Callegari Donatella, Lodola Alessio, Pala Daniele, Rivara Silvia, Mor Marco, Rizzi Andrea, Capelli Anna Maria
Dipartimento di Farmacia, Università degli Studi di Parma , Viale delle scienze 27/A, 43124 Parma, Italy.
Chemistry Research and Drug Design Department, Chiesi Farmaceutici S.p.A. , Largo F. Belloli 11/A, 43122 Parma, Italy.
J Chem Inf Model. 2017 Feb 27;57(2):159-169. doi: 10.1021/acs.jcim.6b00679. Epub 2017 Jan 12.
The duration of drug efficacy in vivo is a key aspect primarily addressed during the lead optimization phase of drug discovery. Hence, the availability of robust computational approaches that can predict the residence time of a compound at its target would accelerate candidate selection. Nowadays the theoretical prediction of this parameter is still very challenging. Starting from methods reported in the literature, we set up and validated a new metadynamics (META-D)-based protocol that was used to rank the experimental residence times of 10 arylpyrazole cyclin-dependent kinase 8 (CDK8) inhibitors for which target-bound X-ray structures are available. The application of reported methods based on the detection of the escape from the first free energy well gave a poor correlation with the experimental values. Our protocol evaluates the energetics of the whole unbinding process, accounting for multiple intermediates and transition states. Using seven collective variables (CVs) encoding both roto-translational and conformational motions of the ligand, a history-dependent biasing potential is deposited as a sum of constant-height Gaussian functions until the ligand reaches an unbound state. The time required to achieve this state is proportional to the integral of the deposited potential over the CV hyperspace. Average values of this time, for replicated META-D simulations, provided an accurate classification of CDK8 inhibitors spanning short, medium, and long residence times.
药物在体内的疗效持续时间是药物研发先导化合物优化阶段主要关注的一个关键方面。因此,能够预测化合物在其靶点停留时间的强大计算方法的出现将加速候选药物的筛选。如今,对该参数的理论预测仍然极具挑战性。从文献报道的方法出发,我们建立并验证了一种基于元动力学(META-D)的新方案,该方案用于对10种芳基吡唑细胞周期蛋白依赖性激酶8(CDK8)抑制剂的实验停留时间进行排序,这些抑制剂都有靶点结合的X射线结构。基于检测从第一个自由能阱逃逸的已报道方法的应用与实验值的相关性较差。我们的方案评估了整个解离过程的能量学,考虑了多个中间体和过渡态。使用七个编码配体旋转平移和构象运动的集体变量(CVs),一个历史依赖的偏向势作为恒定高度高斯函数的总和进行沉积,直到配体达到未结合状态。达到该状态所需的时间与在CV超空间上沉积势的积分成正比。对于重复的META-D模拟,该时间的平均值为跨越短、中、长停留时间的CDK8抑制剂提供了准确的分类。