Toxicophore
{{Short description|Chemical structure related to toxic properties of chemical}}
A toxicophore is a chemical structure or a portion of a structure (e.g., a functional group) that is related to the toxic properties of a chemical. Toxicophores can act directly (e.g., dioxins) or can require metabolic activation (e.g., tobacco-specific nitrosamines).
Most toxic substances exert their toxicity through some interaction (e.g., covalent bonding, oxidation) with cellular macromolecules like proteins or DNA. This interaction leads to changes in the normal cellular biochemistry and physiology and downstream toxic effects.
Occasionally, the toxicophore requires bioactivation, mediated by enzymes, to produce a more reactive metabolite that is more toxic. For example, tobacco-specific nitrosamines are activated by cytochrome P450 enzymes to form a more reactive substance that can covalently bind to DNA, causing mutations that, if not repaired, can lead to cancer. Generally, different chemical compounds that contain the same toxicophore elicit similar toxic effects at the same site of toxicity.{{cite journal
| pmid = 11865664
| last = Williams
| first = D.P.
|author2=Naisbitt, D.J.
| title = Toxicophores: Groups and Metabolic Routes Associated with Increased Safety Risk
| journal = Current Opinion in Drug Discovery & Development
| year = 2002
| volume = 5
| issue = 1
| pages = 104–115
| location = Curr. Opin. Drug. Discov. Devel.
}}
Medicinal chemists and structural biologists study toxicophores in order to predict (and hopefully avoid) potentially toxic compounds early in the drug development process. Toxicophores can also be identified in lead compounds and removed or replaced later in the process with less toxic moieties.{{cite journal
| url = http://www.jcheminf.com/content/pdf/1758-2946-4-10.pdf
| last = Seal
| first = Abhik
|author2=Passi, Anurag |author3=Jaleel, Abdul |author4=Wild, David J
| title = In-silico predictive mutagenicity model generation using supervised learning approaches
|date=May 2012
|volume=4 |issue=1 |doi=10.1186/1758-2946-4-10
|journal=Journal of Cheminformatics
| page = 10
| pmid = 22587596
| pmc = 3542175
|doi-access=free}} Both techniques, in silico (predictive) and a posteriori (experimental), are active areas of chemoinformatics research and development, within the field known as Computational Toxicology.{{cite web
| url = http://www.niehs.nih.gov/research/supported/dert/programs/srp/events/riskelearning/comptox/
| title = Computational Toxicology: Superfund Research Program
| year = 2009
| location = National Institute of Environmental Health Sciences
}} For example, in the United States, the EPA's National Center for Computational Toxicology{{cite web
| url = http://www2.epa.gov/aboutepa/about-national-center-computational-toxicology-ncct
| archive-url = https://archive.today/20140310200545/http://www2.epa.gov/aboutepa/about-national-center-computational-toxicology-ncct
| url-status = dead
| archive-date = March 10, 2014
| title = About the National Center for Computational Toxicology (NCCT)
| year = 2005
| location = Research Triangle Park, NC
}} sponsors several toxicity databases{{cite web
| url = http://www.epa.gov/ncct/toxcast/
| archive-url = https://archive.today/20121212105443/http://www.epa.gov/ncct/toxcast/
| url-status = dead
| archive-date = December 12, 2012
| title = ToxCast: Advancing the next generation of chemical safety evaluation
| accessdate = March 10, 2014
| url = http://actor.epa.gov/actor/faces/ACToRHome.jsp
| archive-url = https://archive.today/20140107051231/http://actor.epa.gov/actor/faces/ACToRHome.jsp
| url-status = dead
| archive-date = January 7, 2014
| title = ACToR: Aggregated Computational Toxicology Resource
| accessdate = March 10, 2014
| url = https://comptox.epa.gov/dashboard
| archive-url = https://archive.today/20180530070557/https://comptox.epa.gov/dashboard
| url-status = dead
| archive-date = May 30, 2018
| title = CompTox Chemistry Dashboard
| accessdate = January 5, 2017
| url = http://www.epa.gov/ncct/dsstox/
| archive-url = https://archive.today/20130217135446/http://www.epa.gov/ncct/dsstox/
| url-status = dead
| archive-date = February 17, 2013
| title = Distributed Structure-Searchable Toxicity (DSSTox) Database Network
| accessdate = March 10, 2014
}} based on predictive modeling as well as high-throughput screening experimental methods.