通过分子模拟探索激酶抑制剂药物重新定位的可能性**

IF 2.8 4区 医学 Q3 CHEMISTRY, MEDICINAL Molecular Informatics Pub Date : 2024-06-21 DOI:10.1002/minf.202300336
Qing‐Xin Wang, Jiao Cai, Zi‐Jun Chen, Jia‐Chuan Liu, Jing‐Jing Wang, Hai Zhou, Qing‐Qing Li, Zi‐Xuan Wang, Yi‐Bo Wang, Zhen‐Jiang Tong, Jin Yang, Tian‐Hua Wei, Meng‐Yuan Zhang, Yun Zhou, Wei‐Chen Dai, Ning Ding, Xue‐Jiao Leng, Xiao‐Ying Yin, Shan‐Liang Sun, Yan‐Cheng Yu, Nian‐Guang Li, Zhi‐Hao Shi
{"title":"通过分子模拟探索激酶抑制剂药物重新定位的可能性**","authors":"Qing‐Xin Wang, Jiao Cai, Zi‐Jun Chen, Jia‐Chuan Liu, Jing‐Jing Wang, Hai Zhou, Qing‐Qing Li, Zi‐Xuan Wang, Yi‐Bo Wang, Zhen‐Jiang Tong, Jin Yang, Tian‐Hua Wei, Meng‐Yuan Zhang, Yun Zhou, Wei‐Chen Dai, Ning Ding, Xue‐Jiao Leng, Xiao‐Ying Yin, Shan‐Liang Sun, Yan‐Cheng Yu, Nian‐Guang Li, Zhi‐Hao Shi","doi":"10.1002/minf.202300336","DOIUrl":null,"url":null,"abstract":"Kinases, a class of enzymes controlling various substrates phosphorylation, are pivotal in both physiological and pathological processes. Although their conserved ATP binding pockets pose challenges for achieving selectivity, this feature offers opportunities for drug repositioning of kinase inhibitors (KIs). This study presents a cost‐effective in silico prediction of KIs drug repositioning via analyzing cross‐docking results. We established the KIs database (278 unique KIs, 1834 bioactivity data points) and kinases database (357 kinase structures categorized by the DFG motif) for carrying out cross‐docking. Comparative analysis of the docking scores and reported experimental bioactivity revealed that the Atypical, TK, and TKL superfamilies are suitable for drug repositioning. Among these kinase superfamilies, Olverematinib, Lapatinib, and Abemaciclib displayed enzymatic activity in our focused AKT‐PI3K‐mTOR pathway with IC<jats:sub>50</jats:sub> values of 3.3, 3.2 and 5.8 μM. Further cell assays showed IC<jats:sub>50</jats:sub> values of 0.2, 1.2 and 0.6 μM in tumor cells. The consistent result between prediction and validation demonstrated that repositioning KIs via <jats:italic>in silico</jats:italic> method is feasible.","PeriodicalId":18853,"journal":{"name":"Molecular Informatics","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring drug repositioning possibilities of kinase inhibitors via molecular simulation**\",\"authors\":\"Qing‐Xin Wang, Jiao Cai, Zi‐Jun Chen, Jia‐Chuan Liu, Jing‐Jing Wang, Hai Zhou, Qing‐Qing Li, Zi‐Xuan Wang, Yi‐Bo Wang, Zhen‐Jiang Tong, Jin Yang, Tian‐Hua Wei, Meng‐Yuan Zhang, Yun Zhou, Wei‐Chen Dai, Ning Ding, Xue‐Jiao Leng, Xiao‐Ying Yin, Shan‐Liang Sun, Yan‐Cheng Yu, Nian‐Guang Li, Zhi‐Hao Shi\",\"doi\":\"10.1002/minf.202300336\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Kinases, a class of enzymes controlling various substrates phosphorylation, are pivotal in both physiological and pathological processes. Although their conserved ATP binding pockets pose challenges for achieving selectivity, this feature offers opportunities for drug repositioning of kinase inhibitors (KIs). This study presents a cost‐effective in silico prediction of KIs drug repositioning via analyzing cross‐docking results. We established the KIs database (278 unique KIs, 1834 bioactivity data points) and kinases database (357 kinase structures categorized by the DFG motif) for carrying out cross‐docking. Comparative analysis of the docking scores and reported experimental bioactivity revealed that the Atypical, TK, and TKL superfamilies are suitable for drug repositioning. Among these kinase superfamilies, Olverematinib, Lapatinib, and Abemaciclib displayed enzymatic activity in our focused AKT‐PI3K‐mTOR pathway with IC<jats:sub>50</jats:sub> values of 3.3, 3.2 and 5.8 μM. Further cell assays showed IC<jats:sub>50</jats:sub> values of 0.2, 1.2 and 0.6 μM in tumor cells. The consistent result between prediction and validation demonstrated that repositioning KIs via <jats:italic>in silico</jats:italic> method is feasible.\",\"PeriodicalId\":18853,\"journal\":{\"name\":\"Molecular Informatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular Informatics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/minf.202300336\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Informatics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/minf.202300336","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0

摘要

激酶是一类控制各种底物磷酸化的酶,在生理和病理过程中都起着关键作用。尽管激酶保守的 ATP 结合口袋给实现选择性带来了挑战,但这一特点为激酶抑制剂(KIs)的药物重新定位提供了机会。本研究通过分析交叉对接结果,提出了一种经济有效的 KIs 药物重新定位的硅学预测方法。我们建立了 KIs 数据库(278 种独特的 KIs,1834 个生物活性数据点)和激酶数据库(按 DFG 主题分类的 357 种激酶结构),用于进行交叉对接。对对接得分和实验生物活性的比较分析表明,非典型激酶超家族、TK 激酶超家族和 TKL 激酶超家族适合药物重新定位。在这些激酶超家族中,Olverematinib、Lapatinib 和 Abemaciclib 在我们重点研究的 AKT-PI3K-mTOR 通路中显示出酶活性,IC50 值分别为 3.3、3.2 和 5.8 μM。进一步的细胞检测显示,肿瘤细胞的 IC50 值分别为 0.2、1.2 和 0.6 μM。预测和验证结果的一致性表明,通过硅学方法重新定位 KIs 是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Exploring drug repositioning possibilities of kinase inhibitors via molecular simulation**
Kinases, a class of enzymes controlling various substrates phosphorylation, are pivotal in both physiological and pathological processes. Although their conserved ATP binding pockets pose challenges for achieving selectivity, this feature offers opportunities for drug repositioning of kinase inhibitors (KIs). This study presents a cost‐effective in silico prediction of KIs drug repositioning via analyzing cross‐docking results. We established the KIs database (278 unique KIs, 1834 bioactivity data points) and kinases database (357 kinase structures categorized by the DFG motif) for carrying out cross‐docking. Comparative analysis of the docking scores and reported experimental bioactivity revealed that the Atypical, TK, and TKL superfamilies are suitable for drug repositioning. Among these kinase superfamilies, Olverematinib, Lapatinib, and Abemaciclib displayed enzymatic activity in our focused AKT‐PI3K‐mTOR pathway with IC50 values of 3.3, 3.2 and 5.8 μM. Further cell assays showed IC50 values of 0.2, 1.2 and 0.6 μM in tumor cells. The consistent result between prediction and validation demonstrated that repositioning KIs via in silico method is feasible.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Molecular Informatics
Molecular Informatics CHEMISTRY, MEDICINAL-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.30
自引率
2.80%
发文量
70
审稿时长
3 months
期刊介绍: Molecular Informatics is a peer-reviewed, international forum for publication of high-quality, interdisciplinary research on all molecular aspects of bio/cheminformatics and computer-assisted molecular design. Molecular Informatics succeeded QSAR & Combinatorial Science in 2010. Molecular Informatics presents methodological innovations that will lead to a deeper understanding of ligand-receptor interactions, macromolecular complexes, molecular networks, design concepts and processes that demonstrate how ideas and design concepts lead to molecules with a desired structure or function, preferably including experimental validation. The journal''s scope includes but is not limited to the fields of drug discovery and chemical biology, protein and nucleic acid engineering and design, the design of nanomolecular structures, strategies for modeling of macromolecular assemblies, molecular networks and systems, pharmaco- and chemogenomics, computer-assisted screening strategies, as well as novel technologies for the de novo design of biologically active molecules. As a unique feature Molecular Informatics publishes so-called "Methods Corner" review-type articles which feature important technological concepts and advances within the scope of the journal.
期刊最新文献
Cover Picture: (Mol. Inf. 9/2024) The freedom space - a new set of commercially available molecules for hit discovery. Cover Picture: (Mol. Inf. 8/2024) Chemography-guided analysis of a reaction path network for ethylene hydrogenation with a model Wilkinson's catalyst. Sulfotransferase-mediated phase II drug metabolism prediction of substrates and sites using accessibility and reactivity-based algorithms.
×
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