Predictive proteochemometric models for kinases derived from 3D protein field-based descriptors

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http://hdl.handle.net/10138/224401

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Subramanian , V , Prusis , P , Xhaard , H & Wohlfahrt , G 2016 , ' Predictive proteochemometric models for kinases derived from 3D protein field-based descriptors ' MedChemComm , vol. 7 , no. 5 , pp. 1007-1015 . DOI: 10.1039/c5md00556f

Title: Predictive proteochemometric models for kinases derived from 3D protein field-based descriptors
Author: Subramanian, Vigneshwari; Prusis, Peteris; Xhaard, Henri; Wohlfahrt, Gerd
Contributor: University of Helsinki, Division of Pharmaceutical Chemistry and Technology
University of Helsinki, Division of Pharmaceutical Chemistry and Technology
Date: 2016
Language: eng
Number of pages: 9
Belongs to series: MedChemComm
ISSN: 2040-2503
URI: http://hdl.handle.net/10138/224401
Abstract: Proteochemometrics, a method that simultaneously uses protein and ligand description, was used to model the target-ligand interaction space of 95 kinases and 1572 inhibitors. To build models, we applied 3-dimensional field-based description of the receptors, which allows the visualization of receptor and ligand features relevant for activity within the spatial framework of the binding sites. Receptor fields were derived from knowledge-based potentials and Schrodinger's WaterMaps, while ligands were described by different 1D, 2D and 3D descriptors. Besides good interpretability, which is important for inhibitor design, the obtained proteochemometric models also predicted external test sets with active and inactive ligands or additional protein targets for ligands with more than 80% accuracy and AUCs above 0.8.
Subject: INHIBITOR SELECTIVITY
DRUG DISCOVERY
DATABASE
KINOME
317 Pharmacy
1182 Biochemistry, cell and molecular biology
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