来自多种抗肥胖靶点的植物成分的计算数据。

Computational data of phytoconstituents from on various anti-obesity targets.

作者信息

Gandhi Sejal P, Lokhande Kiran B, Swamy Venkateswara K, Nanda Rabindra K, Chitlange Sohan S

机构信息

Department of Pharmaceutical Chemistry, Dr. D. Y. Patil Institute of Pharmaceutical Sciences and Research, Pimpri, Pune, India.

Bioinformatics Research Laboratory, Dr. D. Y. Patil Biotechnology & Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Tathawade, Pune, India.

出版信息

Data Brief. 2019 May 16;24:103994. doi: 10.1016/j.dib.2019.103994. eCollection 2019 Jun.

DOI:10.1016/j.dib.2019.103994

PMID:31193691

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6538924/

Abstract

Molecular docking analysis of twenty two phytoconstituents from , against seven targets of obesity like pancreatic lipase, fat and obesity protein (FTO protein), cannabinoid receptor, hormones as ghrelin, leptin and protein as SCH1 and MCH1 is detailed in this data article. Chemical structures of phytoconstituents were downloaded from PubChem and protein structures were retrieved from RCSB protein databank. Docking was performed using FlexX software Lead IT version 2.3.2; Bio Solved IT. Visualization and analysis was done by Schrodinger maestro software. The docking score and interactions with important amino acids were analyzed and compared with marketed drug, orlistat. The findings suggest exploitation of best ligands experimentally to develop novel anti-obesity agent.

摘要

本文详细介绍了来自[具体来源未明确]的22种植物成分针对肥胖的七个靶点（如胰脂肪酶、脂肪和肥胖相关蛋白（FTO蛋白）、大麻素受体、激素如胃饥饿素、瘦素以及蛋白如SCH1和MCH1）的分子对接分析。植物成分的化学结构从PubChem下载，蛋白质结构从RCSB蛋白质数据库检索。使用FlexX软件Lead IT版本2.3.2进行对接；Bio Solved IT。通过Schrodinger maestro软件进行可视化和分析。分析对接分数以及与重要氨基酸的相互作用，并与市售药物奥利司他进行比较。研究结果表明通过实验开发最佳配体以研制新型抗肥胖药物。