Fragmented Molecular Docking to Rationally Improve the Accuracy of Blind Ligand-Receptor Binding Prediction

Molecular docking is a computational screening approach in drug design able to predict the conformation of a protein-ligand complex. Docking algorithms provide an efficient and cost-effective alternative to experimental high-throughput screenings. Molecular docking is generally applied starting from the knowledge of the protein binding region. However, a precise information about the correct binding site is often missing and it becomes necessary to explore the entire protein surface by docking algorithms. Several methods have been developed to overcome the problem of not recognizing the binding site. In the present thesis, a new methodology to identify the experimental binding mode of small molecule ligands into protein structures where the real binding sites are unknown will be presented. The approach consists of to carry out ligand-protein docking separately in multiple fragmented boxes, shifting the location of the box step by step, in order to cover the entire surface of the protein. This fragmented docking has been compared with the blind docking performed by standard docking protocols on 116 protein-ligand complexes of Heat Shock Protein 90 – alpha and 177 of Human Immunodeficiency virus protease 1. The fragmented docking has demonstrated its ability to identify more accurate docking poses than blind docking performed by Autodock-Vina. In order to improve the docking results Molecular-Mechanics/Generalized-Born-Surface-Area has been employed to rescore the docking outcomes. The results deriving from this rescoring show that MM/GBSA is able further increase the accuracy of the approach. The method is relived a good compromise between accuracy and computational effort. Further challenge could be accomplished by calculating the affinity with more rigorous methods to improve the performance achieved.