Parkinson's disease (PD) is a chronic neurodegenerative disorder and reversible inhibitors of human monoamine oxidase (MAO) plays a key role in the metabolism of neurotransmitters and is important targets for the treatment of Parkinson's diseases.1 A training set of 94 compounds were considered and molecular descriptors were calculated by using semi empirical methods. QSAR model was generated from the training set where, R2=0.82 and R2cv=0. 79 further the model was validated with a test set of 18 compounds. The correlation plot of the BMLR model is shown in Figure 1  . More than 80% of the compounds revealed good agreement between experimental and predicted values with consistent descriptors with physical meaning which showed the model is statistically significant. The most active compounds were selected based on experimental data and pharmacological characters of the compounds. In-silicodesign of the human monoamine oxidase (MAO) inhibitors was carried out to virtually design library of new chemical entities with better activity. The most active compounds based on prediction and molecular modeling with the target would be synthesized and experimentally tested against monoamine oxidase (MAO).  Figure 1: Correlation plot of experimental and predicted values of training setRefernce 1Distinto, S., et. al., E. Euro. J. Med. Chem. 2012  ,48, 284-295.

In silico designing of human monoamine oxidase inhibitors

248th National Meeting (2014)

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