Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives.

Q2 Biochemistry, Genetics and Molecular Biology Advances and Applications in Bioinformatics and Chemistry Pub Date : 2022-01-06 eCollection Date: 2022-01-01 DOI:10.2147/AABC.S247950
Shristi Pawnikar, Apurba Bhattarai, Jinan Wang, Yinglong Miao
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Abstract

Biomolecular recognition such as binding of small molecules, nucleic acids, peptides and proteins to their target receptors plays key roles in cellular function and has been targeted for therapeutic drug design. Molecular dynamics (MD) is a computational approach to analyze these binding processes at an atomistic level, which provides valuable understandings of the mechanisms of biomolecular recognition. However, the rather slow biomolecular binding events often present challenges for conventional MD (cMD), due to limited simulation timescales (typically over hundreds of nanoseconds to tens of microseconds). In this regard, enhanced sampling methods, particularly accelerated MD (aMD), have proven useful to bridge the gap and enable all-atom simulations of biomolecular binding events. Here, we will review the recent method developments of Gaussian aMD (GaMD), ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD), which have greatly expanded our capabilities to simulate biomolecular binding processes. Spontaneous binding of various biomolecules to their receptors has been successfully simulated by GaMD. Microsecond LiGaMD and Pep-GaMD simulations have captured repetitive binding and dissociation of small-molecule ligands and highly flexible peptides, and thus enabled ligand/peptide binding thermodynamics and kinetics calculations. We will also present relevant application studies in simulations of important drug targets and future perspectives for rational computer-aided drug design.

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结合分析使用加速分子动力学模拟和未来展望。
生物分子识别,如小分子、核酸、肽和蛋白质与其靶受体的结合,在细胞功能中发挥着关键作用,并已成为治疗药物设计的靶点。分子动力学(MD)是一种在原子水平上分析这些结合过程的计算方法,它为生物分子识别机制提供了有价值的理解。然而,由于有限的模拟时间尺度(通常超过数百纳秒至数十微秒),相当缓慢的生物分子结合事件通常对传统MD(cMD)提出挑战。在这方面,增强的采样方法,特别是加速MD(aMD),已被证明有助于弥合差距,并实现生物分子结合事件的全原子模拟。在这里,我们将回顾高斯aMD(GaMD)、配体GaMD(LiGaMD)和肽GaMD(Pep-GaMD)的最新方法发展,它们极大地扩展了我们模拟生物分子结合过程的能力。GaMD已经成功模拟了各种生物分子与其受体的自发结合。微秒LiGaMD和Pep-GaMD模拟捕捉到了小分子配体和高度柔性肽的重复结合和解离,从而实现了配体/肽结合热力学和动力学计算。我们还将介绍重要药物靶点模拟的相关应用研究,以及合理的计算机辅助药物设计的未来前景。
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来源期刊
Advances and Applications in Bioinformatics and Chemistry
Advances and Applications in Bioinformatics and Chemistry Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (miscellaneous)
CiteScore
6.50
自引率
0.00%
发文量
7
审稿时长
16 weeks
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