State Key Laboratory for Precision Spectroscopy, Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, School of Chemistry and Molecular Engineering , East China Normal University , Shanghai 200062 , China.
NYU-ECNU Center for Computational Chemistry at NYU Shanghai , Shanghai 200062 , China.
J Chem Inf Model. 2019 Jan 28;59(1):272-281. doi: 10.1021/acs.jcim.8b00248. Epub 2018 Nov 27.
Accurate and efficient computation of protein-protein binding free energy remains a grand challenge. In this study, we develop a new strategy to achieve efficient calculation for total protein-protein binding free energies with improved accuracy. The new method combines the recently developed interaction entropy method for efficient computation of entropic change together with the use of residue type-specific dielectric constants in the framework of MM/GBSA to achieve optimal result for protein-protein binding free energies. The new strategy is shown to be computationally efficient and accurate than that using standard MM/GBSA methods in which the entropic computation is performed by the normal model approach and the protein interior is represented by the standard dielectric constant (typically set to 1), both in terms of accuracy and computational efficiency. Our study using the new strategy on a set of randomly selected 20 protein-protein binding systems produced an optimal dielectric constant of 2.7 for charged residues and 1.1 for noncharged residues. Using this new strategy, the mean absolute error in computed binding free energies for these 20 selected protein-protein systems is significantly reduced by more than 3-fold while the computational cost is reduced by more than 2 orders of magnitude, compared to the result using standard MM/GBSA method with the normal mode approach. A similar improvement in accuracy is confirmed for a test set consisting of 10 protein-protein systems.
准确而高效地计算蛋白质-蛋白质结合自由能仍然是一个巨大的挑战。在这项研究中,我们开发了一种新的策略,以实现高效计算总蛋白质-蛋白质结合自由能,同时提高准确性。新方法结合了最近开发的交互熵方法,用于高效计算熵变,同时在 MM/GBSA 框架内使用残基特定介电常数,以实现蛋白质-蛋白质结合自由能的最佳结果。与使用标准 MM/GBSA 方法相比,新策略在计算效率和准确性方面都具有优势,在标准 MM/GBSA 方法中,熵的计算是通过正常模型方法进行的,而蛋白质内部则用标准介电常数(通常设置为 1)表示。我们使用新策略对一组随机选择的 20 个蛋白质-蛋白质结合系统进行了研究,得出了带电荷残基的最佳介电常数为 2.7,不带电荷残基的最佳介电常数为 1.1。使用这种新策略,与使用正常模式方法的标准 MM/GBSA 方法相比,这 20 个选定的蛋白质-蛋白质系统的计算结合自由能的平均绝对误差显著降低了 3 倍以上,而计算成本降低了 2 个数量级以上。对于由 10 个蛋白质-蛋白质系统组成的测试集,也确认了类似的准确性提高。