Prediction of compounds with antiosteoporosis activity in Chrysophyllum cainito L. leaves through in silico approach

Abstract

Objectives: Estrogen deficiency causes various health problems in postmenopausal women, including osteoporosis. Phytoestrogen emerged as a potential alternative of estrogen with minimum side effects. The aims of this study were to analyze the metabolite profiling results of various extract of Chyrsophyllum cainito L. leaves, which contain phytoestrogen, through in silico study against 3OLS protein, an X-ray protein of ERβ, so it can predict the types of the phytoestrogen contents which have antiosteoporosis property.

Methods: In silico analysis was carried out for the compounds from the metabolite profiling data of C. cainito leaves from our previous study. The structure compounds from metabolite profiling results of various extract of C. cainito leaves were prepared with Avogadro 1.0.1 software, molecular docking was done using PyRx 0.8 software, and Biovia Discovery Studio Visualizer 2016 software was used to visualize the structure of compounds against 3OLS protein. The physicochemical characteristics of the compounds were analyzed using the SwissADME web tool.

Results: From in silico studies, it was known that there were total 11 compounds in C. cainito leaves that predicted as phytoestrogens which have ERβ agonist properties against 3OLS protein. The ERβ agonist was a compound that has parameters similar to 17β-estradiol in its interaction with 3OLS protein, which has a pharmacophore distance of 10.862 Å, and binding to amino acids His 475 and Glu 305 or Arg 346 at receptor-ligand docking simulation.

Conclusions: C. cainito leaves contain 11 compounds that are predicted to be phytoestrogens with ERβ agonist properties, which is responsible for antiosteoporosis activity.

Keywords: Chrysophyllum cainito L.; antiosteoporosis; in silico; phytoestrogen.