ArticleJournal of cheminformatics2015
Prediction of the potency of mammalian cyclooxygenase inhibitors with ensemble proteochemometric modeling.
Article in Journal of cheminformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 117 citations in OpenAlex.
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- Prediction of Protein-Ligand Interaction Based on the Positional Similarity Scores Derived from Amino Acid Sequences.International journal of molecular sciences · 2019Article
- KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images.Journal of cheminformatics · 2019Article
- Multi-Layer Identification of Highly-Potent ABCA1 Up-Regulators Targeting LXRβ Using Multiple QSAR Modeling, Structural Similarity Analysis, and Molecular Docking.Molecules (Basel, Switzerland) · 2016Article
- Bioalerts: a python library for the derivation of structural alerts from bioactivity and toxicity data sets.Journal of cheminformatics · 2016Article
- Improved large-scale prediction of growth inhibition patterns using the NCI60 cancer cell line panel.Bioinformatics (Oxford, England) · 2016Article
- Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules.Journal of cheminformatics · 2015Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.