Title |
Cytochrome P450 site of metabolism prediction from 2D topological fingerprints using GPU accelerated probabilistic classifiers
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Published in |
Journal of Cheminformatics, May 2014
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DOI | 10.1186/1758-2946-6-29 |
Pubmed ID | |
Authors |
Jonathan D Tyzack, Hamse Y Mussa, Mark J Williamson, Johannes Kirchmair, Robert C Glen |
Abstract |
The prediction of sites and products of metabolism in xenobiotic compounds is key to the development of new chemical entities, where screening potential metabolites for toxicity or unwanted side-effects is of crucial importance. In this work 2D topological fingerprints are used to encode atomic sites and three probabilistic machine learning methods are applied: Parzen-Rosenblatt Window (PRW), Naive Bayesian (NB) and a novel approach called RASCAL (Random Attribute Subsampling Classification ALgorithm). These are implemented by randomly subsampling descriptor space to alleviate the problem often suffered by data mining methods of having to exactly match fingerprints, and in the case of PRW by measuring a distance between feature vectors rather than exact matching. The classifiers have been implemented in CUDA/C++ to exploit the parallel architecture of graphical processing units (GPUs) and is freely available in a public repository. |
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Geographical breakdown
Country | Count | As % |
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Germany | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Germany | 1 | 2% |
Netherlands | 1 | 2% |
Bulgaria | 1 | 2% |
United Kingdom | 1 | 2% |
Belgium | 1 | 2% |
Spain | 1 | 2% |
Unknown | 58 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 16 | 25% |
Student > Ph. D. Student | 15 | 23% |
Student > Master | 5 | 8% |
Student > Bachelor | 4 | 6% |
Professor | 3 | 5% |
Other | 12 | 19% |
Unknown | 9 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 15 | 23% |
Computer Science | 11 | 17% |
Biochemistry, Genetics and Molecular Biology | 7 | 11% |
Agricultural and Biological Sciences | 6 | 9% |
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 6% |
Other | 9 | 14% |
Unknown | 12 | 19% |