title: Weighted feature significance: a simple, interpretable model of compound toxicity based on the statistical enrichment of structural features.
abstract: In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high-throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation.
authors.affiliation: Department of Health and Human Services, NIH Chemical Genomics Center, National Institutes of Health, Bethesda, Maryland 20892-3370, USA. huangru@mail.nih.gov
authors.forename: Ruili
authors.initials: R
authors.lastname: Huang
authors.forename: Noel
authors.initials: N
authors.lastname: Southall
authors.forename: Menghang
authors.initials: M
authors.lastname: Xia
authors.forename: Ming-Hsuang
authors.initials: MH
authors.lastname: Cho
authors.forename: Ajit
authors.initials: A
authors.lastname: Jadhav
authors.forename: Dac-Trung
authors.initials: DT
authors.lastname: Nguyen
authors.forename: James
authors.initials: J
authors.lastname: Inglese
authors.forename: Raymond R
authors.initials: RR
authors.lastname: Tice
authors.forename: Christopher P
authors.initials: CP
authors.lastname: Austin
mesh_terms: D002460:Cell Line; D006801:Humans; D008962:Models, Theoretical; D009152:Mutagenicity Tests; D012486:Salmonella typhimurium / Q000235:genetics; D013329:Structure-Activity Relationship; D018675:Toxicity Tests