Department of Chemistry and Biochemistry, University of Missouri-St. Louis, St. Louis, Missouri, USA.
Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany.
J Comput Chem. 2022 Oct 30;43(28):1911-1922. doi: 10.1002/jcc.26991. Epub 2022 Sep 8.
Early-stage drug discovery projects often focus on equilibrium binding affinity to the target alongside selectivity and other pharmaceutical properties. The kinetics of drug binding are ignored but can have significant influence on drug efficacy. Therefore, increasing attention has been paid on evaluating drug-binding kinetics early in a drug discovery process. Simulating drug-binding kinetics at the atomic level is challenging for the long time scale involved. Here, we used the transition-based reweighting analysis method (TRAM) with the Markov state model to study the dissociation of a ligand from the protein kinase PYK2. TRAM combines biased and unbiased simulations to reduce computational costs. This work used the umbrella sampling technique for the biased simulations. Although using the potential of mean force from umbrella sampling simulations with the transition-state theory over-estimated the dissociation rate by three orders of magnitude, TRAM gave a dissociation rate within an order of magnitude of the experimental value.
早期药物发现项目通常侧重于平衡结合亲和力与目标物,同时还考虑选择性和其他药物特性。药物结合的动力学通常被忽略,但它可能对药物疗效产生重大影响。因此,人们越来越关注在药物发现过程的早期评估药物结合动力学。在原子水平上模拟药物结合动力学具有挑战性,因为涉及到的时间尺度很长。在这里,我们使用基于跃迁的重新加权分析方法 (TRAM) 和马尔可夫状态模型来研究配体从蛋白激酶 PYK2 上的解离。TRAM 结合了有偏和无偏模拟以降低计算成本。这项工作使用了有偏模拟的伞状取样技术。尽管使用过渡态理论从伞状取样模拟中获取平均力势会高估解离速率三个数量级,但 TRAM 的解离速率与实验值相差一个数量级。