Induced-Fit Docking Enables Accurate Free Energy Perturbation Calculations in Homology ModelsClick to copy article linkArticle link copied!
- Tianchuan XuTianchuan XuSchrödinger, Inc., 1540 Broadway, New York, New York 10036, United StatesMore by Tianchuan Xu
- Kai Zhu
- Alexandre BeautraitAlexandre BeautraitSchrödinger, Inc., 1540 Broadway, New York, New York 10036, United StatesMore by Alexandre Beautrait
- Jeremie VendomeJeremie VendomeSchrödinger, Inc., 1540 Broadway, New York, New York 10036, United StatesMore by Jeremie Vendome
- Kenneth W. BorrelliKenneth W. BorrelliSchrödinger, Inc., 1540 Broadway, New York, New York 10036, United StatesMore by Kenneth W. Borrelli
- Robert AbelRobert AbelSchrödinger, Inc., 1540 Broadway, New York, New York 10036, United StatesMore by Robert Abel
- Richard A. FriesnerRichard A. FriesnerDepartment of Chemistry, Columbia University, 3000 Broadway, MC 3110, New York, New York 10036, United StatesMore by Richard A. Friesner
- Edward B. Miller*Edward B. Miller*Email: [email protected]Schrödinger, Inc., 1540 Broadway, New York, New York 10036, United StatesMore by Edward B. Miller
Abstract
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.
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