{"title":"通过微秒分子动力学模拟深入了解 MRTX1133 和曲美替尼与 KRASG12D 突变蛋白的结合情况,以实现药物的再利用。","authors":"Iruthayaraj Ancy, Sakayanathan Penislusshiyan, Fuad Ameen, Loganathan Chitra","doi":"10.1002/jmr.3103","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The Kirsten Rat Sarcoma (KRAS) G12D mutant protein is a primary driver of pancreatic ductal adenocarcinoma, necessitating the identification of targeted drug molecules. Repurposing of drugs quickly finds new uses, speeding treatment development. This study employs microsecond molecular dynamics simulations to unveil the binding mechanisms of the FDA-approved MEK inhibitor trametinib with KRAS<sup>G12D</sup>, providing insights for potential drug repurposing. The binding of trametinib was compared with clinical trial drug MRTX1133, which demonstrates exceptional activity against KRAS<sup>G12D</sup>, for better understanding of interaction mechanism of trametinib with KRAS<sup>G12D</sup>. The resulting stable MRTX1133-KRAS<sup>G12D</sup> complex reduces root mean square deviation (RMSD) values, in Switch I and II domains, highlighting its potential for inhibiting KRAS<sup>G12D</sup>. MRTX1133's robust interaction with Tyr64 and disruption of Tyr96-Tyr71-Arg68 network showcase its ability to mitigate the effects of the G12D mutation. In contrast, trametinib employs a distinctive binding mechanism involving P-loop, Switch I and II residues. Extended simulations to 1 μs reveal sustained network interactions with Tyr32, Thr58, and GDP, suggesting a role of trametinib in maintaining KRAS<sup>G12D</sup> in an inactive state and impede the further cell signaling. The decomposition binding free energy values illustrate amino acids' contributions to binding energy, elucidating ligand–protein interactions and molecular stability. The machine learning approach reveals that van der Waals interactions among the residues play vital role in complex stability and the potential amino acids involved in drug–receptor interactions of each complex. These details provide a molecular-level understanding of drug binding mechanisms, offering essential knowledge for further drug repurposing and potential drug discovery.</p>\n </div>","PeriodicalId":16531,"journal":{"name":"Journal of Molecular Recognition","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Microsecond Molecular Dynamics Simulation to Gain Insight Into the Binding of MRTX1133 and Trametinib With KRASG12D Mutant Protein for Drug Repurposing\",\"authors\":\"Iruthayaraj Ancy, Sakayanathan Penislusshiyan, Fuad Ameen, Loganathan Chitra\",\"doi\":\"10.1002/jmr.3103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>The Kirsten Rat Sarcoma (KRAS) G12D mutant protein is a primary driver of pancreatic ductal adenocarcinoma, necessitating the identification of targeted drug molecules. Repurposing of drugs quickly finds new uses, speeding treatment development. This study employs microsecond molecular dynamics simulations to unveil the binding mechanisms of the FDA-approved MEK inhibitor trametinib with KRAS<sup>G12D</sup>, providing insights for potential drug repurposing. The binding of trametinib was compared with clinical trial drug MRTX1133, which demonstrates exceptional activity against KRAS<sup>G12D</sup>, for better understanding of interaction mechanism of trametinib with KRAS<sup>G12D</sup>. The resulting stable MRTX1133-KRAS<sup>G12D</sup> complex reduces root mean square deviation (RMSD) values, in Switch I and II domains, highlighting its potential for inhibiting KRAS<sup>G12D</sup>. MRTX1133's robust interaction with Tyr64 and disruption of Tyr96-Tyr71-Arg68 network showcase its ability to mitigate the effects of the G12D mutation. In contrast, trametinib employs a distinctive binding mechanism involving P-loop, Switch I and II residues. Extended simulations to 1 μs reveal sustained network interactions with Tyr32, Thr58, and GDP, suggesting a role of trametinib in maintaining KRAS<sup>G12D</sup> in an inactive state and impede the further cell signaling. The decomposition binding free energy values illustrate amino acids' contributions to binding energy, elucidating ligand–protein interactions and molecular stability. The machine learning approach reveals that van der Waals interactions among the residues play vital role in complex stability and the potential amino acids involved in drug–receptor interactions of each complex. These details provide a molecular-level understanding of drug binding mechanisms, offering essential knowledge for further drug repurposing and potential drug discovery.</p>\\n </div>\",\"PeriodicalId\":16531,\"journal\":{\"name\":\"Journal of Molecular Recognition\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Molecular Recognition\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jmr.3103\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Recognition","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jmr.3103","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
克氏鼠肉瘤(KRAS)G12D 突变蛋白是胰腺导管腺癌的主要致病因素,因此有必要确定靶向药物分子。药物的再利用可以迅速找到新用途,加快治疗方法的开发。本研究利用微秒分子动力学模拟揭示了美国食品及药物管理局批准的MEK抑制剂曲美替尼与KRASG12D的结合机制,为潜在的药物再利用提供了见解。为了更好地理解曲美替尼与KRASG12D的相互作用机制,我们将曲美替尼与临床试验药物MRTX1133的结合进行了比较。由此产生的稳定的 MRTX1133-KRASG12D 复合物降低了开关 I 和开关 II 结构域的均方根偏差 (RMSD) 值,突显了其抑制 KRASG12D 的潜力。MRTX1133与Tyr64的强相互作用以及对Tyr96-Tyr71-Arg68网络的破坏显示了其减轻G12D突变影响的能力。相比之下,曲美替尼采用了一种独特的结合机制,涉及 P 环、Switch I 和 II 残基。扩展到 1 μs 的模拟显示了与 Tyr32、Thr58 和 GDP 的持续网络相互作用,这表明曲美替尼在维持 KRASG12D 处于非活性状态和阻碍进一步的细胞信号传导方面发挥了作用。分解结合自由能值说明了氨基酸对结合能的贡献,阐明了配体与蛋白质的相互作用和分子稳定性。机器学习方法揭示了残基之间的范德华相互作用在复合物稳定性中的重要作用,以及每个复合物中参与药物-受体相互作用的潜在氨基酸。这些细节提供了对药物结合机制的分子级理解,为进一步的药物再利用和潜在药物发现提供了重要知识。
Microsecond Molecular Dynamics Simulation to Gain Insight Into the Binding of MRTX1133 and Trametinib With KRASG12D Mutant Protein for Drug Repurposing
The Kirsten Rat Sarcoma (KRAS) G12D mutant protein is a primary driver of pancreatic ductal adenocarcinoma, necessitating the identification of targeted drug molecules. Repurposing of drugs quickly finds new uses, speeding treatment development. This study employs microsecond molecular dynamics simulations to unveil the binding mechanisms of the FDA-approved MEK inhibitor trametinib with KRASG12D, providing insights for potential drug repurposing. The binding of trametinib was compared with clinical trial drug MRTX1133, which demonstrates exceptional activity against KRASG12D, for better understanding of interaction mechanism of trametinib with KRASG12D. The resulting stable MRTX1133-KRASG12D complex reduces root mean square deviation (RMSD) values, in Switch I and II domains, highlighting its potential for inhibiting KRASG12D. MRTX1133's robust interaction with Tyr64 and disruption of Tyr96-Tyr71-Arg68 network showcase its ability to mitigate the effects of the G12D mutation. In contrast, trametinib employs a distinctive binding mechanism involving P-loop, Switch I and II residues. Extended simulations to 1 μs reveal sustained network interactions with Tyr32, Thr58, and GDP, suggesting a role of trametinib in maintaining KRASG12D in an inactive state and impede the further cell signaling. The decomposition binding free energy values illustrate amino acids' contributions to binding energy, elucidating ligand–protein interactions and molecular stability. The machine learning approach reveals that van der Waals interactions among the residues play vital role in complex stability and the potential amino acids involved in drug–receptor interactions of each complex. These details provide a molecular-level understanding of drug binding mechanisms, offering essential knowledge for further drug repurposing and potential drug discovery.
期刊介绍:
Journal of Molecular Recognition (JMR) publishes original research papers and reviews describing substantial advances in our understanding of molecular recognition phenomena in life sciences, covering all aspects from biochemistry, molecular biology, medicine, and biophysics. The research may employ experimental, theoretical and/or computational approaches.
The focus of the journal is on recognition phenomena involving biomolecules and their biological / biochemical partners rather than on the recognition of metal ions or inorganic compounds. Molecular recognition involves non-covalent specific interactions between two or more biological molecules, molecular aggregates, cellular modules or organelles, as exemplified by receptor-ligand, antigen-antibody, nucleic acid-protein, sugar-lectin, to mention just a few of the possible interactions. The journal invites manuscripts that aim to achieve a complete description of molecular recognition mechanisms between well-characterized biomolecules in terms of structure, dynamics and biological activity. Such studies may help the future development of new drugs and vaccines, although the experimental testing of new drugs and vaccines falls outside the scope of the journal. Manuscripts that describe the application of standard approaches and techniques to design or model new molecular entities or to describe interactions between biomolecules, but do not provide new insights into molecular recognition processes will not be considered. Similarly, manuscripts involving biomolecules uncharacterized at the sequence level (e.g. calf thymus DNA) will not be considered.