Quantum Chemical Approaches in Structure-Based Virtual Screening and Lead Optimization.
Quantum Chemical Approaches in Structure-Based Virtual Screening and Lead Optimization.
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DOI：
10.3389/fchem.2018.00188
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发表时间：
2018
影响因子：
5.5
通讯作者：
Aucar MG
中科院分区：
文献类型：
--
作者：
Cavasotto CN;Adler NS;Aucar MG
如今，计算化学已成为先导药物发现工作的综合工具。由于方法论的发展和计算机硬件的巨大进步，基于量子力学（QM）的方法在过去10年中受到了极大的关注，并且对生物大分子的计算越来越多地进行探索，旨在为蛋白质-配体相互作用的描述和结合亲和力的预测提供更好的准确性。原则上，QM 公式包括对能量的所有贡献，考虑了分子力学力场中通常缺失的术语，例如电子极化效应、金属配位和共价结合；此外，质量管理方法可以系统地改进，并提供更大程度的可转移性。在这篇小综述中，我们介绍了基于显式 QM 的方法在小分子对接和评分以及蛋白质-配体系统中结合自由能计算中的最新应用。尽管在工业药物先导物发现环境中常规使用基于质量管理的方法仍然是一项艰巨的挑战，但它们很可能将越来越多地成为药物发现管道中的积极参与者。
Today computational chemistry is a consolidated tool in drug lead discovery endeavors. Due to methodological developments and to the enormous advance in computer hardware, methods based on quantum mechanics (QM) have gained great attention in the last 10 years, and calculations on biomacromolecules are becoming increasingly explored, aiming to provide better accuracy in the description of protein-ligand interactions and the prediction of binding affinities. In principle, the QM formulation includes all contributions to the energy, accounting for terms usually missing in molecular mechanics force-fields, such as electronic polarization effects, metal coordination, and covalent binding; moreover, QM methods are systematically improvable, and provide a greater degree of transferability. In this mini-review we present recent applications of explicit QM-based methods in small-molecule docking and scoring, and in the calculation of binding free-energy in protein-ligand systems. Although the routine use of QM-based approaches in an industrial drug lead discovery setting remains a formidable challenging task, it is likely they will increasingly become active players within the drug discovery pipeline.
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