DOX: A new computational protocol for accurate prediction of the protein-ligand binding structures

Molecular docking techniques have now been widely used to predict the protein-ligand binding modes, especially when the structures of crystal complexes are not available. Most docking algorithms are able to effectively generate and rank a large number of probable binding poses. However, it is hard for them to accurately evaluate these poses and identify the most accurate binding structure. In this study, we first examined the performance of some docking programs, based on a testing set made of 15 crystal complexes with drug statins for the human 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR). We found that most of the top ranking HMGR-statin binding poses, predicted by the docking programs, were energetically unstable as revealed by the high theoretical-level calculations, which were usually accompanied by the large deviations from the geometric parameters of the corresponding crystal binding structures. Subsequently, we proposed a new computational protocol, DOX, based on the joint use of molecular Docking, ONIOM, and eXtended ONIOM (XO) methods to predict the accurate binding structures for the protein-ligand complexes of interest. Our testing results demonstrate that the DOX protocol can efficiently predict accurate geometries for all 15 HMGR-statin crystal complexes without exception. This study suggests a promising computational route, as an effective alternative to the experimental one, toward predicting the accurate binding structures, which is the prerequisite for all the deep understandings of the properties, functions, and mechanisms of the protein-ligand complexes.