Evidence map›Paper›PMID 29718510›Full record

ArticleNucleic acids research2018

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

Priyanka Banerjee, Andreas O Eckert, Anna K Schrey, Robert Preissner

Abstract read
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,043 papers.

0numbers the graph read from it
0cells of the map it votes in
1,043citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1,043 citing papers in PubMed.

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  19. In vitro study and in silico reveal Teucrium Polium L. methanolic extract as an apoptosis inducer and a potential Bcl-2 inhibitor for breast cancer.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2026
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983 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Priyanka BanerjeeStructural Bioinformatics Group, Institute for Physiology & ECRC, Charité - University Medicine Berlin, 10115 Berlin, Germany.
Andreas O EckertStructural Bioinformatics Group, Institute for Physiology & ECRC, Charité - University Medicine Berlin, 10115 Berlin, Germany.
Anna K SchreyStructural Bioinformatics Group, Institute for Physiology & ECRC, Charité - University Medicine Berlin, 10115 Berlin, Germany.
Robert PreissnerStructural Bioinformatics Group, Institute for Physiology & ECRC, Charité - University Medicine Berlin, 10115 Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Computational BiologyDrug-Related Side Effects and Adverse ReactionsSoftwareHumansInternetMachine LearningRisk Assessment

Identifiers

PMID29718510
PMCPMC6031011

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.