Open Access
Open access
volume 52 issue W1 pages W513-W520

ProTox 3.0: a webserver for the prediction of toxicity of chemicals

Priyanka Banerjee 1, 2
Emanuel Kemmler 1, 2
Mathias Dunkel 1
Robert Preissner 1
2
 
Member of the KFO 339: Food Allergy and Tolerance (Food@), Clinical Research Unit funded by the German Research Foundation , Berlin, Germany
Publication typeJournal Article
Publication date2024-04-22
scimago Q1
wos Q1
SJR7.776
CiteScore31.7
Impact factor13.1
ISSN03051048, 13624962
PubMed ID:  38647086
Abstract

Interaction with chemicals, present in drugs, food, environments, and consumer goods, is an integral part of our everyday life. However, depending on the amount and duration, such interactions can also result in adverse effects. With the increase in computational methods, the in silico methods can offer significant benefits to both regulatory needs and requirements for risk assessments and the pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox 3.0, which incorporates molecular similarity and machine-learning models for the prediction of 61 toxicity endpoints such as acute toxicity, organ toxicity, clinical toxicity, molecular-initiating events (MOE), adverse outcomes (Tox21) pathways, several other toxicological endpoints and toxicity off-targets. All the ProTox 3.0 models are validated on independent external sets and have shown strong performance. ProTox envisages itself as a complete, freely available computational platform for in silico toxicity prediction for toxicologists, regulatory agencies, computational chemists, and medicinal chemists. The ProTox 3.0 webserver is free and open to all users, and there is no login requirement and can be accessed via https://tox.charite.de. The web server takes a 2D chemical structure as input and reports the toxicological profile of the compound for each endpoint with a confidence score and overall toxicity radar plot and network plot.

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GOST |
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GOST Copy
Banerjee P. et al. ProTox 3.0: a webserver for the prediction of toxicity of chemicals // Nucleic Acids Research. 2024. Vol. 52. No. W1. p. W513-W520.
GOST all authors (up to 50) Copy
Banerjee P., Kemmler E., Dunkel M., Preissner R. ProTox 3.0: a webserver for the prediction of toxicity of chemicals // Nucleic Acids Research. 2024. Vol. 52. No. W1. p. W513-W520.
RIS |
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RIS Copy
TY - JOUR
DO - 10.1093/nar/gkae303
UR - https://academic.oup.com/nar/article/52/W1/W513/7655780
TI - ProTox 3.0: a webserver for the prediction of toxicity of chemicals
T2 - Nucleic Acids Research
AU - Banerjee, Priyanka
AU - Kemmler, Emanuel
AU - Dunkel, Mathias
AU - Preissner, Robert
PY - 2024
DA - 2024/04/22
PB - Oxford University Press
SP - W513-W520
IS - W1
VL - 52
PMID - 38647086
SN - 0305-1048
SN - 1362-4962
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2024_Banerjee,
author = {Priyanka Banerjee and Emanuel Kemmler and Mathias Dunkel and Robert Preissner},
title = {ProTox 3.0: a webserver for the prediction of toxicity of chemicals},
journal = {Nucleic Acids Research},
year = {2024},
volume = {52},
publisher = {Oxford University Press},
month = {apr},
url = {https://academic.oup.com/nar/article/52/W1/W513/7655780},
number = {W1},
pages = {W513--W520},
doi = {10.1093/nar/gkae303}
}
MLA
Cite this
MLA Copy
Banerjee, Priyanka, et al. “ProTox 3.0: a webserver for the prediction of toxicity of chemicals.” Nucleic Acids Research, vol. 52, no. W1, Apr. 2024, pp. W513-W520. https://academic.oup.com/nar/article/52/W1/W513/7655780.