MovableType Software for Fast Free Energy-Based Virtual Screening: Protocol Development, Deployment, Validation, and Assessment.

MovableType Software for Fast Free Energy-Based Virtual Screening: Protocol Development, Deployment, Validation, and Assessment.
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DOI:
10.1021/acs.jcim.0c00618
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发表时间:
2020-11-23
影响因子:
5.6
通讯作者:
Westerhoff LM
Westerhoff LM
中科院分区:
化学2区
文献类型:
--
作者:
Zheng Z;Borbulevych OY;Liu H;Deng J;Martin RI;Westerhoff LM

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几十年来,大分子蛋白质:配体结构中发现的复杂能量表面需要大量的计算时间和资源来进行能量状态采样,这一直是工业药物发现工作中快速、常规自由能估计的固有障碍。从 2013 年开始,Merz 研究小组通过引入一种称为“可移动类型”(MT) 的新型抽样方法来解决这一成本问题。使用数值积分方法,MT方法通过从初始分子构象独立计算每个原子配分函数来减少能态采样的计算费用,以便使用原子配分函数的集合来估计分子自由能。在这项工作中,我们报告了一个软件包,即带有 QuantumBio Inc. 的 MovableType 模块的 DivCon Discovery Suite,它以快速、完全封装的方式执行此 MT 自由能估计协议。我们讨论了计算过程和对原始工作的改进,并详细介绍了该软件包的相应设置。最后,我们引入了两个验证基准来评估该方法针对广泛的蛋白质:配体结构情况的整体稳健性。通过这些公开可用的基准,我们表明该方法可以使用各种输入类型和参数,并且无论该方法是使用“昂贵的”X射线结构还是“廉价的对接”理论模型,都表现出相当的可预测性。我们还探索了该方法的一些后续步骤。 MovableType 软件可在以下位置获取:
For decades, the complicated energy surfaces found in macromolecular protein:ligand structures, which require large amounts of computational time and resources for energy state sampling, have been an inherent obstacle to fast, routine free energy estimation in industrial drug discovery efforts. Beginning in 2013, the Merz research group addressed this cost with the introduction of a novel sampling methodology termed “Movable Type” (MT). Using numerical integration methods, the MT method reduces the computational expense for energy state sampling by independently calculating each atomic partition function from an initial molecular conformation in order to estimate the molecular free energy using ensembles of the atomic partition functions. In this work, we report a software package, the DivCon Discovery Suite with the MovableType module from QuantumBio Inc., that performs this MT free energy estimation protocol in a fast, fully encapsulated manner. We discuss the computational procedures and improvements to the original work, and we detail the corresponding settings for this software package. Finally, we introduce two validation benchmarks to evaluate the overall robustness of the method against a broad range of protein:ligand structural cases. With these publicly available benchmarks, we show that the method can use a variety of input types and parameters and exhibits comparable predictability whether the method is presented with “expensive” X-ray structures or “inexpensively docked” theoretical models. We also explore some next steps for the method. The MovableType software is available at
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