title: A radial-distribution-function approach for predicting rodent carcinogenicity.
abstract: Carcinogenic activity has been investigated using the Radial-Distribution-Function (RDF) approach. A discriminant model was developed to predict the carcinogenic and non-carcinogenic activity on a data set of 188 compounds. The percentage of overall classification was 76.4% for the carcinogenic chemicals and 72.5% for the non-carcinogenic chemicals. The predictive power of the model was validated by two tests: a cross-validation by the resubstitution technique and a test set (compounds not used in the development of the model) with 79.3 and 72.5% good classification, respectively. The RDF descriptors were compared with eight other methodologies; Constitutional, Molecular walks counts, Galvez topological charge indices, 2D autocorrelations, Randić molecular profiles, Geometrical, 3D-MORSE, and WHIM, demonstrating that the RDF descriptors are better to the rest of the approaches used.
authors.affiliation: Department of Chemistry, Central University of Las Villas, Santa Clara, Villa Clara, 54830, Cuba.
authors.forename: Aliuska Helguera
authors.initials: AH
authors.lastname: Morales
authors.forename: Miguel Angel
authors.initials: MA
authors.lastname: Cabrera Pérez
authors.forename: Maykel Pérez
authors.initials: MP
authors.lastname: González
mesh_terms: D000818:Animals; D015197:Carcinogenicity Tests; D002273:Carcinogens / Q000737:chemistry / Q000633:toxicity; D008958:Models, Molecular; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship; D012377:Rodentia; D012378:Rodenticides / Q000737:chemistry* / Q000633:toxicity
chemical_list: D002273:Carcinogens; D012378:Rodenticides