ABSTRACT
Trypanosoma cruzi, a flagellate protozoan parasite, is responsible for Chagas disease. The parasite major cysteine protease, cruzain (Cz), plays a vital role at every stage of its life cycle and the active-site region of the enzyme, similar to those of other members of the papain superfamily, is well characterized. Taking advantage of structural information available in public databases about Cz bound to known covalent inhibitors, along with their corresponding activity annotations, in this work, we performed a deep analysis of the molecular interactions at the Cz binding cleft, in order to investigate the enzyme inhibition mechanism. Our toolbox for performing this study consisted of the charge density topological analysis of the complexes to extract the molecular interactions and machine learning classification models to relate the interactions with biological activity. More precisely, such a combination was useful for the classification of molecular interactions as "active-like" or "inactive-like" according to whether they are prevalent in the most active or less active complexes, respectively. Further analysis of interactions with the help of unsupervised learning tools also allowed the understanding of how these interactions come into play together to trigger the enzyme into a particular conformational state. Most active inhibitors induce some conformational changes within the enzyme that lead to an overall better fit of the inhibitor into the binding cleft. Curiously, some of these conformational changes can be considered as a hallmark of the substrate recognition event, which means that most active inhibitors are likely recognized by the enzyme as if they were its own substrate so that the catalytic machinery is arranged as if it is about to break the substrate scissile bond. Overall, these results contribute to a better understanding of the enzyme inhibition mechanism. Moreover, the information about main interactions extracted through this work is already being used in our lab to guide docking solutions in ongoing prospective virtual screening campaigns to search for novel noncovalent cruzain inhibitors.
ABSTRACT
A series of tetrahydroisoquinolines functionalized with carbamates is reported here as highly selective ligands on the dopamine D2 receptor. These compounds were selected by means of a molecular modeling study. The studies were carried out in three stages: first an exploratory study was carried out using combined docking techniques and molecular dynamics simulations. According to these results, the bioassays were performed; these experimental studies corroborated the results obtained by molecular modeling. In the last stage of our study, a QTAIM analysis was performed in order to determine the main molecular interactions that stabilize the different ligand-receptor complexes. Our results show that the adequate use of combined simple techniques is a very useful tool to predict the potential affinity of new ligands at dopamine D1 and D2 receptors. In turn the QTAIM studies show that they are very useful to evaluate in detail the molecular interactions that stabilize the different ligand-receptor complexes; such information is crucial for the design of new ligands.
