A new scoring function for molecular docking

MARCOS ARIEL VILLARREAL; RODRIGO QUIROGA

San Luis.

Congreso; XLVIII Reunión Anual de la SAB; 2019

Sociedad argentina de Biofísica

Molecular Docking is a computational method to predict the strength, position and orientation of the ligand binding to a protein, and is a key tool in structure-based drug design. In essence, the method consists of the search for the global maximum of a mathematical function which represents the affinity of ligand at a given position in the protein surface. This mathematical function, termed scoring function, is developed based on different approaches. Among them, there are semi empirical, fully empirical, knowledge and artificial intelligence based methods. In our lab we started to develop an empirical scoring function based on the well-known Vina scoring function. In this work we present the newest version of our scoring function which includes several improvements. In particular, we focused on a better atom-typing, hydrogen bond interaction, and solvation terms. The philosophy behind our development was to come up with coarse grained interactions, where the atomic parameters that define the interactions are picked from a predefined and discrete set of values. The performance of the scoring function was evaluated for rescoring, redocking and virtual screening tasks. The results show that the new function performs better at the three tasks, when compared with our previous version and also with the original Vina function.