Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States.
Center for Computational Biology and Center for Computational Mathematics, Flatiron Institute, New York 10010, United States.
J Phys Chem Lett. 2024 Oct 24;15(42):10473-10478. doi: 10.1021/acs.jpclett.4c02332. Epub 2024 Oct 11.
Accurately describing protein-ligand binding and unbinding kinetics remains challenging. Computational calculations are difficult and costly, while experimental measurements often lack molecular detail and can be unobtainable. Here, we extend our multiscale milestoning method, Simulation-Enabled Estimation of Kinetics Rates (SEEKR), with metadynamics molecular dynamics simulations to yield accurate small molecule drug residence times. Using the pharmaceutically relevant threonine-tyrosine kinase (TTK) and eight long-residence-time (tens of seconds to hours) inhibitors, we demonstrate accurate prediction of absolute and rank-ordered ligand residence times and free energies of binding.
准确描述蛋白质-配体的结合和非结合动力学仍然具有挑战性。计算计算既困难又昂贵,而实验测量往往缺乏分子细节,并且可能无法获得。在这里,我们通过元动力学分子动力学模拟扩展了我们的多尺度里程碑方法,即“Simulation-Enabled Estimation of Kinetics Rates(SEEKR)”,以获得准确的小分子药物停留时间。使用具有药物相关性的苏氨酸-酪氨酸激酶(TTK)和 8 种长停留时间(数十秒到数小时)抑制剂,我们证明了对绝对和有序配体停留时间和结合自由能的准确预测。