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

*PRI Rank #1 · Topics and Trends in Most Cited Computational Drug Discovery Methods Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/computational-drug-discovery-methods/2026/rank-1*

| Field | Value |
| --- | --- |
| Rank | #1 |
| 18m citations | 583 |
| Journal | Nucleic Acids Research |
| Year | 2024 |
| DOI | 10.1093/nar/gkae303 |
| Corresponding authors | Priyanka Banerjee |
| Institution | Charité - University Medicine Berlin, Germany |

**Ranking page:** [Topics and Trends in Most Cited Computational Drug Discovery Methods Papers, Class of 2026](https://pri.pepkio.com/top-papers/computational-drug-discovery-methods/2026)

**Paper link:** [10.1093/nar/gkae303](https://doi.org/10.1093/nar/gkae303)

## Topics

ProTox 3.0 · Toxicity prediction · Molecular similarity · Machine learning models · acute toxicity · organ toxicity · clinical toxicity · molecular-initiating events · Tox21 pathways · adverse outcomes · toxicity off-targets · external validation · Chemical structure · toxicity endpoints · Confidence score · toxicity radar plot · toxicity network plot · Web server · Risk assessment

## Cite this ranking

```
Pepkio Research Index (PRI). Topics and Trends in Most Cited Computational Drug Discovery Methods Papers, Class of 2026. https://pri.pepkio.com/top-papers/computational-drug-discovery-methods/2026. Accessed 2026-07-22.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459
```