title: Prediction of the potency of mammalian cyclooxygenase inhibitors with ensemble proteochemometric modeling.
abstract: Cyclooxygenases (COX) are present in the body in two isoforms, namely: COX-1, constitutively expressed, and COX-2, induced in physiopathological conditions such as cancer or chronic inflammation. The inhibition of COX with non-steroideal anti-inflammatory drugs (NSAIDs) is the most widely used treatment for chronic inflammation despite the adverse effects associated to prolonged NSAIDs intake. Although selective COX-2 inhibition has been shown not to palliate all adverse effects (e.g. cardiotoxicity), there are still niche populations which can benefit from selective COX-2 inhibition. Thus, capitalizing on bioactivity data from both isoforms simultaneously would contribute to develop COX inhibitors with better safety profiles. We applied ensemble proteochemometric modeling (PCM) for the prediction of the potency of 3,228 distinct COX inhibitors on 11 mammalian cyclooxygenases. Ensemble PCM models ([Formula: see text], and RMSEtest = 0.71) outperformed models exclusively trained on compound ([Formula: see text], and RMSEtest = 1.09) or protein descriptors ([Formula: see text] and RMSEtest = 1.10) on the test set. Moreover, PCM predicted COX potency for 1,086 selective and non-selective COX inhibitors with [Formula: see text] and RMSEtest = 0.76. These values are in agreement with the maximum and minimum achievable [Formula: see text] and RMSEtest values of approximately 0.68 for both metrics. Confidence intervals for individual predictions were calculated from the standard deviation of the predictions from the individual models composing the ensembles. Finally, two substructure analysis pipelines singled out chemical substructures implicated in both potency and selectivity in agreement with the literature. Graphical AbstractPrediction of uncorrelated bioactivity profiles for mammalian COX inhibitors with Ensemble Proteochemometric Modeling.
authors.affiliation: Département de Biologie Structurale et Chimie, Institut Pasteur, Unité de Bioinformatique Structurale; CNRS UMR 3825, 25, rue du Dr Roux, Paris, 75015 France.
authors.forename: Isidro
authors.initials: I
authors.lastname: Cortes-Ciriano
authors.affiliation: Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Cambridge, UK.
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Murrell
authors.affiliation: European Molecular Biology Laboratory European Bioinformatics Institute Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD UK.
authors.forename: Gerard Jp
authors.initials: GJ
authors.lastname: van Westen
authors.affiliation: Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Cambridge, UK.
authors.forename: Andreas
authors.initials: A
authors.lastname: Bender
authors.affiliation: Département de Biologie Structurale et Chimie, Institut Pasteur, Unité de Bioinformatique Structurale; CNRS UMR 3825, 25, rue du Dr Roux, Paris, 75015 France.
authors.forename: Thérèse E
authors.initials: TE
authors.lastname: Malliavin
keywords: Applicability domain; Chemogenomics; Cyclooxygenases; Ensemble modeling; Proteochemometrics; QSAR