Computação biologicamente inspirada aplicada ao estudo da interação da monoamina oxidase e inibidores

Abstract

Parkinson's disease (PD) is a intriguing neurological disorder that affects the general population, attacking mainly in developing countries.This, it creates the need for discovery of therapeutic agents for the treatment of PD. Monoamine Oxidase (MAO) is an enzyme of major importance in neurochemistry, it catalyzes the oxidative deamination of biogenic amines, such as monoamine neurotransmitters and neuromodulators, as well as exogenous bioactive monoamines. On the basis of their substrate and inhibitor specificities, two isoforms of MAO have been described (A and B). Due to their role in the metabolism of catecholamines neurotransmitters, MAO-A and MAO-B have long been of pharmacological interest, and reversible and irreversible inhibitors of these isoforms are used clinically to treat neurological diseases including PD. Since the demonstration that I2-imidazoline sites are associated with mitochondrial membranes 15 years ago, several studies have provided evidence that these sites represent regions on MAOs. In line with this view, it has been demonstrated that imidazoline derivatives inhibit MAO activity. This effect has been attributed to a high affinity I2 binding site on MAO-B (I2B) and to a similar lower affinity site on MAO-A (I2A).Crystallographic studies have identified the field of imidazoline binding on monoamine oxidase B (MAO-B), which opens the possibility of molecular docking studies devoted to this binding site. Thus, this study aimed to identify new potential inhibitors of MAO-B. We are also interested in establishing a fast and reliable computational methodology for future molecular docking simulations focused on the imidazoline binding site of this enzyme. We used the program 'Molegro Virtual Docker' (MVD) in all simulations described here. All results indicated that the simplex algorithm evolution is able to successfully simulate the protein-ligand for MAO-B, and a function score (score MOLDOCK) implemented in the program MVD has a high correlation coefficient with the experimental activity.