In silico analysis of correlation between physicochemical properties of ligands and binding affinity to protein targets

In silico analysis is a powerful technique to identify better therapeutic interventions. Molecular docking is widely used to screen ligands through analysing binding affinities for target receptors. In this study we screened ligands for two proteins which are potential drug targets: deoxyuridine triphosphate nucleotidohydrolase (dUTPase) and 6- phosphoglucolactonase (6PGL). The enzyme dUTPase plays crucial roles in DNA replication and repair and has been implicated in a number of cancers in humans and the protein 6PGL is involved in the pentose phosphate pathway. We used 500 compounds from the dictionary of marine natural products to make the ligand library. The MarvinSketch was used for generating ligand structures. For virtual screening we used the PyRx software which utilizes Autodock vina for molecular docking. Ligand- receptor interactions were visualized using the BIOVIA Discovery Studio Visualizer software. From 500 compounds, 355 ligands followed the Lipinski rule of five. For dUTpase, ligand243 showed the highest binding affinity (-18.2 Kcal/mole). Interestingly, the same ligand exhibited the highest binding affinity (-17.5 Kcal/mole) for 6-PGL. We couldn’t find any significant correlation between binding affinities and physicochemical properties of the ligands. The dUTpase protein has been implicated in cancer pathophysiologies and the 6PGL has been identified as targets for treating sleeping sickness and malarial infections. We found that the ligand243 can bind to both of these drug targets with high affinities. Thus, this ligand can further be developed as a candidate drug for cancer, sleeping sickness and malarial infections.