Background: 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.
Methods: In this paper we propose a structure-based methodology, which is extensively validated, for the
discovery of dual Adenosine A2A Receptor/Monoamine Oxidase B ligands. This methodology involves
molecular docking studies against both receptors and the evaluation of different scoring functions fusion
strategies for maximizing the initial virtual screening enrichment of known dual ligands.
Results: The developed methodology provides high values of enrichment of known ligands, which
outperform that of the individual scoring functions. At the same time, the obtained ensemble can be
translated in a sequence of steps that should be followed to maximize the enrichment of dual target
Adenosine A2A Receptor antagonists and Monoamine Oxidase B inhibitors.
Conclusion: Information relative to docking scores to both targets have to be combined for achieving high dual
ligands enrichment. Combining the rankings derived from different scoring functions proved to be a valuable
strategy for improving the enrichment relative to single scoring function in virtual screening experiments.