ArticleBMC research notes2025
Toxin data quality: a critical examination of bacterial exotoxins and animal toxins.
Article in BMC research notes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Exo-Tox: Identifying Exotoxins from secreted bacterial proteins.BioData mining · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveExisting toxins datasets include a mixture of proteins and toxin peptides. In this study we present two curated datasets of toxic proteins free of associated proteins: bacterial exotoxins and animal toxins. Our stringent selection criteria resulted in two data sets with only toxins that directly target or disrupt vital molecular mechanisms of their target organism. To gain insight in their properties and differences, we compared both sets of toxins to controls, and used simple biophysical features such as protein length, and amino acid composition distinguishing between evolutionary kingdoms (phyla). This approach should reveal if there is a need to consider differences present in toxin sets depending on their origin.
resultsOur analysis revealed biophysical differences between animal and bacterial toxins that should not be ignored. Both toxin groups exhibited preferencial amino acid usage depending on their origin, together with higher cysteine content compared to their respective controls. The animal toxins set contains, on average, significantly shorter sequences than bacterial toxins, and had their isoelectric point shifted towards acidic pH values. We show that animal toxins and bacterial toxins possess intrinsic differences in general biophysical properties, which reinforce the necessity of segregating these datasets to ensure reliability of bioinformatics models aimed at understanding and predicting toxin characteristics.
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