Pharmacophore Modelling and Virtual Screening Studies for the Discovery of Potential Natural Products Based PDE1B Inhibitor Lead Compounds.

Q3 Psychology

Central nervous system agents in medicinal chemistry Pub Date : 2021-01-01 DOI:10.2174/1871524922666211231115638

Teng Woei Shy, Anand Gaurav

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引用次数: 2

Abstract

Aim: The aim of the present study was to apply pharmacophore based virtual screening to a natural product database to identify potential PDE1B inhibitor lead compounds for neurodegenerative and neuropsychiatric disorders.

Background: Neurodegenerative and neuropsychiatric disorders are a major health burden globally. The existing therapies do not provide optimal relief and are associated with substantial adverse effects. This has resulted in a huge unmet medical need for newer and more effective therapies for these disorders. Phosphodiesterase (PDEs) enzymes have been identified as potential targets of drugs for neurodegenerative and neuropsychiatric disorders, and one of the subtypes, i.e., PDE1B, accounts for more than 90 % of total brain PDE activity associated with learning and memory process, making it an interesting drug target for the treatment of neurodegenerative disorders.

Objectives: The present study has been conducted to identify potential PDE1B inhibitor lead compounds from the natural product database.

Methods: Ligand-based pharmacophore models were generated and validated; they were then employed for virtual screening of Universal Natural Products Database (UNPD) followed by docking with PDE1B to identify the best hit compound.

Results: Virtual screening led to the identification of 85 compounds which were then docked into the active site of PDE1B. Out of the 85 compounds, six showed a higher affinity for PDE1B than the standard PDE1B inhibitors. The top scoring compound was identified as Cedreprenone.

Conclusion: Virtual screening of UNPD using Ligand based pharmacophore led to the identification of Cedreprenone, a potential new natural PDE1B inhibitor lead compound.

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基于PDE1B抑制剂先导化合物的潜在天然产物药效团建模和虚拟筛选研究。

目的:本研究的目的是将基于药效团的虚拟筛选应用于天然产物数据库，以识别神经退行性和神经精神疾病的潜在PDE1B抑制剂先导化合物。背景:神经退行性疾病和神经精神疾病是全球主要的健康负担。现有的治疗方法不能提供最佳的缓解，并伴有大量的不良反应。这导致了对这些疾病的更新和更有效的治疗方法的巨大未满足的医疗需求。磷酸二酯酶(PDEs)已被确定为神经退行性疾病和神经精神疾病药物的潜在靶点，其中一种亚型，即PDE1B，占与学习和记忆过程相关的脑PDE总活性的90%以上，使其成为治疗神经退行性疾病的有趣药物靶点。目的:本研究旨在从天然产物数据库中鉴定潜在的PDE1B抑制剂先导化合物。方法:建立基于配体的药效团模型并进行验证;然后将它们用于通用天然产物数据库(UNPD)的虚拟筛选，然后与PDE1B对接以确定最佳命中化合物。结果:通过虚拟筛选，鉴定出85个化合物，并将其连接到PDE1B的活性位点。在85种化合物中，有6种化合物对PDE1B的亲和力高于标准PDE1B抑制剂。得分最高的化合物被确定为cedrepreone。结论:利用基于配体的药效团对UNPD进行虚拟筛选，鉴定出一种潜在的新型天然PDE1B抑制剂先导化合物Cedreprenone。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Central nervous system agents in medicinal chemistry Psychology-Neuropsychology and Physiological Psychology

CiteScore

2.10

自引率

0.00%

发文量

期刊介绍： Central Nervous System Agents in Medicinal Chemistry aims to cover all the latest and outstanding developments in medicinal chemistry and rational drug design for the discovery of new central nervous system agents. Containing a series of timely in-depth reviews written by leaders in the field covering a range of current topics, Central Nervous System Agents in Medicinal Chemistry is an essential journal for every medicinal chemist who wishes to be kept informed and up-to-date with the latest and most important developments in the field.