl. 2020;59:23763-23771.
Not in our library10.1002/anie.202011015
- 331.
Yao H, et al. Molecular Architecture of the SARS-CoV-2 Virus. Cell. 2020;183:730-738.e713.
Not in our library10.1016/j.cell.2020.09.018
- 332.
Sanda M, Morrison L, Goldman R. N- and O-Glycosylation of the SARS-CoV-2 Spike Protein. Anal. Chem. 2021;93:2003-2009.
Not in our library10.1021/acs.analchem.0c03173
- 333.
Yang J, et al. A vaccine targeting the RBD of the S protein of SARS-CoV-2 induces protective immunity. Nature. 2020;586:572-577.
Not in our library10.1038/s41586-020-2599-8
- 334.
Zhou D, et al. Identification of 22 N-glycosites on spike glycoprotein of SARS-CoV-2 and accessible surface glycopeptide motifs: implications for vaccination and antibody therapeutics. Glycobiology. 2021;31:69-80.
Not in our library10.1093/glycob/cwaa052
- 335.
Miller LM, et al. Heterogeneity of glycan processing on trimeric SARS-CoV-2 spike protein revealed by charge detection mass spectrometry. J. Am. Chem. Soc. 2021;143:3959-3966.
Not in our library10.1021/jacs.1c00353
- 336.
Bagdonaite I, et al. Site-specific O-glycosylation analysis of SARS-CoV-2 spike protein produced in insect and human cells. Viruses. 2021;13:551.
Not in our library10.3390/v13040551
- 337.
Andersen KG, et al. The proximal origin of SARS-CoV-2. Nat. Med. 2020;26:450-452.
Not in our library10.1038/s41591-020-0820-9
- 338.
Dong X, et al. Comprehensive O-glycosylation analysis of the SARS-CoV-2 spike protein with biomimetic Trp-Arg materials. Anal. Chem. 2021;93:10444-10452.
Not in our library10.1021/acs.analchem.0c04634
- 339.
Zhang, Y. et al. Mucin-type O-glycosylation landscapes of SARS-CoV-2 Spike Proteins. bioRxiv10.1101/2020.07.29.227785 (2020).
Not in our library
- 340.
Roberts, D. S. et al. Structural O-glycoform heterogeneity of the SARS-CoV-2 spike protein receptor-binding domain revealed by top-down mass spectrometry. J. Am. Chem. Soc.143, 12014–12024 (2021).
Not in our library10.1021/jacs.1c02713
- 341.
Gstöttner C, et al. Structural and functional characterization of SARS-CoV-2 RBD domains produced in mammalian cells. Anal. Chem. 2021;93:6839-6847.
Not in our library10.1021/acs.analchem.1c00893
- 342.
Wang Y, et al. Impact of expressing cells on glycosylation and glycan of the SARS-CoV-2 spike glycoprotein. ACS Omega. 2021;6:15988-15999.
Not in our library10.1021/acsomega.1c01785
- 343.
- 344.
Lowenthal MS, et al. Identification of novel N-glycosylation sites at noncanonical protein consensus motifs. J. Proteome Res. 2016;15:2087-2101.
Not in our library10.1021/acs.jproteome.5b00733
- 345.
Shajahan A, et al. Comprehensive characterization of N- and O- glycosylation of SARS-CoV-2 human receptor angiotensin converting enzyme 2. Glycobiology. 2021;31:410-424.
Not in our library10.1093/glycob/cwaa101
- 346.
Zhang S, et al. Bat and pangolin coronavirus spike glycoprotein structures provide insights into SARS-CoV-2 evolution. Nat. Commun. 2021;12:1607.
Not in our library10.1038/s41467-021-21767-3
- 347.
Sztain, T. et al. A glycan gate controls opening of the SARS-CoV-2 spike protein. bioRxiv10.1101/2021.02.15.431212 (2021).
Not in our library10.1038/s41557-021-00758-3
- 348.
Cao Y, et al. Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients’ B cells. Cell. 2020;182:73-84.e16.
Not in our library10.1016/j.cell.2020.05.025
- 349.
- 350.
Jaimes JA, Millet JK, Whittaker GR. Proteolytic cleavage of the SARS-CoV-2 spike protein and the role of the novel S1/S2 site. iScience. 2020;23:101212.
Not in our library10.1016/j.isci.2020.101212
- 351.
Johnson, B. A. et al. Furin cleavage site is key to SARS-CoV-2 pathogenesis. bioRxiv10.1101/2020.08.26.268854 (2020).
Not in our library
- 352.
- 353.
Teng S, et al. Systemic effects of missense mutations on SARS-CoV-2 spike glycoprotein stability and receptor-binding affinity. Brief. Bioinform. 2021;22:1239-1253.
Not in our library10.1093/bib/bbaa233
- 354.
Rahnama S, Azimzadeh Irani M, Amininasab M, Ejtehadi MR. S494 O-glycosylation site on the SARS-CoV-2 RBD affects the virus affinity to ACE2 and its infectivity; a molecular dynamics study. Sci. Rep. 2021;11:15162.
Not in our library10.1038/s41598-021-94602-w
- 355.
Zhang Y, et al. O-glycosylation landscapes of SARS-CoV-2 spike proteins. Front. Chem. 2021;9:689521.
Not in our library10.3389/fchem.2021.689521
- 356.
Zhang, L. et al. O-glycosylation of the novel SARS-CoV-2 coronavirus spike protein influences furin cleavage. FASEB J. 35. 10.1096/fasebj.2021.35.S1.00261 (2021).
Not in our library
- 357.
- 358.
Schjoldager KT, et al. A systematic study of site-specific GalNAc-type O-glycosylation modulating proprotein convertase processing. J. Biol. Chem. 2011;286:40122-40132.
Not in our library10.1074/jbc.m111.287912
- 359.
Uslupehlivan, M. & Şener, E. Glycoinformatics approach for identifying target positions to inhibit initial binding of SARS-CoV-2 S1 protein to the host cell. bioRxiv10.1101/2020.03.25.007898 (2020).
Not in our library
- 360.
McClenaghan C, Hanson A, Lee SJ, Nichols CG. Coronavirus proteins as ion channels: current and potential research. Front. Immunol. 2020;11:573339.
Not in our library10.3389/fimmu.2020.573339
- 361.
- 362.
Artika IM, Dewantari AK, Wiyatno A. Molecular biology of coronaviruses: current knowledge. Heliyon. 2020;6:e04743.
Not in our library10.1016/j.heliyon.2020.e04743
- 363.
Park SH, et al. Interactions of SARS-CoV-2 envelope protein with amilorides correlate with antiviral activity. PLoS Pathog. 2021;17:e1009519.
Not in our library10.1371/journal.ppat.1009519
- 364.
Mandala VS, et al. Structure and drug binding of the SARS-CoV-2 envelope protein transmembrane domain in lipid bilayers. Nat. Struct. Mol. Biol. 2020;27:1202-1208.
Not in our library10.1038/s41594-020-00536-8
- 365.
- 366.
- 367.
Wilson L, Gage P, Ewart G. Hexamethylene amiloride blocks E protein ion channels and inhibits coronavirus replication. Virology. 2006;353:294-306.
Not in our library10.1016/j.virol.2006.05.028
- 368.
Surya W, et al. MERS coronavirus envelope protein has a single transmembrane domain that forms pentameric ion channels. Virus Res. 2015;201:61-66.
Not in our library10.1016/j.virusres.2015.02.023
- 369.
Verdiá-Báguena C, et al. Coronavirus E protein forms ion channels with functionally and structurally-involved membrane lipids. Virology. 2012;432:485-494.
Not in our library10.1016/j.virol.2012.07.005
- 370.
- 371.
Ruch TR, Machamer CE. The hydrophobic domain of infectious bronchitis virus E protein alters the host secretory pathway and is important for release of infectious virus. J. Virol. 2011;85:675-685.
Not in our library10.1128/jvi.01570-10
- 372.
Singh Tomar PP, Arkin IT. SARS-CoV-2 E protein is a potential ion channel that can be inhibited by Gliclazide and Memantine. Biochem. Biophys. Res. Commun. 2020;530:10-14.
Not in our library10.1016/j.bbrc.2020.05.206
- 373.
- 374.
- 375.
- 376.
- 377.
Masters PS. The molecular biology of coronaviruses. Adv. Virus Res. 2006;66:193-292.
Not in our library10.1016/s0065-3527(06)66005-3
- 378.
de Haan CA, Rottier PJ. Molecular interactions in the assembly of coronaviruses. Adv. Virus Res. 2005;64:165-230.
Not in our library10.1016/s0065-3527(05)64006-7
- 379.
Dawood AA. Glycosylation, ligand binding sites and antigenic variations between membrane glycoprotein of COVID-19 and related coronaviruses. Vacunas. 2021;22:1-9.
Not in our library10.1016/j.vacun.2020.09.005
- 380.
Lu R, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet. 2020;395:565-574.
Not in our library10.1016/s0140-6736(20)30251-8
- 381.
Liu DX, et al. Accessory proteins of SARS-CoV and other coronaviruses. Antiviral Res. 2014;109:97-109.
Not in our library10.1016/j.antiviral.2014.06.013
- 382.
Majumdar P, Niyogi S. ORF3a mutation associated with higher mortality rate in SARS-CoV-2 infection. Epidemiol. Infect. 2020;148:e262.
Not in our library10.1017/s0950268820002599
- 383.
- 384.
Mehta P, et al. COVID-19: consider cytokine storm syndromes and immunosuppression. Lancet. 2020;395:1033-1034.
Not in our library10.1016/s0140-6736(20)30628-0
- 385.
Oostra M, de Haan CA, de Groot RJ, Rottier PJ. Glycosylation of the severe acute respiratory syndrome coronavirus triple-spanning membrane proteins 3a and M. J. Virol. 2006;80:2326-2336.
Not in our library10.1128/jvi.80.5.2326-2336.2006
- 386.
- 387.
Samadizadeh S, et al. COVID-19: Why does disease severity vary among individuals? Respir. Med. 2021;180:106356.
Not in our library10.1016/j.rmed.2021.106356
- 388.
Lan J, et al. Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature. 2020;581:215-220.
Not in our library10.1038/s41586-020-2180-5
- 389.
Chen, M. et al. An epigenetic mechanism underlying chromosome 17p deletion-driven tumorigenesis. Cancer Discov. 10.1158/2159-8290.CD-20-0336 (2020).
Not in our library10.1158/2159-8290.cd-20-0336
- 390.
South AM, Diz DI, Chappell MC. COVID-19, ACE2, and the cardiovascular consequences. Am. J. Physiol. Heart Circ. Physiol. 2020;318:H1084-h1090.
Not in our library10.1152/ajpheart.00217.2020
- 391.
Nishiga M, et al. COVID-19 and cardiovascular disease: from basic mechanisms to clinical perspectives. Nat. Rev. Cardiol. 2020;17:543-558.
Not in our library10.1038/s41569-020-0413-9
- 392.
Allen JD, et al. Subtle Influence of ACE2 Glycan Processing on SARS-CoV-2 Recognition. J. Mol. Biol. 2021;433:166762.
Not in our library10.1016/j.jmb.2020.166762
- 393.
Li W, et al. Identification of sialic acid-binding function for the Middle East respiratory syndrome coronavirus spike glycoprotein. Proc. Natl Acad. Sci. USA. 2017;114:E8508-e8517.
Not in our library10.1073/pnas.1712592114
- 394.
Schwegmann-Wessels C, et al. The sialic acid binding activity of the S protein facilitates infection by porcine transmissible gastroenteritis coronavirus. Virol. J. 2011;8:435.
Not in our library10.1186/1743-422x-8-435
- 395.
Tortorici MA, et al. Structural basis for human coronavirus attachment to sialic acid receptors. Nat. Struct. Mol. Biol. 2019;26:481-489.
Not in our library10.1038/s41594-019-0233-y
- 396.
Wielgat P, Rogowski K, Godlewska K, Car H. Coronaviruses: is sialic acid a gate to the eye of cytokine storm? From the entry to the effects. Cells. 2020;9:1963.
Not in our library10.3390/cells9091963
- 397.
Huang X, et al. Human coronavirus HKU1 spike protein uses O-acetylated sialic acid as an attachment receptor determinant and employs hemagglutinin-esterase protein as a receptor-destroying enzyme. J. Virol. 2015;89:7202-7213.
Not in our library10.1128/jvi.00854-15
- 398.
- 399.
Procko, E. The sequence of human ACE2 is suboptimal for binding the S spike protein of SARS coronavirus 2. bioRxiv10.1101/2020.03.16.994236 (2020).
Not in our library
- 400.
- 401.
Khoury DS, et al. Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection. Nat. Med. 2021;27:1205-1211.
Not in our library10.1038/s41591-021-01377-8
- 402.
Edara VV, et al. Neutralizing antibodies against SARS-CoV-2 variants after infection and vaccination. JAMA. 2021;325:1896-1898.
Not in our library10.1001/jama.2021.4388
- 403.
Mellet, J. & Pepper, M. S. A COVID-19 vaccine: big strides come with big challenges. Vaccines9, 39 (2021).
Not in our library10.3390/vaccines9010039
- 404.
- 405.
- 406.
Pinto D, et al. Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV antibody. Nature. 2020;583:290-295.
Not in our library10.1038/s41586-020-2349-y
- 407.
Ledford H. COVID antibody treatments show promise for preventing severe disease. Nature. 2021;591:513-514.
Not in our library10.1038/d41586-021-00650-7
- 408.
Cathcart, A. L. et al. The dual function monoclonal antibodies VIR-7831 and VIR-7832 demonstrate potent in vitro and in vivo activity against SARS-CoV-2. bioRxiv10.1101/2021.03.09.434607 (2021).
Not in our library
- 409.
- 410.
Palma J, Tokarz-Deptuła B, Deptuła J, Deptuła W. Natural antibodies - facts known and unknown. Cent. Eur. J. Immunol. 2018;43:466-475.
Not in our library10.5114/ceji.2018.81354
- 411.
Lardone RD, et al. How glycobiology can help us treat and beat the COVID-19 pandemic. J. Biol. Chem. 2021;296:100375.
Not in our library10.1016/j.jbc.2021.100375
- 412.
Zlocowski N, et al. Purified human anti-Tn and anti-T antibodies specifically recognize carcinoma tissues. Sci. Rep. 2019;9:8097.
Not in our library10.1038/s41598-019-44601-9
- 413.
- 414.
Breiman A, et al. Low levels of natural anti-α-N-acetylgalactosamine (Tn) antibodies are associated with COVID-19. Front. Microbiol. 2021;12:641460.
Not in our library10.3389/fmicb.2021.641460
- 415.
Williams WB, et al. Fab-dimerized glycan-reactive antibodies are a structural category of natural antibodies. Cell. 2021;184:2955-2972.e2925.
Not in our library10.1016/j.cell.2021.04.042
- 416.
Dai L, Gao GF. Viral targets for vaccines against COVID-19. Nat. Rev. Immunol. 2021;21:73-82.
Not in our library10.1038/s41577-020-00480-0
- 417.
- 418.
Han, B. et al. Safety, tolerability, and immunogenicity of an inactivated SARS-CoV-2 vaccine (CoronaVac) in healthy children and adolescents: a double-blind, randomised, controlled, phase 1/2 clinical trial. Lancet Infect. Dis. 21, 803–812 (2021).
Not in our library10.1016/s1473-3099(21)00319-4
- 419.
Jara, A. et al. Effectiveness of an inactivated SARS-CoV-2 vaccine in Chile. New Engl. J. Med. 385, 946–948 (2021).
Not in our library10.1056/nejmoa2107715
- 420.
- 421.
Nishikawa, T. et al. Anti-CoVid19 plasmid DNA vaccine induces a potent immune response in rodents by Pyro-drive Jet Injector intradermal inoculation. bioRxiv10.1101/2021.01.13.426436 (2021).
Not in our library
- 422.
van Doremalen N, et al. ChAdOx1 nCoV-19 vaccine prevents SARS-CoV-2 pneumonia in rhesus macaques. Nature. 2020;586:578-582.
Not in our library10.1038/s41586-020-2608-y
- 423.
Buchbinder SP, McElrath MJ, Dieffenbach C, Corey L. Use of adenovirus type-5 vectored vaccines: a cautionary tale. Lancet. 2020;396:e68-e69.
Not in our library10.1016/s0140-6736(20)32156-5
- 424.
Corbett KS, et al. Evaluation of the mRNA-1273 vaccine against SARS-CoV-2 in nonhuman primates. New Engl. J. Med. 2020;383:1544-1555.
Not in our library10.1056/nejmoa2024671
- 425.
Jackson LA, et al. An mRNA vaccine against SARS-CoV-2 - preliminary report. New Engl. J. Med. 2020;383:1920-1931.
Not in our library10.1056/nejmoa2022483
- 426.
Keech C, et al. Phase 1-2 trial of a SARS-CoV-2 recombinant spike protein nanoparticle vaccine. New Engl. J. Med. 2020;383:2320-2332.
Not in our library10.1056/nejmoa2026920
- 427.
- 428.
Krammer F. SARS-CoV-2 vaccines in development. Nature. 2020;586:516-527.
Not in our library10.1038/s41586-020-2798-3
- 429.
Tan HX, et al. Immunogenicity of prime-boost protein subunit vaccine strategies against SARS-CoV-2 in mice and macaques. Nat. Commun. 2021;12:1403.
Not in our library10.1038/s41467-021-21665-8
- 430.
- 431.
- 432.
Doores KJ. The HIV glycan shield as a target for broadly neutralizing antibodies. FEBS J. 2015;282:4679-4691.
Not in our library10.1111/febs.13530
- 433.
Balzarini J. Targeting the glycans of glycoproteins: a novel paradigm for antiviral therapy. Nat. Rev. Microbiol. 2007;5:583-597.
Not in our library10.1038/nrmicro1707
- 434.
Wang D. Coronaviruses’ sugar shields as vaccine candidates. Curr. Trends Immunol. 2020;21:17-23.
Not in our library
- 435.
Gao, C. et al. SARS-CoV-2 spike protein interacts with multiple innate immune receptors. bioRxiv10.1101/2020.07.29.227462 (2020).
Not in our library
- 436.
de Oliveira Figueiroa E, et al. Lectin-carbohydrate interactions: implications for the development of new anticancer agents. Curr. Med. Chem. 2017;24:3667-3680.
Not in our library10.2174/0929867324666170523110400
- 437.
- 438.
Liu YM, et al. A carbohydrate-binding protein from the edible lablab beans effectively blocks the infections of influenza viruses and SARS-CoV-2. Cell Rep. 2020;32:108016.
Not in our library10.1016/j.celrep.2020.108016
- 439.
Mori T, et al. Isolation and characterization of griffithsin, a novel HIV-inactivating protein, from the red alga Griffithsia sp. J. Biol. Chem. 2005;280:9345-9353.
Not in our library10.1074/jbc.m411122200
- 440.
Sharma VK, Sharma I, Glick J. The expanding role of mass spectrometry in the field of vaccine development. Mass Spectrom. Rev. 2020;39:83-104.
Not in our library10.1002/mas.21571
- 441.
Cai Y, et al. Griffithsin with a broad-spectrum antiviral activity by binding glycans in viral glycoprotein exhibits strong synergistic effect in combination with a pan-coronavirus fusion inhibitor targeting SARS-CoV-2 spike S2 subunit. Virol. Sin. 2020;35:857-860.
Not in our library10.1007/s12250-020-00305-3
- 442.
Hoffmann, D. et al. Identification of lectin receptors for conserved SARS-CoV-2 glycosylation sites. EMBO J.40, e108375 (2021).
Not in our library10.15252/embj.2021108375
- 443.
Wang W, et al. Lentil lectin derived from Lens culinaris exhibit broad antiviral activities against SARS-CoV-2 variants. Emerg. Microbes Infect. 2021;10:1519-1529.
Not in our library10.1080/22221751.2021.1957720
- 444.
Fajgenbaum DC, June CH. Cytokine storm. New Engl. J. Med. 2020;383:2255-2273.
Not in our library10.1056/nejmra2026131
- 445.
Song P, et al. Cytokine storm induced by SARS-CoV-2. Clin. Chim. Acta. 2020;509:280-287.
Not in our library10.1016/j.cca.2020.06.017
- 446.
- 447.
Coperchini F, et al. The cytokine storm in COVID-19: an overview of the involvement of the chemokine/chemokine-receptor system. Cytokine Growth Factor Rev. 2020;53:25-32.
Not in our library10.1016/j.cytogfr.2020.05.003
- 448.
Talaga ML, et al. Multitasking human lectin galectin-3 interacts with sulfated glycosaminoglycans and chondroitin sulfate proteoglycans. Biochemistry. 2016;55:4541-4551.
Not in our library10.1021/acs.biochem.6b00504
- 449.
Wang WH, et al. The role of galectins in virus infection - a systemic literature review. J. Microbiol. Immunol. Infect. 2020;53:925-935.
Not in our library10.1016/j.jmii.2019.09.005
- 450.
Caniglia JL, et al. Immunopathology of galectin-3: an increasingly promising target in COVID-19. F1000Research. 2020;9:1078.
Not in our library10.12688/f1000research.25979.1
- 451.
Garcia-Revilla J, Deierborg T, Venero JL, Boza-Serrano A. Hyperinflammation and fibrosis in severe COVID-19 patients: galectin-3, a target molecule to consider. Front. Immunol. 2020;11:2069.
Not in our library10.3389/fimmu.2020.02069
- 452.
Caniglia JL, et al. A potential role for Galectin-3 inhibitors in the treatment of COVID-19. PeerJ. 2020;8:e9392.
Not in our library10.7717/peerj.9392
- 453.
Saito S, et al. Pharmacotherapy and adjunctive treatment for idiopathic pulmonary fibrosis (IPF). J. Thorac. Dis. 2019;11:S1740-s1754.
Not in our library10.21037/jtd.2019.04.62
- 454.
Ren, Z. et al. Gal-3 is a potential biomarker for spinal cord injury and Gal-3 deficiency attenuates neuroinflammation through ROS/TXNIP/NLRP3 signaling pathway. Biosci. Rep. 39, BSR20192368 (2019).
Not in our library10.1042/bsr20192368
- 455.
Chalasani N, et al. Effects of belapectin, an inhibitor of galectin-3, in patients with nonalcoholic steatohepatitis with cirrhosis and portal hypertension. Gastroenterology. 2020;158:1334-1345.e1335.
Not in our library10.1053/j.gastro.2019.11.296
- 456.
Williams SJ, Goddard-Borger ED. α-glucosidase inhibitors as host-directed antiviral agents with potential for the treatment of COVID-19. Biochem. Soc. Trans. 2020;48:1287-1295.
Not in our library10.1042/bst20200505
- 457.
Evans DeWald L, et al. Iminosugars: a host-targeted approach to combat Flaviviridae infections. Antivir. Res. 2020;184:104881.
Not in our library10.1016/j.antiviral.2020.104881
- 458.
O’Keefe S, et al. Characterizing the selectivity of ER α-glucosidase inhibitors. Glycobiology. 2019;29:530-542.
Not in our library10.1093/glycob/cwz029
- 459.
Clarke EC, Nofchissey RA, Ye C, Bradfute SB. The iminosugars celgosivir, castanospermine and UV-4 inhibit SARS-CoV-2 replication. Glycobiology. 2021;31:378-384.
Not in our library10.1093/glycob/cwaa091
- 460.
Rajasekharan S, et al. Inhibitors of protein glycosylation are active against the coronavirus severe acute respiratory syndrome coronavirus SARS-CoV-2. Viruses. 2021;13:808.
Not in our library10.3390/v13050808
- 461.
Elbein AD, Tropea JE, Mitchell M, Kaushal GP. Kifunensine, a potent inhibitor of the glycoprotein processing mannosidase I. J. Biol. Chem. 1990;265:15599-15605.
Not in our library
- 462.
Nicholls JM, Moss RB, Haslam SM. The use of sialidase therapy for respiratory viral infections. Antivir. Res. 2013;98:401-409.
Not in our library10.1016/j.antiviral.2013.04.012
- 463.
Triana-Baltzer GB, et al. DAS181, a sialidase fusion protein, protects human airway epithelium against influenza virus infection: an in vitro pharmacodynamic analysis. J. Antimicrob. Chemother. 2010;65:275-284.
Not in our library10.1093/jac/dkp421
- 464.
Banerjee N, Mukhopadhyay S. Viral glycoproteins: biological role and application in diagnosis. Virusdisease. 2016;27:1-11.
Not in our library10.1007/s13337-015-0293-5
- 465.
Supekar, N. T. et al. Variable post-translational modifications of SARS-CoV-2 nucleocapsid protein. Glycobiology31, 1080–1092 (2021).
Not in our library10.1093/glycob/cwab044
- 466.
Tipnis SR, et al. A human homolog of angiotensin-converting enzyme. Cloning and functional expression as a captopril-insensitive carboxypeptidase. J. Biol. Chem. 2000;275:33238-33243.
Not in our library10.1074/jbc.m002615200
- 467.
van der Laarse SAM, Leney AC, Heck AJR. Crosstalk between phosphorylation and O-GlcNAcylation: friend or foe. FEBS J. 2018;285:3152-3167.
Not in our library10.1111/febs.14491
- 468.
Pandeswari PB, Sabareesh V. Middle-down approach: a choice to sequence and characterize proteins/proteomes by mass spectrometry. RSC Adv. 2019;9:313-344.
Not in our library10.1039/c8ra07200k
- 469.
- 470.
- 471.
Korber B, et al. Tracking changes in SARS-CoV-2 spike: evidence that D614G increases infectivity of the COVID-19 virus. Cell. 2020;182:812-827.e819.
Not in our library10.1016/j.cell.2020.06.043
- 472.
- 473.
- 474.
- 475.
Lopez Bernal, J. et al. Effectiveness of Covid-19 vaccines against the B.1.617.2 (Delta) variant. New Engl. J. Med. 385, 585–594 (2021).
Not in our library10.1056/nejmoa2108891
- 476.
Planas, D. et al. Reduced sensitivity of SARS-CoV-2 variant Delta to antibody neutralization. Nature596, 276–280 (2021).
Not in our library10.1038/s41586-021-03777-9
- 477.
Singh J, et al. SARS-CoV-2 variants of concern are emerging in India. Nat. Med. 2021;27:1131-1133.
Not in our library10.1038/s41591-021-01397-4
Cited by papers we hold 1
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.