论文标题
研究配体结合动力学的计算方法的最新进展
Recent advances in computational methods for studying ligand binding kinetics
论文作者
论文摘要
结合动力学参数可以与药物疗效相关，这导致了各种计算方法的发展，以预测结合动力学速率并深入了解近年来蛋白质 - 药水结合路径和机制。在这篇综述中，我们介绍并比较了最近开发的计算方法并应用于两个系统，即胰蛋白酶 - 苯甲酰胺和激酶抑制剂复合物。分子动力学模拟或机器学习中涉及增强采样的方法不仅可以用于预测动力学率，还可以揭示调节停留时间，选择性和对突变耐药性的持续时间的因素。突出显示需要更少的计算时间来进行预测的方法，并提出了减少计算动力学率误差的建议。
Binding kinetic parameters can be correlated with drug efficacy, which led to the development of various computational methods for predicting binding kinetic rates and gaining insight into protein-drug binding paths and mechanisms in recent years. In this review, we introduce and compare computational methods recently developed and applied to two systems, trypsin-benzamidine and kinase-inhibitor complexes. Methods involving enhanced sampling in molecular dynamics simulations or machine learning can be used not only to predict kinetic rates, but also to reveal factors modulating the duration of residence times, selectivity and drug resistance to mutations. Methods which require less computational time to make predictions are highlighted, and suggestions to reduce the error of computed kinetic rates are presented.
