Modeling receptor flexibility in the structure-based design of KRAS(G12C) inhibitors.
Modeling receptor flexibility in the structure-based design of KRAS(G12C) inhibitors.
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DOI：
10.1007/s10822-022-00467-0
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发表时间：
2022-08
影响因子：
3.5
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中科院分区：
文献类型：
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由于KRAS对其同源配体（GDP和GTP）具有高亲和力，并且缺乏易于利用的变构结合袋，因此长期以来被认为是“不可药物”的靶标。KRASG12C共价抑制剂的最新进展表明，位于KRASG12C α3-螺旋和开关- ii环之间的变抗结合位点（有时被称为“开关- ii口袋”）在KRASG12C直接抑制剂的设计中具有很大的潜力。在fda批准的KRASG12C抑制剂sotorasib （AMG 510）的开发过程中，我们研究了多种switch-II口袋粘合剂，发现switch-II口袋具有巨大的构像灵活性，这对基于结构的抑制剂设计提出了重大挑战。在这里，我们提出了在预测配体结合姿态和结合亲和力时处理受体灵活性的计算方法。为了预测结合位姿，我们修改了共价对接程序CovDock，以允许蛋白质构象迁移。这种新的对接方法被称为FlexCovDock，在10个交叉对接案例的数据集上，将结合位姿预测的成功率从55%提高到89%，并在不同的配体化学型上进行了前瞻性验证。对于结合亲和预测，我们发现标准的自由能摄动（FEP）方法不能充分处理开关- ii环的显著构象变化。我们开发了一种新的计算策略，通过使用靶向蛋白质突变来加速构象转变。利用该方法，对14个化合物的结合亲和力预测的平均无符号误差（MUE）从1.44降低到0.89 kcal/mol。这些方法在促进KRASG12C抑制剂的基于结构的设计中具有重要意义，并且预计将进一步用于设计其他构象不稳定蛋白靶点的共价（和非共价）抑制剂。在线版本包含补充材料，可在10.1007/s10822-022-00467-0获得。
KRAS has long been referred to as an ‘undruggable’ target due to its high affinity for its cognate ligands (GDP and GTP) and its lack of readily exploited allosteric binding pockets. Recent progress in the development of covalent inhibitors of KRASG12C has revealed that occupancy of an allosteric binding site located between the α3-helix and switch-II loop of KRASG12C—sometimes referred to as the ‘switch-II pocket’—holds great potential in the design of direct inhibitors of KRASG12C. In studying diverse switch-II pocket binders during the development of sotorasib (AMG 510), the first FDA-approved inhibitor of KRASG12C, we found the dramatic conformational flexibility of the switch-II pocket posing significant challenges toward the structure-based design of inhibitors. Here, we present our computational approaches for dealing with receptor flexibility in the prediction of ligand binding pose and binding affinity. For binding pose prediction, we modified the covalent docking program CovDock to allow for protein conformational mobility. This new docking approach, termed as FlexCovDock, improves success rates from 55 to 89% for binding pose prediction on a dataset of 10 cross-docking cases and has been prospectively validated across diverse ligand chemotypes. For binding affinity prediction, we found standard free energy perturbation (FEP) methods could not adequately handle the significant conformational change of the switch-II loop. We developed a new computational strategy to accelerate conformational transitions through the use of targeted protein mutations. Using this methodology, the mean unsigned error (MUE) of binding affinity prediction were reduced from 1.44 to 0.89 kcal/mol on a set of 14 compounds. These approaches were of significant use in facilitating the structure-based design of KRASG12C inhibitors and are anticipated to be of further use in the design of covalent (and noncovalent) inhibitors of other conformationally labile protein targets. The online version contains supplementary material available at 10.1007/s10822-022-00467-0.
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