Abdelmoujoud Faris, Ibrahim M Ibrahim, Radwan Alnajjar, Hanine Hadni, Mashooq Ahmad Bhat, Muhammad Yaseen, Souvik Chakraborty, Nada Alsakhen, Israa M Shamkh, Fazal Mabood, Ahmed M Naglah, Ihsan Ullah, Noha Ziedan, Menana Elhallaoui
{"title":"qsar驱动的筛选发现并设计了新的嘧啶-4,6-二胺衍生物作为有效的JAK3抑制剂。","authors":"Abdelmoujoud Faris, Ibrahim M Ibrahim, Radwan Alnajjar, Hanine Hadni, Mashooq Ahmad Bhat, Muhammad Yaseen, Souvik Chakraborty, Nada Alsakhen, Israa M Shamkh, Fazal Mabood, Ahmed M Naglah, Ihsan Ullah, Noha Ziedan, Menana Elhallaoui","doi":"10.1080/07391102.2023.2283168","DOIUrl":null,"url":null,"abstract":"<p><p>This study presents a robust and integrated methodology that harnesses a range of computational techniques to facilitate the design and prediction of new inhibitors targeting the JAK3/STAT pathway. This methodology encompasses several strategies, including QSAR analysis, pharmacophore modeling, ADMET prediction, covalent docking, molecular dynamics (MD) simulations, and the calculation of binding free energies (MM/GBSA). An efficacious QSAR model was meticulously crafted through the employment of multiple linear regression (MLR). The initial MLR model underwent further refinement employing an artificial neural network (ANN) methodology aimed at minimizing predictive errors. Notably, both MLR and ANN exhibited commendable performance, showcasing R2 values of 0.89 and 0.95, respectively. The model's precision was assessed via leave-one-out cross-validation (CV) yielding a Q2 value of 0.65, supplemented by rigorous Y-randomization. , The pharmacophore model effectively differentiated between active and inactive drugs, identifying potential JAK3 inhibitors, and demonstrated validity with an ROC value of 0.86. The newly discovered and designed inhibitors exhibited high inhibitory potency, ranging from 6 to 8, as accurately predicted by the QSAR models. Comparative analysis with FDA-approved Tofacitinib revealed that the new compounds exhibited promising ADMET properties and strong covalent docking (CovDock) interactions. The stability of the new discovered and designed inhibitors within the JAK3 binding site was confirmed through 500 ns MD simulations, while MM/GBSA calculations supported their binding affinity. Additionally, a retrosynthetic study was conducted to facilitate the synthesis of these potential JAK3/STAT inhibitors. The overall integrated approach demonstrates the feasibility of designing novel JAK3/STAT inhibitors with robust efficacy and excellent ADMET characteristics that surpass Tofacitinib by a significant margin.Communicated by Ramaswamy H. Sarma.</p>","PeriodicalId":15272,"journal":{"name":"Journal of Biomolecular Structure & Dynamics","volume":" ","pages":"757-786"},"PeriodicalIF":2.7000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"QSAR-driven screening uncovers and designs novel pyrimidine-4,6-diamine derivatives as potent JAK3 inhibitors.\",\"authors\":\"Abdelmoujoud Faris, Ibrahim M Ibrahim, Radwan Alnajjar, Hanine Hadni, Mashooq Ahmad Bhat, Muhammad Yaseen, Souvik Chakraborty, Nada Alsakhen, Israa M Shamkh, Fazal Mabood, Ahmed M Naglah, Ihsan Ullah, Noha Ziedan, Menana Elhallaoui\",\"doi\":\"10.1080/07391102.2023.2283168\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study presents a robust and integrated methodology that harnesses a range of computational techniques to facilitate the design and prediction of new inhibitors targeting the JAK3/STAT pathway. This methodology encompasses several strategies, including QSAR analysis, pharmacophore modeling, ADMET prediction, covalent docking, molecular dynamics (MD) simulations, and the calculation of binding free energies (MM/GBSA). An efficacious QSAR model was meticulously crafted through the employment of multiple linear regression (MLR). The initial MLR model underwent further refinement employing an artificial neural network (ANN) methodology aimed at minimizing predictive errors. Notably, both MLR and ANN exhibited commendable performance, showcasing R2 values of 0.89 and 0.95, respectively. The model's precision was assessed via leave-one-out cross-validation (CV) yielding a Q2 value of 0.65, supplemented by rigorous Y-randomization. , The pharmacophore model effectively differentiated between active and inactive drugs, identifying potential JAK3 inhibitors, and demonstrated validity with an ROC value of 0.86. The newly discovered and designed inhibitors exhibited high inhibitory potency, ranging from 6 to 8, as accurately predicted by the QSAR models. Comparative analysis with FDA-approved Tofacitinib revealed that the new compounds exhibited promising ADMET properties and strong covalent docking (CovDock) interactions. The stability of the new discovered and designed inhibitors within the JAK3 binding site was confirmed through 500 ns MD simulations, while MM/GBSA calculations supported their binding affinity. Additionally, a retrosynthetic study was conducted to facilitate the synthesis of these potential JAK3/STAT inhibitors. The overall integrated approach demonstrates the feasibility of designing novel JAK3/STAT inhibitors with robust efficacy and excellent ADMET characteristics that surpass Tofacitinib by a significant margin.Communicated by Ramaswamy H. Sarma.</p>\",\"PeriodicalId\":15272,\"journal\":{\"name\":\"Journal of Biomolecular Structure & Dynamics\",\"volume\":\" \",\"pages\":\"757-786\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biomolecular Structure & Dynamics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1080/07391102.2023.2283168\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/12/7 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biomolecular Structure & Dynamics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1080/07391102.2023.2283168","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/12/7 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
本研究提出了一种强大的综合方法,利用一系列计算技术来促进设计和预测针对JAK3/STAT通路的新抑制剂。该方法包含多种策略,包括QSAR分析、药效团建模、ADMET预测、共价对接、分子动力学(MD)模拟和结合自由能(MM/GBSA)计算。通过使用多元线性回归(MLR)精心制作了一个有效的QSAR模型。最初的MLR模型采用人工神经网络(ANN)方法进行了进一步的改进,旨在最大限度地减少预测误差。值得注意的是,MLR和ANN的表现都很好,R2分别为0.89和0.95。模型的精度通过留一交叉验证(CV)进行评估,Q2值为0.65,辅以严格的y随机化。药效团模型有效区分了活性药物和非活性药物,识别了潜在的JAK3抑制剂,其ROC值为0.86。新发现和设计的抑制剂显示出高的抑制效力,范围从6到8,正如QSAR模型准确预测的那样。与fda批准的Tofacitinib的比较分析表明,新化合物具有良好的ADMET特性和强的共价对接(CovDock)相互作用。通过500 ns MD模拟证实了新发现和设计的抑制剂在JAK3结合位点内的稳定性,而MM/GBSA计算支持它们的结合亲和力。此外,还进行了一项反合成研究,以促进这些潜在的JAK3/STAT抑制剂的合成。整体集成的方法证明了设计具有强大疗效和出色ADMET特性的新型JAK3/STAT抑制剂的可行性,其显著优于托法替尼。由Ramaswamy H. Sarma传达。
QSAR-driven screening uncovers and designs novel pyrimidine-4,6-diamine derivatives as potent JAK3 inhibitors.
This study presents a robust and integrated methodology that harnesses a range of computational techniques to facilitate the design and prediction of new inhibitors targeting the JAK3/STAT pathway. This methodology encompasses several strategies, including QSAR analysis, pharmacophore modeling, ADMET prediction, covalent docking, molecular dynamics (MD) simulations, and the calculation of binding free energies (MM/GBSA). An efficacious QSAR model was meticulously crafted through the employment of multiple linear regression (MLR). The initial MLR model underwent further refinement employing an artificial neural network (ANN) methodology aimed at minimizing predictive errors. Notably, both MLR and ANN exhibited commendable performance, showcasing R2 values of 0.89 and 0.95, respectively. The model's precision was assessed via leave-one-out cross-validation (CV) yielding a Q2 value of 0.65, supplemented by rigorous Y-randomization. , The pharmacophore model effectively differentiated between active and inactive drugs, identifying potential JAK3 inhibitors, and demonstrated validity with an ROC value of 0.86. The newly discovered and designed inhibitors exhibited high inhibitory potency, ranging from 6 to 8, as accurately predicted by the QSAR models. Comparative analysis with FDA-approved Tofacitinib revealed that the new compounds exhibited promising ADMET properties and strong covalent docking (CovDock) interactions. The stability of the new discovered and designed inhibitors within the JAK3 binding site was confirmed through 500 ns MD simulations, while MM/GBSA calculations supported their binding affinity. Additionally, a retrosynthetic study was conducted to facilitate the synthesis of these potential JAK3/STAT inhibitors. The overall integrated approach demonstrates the feasibility of designing novel JAK3/STAT inhibitors with robust efficacy and excellent ADMET characteristics that surpass Tofacitinib by a significant margin.Communicated by Ramaswamy H. Sarma.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.