研究核糖体-RNA:蛋白质相互作用和人工智能辅助发现新型抑制剂

IF 1.9 4区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY
Monishka Battula, Shovonlal Bhowmick, Pritee Chunarkar Patil, Gaber E. Eldesoky, Rupesh V. Chikhale
{"title":"研究核糖体-RNA:蛋白质相互作用和人工智能辅助发现新型抑制剂","authors":"Monishka Battula,&nbsp;Shovonlal Bhowmick,&nbsp;Pritee Chunarkar Patil,&nbsp;Gaber E. Eldesoky,&nbsp;Rupesh V. Chikhale","doi":"10.1002/slct.202403459","DOIUrl":null,"url":null,"abstract":"<p>This study explores novel ligands that potentially offer superior binding and stability compared to the peptidic molecules currently associated with the ribosomal RNA–protein complex. This study aims to elucidate the molecular mechanisms underlying protein–RNA interactions and their disruptions, identify potential therapeutic targets, and explore novel compounds capable of modulating these interactions for therapeutic benefit. We conducted molecular docking and dynamics simulations using advanced computational tools such as rDock and REINVENT4 to generate novel compounds. ADMET analysis confirmed the chosen compound's advantageous pharmacokinetic attributes and safety profiles. Among the generated compounds, C21, C23, C56, C120, and C195 were identified as the best candidate molecules for inhibiting protein–RNA interactions. These ligands demonstrated superior binding affinity and stability, outperforming the peptidic molecules bound to the reference protein–RNA–peptide complex structure.The ligand molecules were notable for their ability to settle into low–energy states, indicating a strong potential to outperform the peptide bound in the reference protein–RNA–peptide complex structure. These findings highlight the capability of these ligands to serve as more effective therapeutic agents and as superior alternatives to the current peptidic molecules, with implications for developing novel therapeutic strategies targeting protein–RNA interactions.</p>","PeriodicalId":146,"journal":{"name":"ChemistrySelect","volume":"9 43","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investigating the Ribosomal-RNA: Protein Interactions and AI-Assisted Discovery of Novel Inhibitors\",\"authors\":\"Monishka Battula,&nbsp;Shovonlal Bhowmick,&nbsp;Pritee Chunarkar Patil,&nbsp;Gaber E. Eldesoky,&nbsp;Rupesh V. Chikhale\",\"doi\":\"10.1002/slct.202403459\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This study explores novel ligands that potentially offer superior binding and stability compared to the peptidic molecules currently associated with the ribosomal RNA–protein complex. This study aims to elucidate the molecular mechanisms underlying protein–RNA interactions and their disruptions, identify potential therapeutic targets, and explore novel compounds capable of modulating these interactions for therapeutic benefit. We conducted molecular docking and dynamics simulations using advanced computational tools such as rDock and REINVENT4 to generate novel compounds. ADMET analysis confirmed the chosen compound's advantageous pharmacokinetic attributes and safety profiles. Among the generated compounds, C21, C23, C56, C120, and C195 were identified as the best candidate molecules for inhibiting protein–RNA interactions. These ligands demonstrated superior binding affinity and stability, outperforming the peptidic molecules bound to the reference protein–RNA–peptide complex structure.The ligand molecules were notable for their ability to settle into low–energy states, indicating a strong potential to outperform the peptide bound in the reference protein–RNA–peptide complex structure. These findings highlight the capability of these ligands to serve as more effective therapeutic agents and as superior alternatives to the current peptidic molecules, with implications for developing novel therapeutic strategies targeting protein–RNA interactions.</p>\",\"PeriodicalId\":146,\"journal\":{\"name\":\"ChemistrySelect\",\"volume\":\"9 43\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ChemistrySelect\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/slct.202403459\",\"RegionNum\":4,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ChemistrySelect","FirstCategoryId":"92","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/slct.202403459","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

与目前与核糖体 RNA 蛋白复合物相关联的多肽分子相比,本研究探索的新型配体可能具有更强的结合力和稳定性。本研究旨在阐明蛋白质-RNA相互作用及其破坏的分子机制,确定潜在的治疗靶点,并探索能够调节这些相互作用以达到治疗效果的新型化合物。我们使用 rDock 和 REINVENT4 等先进计算工具进行了分子对接和动力学模拟,以生成新型化合物。ADMET 分析证实了所选化合物的药代动力学属性和安全性。在生成的化合物中,C21、C23、C56、C120 和 C195 被确定为抑制蛋白质-RNA 相互作用的最佳候选分子。这些配体表现出卓越的结合亲和力和稳定性,优于与参考蛋白质-RNA-肽复合物结构结合的多肽分子。这些配体分子的显著特点是能够稳定在低能状态,这表明它们具有优于与参考蛋白质-RNA-肽复合物结构结合的多肽的强大潜力。这些发现凸显了这些配体作为更有效的治疗剂和当前多肽分子的优越替代品的能力,对开发针对蛋白质-RNA相互作用的新型治疗策略具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Investigating the Ribosomal-RNA: Protein Interactions and AI-Assisted Discovery of Novel Inhibitors

Investigating the Ribosomal-RNA: Protein Interactions and AI-Assisted Discovery of Novel Inhibitors

This study explores novel ligands that potentially offer superior binding and stability compared to the peptidic molecules currently associated with the ribosomal RNA–protein complex. This study aims to elucidate the molecular mechanisms underlying protein–RNA interactions and their disruptions, identify potential therapeutic targets, and explore novel compounds capable of modulating these interactions for therapeutic benefit. We conducted molecular docking and dynamics simulations using advanced computational tools such as rDock and REINVENT4 to generate novel compounds. ADMET analysis confirmed the chosen compound's advantageous pharmacokinetic attributes and safety profiles. Among the generated compounds, C21, C23, C56, C120, and C195 were identified as the best candidate molecules for inhibiting protein–RNA interactions. These ligands demonstrated superior binding affinity and stability, outperforming the peptidic molecules bound to the reference protein–RNA–peptide complex structure.The ligand molecules were notable for their ability to settle into low–energy states, indicating a strong potential to outperform the peptide bound in the reference protein–RNA–peptide complex structure. These findings highlight the capability of these ligands to serve as more effective therapeutic agents and as superior alternatives to the current peptidic molecules, with implications for developing novel therapeutic strategies targeting protein–RNA interactions.

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
ChemistrySelect
ChemistrySelect Chemistry-General Chemistry
CiteScore
3.30
自引率
4.80%
发文量
1809
审稿时长
1.6 months
期刊介绍: ChemistrySelect is the latest journal from ChemPubSoc Europe and Wiley-VCH. It offers researchers a quality society-owned journal in which to publish their work in all areas of chemistry. Manuscripts are evaluated by active researchers to ensure they add meaningfully to the scientific literature, and those accepted are processed quickly to ensure rapid online publication.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信