Departamento de Física, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil.
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, USA.
Sci Rep. 2021 Jan 13;11(1):1116. doi: 10.1038/s41598-020-80769-1.
Absolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.
通过带有显式溶剂分子模拟的绝对结合自由能计算，可以提供蛋白质-配体亲和力的估计，从而减少寻找新药物候选物所需的时间和成本。然而，这些计算的实现和执行可能很复杂。在这里，我们介绍了软件 BAT.py，这是一个 Python 工具，它调用 AMBER 模拟包来自动化计算一系列配体与蛋白质的结合自由能。该软件支持附着-拉伸-释放 (APR) 和双重去耦 (DD) 结合自由能方法，以及同时去耦-再耦 (SDR) 方法，这是一种双重去耦的变体，可以避免与带电配体相关的数值伪影。我们报告了该软件的初步测试应用，包括重新排列对接构象和估计整体结合自由能。我们还表明，通过在为此目的构建的普通机器上使用图形处理单元，可以廉价地进行这些计算。自动化和低成本的结合使该程序能够以相对高通量的模式应用，从而有望在药物发现的早期阶段实现新的应用。
