通过化学信息学和网络药理学重新利用cofilin靶向化合物治疗缺血性卒中。

IF 4.8 3区 医学 Q2 CHEMISTRY, MEDICINAL
Pharmaceuticals Pub Date : 2025-09-04 DOI:10.3390/ph18091323
Saleh I Alaqel, Abida Khan, Mashael N Alanazi, Naira Nayeem, Hayet Ben Khaled, Mohd Imran
{"title":"通过化学信息学和网络药理学重新利用cofilin靶向化合物治疗缺血性卒中。","authors":"Saleh I Alaqel, Abida Khan, Mashael N Alanazi, Naira Nayeem, Hayet Ben Khaled, Mohd Imran","doi":"10.3390/ph18091323","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background/Objectives</b>: Cofilin, a key regulator of actin cytoskeleton dynamics, contributes to neuroinflammation, synaptic damage, and blood-brain barrier disruption in ischemic stroke. Despite its established role in stroke pathology, cofilin remains largely untargeted by existing therapeutics. This study aimed to identify potential cofilin-binding molecules by repurposing <i>LIMK1</i> inhibitors through an integrated computational strategy. <b>Methods</b>: A cheminformatics pipeline combined QSAR modeling with four molecular fingerprint sets and multiple machine learning algorithms. The best-performing QSAR model (substructure-Random Forest) achieved R<sup>2</sup>_train = 0.8747 and R<sup>2</sup>_test = 0.8078, supporting the reliability of compound prioritization. Feature importance was assessed through SHAP analysis. Top candidates were subjected to molecular docking against cofilin, followed by 300 ns molecular dynamics simulations, MM-GBSA binding energy calculations, principal component analysis (PCA), and dynamic cross-correlation matrix (DCCM) analyses. Network pharmacology identified overlapping targets between selected compounds and stroke-related genes. <b>Results</b>: Three compounds, CHEMBL3613624, ZINC000653853876, and Gandotinib, were prioritized based on QSAR performance, binding affinity (-6.68, -6.25, and -5.61 Kcal/mol, respectively), and structural relevance. Docking studies confirmed key interactions with Asp98 and His133 on cofilin. Molecular dynamics simulations supported the stability of these interactions, with Gandotinib showing the highest conformational stability, and ZINC000653853876 exhibiting the most favorable energetic profile. Network pharmacology analysis revealed eight intersecting targets, including <i>MAPK1</i>, <i>PRKCB</i>, <i>HDAC1</i>, and serotonin receptors, associated with neuroinflammatory and vascular pathways in strokes. <b>Conclusions</b>: This study presents a rational, integrative repurposing framework for identifying cofilin-targeting compounds with potential therapeutic relevance in ischemic stroke. The selected candidates warrant further experimental validation.</p>","PeriodicalId":20198,"journal":{"name":"Pharmaceuticals","volume":"18 9","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12472226/pdf/","citationCount":"0","resultStr":"{\"title\":\"Repurposing Cofilin-Targeting Compounds for Ischemic Stroke Through Cheminformatics and Network Pharmacology.\",\"authors\":\"Saleh I Alaqel, Abida Khan, Mashael N Alanazi, Naira Nayeem, Hayet Ben Khaled, Mohd Imran\",\"doi\":\"10.3390/ph18091323\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Background/Objectives</b>: Cofilin, a key regulator of actin cytoskeleton dynamics, contributes to neuroinflammation, synaptic damage, and blood-brain barrier disruption in ischemic stroke. Despite its established role in stroke pathology, cofilin remains largely untargeted by existing therapeutics. This study aimed to identify potential cofilin-binding molecules by repurposing <i>LIMK1</i> inhibitors through an integrated computational strategy. <b>Methods</b>: A cheminformatics pipeline combined QSAR modeling with four molecular fingerprint sets and multiple machine learning algorithms. The best-performing QSAR model (substructure-Random Forest) achieved R<sup>2</sup>_train = 0.8747 and R<sup>2</sup>_test = 0.8078, supporting the reliability of compound prioritization. Feature importance was assessed through SHAP analysis. Top candidates were subjected to molecular docking against cofilin, followed by 300 ns molecular dynamics simulations, MM-GBSA binding energy calculations, principal component analysis (PCA), and dynamic cross-correlation matrix (DCCM) analyses. Network pharmacology identified overlapping targets between selected compounds and stroke-related genes. <b>Results</b>: Three compounds, CHEMBL3613624, ZINC000653853876, and Gandotinib, were prioritized based on QSAR performance, binding affinity (-6.68, -6.25, and -5.61 Kcal/mol, respectively), and structural relevance. Docking studies confirmed key interactions with Asp98 and His133 on cofilin. Molecular dynamics simulations supported the stability of these interactions, with Gandotinib showing the highest conformational stability, and ZINC000653853876 exhibiting the most favorable energetic profile. Network pharmacology analysis revealed eight intersecting targets, including <i>MAPK1</i>, <i>PRKCB</i>, <i>HDAC1</i>, and serotonin receptors, associated with neuroinflammatory and vascular pathways in strokes. <b>Conclusions</b>: This study presents a rational, integrative repurposing framework for identifying cofilin-targeting compounds with potential therapeutic relevance in ischemic stroke. The selected candidates warrant further experimental validation.</p>\",\"PeriodicalId\":20198,\"journal\":{\"name\":\"Pharmaceuticals\",\"volume\":\"18 9\",\"pages\":\"\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2025-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12472226/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pharmaceuticals\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3390/ph18091323\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmaceuticals","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/ph18091323","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0

摘要

背景/目的:Cofilin是肌动蛋白细胞骨架动力学的关键调节因子,在缺血性脑卒中中参与神经炎症、突触损伤和血脑屏障破坏。尽管cofilin在脑卒中病理中起着既定的作用,但它在很大程度上仍未被现有的治疗方法所靶向。本研究旨在通过综合计算策略重新利用LIMK1抑制剂来识别潜在的cofilin结合分子。方法:化学信息学管道将QSAR建模与四种分子指纹集和多种机器学习算法相结合。表现最好的QSAR模型(substructure-Random Forest)的R2_train = 0.8747, R2_test = 0.8078,支持复合优先排序的可靠性。通过SHAP分析评估特征重要性。将候选分子与cofilin进行分子对接,然后进行300 ns分子动力学模拟、MM-GBSA结合能计算、主成分分析(PCA)和动态相互关联矩阵(DCCM)分析。网络药理学鉴定了选定化合物和中风相关基因之间的重叠靶点。结果:三个化合物CHEMBL3613624、ZINC000653853876和Gandotinib基于QSAR性能、结合亲和力(分别为-6.68、-6.25和-5.61 Kcal/mol)和结构相关性被优先考虑。对接研究证实了与cofilin上的Asp98和His133的关键相互作用。分子动力学模拟支持了这些相互作用的稳定性,Gandotinib表现出最高的构象稳定性,而ZINC000653853876表现出最有利的能量分布。网络药理学分析揭示了8个交叉靶点,包括MAPK1、PRKCB、HDAC1和血清素受体,它们与中风的神经炎症和血管通路相关。结论:本研究提出了一个合理的、综合的重新定位框架,用于鉴定cofilin靶向化合物与缺血性卒中的潜在治疗相关性。选定的候选物需要进一步的实验验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Repurposing Cofilin-Targeting Compounds for Ischemic Stroke Through Cheminformatics and Network Pharmacology.

Background/Objectives: Cofilin, a key regulator of actin cytoskeleton dynamics, contributes to neuroinflammation, synaptic damage, and blood-brain barrier disruption in ischemic stroke. Despite its established role in stroke pathology, cofilin remains largely untargeted by existing therapeutics. This study aimed to identify potential cofilin-binding molecules by repurposing LIMK1 inhibitors through an integrated computational strategy. Methods: A cheminformatics pipeline combined QSAR modeling with four molecular fingerprint sets and multiple machine learning algorithms. The best-performing QSAR model (substructure-Random Forest) achieved R2_train = 0.8747 and R2_test = 0.8078, supporting the reliability of compound prioritization. Feature importance was assessed through SHAP analysis. Top candidates were subjected to molecular docking against cofilin, followed by 300 ns molecular dynamics simulations, MM-GBSA binding energy calculations, principal component analysis (PCA), and dynamic cross-correlation matrix (DCCM) analyses. Network pharmacology identified overlapping targets between selected compounds and stroke-related genes. Results: Three compounds, CHEMBL3613624, ZINC000653853876, and Gandotinib, were prioritized based on QSAR performance, binding affinity (-6.68, -6.25, and -5.61 Kcal/mol, respectively), and structural relevance. Docking studies confirmed key interactions with Asp98 and His133 on cofilin. Molecular dynamics simulations supported the stability of these interactions, with Gandotinib showing the highest conformational stability, and ZINC000653853876 exhibiting the most favorable energetic profile. Network pharmacology analysis revealed eight intersecting targets, including MAPK1, PRKCB, HDAC1, and serotonin receptors, associated with neuroinflammatory and vascular pathways in strokes. Conclusions: This study presents a rational, integrative repurposing framework for identifying cofilin-targeting compounds with potential therapeutic relevance in ischemic stroke. The selected candidates warrant further experimental validation.

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
Pharmaceuticals
Pharmaceuticals Pharmacology, Toxicology and Pharmaceutics-Pharmaceutical Science
CiteScore
6.10
自引率
4.30%
发文量
1332
审稿时长
6 weeks
期刊介绍: Pharmaceuticals (ISSN 1424-8247) is an international scientific journal of medicinal chemistry and related drug sciences.Our aim is to publish updated reviews as well as research articles with comprehensive theoretical and experimental details. Short communications are also accepted; therefore, there is no restriction on the maximum length of the papers.
×
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:604180095
Book学术官方微信