Abstract
A unified proteochemometric (PCM) model for the prediction of the ability of drug-like chemicals to inhibit five major drug metabolizing CYP isoforms (i.e. CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) was created and made publicly available under the Bioclipse Decision Support open source system at www.cyp450model.org. In regards to the proteochemometric modeling we represented the chemical compounds by molecular signature descriptors and the CYP-isoforms by alignment-independent description of composition and transition of amino acid properties of their protein primary sequences. The entire training dataset contained 63 391 interactions and the best PCM model was obtained using signature descriptors of height 1, 2 and 3 and inducing the model with a support vector machine. The model showed excellent predictive ability with internal AUC = 0.923 and an external AUC = 0.940, as evaluated on a large external dataset. The advantage of PCM models is their extensibility making it possible to extend our model for new CYP isoforms and polymorphic CYP forms. A key benefit of PCM is that all proteins are confined in one single model, which makes it generally more stable and predictive as compared with single target models. The inclusion of the model in Bioclipse Decision Support makes it possible to make virtual instantaneous predictions (∼100 ms per prediction) while interactively drawing or modifying chemical structures in the Bioclipse chemical structure editor.
Highlights
There are close to sixty Cytochrome P450 enzymes (CYPs) present in humans, where they facilitate oxidative metabolism of endogenous substances and xenobiotics
More than half of the compounds that are inhibitory on CYP1A2 inhibit CYP2C19 (3 252 of 5 838)
CYP1A2 shares more than 40% of its inhibitors with CYP3A4 and 35% with CYP2C9
Summary
There are close to sixty Cytochrome P450 enzymes (CYPs) present in humans, where they facilitate oxidative metabolism of endogenous substances and xenobiotics. Techniques for high throughput in vitro screening of CYP inhibition were developed and implemented on a broad scale in the drug discovery pipelines of pharmaceutical companies, as well as much open data has accumulated through academic research initiatives (e.g. PubChem Bioassays AID 410 and 1851) [5]. Vasanthanathan et al [6] and Novotarskyi et al [7] recently developed large-scale single target models for CYP1A2 isoform, and Cheng and co-workers [8] created single target models for five CYP isoforms (i.e. QSAR models). These models show good predictive performances, but have the disadvantage that they are not implemented as publicly available services. Another deficiency of these models (except the work by Cheng et al [8]) is the use of molecular descriptors that are calculated by commercial software packages, which does not allow implementation of the models in free, open source software
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