ArticlePLoS computational biology2021
Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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
28 citing papers in PubMed.
- Predicting Functional Diversity Within Enzyme Families: A Practical Perspective.Chembiochem : a European journal of chemical biology · 2026Review
- The Factors Governing Metal Dependence of an Emergent Superfamily of Bimetallic Oxygenases.Journal of the American Chemical Society · 2026Article
- Comparative Genomic and Functional Profiling of ECM-Targeting Enzymes inbioRxiv : the preprint server for biology · 2026Article
- Genomic insights into the functional and metabolic versatility of gut microbiomeMicrobial genomics · 2026Article
- Computational approaches to enzymatic reaction assignment: a review of methods, validations, and future directions.Briefings in bioinformatics · 2025Review
- Limitations of current machine learning models in predicting enzymatic functions for uncharacterized proteins.G3 (Bethesda, Md.) · 2025Article
- NGATHA carpel development genes evolved in the common ancestor of seed plants.The Plant journal : for cell and molecular biology · 2025Article
- Hidden Markov Model-Based Prokaryotic Genome Space Mining Reveals the Widespread Pervasiveness of Complex I and Its Potential Evolutionary Scheme.Genome biology and evolution · 2025Article
- Annotating the microbial dark matter with HiFi-NN.iScience · 2025Article
- Evolutionary-scale enzymology enables exploration of a rugged catalytic landscape.Science (New York, N.Y.) · 2025Article
- Intramolecular epistasis correlates with divergence of specificity in promiscuous and bifunctional NSAR/OSBS enzymes.Protein science : a publication of the Protein Society · 2025Article
- TopEC: prediction of Enzyme Commission classes by 3D graph neural networks and localized 3D protein descriptor.Nature communications · 2025Article
- Biological databases in the age of generative artificial intelligence.Bioinformatics advances · 2025Article
- Interactive tools for functional annotation of bacterial genomes.Database : the journal of biological databases and curation · 2024Article
- Metalloproteinases in Restorative Dentistry: An In Silico Study toward an Ideal Animal Model.Biomedicines · 2023Article
- Bactabolize is a tool for high-throughput generation of bacterial strain-specific metabolic models.eLife · 2023Article
- Predicted structural proteome of Sphagnum divinum and proteome-scale annotation.Bioinformatics (Oxford, England) · 2023Article
- EFI-EST, EFI-GNT, and EFI-CGFP: Enzyme Function Initiative (EFI) Web Resource for Genomic Enzymology Tools.Journal of molecular biology · 2023Article
- A general model to predict small molecule substrates of enzymes based on machine and deep learning.Nature communications · 2023Article
- Real or fake? Measuring the impact of protein annotation errors on estimates of domain gain and loss events.Frontiers in bioinformatics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Only a small fraction of genes deposited to databases have been experimentally characterised. The majority of proteins have their function assigned automatically, which can result in erroneous annotations. The reliability of current annotations in public databases is largely unknown; experimental attempts to validate the accuracy within individual enzyme classes are lacking. In this study we performed an overview of functional annotations to the BRENDA enzyme database. We first applied a high-throughput experimental platform to verify functional annotations to an enzyme class of S-2-hydroxyacid oxidases (EC 1.1.3.15). We chose 122 representative sequences of the class and screened them for their predicted function. Based on the experimental results, predicted domain architecture and similarity to previously characterised S-2-hydroxyacid oxidases, we inferred that at least 78% of sequences in the enzyme class are misannotated. We experimentally confirmed four alternative activities among the misannotated sequences and showed that misannotation in the enzyme class increased over time. Finally, we performed a computational analysis of annotations to all enzyme classes in the BRENDA database, and showed that nearly 18% of all sequences are annotated to an enzyme class while sharing no similarity or domain architecture to experimentally characterised representatives. We showed that even well-studied enzyme classes of industrial relevance are affected by the problem of functional misannotation.
Indexed as
Identifiers
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.