ToxinPred2: an improved method for predicting toxicity of proteins
Authors/Creators
Description
Title:
ToxinPred2 Dataset – Experimentally validated toxic and non-toxic proteins (non-redundant, multiple datasets)
Description:
Project: ToxinPred2 – An improved method for predicting toxicity of proteins
Publication: Sharma, N., Naorem, L.D., Jain, S., & Raghava, G.P.S. (2022). ToxinPred2: an improved method for predicting toxicity of proteins. Briefings in Bioinformatics, 23(5), bbac174. https://doi.org/10.1093/bib/bbac174
Overview: This dataset accompanies ToxinPred2, an upgraded version of ToxinPred designed for predicting toxicity of proteins (ToxinPred was limited to peptides ≤35 aa). It provides three datasets curated from UniProt/Swiss-Prot for training and evaluating toxicity predictors.
Content:
| Dataset | Toxic proteins | Non‑toxic proteins | Redundancy (CD‑HIT) |
|---|---|---|---|
| Main | 8,233 | 8,233 | No (raw) |
| Alternate | 1,924 | 1,924 | Yes (≤40% identity) |
| Realistic | 1,924 | 19,240 | Yes (1:10 ratio) |
Best Model Performance (RF + BLAST + MERCI – hybrid, main dataset):
| Metric | Training | Validation |
|---|---|---|
| AUC | 0.98 | 0.99 |
| MCC | 0.91 | 0.91 |
| Accuracy | 95.3% | 95.5% |
| Sensitivity | 92.9% | 93.7% |
| Specificity | 97.6% | 97.4% |
Comparison with existing methods (validation dataset of ToxinPred2):
| Method | AUC | Notes |
|---|---|---|
| ToxinPred2 | 0.99 | Proteins |
| TOXIFY | 0.88 | Limited to length ≤500 aa |
Usage: Predicting toxicity of therapeutic proteins, screening protein libraries, complementing ToxinPred (for peptides).
Related Resources: Web server: https://webs.iiitd.edu.in/raghava/toxinpred2/ | GitHub: https://github.com/raghavagps/toxinpred2
Contact: raghava@iiitd.ac.in (Gajendra P. S. Raghava)
Files
raghavagps/toxinpred2-v1.0.zip
Files
(13.2 MB)
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Additional details
Related works
- Is supplement to
- Software: https://github.com/raghavagps/toxinpred2/tree/v1.0 (URL)
Software
- Repository URL
- https://github.com/raghavagps/toxinpred2