EaStChem School of Chemistry, Joseph Black Building, University of Edinburgh, Edinburgh, UK.
Evotec (UK) Ltd., In Silico Research and Development, Abingdon, Oxfordshire, UK.
Methods Mol Biol. 2024;2716:241-264. doi: 10.1007/978-1-0716-3449-3_11.
Alchemical free energy methods can be used for the efficient computation of relative binding free energies during preclinical drug discovery stages. In recent years, this has been facilitated further by the implementation of workflows that enable non-experts to quickly and consistently set up the required simulations. Given the correct input structures, workflows handle the difficult aspects of setting up perturbations, including consistently defining the perturbable molecule, its atom mapping and topology generation, perturbation network generation, running of the simulations via different sampling methods, and analysis of the results. Different academic and commercial workflows are discussed, including FEW, FESetup, FEPrepare, CHARMM-GUI, Transformato, PMX, QLigFEP, TIES, ProFESSA, PyAutoFEP, BioSimSpace, FEP+, Flare, and Orion. These workflows differ in various aspects, such as mapping algorithms or enhanced sampling methods. Some workflows can accommodate more than one molecular dynamics (MD) engine and use external libraries for tasks. Differences between workflows can present advantages for different use cases, however a lack of interoperability of the workflows' components hinders systematic comparisons.
可以使用无化学自由能方法在临床前药物发现阶段高效计算相对结合自由能。近年来,通过实施使非专家能够快速且一致地设置所需模拟的工作流程,进一步促进了这一点。给定正确的输入结构,工作流程处理设置扰动的困难方面,包括一致地定义可扰动分子、其原子映射和拓扑生成、扰动网络生成、通过不同采样方法运行模拟以及分析结果。讨论了不同的学术和商业工作流程,包括 FEW、FESetup、FEPrepare、CHARMM-GUI、Transformato、PMX、QLigFEP、TIES、ProFESSA、PyAutoFEP、BioSimSpace、FEP+、Flare 和 Orion。这些工作流程在映射算法或增强采样方法等方面存在差异。一些工作流程可以容纳多个分子动力学 (MD) 引擎,并使用外部库执行任务。工作流程之间的差异可能为不同的用例带来优势,但是工作流程组件的互操作性缺乏会阻碍系统比较。