ArticlePharmaceutics2023
CSM-Toxin: A Web-Server for Predicting Protein Toxicity.
Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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.
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.
Who cites it
39 citing papers in PubMed.
- UniPept: A Universal Model for Predicting Peptide Properties Based on Atom-Residue Dual-Scale Integration.Interdisciplinary sciences, computational life sciences · 2026Article
- Venom-Derived Enzyme Inhibitors as Anticancer Agents: Structure-Activity Relationships, Molecular Targets and Mechanistic Insights.Molecules (Basel, Switzerland) · 2026Review
- Genetic Variability and Conserved T-Cell Epitope Prediction of the HPV16 E1 Protein in Cervix Samples from Peru.Pathogens (Basel, Switzerland) · 2026Article
- Immunoinformatics driven multi-epitope vaccine design targeting clade IIb Mpox variant.Scientific reports · 2026Article
- Risk Evaluation and Molecular Characterisation of AtNPR1 Transgenic Citrus Lines Tolerant to Citrus Greening Disease.Plant biotechnology journal · 2026Article
- In Silico Analysis of Potential Vaccine Antigens for the Treatment of Crimean-Congo Hemorrhagic Fever Virus (Cchfv).Pharmaceutical research · 2026Article
- Algae-Derived Peptides as Functional Food Ingredients: Bioactivities, Processing Challenges, and Computational Design Strategies.Foods (Basel, Switzerland) · 2026Review
- Computational examination of magainin-I-KL mediated disruption of E. coli biofilms via CsgA amyloid interference.Archives of microbiology · 2026Article
- Computational design of a novel multi-epitope vaccine candidate against group A rotavirus.Virology journal · 2026Article
- Harnessing epitope reciprocity and multimeric epitope density for a novel multiepitope vaccine design against Acinetobacter baumannii.Scientific reports · 2026Article
- Design and computational evaluation of a prophylactic and therapeutic multi-epitope vaccine candidate against cervical cancer.Virology journal · 2026Article
- Article
- Animal Venoms as Peptide Libraries for the Discovery of Antiglioblastoma Agents.Biochemistry research international · 2026Review
- TPT: a compact CNN-transformer encoder for efficient microbial small protein modeling.Frontiers in microbiology · 2026Article
- A Comprehensive In-Silico Pipeline for the Discovery of Non-toxic, Stable Antimicrobial Peptides From Databases for Targeting Multi-Drug ResistantBioinformatics and biology insights · 2026Article
- An innovative peptide toxicity prediction model based on multi-scale convolutional neural network and residual connection.Bioinformatics (Oxford, England) · 2025Article
- ProToxin, a Predictor of Protein Toxicity.Toxins · 2025Article
- Structure-guided design of a novel, stable, and soluble Cecropin A variant for antimicrobial therapeutic applications.Scientific reports · 2025Article
- Exo-Tox: Identifying Exotoxins from secreted bacterial proteins.BioData mining · 2025Article
- A large language model for predicting neurotoxic peptides and neurotoxins.Protein science : a publication of the Protein Society · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Biologics are one of the most rapidly expanding classes of therapeutics, but can be associated with a range of toxic properties. In small-molecule drug development, early identification of potential toxicity led to a significant reduction in clinical trial failures, however we currently lack robust qualitative rules or predictive tools for peptide- and protein-based biologics. To address this, we have manually curated the largest set of high-quality experimental data on peptide and protein toxicities, and developed CSM-Toxin, a novel in-silico protein toxicity classifier, which relies solely on the protein primary sequence. Our approach encodes the protein sequence information using a deep learning natural languages model to understand "biological" language, where residues are treated as words and protein sequences as sentences. The CSM-Toxin was able to accurately identify peptides and proteins with potential toxicity, achieving an MCC of up to 0.66 across both cross-validation and multiple non-redundant blind tests, outperforming other methods and highlighting the robust and generalisable performance of our model. We strongly believe the CSM-Toxin will serve as a valuable platform to minimise potential toxicity in the biologic development pipeline. Our method is freely available as an easy-to-use webserver.
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What OpenQuestion holds
Registered trials
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.