In silico approach of antidiabetic compounds from Caesalpinia crista seed through docking analysis and ADMET predictions

Abstract

Abstract Caesalpinia crista (Fabaceae) is one of the herbs traditionally used as a drug for the diabetic. This study aimed to discover bioactivity of the α-caesalpin compound from Caesalpinia crista for antidiabetic based on reverse docking studies. Structures of chemical constituents of Caesalpina crista (α-caesalpin) was collected from published literature. The water molecule and ligands were removed by using PyMOL v1.7.4.5 Software (Schrödinger). Molecular docking experiments were performed using the PyRx 0.8 software. Prediction and significant descriptors of Physicochemical Properties, Lipophilicity, Pharmacokinetics and Druglikeness properties of the compounds were predicted using Swissadme. The results showed that α-caesalpin has greater potential as an antidiabetic based on its binding affinity and intermolecular interactions. The binding affinity of α-caesalpin with NOS 3 protein is -7.9, while binding affinity NOS 3 with the control compound β-estradiol is -10.1. AMES Test showed that α-caesalpin is not potential mutagens and not carcinogens. Druglikeness prediction showed that α-caesalpin fulfil the rules of Lipinski, Ghose, Veber, Egan and Muegge with 0.55 Bioavailability Score.

Access to Document

Other files and links

• Link to publication in Scopus
• Open Access Version Available

Fingerprint