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RESEARCH PRODUCT
Reliability of Virtual Screening Methods in Prediction of PDE4Binhibitor Activity
Sanna NiinivehmasOlli T. PentikäinenVictoria Shubinasubject
Computer scienceQuantitative Structure-Activity RelationshipMultiple methodsLigandsComputers MolecularDrug DiscoveryProtein Interaction MappingHumansSimulationPharmacological Phenomenathree-dimensional quantitative structure-activity relationshipVirtual screeningbusiness.industryta1182Pattern recognitionmolecular dockingmolecular mechanics-generalized born-surface areavirtual screeningCyclic Nucleotide Phosphodiesterases Type 4Molecular Docking SimulationDocking (molecular)pharmacophore modelingArtificial intelligencePhosphodiesterase 4 InhibitorsPharmacophorebusinessphosphodiesterasedescription
Identification of active ligands using computational methods is a challenging task. For example, molecular docking, pharmacophore modeling, and three dimensional quantitative structure-activity relationship models (3D-QSAR) are widely used methods to identify novel small molecules. However, all these methods have, in addition to advantages, also significant pitfalls. The aim of this study was to compare some commonly used computational methods to estimate their ability to separate highly active PDE4B-inhibitors from less active and inactive ones. Here, 152 molecules with pIC 50 -range of 3.4-10.5, originating from six original studies were used. High correlation coefficients by using docking, docking with postprocessing with molecular mechanics-generalized Born-surface area -method (MMGBSA), pharmacophore modeling, and 3D-QSAR were obtained. These results are well in line with earlier studies done with similar methods, and suggest that computational methods could be successfully used to identify novel PDE4B-inhibitors, especially if using multiple methods together.
year | journal | country | edition | language |
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2015-08-06 | Current Drug Discovery Technologies |