How Robust Is the Ligand Binding Transition State?
How Robust Is the Ligand Binding Transition State?
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DOI：
10.1021/jacs.3c08940
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发表时间：
2023-11-09
影响因子：
15
通讯作者：
Dickson，Alex
中科院分区：
文献类型：
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作者：
Bose，Samik;Lotz，Samuel D.;Dickson，Alex
对于许多药物靶标，已经表明药物结合的动力学（例如，打开速率和关闭速率）比单独的热力学量更能预测药物功效。这促使预测计算模型的发展，可用于优化化合物的动力学的基础上。支撑这些计算模型的结构细节不仅存在于结合态，而且存在于短寿命的配体结合过渡态。虽然过渡态不能直接观察到的实验，由于其极短的寿命，最近的成功已经证明，建模的配体结合过渡态是可能的帮助下，增强的采样分子动力学方法。在此之前，我们产生的解结合路径的可溶性环氧化物水解酶（sEH）的抑制剂的停留时间为11分钟。在这里，我们计算建模的解结合事件与加权合奏方法REVO（通过变化优化的合奏restenance）为5个额外的抑制剂sEH的停留时间范围从14.25到31.75分钟，平均预测精度在一个数量级。对非结合态系综进行了详细的分析，重点讨论了配体结合过渡态系综的特点。我们发现，具有相似结合位姿的配体在其配体结合TSE中，在其空间分布和蛋白质-配体相互作用方面可以显示出显着差异。然而，我们也发现在检查更一般的功能，如配体自由度的TSE的相似之处。这些发现共同显示了基于动力学的合理药物设计的重大挑战。
For many drug targets, it has been shown that the kinetics of drug binding (e.g., on rate and off rate) is more predictive of drug efficacy than thermodynamic quantities alone. This motivates the development of predictive computational models that can be used to optimize compounds on the basis of their kinetics. The structural details underpinning these computational models are found not only in the bound state but also in the short-lived ligand binding transition states. Although transition states cannot be directly observed experimentally due to their extremely short lifetimes, recent successes have demonstrated that modeling the ligand binding transition state is possible with the help of enhanced sampling molecular dynamics methods. Previously, we generated unbinding paths for an inhibitor of soluble epoxide hydrolase (sEH) with a residence time of 11 min. Here, we computationally modeled unbinding events with the weighted ensemble method REVO (resampling of ensembles by variation optimization) for five additional inhibitors of sEH with residence times ranging from 14.25 to 31.75 min, with average prediction accuracy within an order of magnitude. The unbinding ensembles are analyzed in detail, focusing on features of the ligand binding transition state ensembles (TSEs). We find that ligands with similar bound poses can show significant differences in their ligand binding TSEs, in terms of their spatial distribution and protein–ligand interactions. However, we also find similarities across the TSEs when examining more general features such as ligand degrees of freedom. Together these findings show significant challenges for rational, kinetics-based drug design.