Schrödinger, Inc., 120 West 45th Street, New York, New York 10036, United States.
Schrödinger, Inc., 10201 Wateridge Circle, San Diego, California 92121, United States.
J Chem Theory Comput. 2021 Apr 13;17(4):2630-2639. doi: 10.1021/acs.jctc.1c00136. Epub 2021 Mar 29.
We present a reliable and accurate solution to the induced fit docking problem for protein-ligand binding by combining ligand-based pharmacophore docking, rigid receptor docking, and protein structure prediction with explicit solvent molecular dynamics simulations. This novel methodology in detailed retrospective and prospective testing succeeded to determine protein-ligand binding modes with a root-mean-square deviation within 2.5 Å in over 90% of cross-docking cases. We further demonstrate these predicted ligand-receptor structures were sufficiently accurate to prospectively enable predictive structure-based drug discovery for challenging targets, substantially expanding the domain of applicability for such methods.
我们提出了一种可靠且精确的解决诱导契合对接问题的方法,该方法将配体基于药效团的对接、刚性受体对接和蛋白质结构预测与带溶剂分子动力学模拟的显式溶剂结合在一起。这种新的方法在详细的回顾性和前瞻性测试中成功地确定了蛋白质-配体结合模式,其中超过 90%的交叉对接案例的均方根偏差在 2.5Å 以内。我们进一步证明,这些预测的配体-受体结构足够准确,可以前瞻性地实现具有挑战性的靶标基于结构的药物发现,从而大大扩展了此类方法的适用范围。