Laboratory of Drug Design and Discovery, Department of Pharmaceutical Sciences, Dr Harisingh Gour University, Sagar 470003, Madhya Pradesh, India.
Laboratory of Drug Design and Discovery, Department of Pharmaceutical Sciences, Dr Harisingh Gour University, Sagar 470003, Madhya Pradesh, India.
Phytomedicine. 2021 May;85:153523. doi: 10.1016/j.phymed.2021.153523. Epub 2021 Feb 20.
Extensive research over the past several decades, explored that the natural compounds contain different plant secondary metabolites and have the potential to inhibit breast cancer resistance protein (BCRP).
To identify crucial molecular fingerprints of some natural products for the inhibition of breast cancer resistance protein and also to screen out some potent natural BCRP inhibitors.
Multiple modelling strategies were applied with three main mottos: (a) Generation of robust classification models to identify the linear and non-linear relationships among the natural compounds and the inhibition of BCRP, (b) Identification of important structural fingerprints that modulate BCRP inhibition and screening of natural database to find the probable hit molecules, (c) Comprehensive ligand-receptor interactions analysis of those against the putative breast cancer resistant protein through molecular docking analysis.
Monte Carlo optimization and SPCI analysis was used to identify important structural fingerprints. QSARCo. and swissADME analysis were used for screening and prediction of hits. Finally, docking analysis was performed for interaction study.
In this study, some important structural fingerprints of BCRP inhibitors were identified. Additionally, eleven natural anti-cancer compounds were predicted to be active against the BCRP and also satisfy the different drug-likeliness properties. Among them, apigenin was found to have better binding affinities against the putative target as obtained from molecular docking analysis.
This study is an attempt to understand about the molecular fingerprints of natural compounds for the inhibition of BCRP and also to dig out some novel natural inhibitors against BCRP.
在过去几十年的广泛研究中，探索了天然化合物包含不同的植物次生代谢物，并具有抑制乳腺癌耐药蛋白（BCRP）的潜力。
确定一些天然产物抑制乳腺癌耐药蛋白的关键分子指纹，并筛选出一些有效的天然 BCRP 抑制剂。
应用了多种建模策略，主要有三个宗旨：（a）生成强大的分类模型，以识别天然化合物与 BCRP 抑制之间的线性和非线性关系，（b）确定调节 BCRP 抑制的重要结构指纹，并筛选天然数据库以寻找可能的命中分子，（c）通过分子对接分析对那些针对假定的乳腺癌耐药蛋白进行综合配体-受体相互作用分析。
使用蒙特卡罗优化和 SPCI 分析来识别重要的结构指纹。QSARCo.和 swissADME 分析用于筛选和预测命中。最后，进行对接分析以进行相互作用研究。
在这项研究中，确定了 BCRP 抑制剂的一些重要结构指纹。此外，预测了十一种天然抗癌化合物对 BCRP 的活性，并且还满足不同的药物相似性特性。其中，从分子对接分析中发现，芹菜素对假定的靶标具有更好的结合亲和力。
这项研究旨在了解天然化合物抑制 BCRP 的分子指纹，并挖掘出一些针对 BCRP 的新型天然抑制剂。
