In Silico Molecular Docking, Validation, ADMET, and Drug Likeness Prediction of Phytochemicals Against Multiple Therapeutic Targets of Diabetes Mellitus: In Silico Evaluation of Antidiabetic Phytochemicals

نویسندگان

1 Department of Pharmaceutical Chemistry, Netaji Subhas Chandra Bose Institute of Pharmacy (NSCBIP), West Bengal, 741222, India.

2 Department of Pharmaceutical Chemistry, Netaji Subhas Chandra Bose Institute of Pharmacy (NSCBIP), West Bengal, 741222, India.

3 Department of Pharmaceutical Chemistry, Netaji Subhas Chandra Bose Institute of Pharmacy (NSCBIP), West Bengal, 741222, India.

4 Department of Pharmaceutical Chemistry, Netaji Subhas Chandra Bose Institute of Pharmacy (NSCBIP), West Bengal, 741222, India.

5 Department of Pharmaceutical Chemistry, Netaji Subhas Chandra Bose Institute of Pharmacy (NSCBIP), West Bengal, 741222, India.

doi
10.22037/ijps.v21i1.47074
چکیده

Diabetes mellitus (DM) is among the most prevalent chronic metabolic disorders worldwide. According to the World Health Organization (WHO) and the International Diabetes Federation (IDF), the incidence of diabetes is rising sharply in both India and Western countries. In silico approaches, including molecular docking, ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis, drug-likeness prediction, and virtual screening, offer valuable insights for identifying effective ligands from phytochemicals that may serve as potential antidiabetic agents. This study focused on the evaluation of 277 phytochemicals derived from 20 plants reported to have antidiabetic properties, targeting six key receptors involved in the development of diabetes mellitus. Molecular docking was conducted at the active sites of these receptors, and Discovery Studio V24 was employed to map the interactions of the amino acid residues in both two- and three-dimensional representations with the phytochemical ligands. The docking study was validated by superimposing the re-docked complex onto the native co-crystallized ligand. Additionally, the Ramachandran plot was utilized to confirm the secondary structural integrity of the protein models. The in-silico analysis revealed that phytochemicals such as Quercetin, isomonospermoside, isocoreopsin, lukianol, ellagic acid, isosteviol, glutinone, monospermoside, and cadabicine exhibited significant binding affinities with the target proteins. Furthermore, these compounds demonstrated favorable oral bioavailability, drug-like properties, and ADMET profiles compared to standard antidiabetic drugs. Medicinal plants such as Butea monosperma (Palash), Coccinia grandis (Telakucha), Carissa carandas (Koromcha), Euphorbia neriifolia (Indian Spurge Tree), and Capparis decidua (Karil), which contain these bioactive phytochemicals, hold promise for the development of novel antidiabetic therapies within conventional medicine. These findings suggest that natural compounds with these core structures could serve as valuable lead compounds for diabetes treatment, contingent upon further validation through comprehensive in vitro and in vivo studies.