Mirabzadeh Christopher A, Ytreberg F Marty
Department of Physics, University of Idaho, Moscow, ID, United States of America.
Institute for Modeling Collaboration and Innovation, University of Idaho, Moscow, ID, United States of America.
PeerJ Comput Sci. 2020;6. doi: 10.7717/peerj-cs.264. Epub 2020 Mar 16.
Estimating free energy differences by computer simulation is useful for a wide variety of applications such as virtual screening for drug design and for understanding how amino acid mutations modify protein interactions. However, calculating free energy differences remains challenging and often requires extensive trial and error and very long simulation times in order to achieve converged results. Here, we present an implementation of the adaptive integration method (AIM). We tested our implementation on two molecular systems and compared results from AIM to those from a suite of other methods. The model systems tested here include calculating the solvation free energy of methane, and the free energy of mutating the peptide GAG to GVG. We show that AIM is more efficient than other tested methods for these systems, that is, AIM results converge to a higher level of accuracy and precision for a given simulation time.
通过计算机模拟估算自由能差，对药物设计虚拟筛选等多种应用很有用，也有助于理解氨基酸突变如何改变蛋白质相互作用。然而，计算自由能差仍然具有挑战性，通常需要大量反复试验和很长的模拟时间才能得到收敛结果。在此，我们展示了自适应积分方法（AIM）的一种实现方式。我们在两个分子系统上测试了我们的实现方式，并将AIM的结果与其他一系列方法的结果进行了比较。这里测试的模型系统包括计算甲烷的溶剂化自由能，以及将肽GAG突变为GVG的自由能。我们表明，对于这些系统，AIM比其他测试方法更高效，即在给定模拟时间内，AIM的结果能收敛到更高的准确度和精密度水平。
