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Bioinformatics and Biosimulations as Toolbox for Peptides and Peptidomimetics Design: Where Are We?生物信息学与生物模拟作为肽和拟肽设计的工具箱:我们现在处于什么阶段?
Front Mol Biosci. 2020 May 5;7:66. doi: 10.3389/fmolb.2020.00066. eCollection 2020.
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Advances in the calculation of binding free energies.结合自由能计算的进展。
Curr Opin Struct Biol. 2020 Apr;61:207-212. doi: 10.1016/j.sbi.2020.01.016. Epub 2020 Feb 20.
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Structural Determinants Mediating Tertiapin Block of Neuronal Kir3.2 Channels.介导 Tertiapin 阻断神经元 Kir3.2 通道的结构决定因素。
Biochemistry. 2020 Feb 25;59(7):836-850. doi: 10.1021/acs.biochem.9b01098. Epub 2020 Feb 7.
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Correcting electrostatic artifacts due to net-charge changes in the calculation of ligand binding free energies.纠正配体结合自由能计算中由于净电荷变化引起的静电伪影。
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实施和评估一种计算蛋白质-蛋白质结合自由能的炼金术方法。

Implementing and Assessing an Alchemical Method for Calculating Protein-Protein Binding Free Energy.

机构信息

Institute for Modeling Collaboration and Innovation, University of Idaho, Moscow, Idaho 83844, United States.

Department of Biological Sciences, University of Idaho, Moscow, Idaho 83844, United States.

出版信息

J Chem Theory Comput. 2021 Apr 13;17(4):2457-2464. doi: 10.1021/acs.jctc.0c01045. Epub 2021 Mar 12.

DOI:10.1021/acs.jctc.0c01045
PMID:33709712
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8044032/
Abstract

Protein-protein binding is fundamental to most biological processes. It is important to be able to use computation to accurately estimate the change in protein-protein binding free energy due to mutations in order to answer biological questions that would be experimentally challenging, laborious, or time-consuming. Although nonrigorous free-energy methods are faster, rigorous alchemical molecular dynamics-based methods are considerably more accurate and are becoming more feasible with the advancement of computer hardware and molecular simulation software. Even with sufficient computational resources, there are still major challenges to using alchemical free-energy methods for protein-protein complexes, such as generating hybrid structures and topologies, maintaining a neutral net charge of the system when there is a charge-changing mutation, and setting up the simulation. In the current study, we have used the package to generate hybrid structures and topologies, and a double-system/single-box approach to maintain the net charge of the system. To test the approach, we predicted relative binding affinities for two protein-protein complexes using a nonequilibrium alchemical method based on the Crooks fluctuation theorem and compared the results with experimental values. The method correctly identified stabilizing from destabilizing mutations for a small protein-protein complex, and a larger, more challenging antibody complex. Strong correlations were obtained between predicted and experimental relative binding affinities for both protein-protein systems.

摘要

蛋白质-蛋白质相互作用是大多数生物过程的基础。能够使用计算来准确估计由于突变而导致的蛋白质-蛋白质结合自由能的变化,对于回答那些实验上具有挑战性、费力或耗时的生物学问题是很重要的。虽然非刚性自由能方法更快,但严格的基于分子动力学的热力学方法要准确得多,并且随着计算机硬件和分子模拟软件的进步,变得更加可行。即使有足够的计算资源,使用热力学方法研究蛋白质-蛋白质复合物仍然存在重大挑战,例如生成杂种结构和拓扑结构,在发生电荷变化突变时保持系统的净电荷中性,以及设置模拟。在本研究中,我们使用了 包生成杂种结构和拓扑结构,并采用双系统/单盒方法来保持系统的净电荷。为了测试该方法,我们使用基于克罗克斯涨落定理的非平衡热力学方法预测了两个蛋白质-蛋白质复合物的相对结合亲和力,并将结果与实验值进行了比较。该方法正确地识别了小蛋白质-蛋白质复合物和更大、更具挑战性的抗体复合物中的稳定和不稳定突变。对于两种蛋白质-蛋白质系统,预测的和实验的相对结合亲和力之间都获得了很强的相关性。