Identification of cryptic pockets has the potential to open new therapeutic opportunities by discovering ligand binding sites that remain hidden in static apo structures of a target protein. Moreover, allosteric cryptic pockets can become valuable for designing target-selective ligands when the natural ligand binding sites are conserved in variants of a protein. For example, before an allosteric cryptic pocket was discovered, KRAS was considered undruggable due to its smooth surface and conservation of the GDP/GTP binding pocket across the wild type and oncogenic isoforms. Recent identification of the Switch-II cryptic pocket in the KRAS^G12C mutant and FDA approval of anticancer drugs targeting this site underscores the importance of cryptic pockets in solving pharmaceutical challenges. Here, we present a newly developed approach for the exploration of cryptic pockets using weighted ensemble molecular dynamics simulations with inherent normal modes as progress coordinates applied to the wild type KRAS and the G12D mutant. We performed extensive all-atomic simulations (>400 μs) with and without several cosolvents (xenon, ethanol, benzene), and analyzed trajectories using three distinct methods to search for potential binding pockets. These methods have been applied as a proof-of-concept to KRAS and have shown they can predict known cryptic binding sites. Furthermore, we performed ligand-binding simulations of a known inhibitor (MRTX1133) to shed light on the nature of cryptic pockets in KRAS^G12D and the role of conformational selection vs induced-fit mechanism in the formation of these cryptic pockets.

中文翻译：

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沿正则模式使用增强采样探索隐蔽口袋：KRAS G12D 的案例研究


鉴定隐蔽的口袋有可能通过发现隐藏在靶蛋白静态 apo 结构中的配体结合位点来开辟新的治疗机会。此外，当天然配体结合位点在蛋白质的变体中保守时，变构隐蔽的口袋对于设计靶标选择性配体很有价值。例如，在发现变构隐蔽口袋之前，KRAS 被认为不可成药，因为它的表面光滑，并且在野生型和致癌亚型中保留了 GDP/GTP 结合口袋。最近在 KRAS^G12C 突变体中发现了 Switch-II 隐蔽口袋，并且 FDA 批准了针对该部位的抗癌药物，这强调了隐蔽口袋在解决药物挑战中的重要性。在这里，我们提出了一种新开发的方法，用于使用加权集成分子动力学模拟来探索隐蔽口袋，其中固有的正则模式作为应用于野生型 KRAS 和 G12D 突变体的进程坐标。我们在有和没有几种助溶剂（氙、乙醇、苯）的情况下进行了广泛的全原子模拟 （>400 μs），并使用三种不同的方法分析轨迹以寻找潜在的结合口袋。这些方法已作为 KRAS 的概念验证应用，并表明它们可以预测已知的隐蔽结合位点。此外，我们对已知抑制剂 （MRTX1133） 进行了配体结合模拟，以阐明 KRAS^G12D 中隐蔽口袋的性质以及构象选择与诱导拟合机制在这些隐蔽口袋形成中的作用。