Department of Integrative Structural and Computational Biology, Scripps Research Institute, 10550 N. Torrey Pines, La Jolla, California 92037-1000, United States.
J Chem Inf Model. 2023 Sep 11;63(17):5631-5640. doi: 10.1021/acs.jcim.3c00832. Epub 2023 Aug 28.
We describe the formalization of the reactive docking protocol, a method developed to model and predict reactions between small molecules and biological macromolecules. The method has been successfully used in a number of applications already, including recapitulating large proteomics data sets, performing structure-reactivity target optimizations, and prospective virtual screenings. By modeling a near-attack conformation-like state, no QM calculations are required to model the ligand and receptor geometries. Here, we present its generalization using a large data set containing more than 400 ligand-target complexes, 8 nucleophilic modifiable residue types, and more than 30 warheads. The method correctly predicts the modified residue in ∼85% of complexes and shows enrichments comparable to standard focused virtual screenings in ranking ligands. This performance supports this approach for the docking and screening of reactive ligands in virtual chemoproteomics and drug design campaigns.
我们描述了反应对接协议的形式化,这是一种用于模拟和预测小分子和生物大分子之间反应的方法。该方法已经在许多应用中成功使用,包括重现大型蛋白质组学数据集、进行结构反应性靶标优化和前瞻性虚拟筛选。通过模拟近似攻击构象样状态,不需要进行量子力学计算来模拟配体和受体的几何形状。在这里,我们使用包含超过 400 个配体-靶复合物、8 种亲核可修饰残基类型和 30 多种弹头的大型数据集来展示其推广。该方法正确预测了约 85%的复合物中的修饰残基,并在配体排序方面表现出与标准聚焦虚拟筛选相当的富集。这种性能支持了该方法在虚拟化学生物和药物设计中的反应性配体对接和筛选。