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Nucleic Acids Research· 2018Q1

ProTox-II: a webserver for the prediction of toxicity of chemicals

Priyanka Banerjee, Andreas Eckert, Anna K. Schrey, Robert Preißner

Short summary

ProTox-II is a new webserver that predicts 11 different toxicity endpoints for chemicals using molecular similarity, pharmacophores, fragment propensities, and machine learning models trained on in vitro and in vivo data.

AI-generated from the title and abstract; the full text is not read.

Key points

  • ProTox-II predicts 11 toxicity endpoints (acute toxicity, hepatotoxicity, cytotoxicity, carcinogenicity, mutagenicity, immunotoxicity, adverse outcomes pathways, and toxicity targets).
  • It utilizes a combination of molecular similarity, pharmacophores, fragment propensities, and machine learning models.
  • Models are trained on diverse data from in vitro assays (Tox21, Ames, hepG2, Immunotoxicity) and in vivo cases (carcinogenicity, hepatotoxicity).
  • The webserver provides confidence scores for 33 models, an overall toxicity radar chart, and identifies three similar compounds with known acute toxicity.

AI-generated from the title and abstract; the full text is not read.

Abstract

Advancement in the field of computational research has made it possible for the in silico methods to offer significant benefits to both regulatory needs and requirements for risk assessments, and pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox-II that incorporates molecular similarity, pharmacophores, fragment propensities and machine-learning models for the prediction of various toxicity endpoints; such as acute toxicity, hepatotoxicity, cytotoxicity, carcinogenicity, mutagenicity, immunotoxicity, adverse outcomes pathways (Tox21) and toxicity targets. The predictive models are built on data from both in vitro assays (e.g. Tox21 assays, Ames bacterial mutation assays, hepG2 cytotoxicity assays, Immunotoxicity assays) and in vivo cases (e.g. carcinogenicity, hepatotoxicity). The models have been validated on independent external sets and have shown strong performance. ProTox-II provides a freely available webserver for in silico toxicity prediction for toxicologists, regulatory agencies, computational and medicinal chemists, and all users without login at http://tox.charite.de/protox_II. The webserver takes a two-dimensional chemical structure as an input and reports the possible toxicity profile of the chemical for 33 models with confidence scores, and an overall toxicity radar chart along with three most similar compounds with known acute toxicity.

The authors' abstract, as published at the source. Nucleic Acids Research, 2018 · DOI ↗

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Field: Computational Theory and Mathematics

Computational Theory and MathematicsComputer Science