ReviewBiochemistry2011
The Enzyme Function Initiative.
Review in Biochemistry, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 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
106 citing papers in PubMed.
- Advances in amidases and urethanases as depolymerization biocatalysts.Nature chemical biology · 2026Review
- A cloaked glutamate decarboxylase sustains the GABA shunt inProceedings of the National Academy of Sciences of the United States of America · 2026Article
- HaloTag-Based FACS-Compatible Assay for Intracellular Haloalkane Detection with a Potential Application to Halogenase Screening.Analytical chemistry · 2026Article
- Backbone Thioamidation of a Ribosomal Subunit Protein in Pseudomonadota.Biochemistry · 2026Article
- Broad Substrate Specificity and High Catalytic Activity ofACS omega · 2025Article
- Genomic context analysis enables the discovery of an unusual NAD-dependent racemase in phosphonate catabolism.The FEBS journal · 2025Article
- TopEC: prediction of Enzyme Commission classes by 3D graph neural networks and localized 3D protein descriptor.Nature communications · 2025Article
- A Survey of Biological Function Prediction Methods with Focus on Natural Language Processing (NLP) and Large Language Models (LLM).Methods in molecular biology (Clifton, N.J.) · 2025Article
- The Impact of Metagenomics on Biocatalysis.Angewandte Chemie (International ed. in English) · 2024Review
- Back to the Future of Metabolism-Advances in the Discovery and Characterization of Unknown Biocatalytic Functions and Pathways.Life (Basel, Switzerland) · 2024Review
- Meta-Research: understudied genes are lost in a leaky pipeline between genome-wide assays and reporting of results.bioRxiv : the preprint server for biology · 2024Article
- EFI-EST, EFI-GNT, and EFI-CGFP: Enzyme Function Initiative (EFI) Web Resource for Genomic Enzymology Tools.Journal of molecular biology · 2023Article
- Cytochromes P450 involved in bacterial RiPP biosyntheses.Journal of industrial microbiology & biotechnology · 2023Review
- Expanding the viewpoint: Leveraging sequence information in enzymology.Current opinion in chemical biology · 2023Review
- Current successes and remaining challenges in protein function prediction.Frontiers in bioinformatics · 2023Article
- Mutation of the eunicellane synthase Bnd4 alters its product profile and expands its prenylation ability.Organic & biomolecular chemistry · 2022Article
- Understudied proteins: opportunities and challenges for functional proteomics.Nature methods · 2022Article
- The Birth of Genomic Enzymology: Discovery of the Mechanistically Diverse Enolase Superfamily.Biochemistry · 2021Article
- A Novel GlutathioneToxins · 2021Article
- Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class.PLoS computational biology · 2021Article
46 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic, we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include (1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation), (2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia, (3) computational and bioinformatic tools for using the strategy, (4) provision of experimental protocols and/or reagents for enzyme production and characterization, and (5) dissemination of data via the EFI's Website, http://enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal, and pharmaceutical efforts.
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.