Integrated Binary QSAR-Driven Virtual Screening and In Vitro Studies for Finding Novel hMAO-B-Selective Inhibitors

The increased activity of monoamine oxidase (MAO) enzymes may lead to serious consequences since they reduce the level of neurotransmitters and are associated with severe neurodegenerative diseases. The inhibition of this enzyme, especially the B isoform, plays a vital role in the treatment of Parkinson's disease (PD). This study is aimed to find novel human MAO-B (hMAO-B) selective inhibitors. A total of 256.750 compounds from the Otava small molecules database were virtually screened gradually by employing several screening techniques for this purpose. Initially, a high-throughput virtual screening (HTVS) method was employed, and 10% of the molecules having high docking scores were subjected to binary QSAR models for further screening of their therapeutic activities against PD, Alzheimer's disease (AD), and depression as well as for their toxicity and pharmacokinetic properties. Then, enzyme selectivity of the ligands towards the A and B forms that passed through all the filters were studied using the induced-fit docking method and molecular dynamics simulations. At the end of this exhaustive research, we identified two hit molecules ligand (Otava ID: 7131545) and ligand (Otava ID: 7566820). Based on the in vitro results, these two compounds (ligands and ) together with ligands and found in our previous study showed activity at the nanomolar (nM) level, and the results indicated that these four ligands inhibit hMAO-B better than the FDA-approved drug selegiline.