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药物设计中的 QM 实施:真的有帮助吗?

QM Implementation in Drug Design: Does It Really Help?

机构信息

Department of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.

Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, China.

出版信息

Methods Mol Biol. 2020;2114:19-35. doi: 10.1007/978-1-0716-0282-9_2.

Abstract

Computational chemistry allows one to characterize the structure, dynamics, and energetics of protein-ligand interactions, which makes it a valuable tool in drug discovery in both academic research and pharmaceutical industry. Molecular mechanics (MM)-based approaches are widely utilized to assist the discovery of new drug candidates. However, the complexity of protein-ligand interactions challenges the accuracy and efficiency of the commonly used empirical methods. Aiming to provide better accuracy in the description of protein-ligand interactions, quantum mechanics (QM)-based approaches are becoming increasingly explored. In principle, QM calculation includes all contributions to the energy, accounting for terms usually missing in empirical force fields, and provides a greater degree of transferability. The usefulness of QM in drug design cannot be overemphasized. In this chapter, we present recent developments and applications of fragment-based QM method in studying the protein-ligand and protein-protein interactions. We critically discuss the performance of the fragment-based QM method at different ab initio levels while trying to answer a critical question: do QM-based methods really help in drug design?

摘要

计算化学可以描述蛋白质-配体相互作用的结构、动态和能量学,使其成为学术研究和制药行业药物发现的有价值的工具。基于分子力学 (MM) 的方法被广泛用于辅助新候选药物的发现。然而,蛋白质-配体相互作用的复杂性挑战了常用经验方法的准确性和效率。为了在描述蛋白质-配体相互作用方面提供更好的准确性,基于量子力学 (QM) 的方法越来越受到探索。原则上,QM 计算包括对能量的所有贡献,考虑到经验力场中通常缺失的项,并提供更大程度的可转移性。QM 在药物设计中的重要性怎么强调都不为过。在本章中,我们介绍了基于片段的 QM 方法在研究蛋白质-配体和蛋白质-蛋白质相互作用方面的最新进展和应用。我们批判性地讨论了基于片段的 QM 方法在不同从头算水平下的性能,同时试图回答一个关键问题:基于 QM 的方法真的有助于药物设计吗?

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