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Improved virtual screening performance through docking scoring fusion in the discovery of dual target ligands for Parkinson’s disease
* 1, 2 , 1 , 3 , 4 , 4 , 5 , 6 , 4, 6
1  Molecular Simulation and Drug Design Group, Centro de Bioactivos Químicos (CBQ), Central University of Las Villas, Santa Clara, 54830, Cuba
2  Sección Físico Química y Matemáticas, Departamento de Química, Universidad Técnica Particular de Loja, San Cayetano Alto S/N, EC1101608 Loja, Ecuador
3  REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
4  Instituto de Investigaciones Biomédicas (IIB), Universidad de Las Américas, 170513 Quito, Ecuador
5  Departamento de Ciencias Naturales, Universidad Técnica Particular de Loja, Calle París S/N, EC1101608 Loja, Ecuador
6  CIQUP/Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, Porto 4169-007, Portugal.


Virtual methodologies have become essential components of the drug discovery pipeline. Specifically, structure-based drug design methodologies exploit the 3D structure of molecular targets to discover new drug candidates through molecular docking. Recently, dual target ligands of the Adenosine A2A Receptor and Monoamine Oxidase B enzyme have been proposed as effective therapies for the treatment of Parkinson’s disease. To the best of our knowledge, no theoretical study has been devoted to developing structure-based virtual screening methodologies for the discovery of dual A2AAR antagonists and MAO-B inhibitors. In this communication we propose a structure-based methodology for the discovery this type of molecules

Keywords: Parkinson’s disease, Dual target ligands, Molecular docking, Scoring fusion.