Virtual screening and drug repurposing experiments to identify potential novel selective MAO-B inhibitors for Parkinson’s disease treatment,Molecular Diversity

当前位置： X-MOL 学术 › Mol. Divers. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Virtual screening and drug repurposing experiments to identify potential novel selective MAO-B inhibitors for Parkinson’s disease treatment
Molecular Diversity ( IF 3.9 ) Pub Date : 2020-11-25 , DOI: 10.1007/s11030-020-10155-6
Luminita Crisan ₁ , Daniela Istrate ₁ , Alina Bora ₁ , Liliana Pacureanu ₁

Affiliation

Abstract

The main study’s purpose is to detect novel natural products (NPs) that are potentially selective MAO-B inhibitors and, additionally, to computationally reposition the marketed drugs with a new therapeutic role for Parkinson’s disease. To reach the goals, 3D similarity search, docking, ADMETox, and drug repurposing approaches were employed. Thus, an unbiased benchmarking dataset was built including selective and nonselective inhibitors for MAO-B compliant with both ligand- and structure-based virtual screening approaches. A retrospective and prospective mining scenario was applied to SPECS NP and DrugBank databases to detect novel scaffolds with potential benefits for Parkinson’s disease patients. Out of the three best selected natural products, cardamomin showed excellently predicted drug-like properties, superior pharmacological profile, and specific interactions with MAO-B active site, indicating a potential selectivity over MAO-B. Two marketed drugs, fenamisal and monobenzone, were proposed as promising candidates repurposed for Parkinson’s disease. The application of shape, physicochemical, and electrostatic similarity searches protocol emerged as a plausible solution to explore MAO-B inhibitors selectivity. This protocol might serve as a rewarding tool in early drug discovery and can be extended to other protein targets.

Graphic abstract

中文翻译：

虚拟筛选和药物再利用实验，以确定用于帕金森病治疗的潜在新型选择性 MAO-B 抑制剂

摘要

主要研究的目的是检测具有潜在选择性 MAO-B 抑制剂的新型天然产物 (NPs)，此外，通过计算重新定位已上市药物对帕金森病的新治疗作用。为了达到目标，采用了 3D 相似性搜索、对接、ADMETox 和药物再利用方法。因此，建立了一个无偏见的基准数据集，包括 MAO-B 的选择性和非选择性抑制剂，符合基于配体和结构的虚拟筛选方法。将回顾性和前瞻性挖掘场景应用于 SPECS NP 和 DrugBank 数据库，以检测对帕金森病患者具有潜在益处的新型支架。在三种最佳选择的天然产品中，豆蔻素显示出极好的预测药物特性、优越的药理特性、以及与 MAO-B 活性位点的特定相互作用，表明对 MAO-B 的潜在选择性。两种上市药物，fenamisal 和 Monobenzone，被提议作为重新用于帕金森病的有希望的候选药物。形状、物理化学和静电相似性搜索协议的应用成为探索 MAO-B 抑制剂选择性的合理解决方案。该协议可作为早期药物发现的有益工具，并可扩展到其他蛋白质靶标。静电相似性搜索协议成为探索 MAO-B 抑制剂选择性的合理解决方案。该协议可作为早期药物发现的有益工具，并可扩展到其他蛋白质靶标。静电相似性搜索协议成为探索 MAO-B 抑制剂选择性的合理解决方案。该协议可作为早期药物发现的有益工具，并可扩展到其他蛋白质靶标。

图形摘要

更新日期：2020-11-25

点击分享查看原文

点击收藏

阅读更多本刊最新论文本刊介绍/投稿指南11