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通过几何路径和遍历采样实现准确的标准蛋白质-蛋白质结合自由能计算。

Achieving Accurate Standard Protein-Protein Binding Free Energy Calculations through the Geometrical Route and Ergodic Sampling.

机构信息

Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China.

Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China.

出版信息

J Chem Inf Model. 2023 Apr 24;63(8):2512-2519. doi: 10.1021/acs.jcim.3c00487. Epub 2023 Apr 12.

Abstract

A new strategy for the prediction of binding free energies of protein-protein complexes is reported in the present article. By combining an ergodic-sampling algorithm with the so-called "geometrical route", which introduces a series of geometrical restraints as a preamble to the physical separation of the two partners, we achieve accurate binding free energy calculations for medium-sized protein-protein complexes within the microsecond timescale. The ergodic-sampling algorithm, namely, Gaussian-accelerated molecular dynamics (GaMD), implicitly helps explore the conformational change of the two binding partners as they associate reversibly by raising the energy wells. Therefore, independent simulations capturing the isomerization of proteins are no longer needed, reducing both the computational cost and human effort. Numerical applications indicate errors on the order of 0.1 kcal/mol for the Abl-SH3 domain binding a decapeptide, of 2.6 kcal/mol for the barnase-barstar complex, and of 0.2 kcal/mol for human leukocyte elastase binding the third domain of the turkey ovomucoid inhibitor. Compared with the classical geometrical route, which resorts to collective variables to describe the isomerization of proteins, our new strategy possesses remarkable convergence properties and robustness for protein-protein complexes owing to improved ergodic sampling. We are confident that the strategy presented in this study will have a broad range of applications, helping us understand recognition-association phenomena in the areas of physical, biological, and medicinal chemistry.

摘要

本文报道了一种预测蛋白质-蛋白质复合物结合自由能的新策略。通过将遍历采样算法与所谓的“几何途径”相结合,该策略在物理分离两个配体之前引入了一系列几何约束,从而在微秒时间尺度内实现了中等大小蛋白质-蛋白质复合物的准确结合自由能计算。遍历采样算法,即高斯加速分子动力学(GaMD),通过提高能量势阱,隐式地帮助探索两个结合配体在可逆缔合时的构象变化。因此,不再需要捕获蛋白质异构化的独立模拟,从而降低了计算成本和人力。数值应用表明,Abl-SH3 结构域与十肽结合的误差约为 0.1 kcal/mol, barnase-barstar 复合物的误差约为 2.6 kcal/mol,人白细胞弹性蛋白酶与火鸡卵类黏蛋白抑制剂第三结构域结合的误差约为 0.2 kcal/mol。与经典的几何途径相比,该途径使用整体变量来描述蛋白质的异构化,由于改进了遍历采样,我们的新策略对于蛋白质-蛋白质复合物具有显著的收敛特性和稳健性。我们相信,本研究提出的策略将在物理、生物和药物化学等领域的识别-缔合现象的研究中具有广泛的应用前景。

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