CypReact: A Software Tool for in Silico Reactant Prediction for Human Cytochrome P450 Enzymes
- Siyang Tian
- Yannick Djoumbou Feunang
- Russ Greiner, Dept of Computing Science; PI of AICML
- David S. Wishart
In silico metabolism prediction requires first predicting whether a specific molecule will interact with one or more specific metabolizing enzymes, then predicting the result of each enzymatic reaction. CypReact, for performing this first task of reactant prediction. Specifically, CypReact takes as input an arbitrary molecule (specified as a SMILES string or a standard SDF file), and any one of the nine of the most important human cytochrome P450 (CYP450) enzymes -- CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1 or CYP3A4 -- and accurately predicts whether the query molecule will react with that given CYP450 enzyme. Tests of CypReact, conducted over a dataset of 1632 molecules (each considered a "plausible'' reactant) shows that it is very effective, with a (cross-validation) AUROC (area under the receiver operating characteristic curve) of 0.83 to 0.92. We also show that CypReact performs significantly better than other reactant prediction tools such as ADMET and (a reactant-predicting extension of) SmartCyp, whose average AUROCs are 0.75 and 0.53 respectively We then applied the learned CypReact models to a previously unseen set of molecules, and found that our CypReact did even better, and still significantly surpassed the performance of SmartCyp and ADMET. These results suggest that CypReact could be an important component of a suite of in silico metabolism prediction tools for accurately predicting the products of Phase I, Phase II and microbial metabolism in humans. CypReact is available at https://bitbucket.org/Leon_Ti/cypreact.
Citation
S. Tian, Y. Djoumbou Feunang, R. Greiner, D. Wishart. "CypReact: A Software Tool for in Silico Reactant Prediction for Human Cytochrome P450 Enzymes". Journal of Chemical Information and Modeling, 58(6), pp 1282–1291, May 2018.| Keywords: | biotransformer, machine learning, biochemistry, metabolomics, bioinformatcs |
| Category: | In Journal |
| Web Links: | Journal URL |
| DOI |
BibTeX
@article{Tian+al:JCIM18,
author = {Siyang Tian and Yannick Djoumbou Feunang and Russ Greiner and David
S. Wishart},
title = {CypReact: A Software Tool for in Silico Reactant Prediction for
Human Cytochrome P450 Enzymes},
Volume = "58",
Number = "6",
Pages = {1282–1291},
journal = {Journal of Chemical Information and Modeling},
year = 2018,
}Last Updated: October 04, 2020Submitted by Russ Greiner
