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使用基于片段的半经验量子化学快速简便地验证蛋白质-配体结合模型

Quick-and-Easy Validation of Protein-Ligand Binding Models Using Fragment-Based Semiempirical Quantum Chemistry.

作者信息

Bowling Paige E, Broderick Dustin R, Herbert John M

机构信息

Biophysics Graduate Program, The Ohio State University, Columbus, Ohio 43210, United States.

Department of Chemistry & Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States.

出版信息

J Chem Inf Model. 2025 Jan 27;65(2):937-949. doi: 10.1021/acs.jcim.4c01987. Epub 2025 Jan 3.

Abstract

Electronic structure calculations in enzymes converge very slowly with respect to the size of the model region that is described using quantum mechanics (QM), requiring hundreds of atoms to obtain converged results and exhibiting substantial sensitivity (at least in smaller models) to which amino acids are included in the QM region. As such, there is considerable interest in developing automated procedures to construct a QM model region based on well-defined criteria. However, testing such procedures is burdensome due to the cost of large-scale electronic structure calculations. Here, we show that semiempirical methods can be used as alternatives to density functional theory (DFT) to assess convergence in sequences of models generated by various automated protocols. The cost of these convergence tests is reduced even further by means of a many-body expansion. We use this approach to examine convergence (with respect to model size) of protein-ligand binding energies. Fragment-based semiempirical calculations afford well-converged interaction energies in a tiny fraction of the cost required for DFT calculations. Two-body interactions between the ligand and single-residue amino acid fragments afford a low-cost way to construct a "QM-informed" enzyme model of reduced size, furnishing an automatable active-site model-building procedure. This provides a streamlined, user-friendly approach for constructing ligand binding-site models that requires neither information nor manual adjustments. Extension to model-building for thermochemical calculations should be straightforward.

摘要

在酶中进行电子结构计算时,相对于使用量子力学(QM)描述的模型区域大小,收敛速度非常缓慢,需要数百个原子才能获得收敛结果,并且对QM区域中包含哪些氨基酸表现出极大的敏感性(至少在较小的模型中如此)。因此,人们对开发基于明确标准构建QM模型区域的自动化程序有着浓厚的兴趣。然而,由于大规模电子结构计算的成本,测试此类程序非常繁琐。在这里,我们表明半经验方法可以用作密度泛函理论(DFT)的替代方法,以评估由各种自动化协议生成的模型序列中的收敛性。通过多体展开,这些收敛测试的成本进一步降低。我们使用这种方法来研究蛋白质-配体结合能(相对于模型大小)的收敛性。基于片段的半经验计算以DFT计算所需成本的极小部分提供了收敛良好的相互作用能。配体与单残基氨基酸片段之间的二体相互作用提供了一种低成本的方法来构建尺寸减小的“QM信息”酶模型,提供了一种可自动化的活性位点模型构建程序。这提供了一种简化的、用户友好的方法来构建配体结合位点模型,既不需要信息也不需要手动调整。扩展到用于热化学计算的模型构建应该很简单。

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