Cavasotto Claudio N, Aucar M Gabriela
Computational Drug Design and Biomedical Informatics Laboratory, Translational Medicine Research Institute (IIMT), CONICET-Universidad Austral, Pilar, Argentina.
Facultad de Ciencias Biomédicas and Facultad de Ingeniería, Universidad Austral, Pilar, Argentina.
Front Chem. 2020 Apr 21;8:246. doi: 10.3389/fchem.2020.00246. eCollection 2020.
Today high-throughput docking is one of the most commonly used computational tools in drug lead discovery. While there has been an impressive methodological improvement in docking accuracy, docking scoring still remains an open challenge. Most docking programs are rooted in classical molecular mechanics. However, to better characterize protein-ligand interactions, the use of a more accurate quantum mechanical (QM) description would be necessary. In this work, we introduce a QM-based docking scoring function for high-throughput docking and evaluate it on 10 protein systems belonging to diverse protein families, and with different binding site characteristics. Outstanding results were obtained, with our QM scoring function displaying much higher enrichment (screening power) than a traditional docking method. It is acknowledged that developments in quantum mechanics theory, algorithms and computer hardware throughout the upcoming years will allow semi-empirical (or low-cost) quantum mechanical methods to slowly replace force-field calculations. It is thus urgently needed to develop and validate novel quantum mechanical-based scoring functions for high-throughput docking toward more accurate methods for the identification and optimization of modulators of pharmaceutically relevant targets.
如今,高通量对接是药物先导物发现中最常用的计算工具之一。虽然对接准确性在方法上有了显著改进,但对接评分仍然是一个悬而未决的挑战。大多数对接程序都基于经典分子力学。然而,为了更好地表征蛋白质-配体相互作用,使用更精确的量子力学(QM)描述将是必要的。在这项工作中,我们引入了一种基于量子力学的高通量对接评分函数,并在属于不同蛋白质家族且具有不同结合位点特征的10个蛋白质系统上对其进行了评估。我们获得了出色的结果,我们的量子力学评分函数显示出比传统对接方法更高的富集度(筛选能力)。人们认识到,在未来几年中,量子力学理论、算法和计算机硬件的发展将使半经验(或低成本)量子力学方法逐渐取代力场计算。因此,迫切需要开发和验证基于量子力学的新型高通量对接评分函数,以实现更准确的方法来识别和优化与药物相关靶点的调节剂。