Ranking of Ligand Binding Kinetics Using a Weighted Ensemble Approach and Comparison with a Multiscale Milestoning Approach
Ranking of Ligand Binding Kinetics Using a Weighted Ensemble Approach and Comparison with a Multiscale Milestoning Approach
复制标题
DOI：
10.1021/acs.jcim.9b00968
复制
发表时间：
2020-11-23
影响因子：
5.6
通讯作者：
Amaro, Rommie E.
中科院分区：
文献类型：
--
作者：
Ahn, Surl-Hee;Jagger, Benjamin R.;Amaro, Rommie E.
为了改善寻找合适配体的先导优化工作，制药行业需要了解配体的结合动力学，例如结合和解结合速率常数，这通常与配体在体内的功效相关。为了有效地预测结合动力学，改进的采样方法，如里程碑和加权系综（WE）方法，已被用于这些系统的分子动力学（MD）模拟。然而，这些增强的抽样方法在配体排序方面的比较尚未完成。因此，一种称为并行自适应采样（CAS）算法的WE方法使用MD模拟对β -环糊精的7个配体进行排序，该系统还使用了一种称为模拟激活动力学速率估计（SEEKR）的多尺度里程碑方法，该方法同时使用MD和布朗动力学模拟。总的来说，CAS算法可以像SEEKR一样，利用解结合速率常数k（off）值和结合自由能δ G值成功地对配体进行排序，并且减少了与SEEKR大致相同的计算成本。我们比较了不同参数下CAS算法的模拟结果，并讨论了参数对配体排序、获得速率常数和结合自由能的影响。讨论了SEEKR算法与CAS算法的异同和优缺点，以供今后使用。
To improve lead optimization efforts in finding the right ligand, pharmaceutical industries need to know the ligand's binding kinetics, such as binding and unbinding rate constants, which often correlate with the ligand's efficacy in vivo. To predict binding kinetics efficiently, enhanced sampling methods, such as milestoning and the weighted ensemble (WE) method, have been used in molecular dynamics (MD) simulations of these systems. However, a comparison of these enhanced sampling methods in ranking ligands has not been done. Hence, a WE approach called the concurrent adaptive sampling (CAS) algorithm that uses MD simulations was used to rank seven ligands for beta-cyclodextrin, a system in which a multiscale milestoning approach called simulation enabled estimation of kinetic rates (SEEKR) was also used, which uses both MD and Brownian dynamics simulations. Overall, the CAS algorithm can successfully rank ligands using the unbinding rate constant k(off) values and binding free energy Delta G values, as SEEKR did, with reduced computational cost that is about the same as SEEKR. We compare the CAS algorithm simulations with different parameters and discuss the impact of parameters in ranking ligands and obtaining rate constant and binding free energy estimates. We also discuss similarities and differences and advantages and disadvantages of SEEKR and the CAS algorithm for future use.