A Rationalized Approach to Design and Discover Novel Non-steroidal Derivatives through Computational Aid for the Treatment of Prostate Cancer.

IF 1.5 4区 医学 Q4 CHEMISTRY, MEDICINAL
Shubham Kumar, Pinky Arora, Pankaj Wadhwa, Paranjeet Kaur
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引用次数: 0

Abstract

Background: Prostate cancer is one of the most prevalent cancers in men, leading to the second most common cause of death in men. Despite the availability of multiple treatments, the prevalence of prostate cancer remains high. Steroidal antagonists are associated with poor bioavailability and side effects, while non-steroidal antagonists show serious side effects, such as gynecomastia. Therefore, there is a need for a potential candidate for the treatment of prostate cancer with better bioavailability, good therapeutic effects, and minimal side effects.

Objective: This current research work focused on identifying a novel non-steroidal androgen receptor antagonist through computational tools, such as docking and in silico ADMET analysis.

Methods: Molecules were designed based on a literature survey, followed by molecular docking of all designed compounds and ADMET analysis of the hit compounds.

Results: A library of 600 non-steroidal derivatives (cis and trans) was designed, and molecular docking was performed in the active site of the androgen receptor (PDBID: 1Z95) using Auto- Dock Vina 1.5.6. Docking studies resulted in 15 potent hits, which were then subjected to ADME analysis using SwissADME. ADME analysis predicted three compounds (SK-79, SK-109, and SK-169) with the best ADME profile and better bioavailability. Toxicity studies using Protox-II were performed on the three best compounds (SK-79, SK-109, and SK-169), which predicted ideal toxicity for these lead compounds.

Conclusion: This research work will provide ample opportunities to explore medicinal and computational research areas. It will facilitate the development of novel androgen receptor antagonists in future experimental studies.

通过计算辅助设计和发现治疗前列腺癌的新型非类固醇衍生物的合理方法。
背景:前列腺癌是男性最常见的癌症之一,也是导致男性死亡的第二大原因。尽管有多种治疗方法,但前列腺癌的发病率仍然很高。类固醇拮抗剂的生物利用度差,副作用大,而非类固醇拮抗剂则会产生严重的副作用,如妇科炎症。因此,需要一种生物利用度更好、治疗效果好、副作用小的潜在候选药物来治疗前列腺癌:目前这项研究工作的重点是通过计算工具,如对接和硅学 ADMET 分析,确定一种新型非类固醇雄激素受体拮抗剂:方法:根据文献调查设计分子,然后对所有设计的化合物进行分子对接,并对命中的化合物进行 ADMET 分析:结果:设计了一个包含 600 个非甾体衍生物(顺式和反式)的化合物库,并使用 Auto- Dock Vina 1.5.6 在雄激素受体(PDBID:1Z95)的活性位点进行了分子对接。对接研究产生了 15 个强效化合物,然后使用 SwissADME 对其进行了 ADME 分析。ADME 分析预测出三种化合物(SK-79、SK-109 和 SK-169)具有最佳的 ADME 特征和更好的生物利用度。利用 Protox-II 对三种最佳化合物(SK-79、SK-109 和 SK-169)进行了毒性研究,结果表明这些先导化合物具有理想的毒性:这项研究工作将为探索药物和计算研究领域提供大量机会。结论:这项研究工作将为探索药物和计算研究领域提供大量机会,有助于在未来的实验研究中开发新型雄激素受体拮抗剂。
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
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
46
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.
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