Toward Focusing Conformational Ensembles on Bioactive Conformations: A Molecular Mechanics/Quantum Mechanics Study

The identification of bound conformations, namely, conformations adopted by ligands when binding their target is critical for target-based and ligand-based drug design. Bound conformations could be obtained computationally from unbound conformational ensembles generated by conformational search tools. However, these tools also generate many nonrelevant conformations thus requiring a focusing mechanism. To identify such a mechanism, this work focuses on a comparison of energies and structural properties of bound and unbound conformations for a set of FDA approved drugs whose complexes are available in the PDB. Unbound conformational ensembles were initially obtained with three force fields. These were merged, clustered, and reminimized using the same force fields and four QM methods. Bound conformations of all ligands were represented by their crystal structures or by approximations to these structures. Energy differences were calculated between global minima of the unbound state or the Boltzmann averaged energies of the unbound ensemble and the approximated bound conformations. Ligand conformations which resemble the X-ray conformation (RMSD < 1.0 Å) were obtained in 91%-97% and 96%-98% of the cases using the ensembles generated by the individual force fields and the reminimized ensembles, respectively, yet only in 52%-56% (original ensembles) and 47%-65% (reminimized ensembles) as global energy minima. The energy window within which the different methods identified the bound conformation (approximated by its closest local energy minimum) was found to be at 4-6 kcal/mol with respect to the global minimum and marginally lower with respect to a Boltzmann averaged energy of the unbound ensemble. Better approximations to the bound conformation obtained with a constrained minimization using the crystallographic B-factors or with a newly developed Knee Point Detection (KPD) method gave lower values (2-5 kcal/mol). Overall, QM methods gave lower energy differences than force field methods. These energy thresholds could be used for focusing conformational ensembles on bound conformations. For example, when using energy cutoffs which corresponded to retaining 50% and 70% of the ensembles, QM methods and CHARMm offer 60-65% and 80-84% probability of obtaining the bound conformation, respectively. In contrast, none of the structural criteria considered in this work was able to differentiate between bound and unbound conformations.