Computational Drug Design and Biomedical Informatics Laboratory, Translational Medicine Research Institute (IIMT), CONICET-Universidad Austral, Derqui-Pilar, Buenos Aires, Argentina.
Austral Institute for Applied Artificial Intelligence, Universidad Austral, Derqui-Pilar, Buenos Aires, Argentina.
Methods Mol Biol. 2020;2114:269-284. doi: 10.1007/978-1-0716-0282-9_17.
Computational methods are a powerful and consolidated tool in the early stage of the drug lead discovery process. Among these techniques, high-throughput molecular docking has proved to be extremely useful in identifying novel bioactive compounds within large chemical libraries. In the docking procedure, the predominant binding mode of each small molecule within a target binding site is assessed, and a docking score reflective of the likelihood of binding is assigned to them. These methods also shed light on how a given hit could be modified in order to improve protein-ligand interactions and are thus able to guide lead optimization. The possibility of reducing time and cost compared to experimental approaches made this technology highly appealing. Due to methodological developments and the increase of computational power, the application of quantum mechanical methods to study macromolecular systems has gained substantial attention in the last decade. A quantum mechanical description of the interactions involved in molecular association of biomolecules may lead to better accuracy compared to molecular mechanics, since there are many physical phenomena that cannot be correctly described within a classical framework, such as covalent bond formation, polarization effects, charge transfer, bond rearrangements, halogen bonding, and others, that require electrons to be explicitly accounted for. Considering the fact that quantum mechanics-based approaches in biomolecular simulation constitute an active and important field of research, we highlight in this work the recent developments of quantum mechanical-based molecular docking and high-throughput docking.
计算方法是药物先导物发现过程早期的有力且成熟的工具。在这些技术中,高通量分子对接已被证明在从大型化学库中鉴定新型生物活性化合物方面非常有用。在对接过程中,评估了小分子在靶标结合部位中的主要结合模式,并为它们分配了反映结合可能性的对接分数。这些方法还揭示了给定命中物如何进行修饰以改善蛋白-配体相互作用,从而能够指导先导物优化。与实验方法相比,该技术具有减少时间和成本的可能性,因此具有很高的吸引力。由于方法学的发展和计算能力的提高,过去十年中,量子力学方法在研究大分子系统中的应用引起了广泛关注。与分子力学相比,对生物分子分子缔合中涉及的相互作用进行量子力学描述可能会具有更高的准确性,因为有许多物理现象不能在经典框架内正确描述,例如共价键形成、极化效应、电荷转移、键重排、卤键等,这需要明确考虑电子。考虑到基于量子力学的生物分子模拟方法是一个活跃且重要的研究领域,我们在本文中重点介绍了基于量子力学的分子对接和高通量对接的最新发展。