Fusing docking scoring functions improves the virtual screening performance for discovering Parkinson¿s disease dual target ligands

• Type: Article in International Scientific Journal
• Date: 2017

Authors

Perez Castillo, Y (Author) Other; Helguera, AM (Author) Other; Natalia N D S Cordeiro (Author) FCUP; Tejera, E (Author) Other; Paz Y Miño, C (Author) Other; Sánchez Rodríguez, A (Author) Other; Fernanda Borges (Author) FCUP; Cruz Monteagudo, M (Author) Other

Journal

Title: Current Neuropharmacology

Vol. 15

Pages: 1107-1116

ISSN: 1570-159X

Publisher: Bentham Science

Indexing

Scopus - 11 Citations

Other information

Authenticus ID: P-00T-QRR

DOI: 10.2174/1570159x15666170109143757

Abstract (EN): 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. © 2017 Bentham Science Publishers.

Language: English

Type (Professor's evaluation): Scientific