Skip to content
naulon
Not checkedNot checked for notices yet.

In Silico Target Identification and Validation for Antioxidant and Anti-inflammatory Activity of Selective Phytochemicals.

Shikha Rana, Savita Dixit, Alok Mittal

Brazilian Archives of Biology and Technology · 2019

doi:10.1590/1678-4324-2019190048 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

Abstract Phytochemicals present in plant extract include a number of biological active compounds which have shown promising antioxidant and anti-inflammatory activities in many animal studies. Present knowledge about the biochemical interactions of these compounds present in phytochemical extracts and target enzymes or proteins responsible for antioxidant and anti-inflammatory activity is limited. Present work is an attempt to identify and validate possible biological targets as enzymes or proteins involved in these targeted studies using molecular docking as computational method. IMPPAT: Indian Medicinal Plants, Photochemistry and Therapeutics (a curated database) has been used to retrieve various phytochemicals derived from selected plants which includes Carica papaya, Citrus limon, Curcuma longa, Dalbergia sissoo and Punica granatum. These phytochemicals are further evaluated using molecular docking against three enzymes involved in antioxidant activity which includes Superoxide dismutase (SOD), Glutathione peroxidase (GPX) and Catalase (CAT). Cyclooxigenase-2 (COX-2) has been tested for anti-inflammatory activity of these phytochemicals. Gliadin (Triticum aestivum), Tea Extract (Punica granatum), Hesperidin (Citrus limon), Terrestribisamide (Triticum aestivum), Vitamin P (Carica papaya) and 1,2,6-Trigalloylglucose (Punica granatum) are few phytochemicals which has shown promising binding affinities towards target proteins or enzymes Superoxide dismutase (SOD), Glutathione peroxidase (GPX) and Catalase (CAT) and cyclooxigenase-2 (COX-2).

Abstract licence: CC BY-NC

References18

    18 more references, whose wording the paper’s licence keeps private.

    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.