Schrödinger, Inc., 1540 Broadway, New York, New York 10036, United States.
Department of Chemistry, Columbia University, 3000 Broadway, MC 3110, New York, New York 10036, United States.
J Chem Theory Comput. 2022 Sep 13;18(9):5710-5724. doi: 10.1021/acs.jctc.2c00371. Epub 2022 Aug 16.
Homology models have been used for virtual screening and to understand the binding mode of a known active compound; however, rarely have the models been shown to be of sufficient accuracy, comparable to crystal structures, to support free-energy perturbation (FEP) calculations. We demonstrate here that the use of an advanced induced-fit docking methodology reliably enables predictive FEP calculations on congeneric series across homology models ≥30% sequence identity. Furthermore, we show that retrospective FEP calculations on a congeneric series of drug-like ligands are sufficient to discriminate between predicted binding modes. Results are presented for a total of 29 homology models for 14 protein targets, showing FEP results comparable to those obtained using experimentally determined crystal structures for 86% of homology models with template structure sequence identities ranging from 30 to 50%. Implications for the use and validation of homology models in drug discovery projects are discussed.
同源模型已被用于虚拟筛选和了解已知活性化合物的结合模式;然而,这些模型很少被证明具有足够的准确性,可与晶体结构相媲美,以支持自由能微扰(FEP)计算。在这里,我们证明了使用先进的诱导契合对接方法,可以可靠地对同源模型≥30%序列同一性的同类系列进行预测性 FEP 计算。此外,我们还表明,对药物样配体的同类系列进行回顾性 FEP 计算足以区分预测的结合模式。总共为 14 个蛋白质靶标提供了 29 个同源模型的结果,对于模板结构序列同一性为 30%至 50%的同源模型,86%的同源模型的 FEP 结果与使用实验确定的晶体结构获得的结果相当。讨论了同源模型在药物发现项目中的使用和验证的意义。