In Silico Methods for Carcinogenicity Assessment.
Screening compounds for potential carcinogenicity is of major importance for prevention of environmentally induced cancers. A large sequence of alternative predictive models, ranging from short-term biological assays (e.g. mutagenicity tests) to theoretical models, have been attempted in this field. Theoretical approaches such as (Q)SAR are highly desirable for identifying carcinogens, since they actively promote the replacement, reduction, and refinement of animal tests. This chapter reports and describes some of the most noted (Q)SAR models based on the human expert knowledge and statistically approach, aiming at predicting the carcinogenicity of chemicals. Additionally, the performance of the selected models has been evaluated and the results are interpreted in details by applying these prediction models to some pharmaceutical molecules.
Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche "Mario Negri", Via La Masa 19, 20156, Milano, Italy. azadi.golbamaki@marionegri.it.
Azadi
A
Golbamaki
Mario Negri Institute for Pharmacological Research, IRCCS, Milano, Italy.
Emilio
E
Benfenati
D015197:Carcinogenicity Tests; D002273:Carcinogens / Q000737:chemistry*; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D008956:Models, Chemical; D021281:Quantitative Structure-Activity Relationship
D002273:Carcinogens
Applicability domain index; Carcinogenicity; Genotoxicity; In silico; Non-genotoxicity; QSAR; SARpy; Structural alerts; Toxtree