QSAR and Molecular Docking Techniques for the Discovery of Potent Monoamine Oxidase B Inhibitors: Computer-Aided Generation of New Rasagiline Bioisosteres

The search for new therapies against neurodegenerative disorders (NDs) such as Alzheimer (AD) and Parkinson (PD) constitutes a very active area. Although the scientific community has realized great efforts for the study of AD and PD from the most diverse points of view, these diseases remain incurable. Consequently, the design of new and more potent compounds for proteins associated with AD and PD represents nowadays, an objective of major importance. In this sense, the protein known as monoamine oxidase B (MAO-B) constitutes one of the key targets for the search of new drug candidates which could be employed as neuroprotective agents in both anti-AD and anti-PD chemotherapies. The present work is focused on the role of the Quantitative-Structure Activity Relationship (QSAR) analysis and molecular docking (MDock) techniques which have been applied for the discovery of new and promising molecular entities with high inhibitory activity against MAO-B. We also give a brief overview about one of the most potent MAO-B inhibitor drugs: rasagiline. Finally, as contribution to the field, we constructed a QSAR model using artificial neural network (ANN) analysis for the virtual screening of potent MAO-B inhibitors. By realizing a careful inspection of the meaning of the variables in the QSAR-ANN model, new rasagiline bioisosteres were suggested as possible potent MAO-B inhibitors.