Improved Alchemical Free Energy Calculations with Optimized Smoothstep Softcore Potentials
Improved Alchemical Free Energy Calculations with Optimized Smoothstep Softcore Potentials
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DOI：
10.1021/acs.jctc.0c00237
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发表时间：
2020-09-08
影响因子：
5.5
通讯作者：
York, Darrin M.
中科院分区：
文献类型：
--
作者：
Lee, Tai-Sung;Lin, Zhixiong;York, Darrin M.
gpu加速的自由能模拟软件的发展取得了进展，使复杂生物系统的实际应用成为可能，并推动了开发更准确、更强大的预测方法的努力。特别是，这项工作重新审视了通常用于水化和相对结合自由能（rbes）预测的协调（即一步或统一）炼金术转化。我们首先将这些计算中的几个已知挑战分为三类：端点灾难、粒子坍缩和大梯度跳跃。虽然端点灾难长期以来一直使用软核势来解决，但剩下的两个问题更加偶然地发生，可能导致数值不稳定（即，模拟完全失败）或不一致的估计（即，随机收敛到不正确的结果）。粒子坍缩问题源于短程静电和斥力相互作用的不平衡，原则上可以通过适当平衡各自的软核参数来解决。然而，大的梯度跳跃问题本身是由自由能对软核参数的大值的敏感性引起的，这可能用于试图解决粒子坍缩问题。通常，与现有的软核潜在形式没有令人满意的妥协。作为解决这些问题的框架，我们通过分析沿着炼金术路径的衍生物，开发了一个新的平滑阶软核（SSC）势族。平滑步多项式推广了在大多数实现中使用的单项式函数，并提供了一个额外的路径相关平滑参数。这种方法的有效性在简单而病理的案例中得到了证明，这些案例说明了概述的三个问题。通过适当的参数选择，我们发现二阶SSC(2)势至少与传统方法一样好，并且在所有情况下的一致性方面提供了巨大的改进。最后，我们比较了协同SSC(2)方法与金标准逐步（即解耦或多步骤）方案在药物发现中可能遇到的大量RBFE计算。
Progress in the development of GPU-accelerated free energy simulation software has enabled practical applications on complex biological systems and fueled efforts to develop more accurate and robust predictive methods. In particular, this work reexamines concerted (a.k.a., one-step or unified) alchemical transformations commonly used in the prediction of hydration and relative binding free energies (RBFEs). We first classify several known challenges in these calculations into three categories: endpoint catastrophes, particle collapse, and large gradient-jumps. While endpoint catastrophes have long been addressed using softcore potentials, the remaining two problems occur much more sporadically and can result in either numerical instability (i.e., complete failure of a simulation) or inconsistent estimation (i.e., stochastic convergence to an incorrect result). The particle collapse problem stems from an imbalance in short-range electrostatic and repulsive interactions and can, in principle, be solved by appropriately balancing the respective softcore parameters. However, the large gradient-jump problem itself arises from the sensitivity of the free energy to large values of the softcore parameters, as might be used in trying to solve the particle collapse issue. Often, no satisfactory compromise exists with the existing softcore potential form. As a framework for solving these problems, we developed a new family of smoothstep softcore (SSC) potentials motivated by an analysis of the derivatives along the alchemical path. The smoothstep polynomials generalize the monomial functions that are used in most implementations and provide an additional path-dependent smoothing parameter. The effectiveness of this approach is demonstrated on simple yet pathological cases that illustrate the three problems outlined. With appropriate parameter selection, we find that a second-order SSC(2) potential does at least as well as the conventional approach and provides vast improvement in terms of consistency across all cases. Last, we compare the concerted SSC(2) approach against the gold-standard stepwise (a.k.a., decoupled or multistep) scheme over a large set of RBFE calculations as might be encountered in drug discovery.