Publication: Accurate assessment of the strain energy in a protein-bound drug using QM/MM X-ray refinement and converged quantum chemistry

Abstract: An ongoing question regarding the energetics of protein-ligand binding has been; what is the strain energy that a ligand pays (if any) when binding to its protein target? The traditional method to estimate strain energy uses force fields to calculate the energy difference between the ligand bound conformation and its nearest local minimum/global minimum on the gas-phase or aqueous phase potential energy surface. This makes the implicit assumption that the underlying force field as well as the reference crystal structure is accurate. Herein, we use ibuprofen as a test case and compare MMFF and ab initio QM methods to identify the local and global minimum conformations. Nine low energy conformations were identified with HF/6-31G* geometry optimization in vacuo. We also obtained highly accurate relative energies for ibuprofen’s conformational energy surface based on M06/aug-cc-pVXZ (X = D and T), MP2/aug-cc-pVXZ (X = D and T) and the MP2/CBS method (with and without solvent corrections). Moreover, we curate and re-refine the ibuprofen-protein complex (PDB 2BXG) using QM/MM X-ray refinement approaches (HF/6-31G* was the QM method and the MM model was the AMBER force field ff99sb), which were compared with the low energy conformers to calculate the strain energy. The result indicates that there was an 88% reduction in ibuprofen conformation strain using the QM/MM refined structure versus the original PDB ibuprofen conformations. Furthermore, our results indicate that, due to its inherent limitations in estimating electrostatic interactions, force fields are not suitable to gauge strain energy for charged drug molecules like ibuprofen. The present work offers a carefully validated conformational potential energy surface for a drug molecule as well as a reliable QM/MM re-refined X-ray structure that can be used to test current structure-based drug design approaches.

Authors: Zheng Fu, Xue Li, and Kenneth M. Merz Jr.

Reference: J. Comput. Chem., 32: 2587–2597 (see link for full paper).