Binding mechanism of inhibitors to DFG-in and DFG-out P38α deciphered using multiple independent Gaussian accelerated molecular dynamics simulations and deep learning.

IF 2.3 3区 环境科学与生态学 Q3 CHEMISTRY, MULTIDISCIPLINARY
G Xu, W Zhang, J Du, J Cong, P Wang, X Li, X Si, B Wei
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引用次数: 0

Abstract

P38α has been identified as a key target for drug design to treat a wide range of diseases. In this study, multiple independent Gaussian accelerated molecular dynamics (GaMD) simulations, deep learning (DL), and the molecular mechanics generalized Born surface area (MM-GBSA) method were used to investigate the binding mechanism of inhibitors (SB2, SK8, and BMU) to DFG-in and DFG-out P38α and clarify the effect of conformational differences in P38α on inhibitor binding. GaMD trajectory-based DL effectively identified important functional domains, such as the A-loop and N-sheet. Post-processing analysis on GaMD trajectories showed that binding of the three inhibitors profoundly affected the structural flexibility and dynamical behaviour of P38α situated at the DFG-in and DFG-out states. The MM-GBSA calculations not only revealed that differences in the binding ability of inhibitors are affected by DFG-in and DFG-out conformations of P38α, but also confirmed that van der Waals interactions are the primary force driving inhibitor-P38α binding. Residue-based free energy estimation identifies hot spots of inhibitor-P38α binding across DFG-in and DFG-out conformations, providing potential target sites for drug design towards P38α. This work is expected to offer valuable theoretical support for the development of selective inhibitors of P38α family members.

利用多重独立的高斯加速分子动力学模拟和深度学习,破解了抑制剂与DFG-in和DFG-out P38α的结合机制。
P38α已被确定为治疗多种疾病的药物设计的关键靶点。本研究采用多重独立高斯加速分子动力学(GaMD)模拟、深度学习(DL)和分子力学广义Born表面积(MM-GBSA)方法研究了抑制剂(SB2、SK8和BMU)与DFG-in和DFG-out P38α的结合机制,阐明了P38α构象差异对抑制剂结合的影响。基于GaMD轨迹的DL有效地识别了重要的功能域,如a环和N-sheet。GaMD轨迹的后处理分析表明,三种抑制剂的结合深刻地影响了位于DFG-in和DFG-out状态的P38α的结构灵活性和动力学行为。MM-GBSA计算不仅揭示了抑制剂结合能力的差异受到P38α的DFG-in和DFG-out构象的影响,而且证实了范德华相互作用是驱动抑制剂与P38α结合的主要力量。基于残基的自由能估计确定了抑制剂-P38α在DFG-in和DFG-out构象上结合的热点,为针对P38α的药物设计提供了潜在的靶点。这项工作有望为P38α家族成员的选择性抑制剂的开发提供有价值的理论支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.20
自引率
20.00%
发文量
78
审稿时长
>24 weeks
期刊介绍: SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.
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