Exploring Potential Non-steroidal Aromatase Inhibitors for Therapeutic Application against Estrogen-dependent Breast Cancer.

IF 1.5 4区医学 Q4 CHEMISTRY, MEDICINAL

Current computer-aided drug design Pub Date : 2023-01-01 DOI:10.2174/1573409919666230112170025

Khushboo Pandey, Kiran Bharat Lokhande, Achintya Saha, Arvind Goja, K Venkateswara Swamy, Shuchi Nagar

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引用次数: 0

Abstract

Background: Breast cancer is one of the most commonly diagnosed cancer types among women worldwide. Cytochrome P450 aromatase (CYP19A1) is an enzyme in vertebrates that selectively catalyzes the biosynthesis of estrogens from androgenic precursors. Researchers have increasingly focused on developing non-steroidal aromatase inhibitors (NSAIs) for their potential clinical use, avoiding steroidal side effects.

Objectives: The objective of the present work is to search for potential lead compounds from the ZINC database through various in silico approaches.

Methods: In the present study, compounds from the ZINC database were initially screened through receptor independent-based pharmacophore virtual screening. These screened molecules were subjected to several assessments, such as Lipinski rule of 5, SMART filtration, ADME prediction using SwissADME and lead optimization. Molecular docking was further applied to study the interaction of the filtered compounds with the active site of aromatase. Finally, the obtained hit compounds, consequently represented to be ideal lead candidates, were escalated to the MD simulations.

Results: The results indicated that the lead compounds might be potential anti-aromatase drug candidate.

Conclusion: The findings provided a valuable approach in developing novel anti-aromatase inhibitors for the treatment of ER+ breast cancer.

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探索潜在的非甾体芳香化酶抑制剂治疗雌激素依赖性乳腺癌的应用。

背景:乳腺癌是全世界女性中最常见的癌症类型之一。细胞色素P450芳香化酶(CYP19A1)是一种在脊椎动物中选择性催化雄激素前体生物合成雌激素的酶。研究人员越来越关注于开发非甾体芳香化酶抑制剂(NSAIs)用于潜在的临床应用，以避免甾体副作用。目的:本工作的目的是通过各种计算机方法从锌数据库中寻找潜在的铅化合物。方法:采用基于受体独立的药效团虚拟筛选方法对锌数据库中的化合物进行初步筛选。这些筛选的分子进行了几项评估，如Lipinski法则5,SMART过滤，使用SwissADME预测ADME和导联优化。进一步应用分子对接技术研究了过滤后的化合物与芳香化酶活性位点的相互作用。最后，获得的命中化合物被认为是理想的先导候选化合物，并升级到MD模拟。结果:这些先导化合物可能是潜在的抗芳香化酶候选药物。结论:研究结果为开发新型抗芳香化酶抑制剂治疗ER+乳腺癌提供了有价值的途径。

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

Current computer-aided drug design 医学-计算机：跨学科应用

CiteScore

3.70

自引率

5.90%

发文量

审稿时长

>12 weeks

期刊介绍： Aims & Scope Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews, original research articles and letter articles written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, theoretical chemistry; computational chemistry; computer and molecular graphics; molecular modeling; protein engineering; drug design; expert systems; general structure-property relationships; molecular dynamics; chemical database development and usage etc., providing excellent rationales for drug development.