Identification of Small Inhibitors for Human Metadherin, an Oncoprotein, through in silico Approach.

IF 1.5 4区 医学 Q4 CHEMISTRY, MEDICINAL Current computer-aided drug design Pub Date : 2023-01-01 DOI:10.2174/1573409919666230110112356
Arif Ali Khattak, Ayaz Ahmad, Haider Ali Khattak, Muhammad Zafar Irshad Khan
{"title":"Identification of Small Inhibitors for Human Metadherin, an Oncoprotein, through <i>in silico</i> Approach.","authors":"Arif Ali Khattak,&nbsp;Ayaz Ahmad,&nbsp;Haider Ali Khattak,&nbsp;Muhammad Zafar Irshad Khan","doi":"10.2174/1573409919666230110112356","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>Cancer is a disease that takes lives of thousands of people each year. There are more than 100 different types of cancers known to man. This fatal disease is one of the leading causes of death today.</p><p><strong>Background: </strong>Astrocyte elevated gene-1(AEG-1)/Metadherin (MTDH) activates multiple oncogenic signaling pathways and leads to different types of cancers. MTDH interacting with staphylococcal nuclease domain containing 1(SND1) supports the survival and growth of mammary epithelial cells under oncogenic conditions.</p><p><strong>Objective: </strong>Silencing MTDH or SND1 individually or disrupting their interaction compromises the tumorigenic potential of tumor-initiating cells. The aim of our present study was to investigate novel interactions of staphylococcal nuclease domain containing 1 (SND1) binding domain of AEG-1/MTDH with different lead compounds through molecular docking approach using MOE software.</p><p><strong>Methods: </strong>Molecular docking was done by docking the ChemBridge database against important residues of MTDH involved in interaction with SND1. After docking the whole ChemBridge database, the top 200 interactive compounds were selected based on docking scores. After applying Lipinski's rule, all the remaining chosen compounds were studied on the basis of binding affinity, binding energy, docking score and protein-ligand interactions. Finally, 10 compounds showing multiple interactions with different amino acid residues were selected as the top interacting compounds.</p><p><strong>Results: </strong>Three compounds were selected for simulation studies after testing these compounds using topkat toxicity and ADMET studies. The simulation study indicated that compound 32538601 is a lead compound for inhibiting MTDH-SND1 complex formation.</p><p><strong>Conclusion: </strong>These novels, potent inhibitors of MTDH-SND1 complex can ultimately help us in controlling cancer up to some extent.</p>","PeriodicalId":10886,"journal":{"name":"Current computer-aided drug design","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current computer-aided drug design","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/1573409919666230110112356","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 2

Abstract

Aims: Cancer is a disease that takes lives of thousands of people each year. There are more than 100 different types of cancers known to man. This fatal disease is one of the leading causes of death today.

Background: Astrocyte elevated gene-1(AEG-1)/Metadherin (MTDH) activates multiple oncogenic signaling pathways and leads to different types of cancers. MTDH interacting with staphylococcal nuclease domain containing 1(SND1) supports the survival and growth of mammary epithelial cells under oncogenic conditions.

Objective: Silencing MTDH or SND1 individually or disrupting their interaction compromises the tumorigenic potential of tumor-initiating cells. The aim of our present study was to investigate novel interactions of staphylococcal nuclease domain containing 1 (SND1) binding domain of AEG-1/MTDH with different lead compounds through molecular docking approach using MOE software.

Methods: Molecular docking was done by docking the ChemBridge database against important residues of MTDH involved in interaction with SND1. After docking the whole ChemBridge database, the top 200 interactive compounds were selected based on docking scores. After applying Lipinski's rule, all the remaining chosen compounds were studied on the basis of binding affinity, binding energy, docking score and protein-ligand interactions. Finally, 10 compounds showing multiple interactions with different amino acid residues were selected as the top interacting compounds.

Results: Three compounds were selected for simulation studies after testing these compounds using topkat toxicity and ADMET studies. The simulation study indicated that compound 32538601 is a lead compound for inhibiting MTDH-SND1 complex formation.

Conclusion: These novels, potent inhibitors of MTDH-SND1 complex can ultimately help us in controlling cancer up to some extent.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过计算机方法鉴定人肿瘤蛋白Metadherin的小抑制剂。
目的:癌症是一种每年夺去数千人生命的疾病。人类已知的癌症有100多种。这种致命的疾病是当今导致死亡的主要原因之一。背景:星形胶质细胞升高基因-1(AEG-1)/Metadherin (MTDH)激活多种致癌信号通路,导致不同类型的癌症。MTDH与葡萄球菌核酸酶结构域1(SND1)相互作用,支持乳腺上皮细胞在致癌条件下的存活和生长。目的:单独沉默MTDH或SND1或破坏它们的相互作用会损害肿瘤启动细胞的致瘤潜能。本研究利用MOE软件,通过分子对接的方法,研究葡萄球菌AEG-1/MTDH中含有1 (SND1)结合域的核酸酶结构域与不同先导化合物的新型相互作用。方法:将ChemBridge数据库与参与SND1相互作用的MTDH的重要残基进行分子对接。对接整个ChemBridge数据库后,根据对接得分选择出交互作用最强的200个化合物。应用Lipinski规则后,根据结合亲和力、结合能、对接评分和蛋白质与配体的相互作用对所有选择的化合物进行研究。最后,筛选出10个与不同氨基酸残基具有多重相互作用的化合物作为最易相互作用的化合物。结果:通过topkat毒性和ADMET研究,选择了三种化合物进行模拟研究。模拟研究表明,化合物32538601是抑制MTDH-SND1复合物形成的先导化合物。结论:这些新的、有效的MTDH-SND1复合物抑制剂最终可以在一定程度上帮助我们控制癌症。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
Detection of Brain Tumor Employing Residual Network-based Optimized Deep Learning Computer-Aided Drug Discovery Approaches in the Identification of Anticancer Drugs from Natural Products: A Review An Enhanced Computational Approach Using Multi-kernel Positive Unlabeled Learning for Predicting Drug-target Interactions Study on the Mechanism of Competing Endogenous Network of 'Scutellaria barbata D.Don-Houttuynia cordata- Radix Scutellariae' in the Treatment of NSCLC based on Bioinformatics, Molecular Dynamics and Experimental Verification Designing a Novel di-epitope Diphtheria Vaccine: A Rational Structural Immunoinformatics Approach
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1