In Silico Exploration of Phytochemicals as Potential Drug Candidates against Dipeptidyl Peptidase-4 Target for the Treatment of Type 2 Diabetes

Abstract

Background: The objective of the study was to use docking and pharmacological research to explore phytochemicals as therapeutic candidates for the treatment of type 2 Diabetes Mellitus. Methods: The 100 plant compounds for the study were selected after a thorough review of the most recent literature using PubMed and Google Scholar. Three-dimensional structure in Structure-Data File Format of all phytochemicals was downloaded and collected from the PubChem platform. In parallel, the three-dimensional structure of the target protein dipeptidyl peptidase-4 in Protein Data Bank (PDB) format was obtained from the website of the Research Collaboratory for Structural Bioinformatics-PDB. AutoDock Vina software was used for the docking purpose. SwissADME and the admetSAR web server were used to further examine the top docked compounds for the pharmacological investigation. Results: Out of 100 phytochemicals, only 15 have shown better or comparable binding affinity above the benchmark medication, sitagliptin (−7.9 kcal/mol). All of these compounds were assessed to determine their viability as potential drugs by predicting their Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties. Two of these phytochemicals have proven their potential as medication candidates by passing the ADMET requirements. Conclusions: In silico studies help explore and find drug candidates among the enormous pool of phytochemicals and narrow down the screening process, saving time and money on experiments. In vitro and in vivo testing can be used in the future to further validate drug candidature.