title: A neural network based classification scheme for cytotoxicity predictions:Validation on 30,000 compounds.
abstract: Elimination of cytotoxic compounds in the early phases of drug discovery can save substantial amounts of research and development costs. An artificial neural network based approach using atomic fragmental descriptors has been developed to categorize compounds according to their in vitro human cytotoxicity. Fragmental descriptors were obtained from the Atomic7 linear logP calculation method implemented in Pallas PrologP program. We used cytotoxicity values obtained from an in-house screening campaign of a diverse set of 30,000 drug-like molecules. The training set included only the most and least toxic 12,998 compounds, however, cytotoxicity data for all compounds were used for validation. The proposed approach can be safely used for filtering out potentially cytotoxic candidates from the development pipeline before synthesis or assays during lead development or lead optimisation. The trained neural network misclassified less than 5% percent of the non-toxic and 9% of the toxic compounds.
authors.affiliation: Department of Chemical Information Technology, Budapest University of Technology and Economics, Szent Gellért tér 4., H-1111 Budapest, Hungary.
authors.forename: László
authors.initials: L
authors.lastname: Molnár
authors.forename: György M
authors.initials: GM
authors.lastname: Keseru
authors.forename: Akos
authors.initials: A
authors.lastname: Papp
authors.forename: Zsolt
authors.initials: Z
authors.lastname: Lorincz
authors.forename: Géza
authors.initials: G
authors.lastname: Ambrus
authors.forename: Ferenc
authors.initials: F
authors.lastname: Darvas
mesh_terms: D002460:Cell Line; D045744:Cell Line, Tumor; D002470:Cell Survival / Q000187:drug effects; D005347:Fibroblasts / Q000187:drug effects; D022781:Hepatocytes / Q000187:drug effects; D006801:Humans; D066298:In Vitro Techniques; D016571:Neural Networks, Computer; D004364:Pharmaceutical Preparations / Q000737:chemistry* / Q000145:classification*; D012986:Software Validation; D013329:Structure-Activity Relationship
chemical_list: D004364:Pharmaceutical Preparations