Molecular Docking Studies Applied to a Dataset of Cruzain Inhibitors

Abstract

Chagas' disease is one of the main causes of heart failure in developing countries. The disadvantages of current therapy include the undesirable side-effects, resistance, and therapeutic adhesion. The development of new efficient and safe drugs is, therefore, an issue of extreme importance. In order to gain a better understanding of how the compounds interact with the target, computational methods are essential. In this theoretical study, we report a docking protocol applied to a dataset of 173 cruzain inhibitors with IC50 values of less than 10 µM, belonging 16 different chemical classes. A preliminary analysis was performed, where the best protein structure for the study was identified. The enzyme was validated by redocking and a fingerprint graph for the ligand-enzyme interactions was generated, allowing the identification of the main amino acid residues related to the activity. Additionally, a larger cluster was generated, allowing the visualization of the orientation of the compounds and providing binding information for the different classes of compounds as well as their interaction in the cruzain active site. Amino acid residues other than those known as the catalytic triad (Gly23, Cys25, and Gly65) were identified, for example, Gln19 and Asp158. This provides a better insight into the mode of interaction of various cruzain inhibitors, which show IC50 values in the nanomolar range but which do not interact with the triad. These findings can help researchers to find new cruzain inhibitors for use in the fight against the Chagas disease.