title: Fragment Prioritization on a Large Mutagenicity Dataset.
abstract: The identification of structural alerts is one of the simplest tools used for the identification of potentially toxic chemical compounds. Structural alerts have served as an aid to quickly identify chemicals that should be either prioritized for testing or for elimination from further consideration and use. In the recent years, the availability of larger datasets, often growing in the context of collaborative efforts and competitions, created the raw material needed to identify new and more accurate structural alerts. This work applied a method to efficiently mine large toxicological dataset for structural alert showing a strong statistical association with mutagenicity. In details, we processed a large Ames mutagenicity dataset comprising 14,015 unique molecules obtained by joining different data sources. After correction for multiple testing, we were able to assign a probability value to each fragment. A total of 51 rules were identified, with p-value < 0.05. Using the same method, we also confirmed the statistical significance of several mutagenicity rules already present and largely recognized in the literature. In addition, we have extended the application of our method by predicting the mutagenicity of an external data set.
authors.affiliation: CRS4 - Center for advanced studies, research and development in Sardinia, Loc. Piscina Manna, Building 1, 09010, Pula (CA), Italy.|Department of Biomedical Sciences, University of Sassari, Sassari, Italy.
authors.forename: Matteo
authors.initials: M
authors.lastname: Floris
authors.affiliation: IRCCS - Istituto di Ricerche Farmacologiche "Mario Negri", Department of Environmental Health Sciences, Laboratory of Environmental Chemistry and Toxicology, Via La Masa 19, 20159, Milan, Italy.
authors.forename: Giuseppa
authors.initials: G
authors.lastname: Raitano
authors.affiliation: CRS4 - Center for advanced studies, research and development in Sardinia, Loc. Piscina Manna, Building 1, 09010, Pula (CA), Italy.
authors.forename: Ricardo
authors.initials: R
authors.lastname: Medda
authors.affiliation: IRCCS - Istituto di Ricerche Farmacologiche "Mario Negri", Department of Environmental Health Sciences, Laboratory of Environmental Chemistry and Toxicology, Via La Masa 19, 20159, Milan, Italy.
authors.forename: Emilio
authors.initials: E
authors.lastname: Benfenati
mesh_terms: D000818:Animals; D016208:Databases, Factual; D006801:Humans; D015394:Molecular Structure; D016296:Mutagenesis / Q000187:drug effects; D009152:Mutagenicity Tests; D009153:Mutagens / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship
chemical_list: D009153:Mutagens
keywords: Computational toxicology; QSAR; Read Across