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使用引导分子动力学对粘着斑激酶配体解离动力学进行定性预测。

Qualitative Prediction of Ligand Dissociation Kinetics from Focal Adhesion Kinase Using Steered Molecular Dynamics.

作者信息

Spiriti Justin, Wong Chung F

机构信息

Department of Chemistry and Bochemistry, University of Missouri-St. Louis, St. Louis, MO 63121-4400, USA.

出版信息

Life (Basel). 2021 Jan 20;11(2):74. doi: 10.3390/life11020074.

Abstract

Most early-stage drug discovery projects focus on equilibrium binding affinity to the target alongside selectivity and other pharmaceutical properties. Since many approved drugs have nonequilibrium binding characteristics, there has been increasing interest in optimizing binding kinetics early in the drug discovery process. As focal adhesion kinase (FAK) is an important drug target, we examine whether steered molecular dynamics (SMD) can be useful for identifying drug candidates with the desired drug-binding kinetics. In simulating the dissociation of 14 ligands from FAK, we find an empirical power-law relationship between the simulated time needed for ligand unbinding and the experimental rate constant for dissociation, with a strong correlation depending on the SMD force used. To improve predictions, we further develop regression models connecting experimental dissociation rate with various structural and energetic quantities derived from the simulations. These models can be used to predict dissociation rates from FAK for related compounds.

摘要

大多数早期药物发现项目专注于与靶点的平衡结合亲和力以及选择性和其他药物特性。由于许多已批准的药物具有非平衡结合特性,因此在药物发现过程的早期优化结合动力学方面的兴趣日益浓厚。由于粘着斑激酶(FAK)是一个重要的药物靶点,我们研究了引导分子动力学(SMD)是否有助于识别具有所需药物结合动力学的候选药物。在模拟14种配体从FAK的解离过程中,我们发现配体解离所需的模拟时间与实验解离速率常数之间存在经验幂律关系,且相关性很强,这取决于所使用的SMD力。为了改进预测,我们进一步开发了回归模型,将实验解离速率与从模拟中得出的各种结构和能量参数联系起来。这些模型可用于预测相关化合物从FAK的解离速率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf00/7909260/fd57d5edc717/life-11-00074-g001.jpg

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