An accelerated molecular dynamics study for investigating protein pathways using the bond-boost hyperdynamics method.

IF 5.2 3区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Protein Science Pub Date : 2025-03-01 DOI:10.1002/pro.70073
Soon Woo Park, Moon-Ki Choi, Byung Ho Lee, Sangjae Seo, Woo Kyun Kim, Moon Ki Kim
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Abstract

Molecular dynamics (MD) simulation is an important tool for understanding protein dynamics and the thermodynamic properties of proteins. However, due to the high computational cost of MD simulations, it is still challenging to explore a wide conformational space. To solve this problem, a variety of accelerated MD (aMD) schemes have been proposed over the past few decades. The bond-boost method (BBM) is one of such aMD schemes, which expedites escape events from energy basins by adding a bias potential based on changes in bond length. In this paper, we present a new methodology based on the BBM for accelerating the conformational transition of proteins. In our modified BBM, the bias potential is constructed using the dihedral angle and hydrogen bond, which are more suitable variables to monitor the conformational change in proteins. Additionally, we have developed an efficient algorithm compatible with the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) package. The method is validated with the conformational change of ribose binding protein and adenylate kinase by comparing the conventional and accelerated MD simulation results. Based on the aMD results, the characteristics of the proteins are investigated by monitoring the conformational transition pathways. Moreover, the free energy landscape calculated using umbrella sampling confirms all the states identified by the aMD simulation are the free energy minima, and the system makes transitions following the path indicated by the free energy landscape. Our efficient approach is expected to play a key role in investigating transition pathways in a wide range of protein simulations.

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一种加速分子动力学研究,用于研究蛋白质途径,使用bond-boost超动力学方法。
分子动力学(MD)模拟是了解蛋白质动力学和蛋白质热力学性质的重要工具。然而,由于MD模拟的计算成本高,探索广泛的构象空间仍然具有挑战性。为了解决这个问题,在过去的几十年里,人们提出了各种加速MD (aMD)方案。bond-boost方法(BBM)就是其中一种aMD方案,它通过增加基于键长变化的偏置电位来加速能量盆地的逃逸事件。在本文中,我们提出了一种基于BBM的新方法来加速蛋白质的构象转变。在我们改进的BBM中,偏置电位是使用二面角和氢键来构建的,这是更适合监测蛋白质构象变化的变量。此外,我们还开发了一种与大规模原子/分子大规模并行模拟器(LAMMPS)包兼容的高效算法。通过对常规和加速MD模拟结果的比较,验证了该方法与核糖结合蛋白和腺苷酸激酶构象变化的关系。基于aMD的结果,通过监测蛋白质的构象转变途径来研究蛋白质的特征。此外,使用伞式采样计算的自由能格局证实了aMD模拟识别的所有状态都是自由能最小值,并且系统按照自由能格局所指示的路径进行转变。我们的有效方法有望在广泛的蛋白质模拟中研究过渡途径方面发挥关键作用。
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来源期刊
Protein Science
Protein Science 生物-生化与分子生物学
CiteScore
12.40
自引率
1.20%
发文量
246
审稿时长
1 months
期刊介绍: Protein Science, the flagship journal of The Protein Society, is a publication that focuses on advancing fundamental knowledge in the field of protein molecules. The journal welcomes original reports and review articles that contribute to our understanding of protein function, structure, folding, design, and evolution. Additionally, Protein Science encourages papers that explore the applications of protein science in various areas such as therapeutics, protein-based biomaterials, bionanotechnology, synthetic biology, and bioelectronics. The journal accepts manuscript submissions in any suitable format for review, with the requirement of converting the manuscript to journal-style format only upon acceptance for publication. Protein Science is indexed and abstracted in numerous databases, including the Agricultural & Environmental Science Database (ProQuest), Biological Science Database (ProQuest), CAS: Chemical Abstracts Service (ACS), Embase (Elsevier), Health & Medical Collection (ProQuest), Health Research Premium Collection (ProQuest), Materials Science & Engineering Database (ProQuest), MEDLINE/PubMed (NLM), Natural Science Collection (ProQuest), and SciTech Premium Collection (ProQuest).
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