Parkinson’s disease is considered as common age-related progressive neuronal disorder characterized by motor, sensory, and cognitive dysfunction. Current medication for PD offers only symptomatic relief but no cure. Although it is considered that these medicines can produce acute or chronic side effects, and becomes less effective over a time. Owing to this concerns, the discovery of novel molecule is of considerable interest. Depletion of dopamine is one of the major cause of PD which is regulated by Monoamines. In this regards monoamine oxidase (MAO-B) inhibitors are of great interest to combat PD. Among several known molecules Pyrazolone has been evident for the MAO-B inhibitory potential. Therefore, in the present study MAO-B is selected as a key target to examine the interaction of Pyrazolone derivatives with crystal structure of MAO-B. For this purpose, Molecular docking, Quick prop module, and Mechanics/generalized born surface area (MM-GBSA) parameters are analyzed, to evaluate Molecular interaction, Pharmacokinetic parameters, and Binding energy. Further results show that compounds attached with chloride and nitrogen group have better binding efficiency, therefore they can be selected as a promising drug candidate for the treatment of PD.

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Aim: We explored pyrazolone derivatives for anti-Parkinson’s activity using in-silico tools to identify novel lead hits against Parkinson’s disease. Background: Parkinson’s disease is the most predominant neuronal degenerative disorder, caused by protein aggregation and dopamine imbalance. The available therapeutic agents on prolonged exposure lead to severe adverse eff ects and provide only symptomatic relief. Therefore, it is a need for novel drug molecules that would modulate the disease condition. Objectives: To identify novel hit molecule for a sequence of molecules designed using pyrazolone as a parent moiety by computer-aided drug design techniques. Materials and Methods: Derivatives are generated by various substituted functional groups and further, pharmacokinetic profi le, the biological spectrum, adverse drug eff ect, molecular docking, molecular dynamic, and MMPBSA evaluation was performed. Results: Thirty-four compounds follow a pharmacokinetic profi le. 15 compounds were predicted to possess a positive central nervous system activity score. The compounds C13, C12, C14, A1, C9, and C7 possessed the highest binding affi nity of -7.81, -3.15, -8.49, -3.43, -6.09, and -2.77 kcal/mol with various targets involved in Parkinson’s disease. Compound C13 exhibit ed highest binding score of -9.78 kcal/mol formono amino oxidase-B. Conclusion: From our investigations, we hope that novel substituted pyrazolone derivatives can act as an assuring virtual hit molecule for developing anti-Parkinson’s agents. These predictions obtained via in-silico techniques could aid the development of pharmacological inhibitors for Parkinson’s disease.