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Exploration of structural and physicochemical requirements and search of virtual hits for aminopeptidase N inhibitors
Aminopeptidase N (APN) inhibitors have been reported to be effective in treating of life threatening diseases including cancer. Validated ligand- and structure-based pharmacophore mapping approaches were combined with Bayesian modeling and recursive partitioning to identify structural and physicoche...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089330/ https://www.ncbi.nlm.nih.gov/pubmed/23341006 http://dx.doi.org/10.1007/s11030-013-9422-5 |
Sumario: | Aminopeptidase N (APN) inhibitors have been reported to be effective in treating of life threatening diseases including cancer. Validated ligand- and structure-based pharmacophore mapping approaches were combined with Bayesian modeling and recursive partitioning to identify structural and physicochemical requirements for highly active APN inhibitors. Based on the assumption that ligand- and structure-based pharmacophore models are complementary, the efficacy of ‘multiple pharmacophore screening’ for filtering true positive virtual hits was investigated. These multiple pharmacophore screening methods were utilized to search novel virtual hits for APN inhibition. The number of hits was refined and reduced by recursive partitioning, drug-likeliness, pharmacokinetic property prediction, and comparative molecular-docking studies. Four compounds were proposed as the potential virtual hits for APN enzyme inhibition. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11030-013-9422-5) contains supplementary material, which is available to authorized users. |
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