Abstract
Background: Virtual Screening methodologies have emerged as efficient alternatives for the discovery of new drug candidates. At the same time, ensemble methods are nowadays frequently used to overcome the limitations of employing a single model in ligand-based drug design. However, many applications of ensemble methods to this area do not consider important aspects related to both virtual screening and the modeling process. During the application of ensemble methods to virtual screening the proper validation of the models in virtual screening conditions is often neglected. No analysis of the diversity of the ensemble members is performed frequently or no considerations regarding the applicability domain of the base models are being made. Methods: In this research, we review basic concepts and definitions related to virtual screening. We comment recent applications of ensemble methods to ligand-based virtual screening and highlight their advantages and limitations. Results: Next, we propose a method based on genetic algorithms optimization for the generation of virtual screening tailored ensembles which address the previously identified problems in the current applications of ensemble methods to virtual screening. Conclusion: Finally, the proposed methodology is successfully applied to the generation of ensemble models for the ligand-based virtual screening of dual target A2A adenosine receptor antagonists and MAO-B inhibitors as potential Parkinson’s disease therapeutics.
Keywords: Dual-target drugs, Virtual screening, MAO-B inhibitors, A2A adenosine receptors antagonist, Ensemble modeling, QSAR.
Current Pharmaceutical Design
Title:Ligand-Based Virtual Screening Using Tailored Ensembles: A Prioritization Tool for Dual A2A Adenosine Receptor Antagonists / Monoamine Oxidase B Inhibitors
Volume: 22 Issue: 21
Author(s): Aliuska Morales Helguera, Yunierkis Perez-Castillo, M. Natália D.S. Cordeiro, Eduardo Tejera, César Paz-y-Miño, Aminael Sánchez-Rodríguez, Marta Teijeira, Evys Ancede-Gallardo, Fernando Cagide, Fernanda Borges and Maykel Cruz-Monteagudo
Affiliation:
Keywords: Dual-target drugs, Virtual screening, MAO-B inhibitors, A2A adenosine receptors antagonist, Ensemble modeling, QSAR.
Abstract: Background: Virtual Screening methodologies have emerged as efficient alternatives for the discovery of new drug candidates. At the same time, ensemble methods are nowadays frequently used to overcome the limitations of employing a single model in ligand-based drug design. However, many applications of ensemble methods to this area do not consider important aspects related to both virtual screening and the modeling process. During the application of ensemble methods to virtual screening the proper validation of the models in virtual screening conditions is often neglected. No analysis of the diversity of the ensemble members is performed frequently or no considerations regarding the applicability domain of the base models are being made. Methods: In this research, we review basic concepts and definitions related to virtual screening. We comment recent applications of ensemble methods to ligand-based virtual screening and highlight their advantages and limitations. Results: Next, we propose a method based on genetic algorithms optimization for the generation of virtual screening tailored ensembles which address the previously identified problems in the current applications of ensemble methods to virtual screening. Conclusion: Finally, the proposed methodology is successfully applied to the generation of ensemble models for the ligand-based virtual screening of dual target A2A adenosine receptor antagonists and MAO-B inhibitors as potential Parkinson’s disease therapeutics.
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Morales Helguera Aliuska, Perez-Castillo Yunierkis, Natália D.S. Cordeiro M., Tejera Eduardo, Paz-y-Miño César, Sánchez-Rodríguez Aminael, Teijeira Marta, Ancede-Gallardo Evys, Cagide Fernando, Borges Fernanda and Cruz-Monteagudo Maykel, Ligand-Based Virtual Screening Using Tailored Ensembles: A Prioritization Tool for Dual A2A Adenosine Receptor Antagonists / Monoamine Oxidase B Inhibitors, Current Pharmaceutical Design 2016; 22 (21) . https://dx.doi.org/10.2174/1381612822666160302103542
DOI https://dx.doi.org/10.2174/1381612822666160302103542 |
Print ISSN 1381-6128 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4286 |
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