Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG, Groningen, Netherlands.
Faculty of Biomedical Sciences, Institute of Computational Science, Università della Svizzera italiana (USI), via G. Buffi 13, CH-6900, Lugano, Switzerland.
Nat Commun. 2020 Jul 24;11(1):3714. doi: 10.1038/s41467-020-17437-5.
The detailed understanding of the binding of small molecules to proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of protein-ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of protein-ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the well-characterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of ligand libraries or protein mutations using the coarse-grained Martini model.
详细了解小分子与蛋白质的结合情况是开发新型药物或提高酶对底物的接受能力的关键。如今，基于计算机的蛋白质-配体结合设计是完成这项任务的重要工具。目前的方法通常依赖于高通量对接实验或计算成本高昂的原子分子动力学模拟。在这里，我们提出了一种使用最近重新参数化的粗粒化 Martini 模型来对小药物样分子的蛋白质-配体相互作用进行无偏毫秒级采样的方法。值得注意的是，我们在不需要任何结合口袋或途径的先验知识的情况下实现了高精度。我们的方法应用于一系列系统，从经过充分研究的 T4 溶菌酶到 GPCR 家族和核受体成员，再到各种酶。所呈现的结果为使用粗粒化 Martini 模型进行配体文库或蛋白质突变的高通量筛选开辟了道路。
