Zhong, Min published the artcileCarcinogenicity Prediction of Noncongeneric Chemicals by a Support Vector Machine, Application In Synthesis of 59973-80-7, the publication is Chemical Research in Toxicology (2013), 26(5), 741-749, database is CAplus and MEDLINE.
The ability to identify carcinogenic compounds is of fundamental importance to the safe application of chems. In this study, the authors generated an array of in silico models allowing the classification of compounds into carcinogenic and noncarcinogenic agents based on a data set of 852 noncongeneric chems. collected from the Carcinogenic Potency Database (CPDBAS). Twenty-four mol. descriptors were selected by Pearson correlation, F-score, and stepwise regression anal. These descriptors cover a range of physicochem. properties, including electrophilicity, geometry, mol. weight, size, and solubility The descriptor mutagenic showed the highest correlation coefficient with carcinogenicity. On the basis of these descriptors, a support vector machine-based (SVM) classification model was developed and fine-tuned by a 10-fold cross-validation approach. Both the SVM model (Model A1) and the best model from the 10-fold cross-validation (Model B3) runs gave good results on the test set with prediction accuracy over 80%, sensitivity over 76%, and specificity over 82%. In addition, extended connectivity fingerprints (ECFPs) and the Toxtree software were used to analyze the functional groups and substructures linked to carcinogenicity. It was found that the results of both methods are in good agreement.
Chemical Research in Toxicology published new progress about 59973-80-7. 59973-80-7 belongs to naphthyridine, auxiliary class Immunology/Inflammation,COX, name is Sulindac sulfone, and the molecular formula is C10H16Br3N, Application In Synthesis of 59973-80-7.
Referemce:
https://en.wikipedia.org/wiki/1,8-Naphthyridine,
1,8-Naphthyridine | C8H6N2 – PubChem