Format

Send to

Choose Destination
J Cheminform. 2016 Nov 4;8:61. eCollection 2016.

ClassyFire: automated chemical classification with a comprehensive, computable taxonomy.

Author information

1
Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8 Canada.
2
Jobber - Field Service Software, 10520 Jasper Ave, Edmonton, AB T5J 1Z7 Canada.
3
Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8 Canada.
4
Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Civic Campus, 1053 Carling Ave, Ottawa, ON K1Y 4E9 Canada.
5
European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge UK.
6
Department of Bioengineering, University of California, La Jolla, San Diego, CA 92093 USA.
7
Department of Health and Human Services, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894 USA.
8
Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8 Canada ; Department of Computing Science 2-21 Athabasca Hall, Alberta Innovates Centre for Machine Learning (AICML), University of Alberta, Edmonton, AB T6G 2E8 Canada.
9
Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8 Canada ; Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8 Canada ; National Research Council, National Institute for Nanotechnology (NINT), Edmonton, AB T6G 2M9 Canada ; The Metabolomics Innovation Center, University of Alberta, Edmonton, AB T6G 2E9 Canada.

Abstract

BACKGROUND:

Scientists have long been driven by the desire to describe, organize, classify, and compare objects using taxonomies and/or ontologies. In contrast to biology, geology, and many other scientific disciplines, the world of chemistry still lacks a standardized chemical ontology or taxonomy. Several attempts at chemical classification have been made; but they have mostly been limited to either manual, or semi-automated proof-of-principle applications. This is regrettable as comprehensive chemical classification and description tools could not only improve our understanding of chemistry but also improve the linkage between chemistry and many other fields. For instance, the chemical classification of a compound could help predict its metabolic fate in humans, its druggability or potential hazards associated with it, among others. However, the sheer number (tens of millions of compounds) and complexity of chemical structures is such that any manual classification effort would prove to be near impossible.

RESULTS:

We have developed a comprehensive, flexible, and computable, purely structure-based chemical taxonomy (ChemOnt), along with a computer program (ClassyFire) that uses only chemical structures and structural features to automatically assign all known chemical compounds to a taxonomy consisting of >4800 different categories. This new chemical taxonomy consists of up to 11 different levels (Kingdom, SuperClass, Class, SubClass, etc.) with each of the categories defined by unambiguous, computable structural rules. Furthermore each category is named using a consensus-based nomenclature and described (in English) based on the characteristic common structural properties of the compounds it contains. The ClassyFire webserver is freely accessible at http://classyfire.wishartlab.com/. Moreover, a Ruby API version is available at https://bitbucket.org/wishartlab/classyfire_api, which provides programmatic access to the ClassyFire server and database. ClassyFire has been used to annotate over 77 million compounds and has already been integrated into other software packages to automatically generate textual descriptions for, and/or infer biological properties of over 100,000 compounds. Additional examples and applications are provided in this paper.

CONCLUSION:

ClassyFire, in combination with ChemOnt (ClassyFire's comprehensive chemical taxonomy), now allows chemists and cheminformaticians to perform large-scale, rapid and automated chemical classification. Moreover, a freely accessible API allows easy access to more than 77 million "ClassyFire" classified compounds. The results can be used to help annotate well studied, as well as lesser-known compounds. In addition, these chemical classifications can be used as input for data integration, and many other cheminformatics-related tasks.

KEYWORDS:

Annotation; Data integration; Database; Inference; Ontology; Structure-based classification; Taxonomy; Text-based search

Supplemental Content

Full text links

Icon for Springer Icon for PubMed Central
Loading ...
Support Center