Show simple item record Seus, Vinicius Rosa Perazzo, Giovanni Xavier Winck, Ana Trindade Werhli, Adriano Velasque Machado, Karina dos Santos 2014-12-24T00:12:54Z 2014-12-24T00:12:54Z 2014
dc.identifier.citation SEUS, Vinicius Rosa et al. An Infrastructure to Mine Molecular Descriptors for Ligand Selection on Virtual Screening. BioMed Research International, v. 2014, p. 1-9, 2014. Disponível em: <>. Acesso em: 04 nov. 2014. pt_BR
dc.identifier.issn 2314-6141
dc.description.abstract The receptor-ligand interaction evaluation is one important step in rational drug design. The databases that provide the structures of the ligands are growing on a daily basis. This makes it impossible to test all the ligands for a target receptor. Hence, a ligand selection before testing the ligands is needed. One possible approach is to evaluate a set of molecular descriptors. With the aim of describing the characteristics of promising compounds for a specific receptor we introduce a data warehouse-based infrastructure to mine molecular descriptors for virtual screening (VS). We performed experiments that consider as target the receptor HIV-1 protease and different compounds for this protein. A set of 9 molecular descriptors are taken as the predictive attributes and the free energy of binding is taken as a target attribute. By applying the J48 algorithm over the data we obtain decision tree models that achieved up to 84% of accuracy. The models indicate which molecular descriptors and their respective values are relevant to influence good FEB results. Using their rules we performed ligand selection on ZINC database. Our results show important reduction in ligands selection to be applied in VS experiments; for instance, the best selection model picked only 0.21% of the total amount of drug-like ligands. pt_BR
dc.language.iso eng pt_BR
dc.rights open access pt_BR
dc.title An Infrastructure to Mine Molecular Descriptors for Ligand Selection on Virtual Screening pt_BR
dc.type article pt_BR
dc.identifier.doi pt_BR

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