ReviewNatural products and bioprospecting2024
Precision enzyme discovery through targeted mining of metagenomic data.
Review in Natural products and bioprospecting, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Genome-Resolved Metagenomics Reveals Thermophilic Microbial Diversity and Putative Hydrolase-Encoding Genes in the El Tatio Geothermal Field.International journal of molecular sciences · 2026Article
- EnzymeMiner 2.0: advancing automated enzyme discovery with expansive sequence mining and smart property analysis.Nucleic acids research · 2026Article
- Current Progress and Future Directions of Enzyme Technology in Food Nutrition: A Comprehensive Review of Processing, Nutrition, and Functional Innovation.Foods (Basel, Switzerland) · 2026Review
- Precision hydrolysis: tailored yeast processing enzymes for yeast-based products.Applied microbiology and biotechnology · 2026Review
- Identification of novel metagenomic lipases through integrated structural and sequence-based analysis.PeerJ · 2026Article
- Advances in Lignocellulose-Degrading Enzyme Discovery from Anaerobic Rumen Fungi.Microorganisms · 2025Review
- Metagenomic laccase-catalyzed crosslinking of wheat proteins for enhanced soybean meal nutritional value: applications in poultry feed and food industry.BMC biotechnology · 2025Article
- Discovery and engineering of bifunctional enzymes for lignocellulose degradation: Metagenomic and computational approaches.Biotechnology reports (Amsterdam, Netherlands) · 2025Review
- Gut microbiota and microbial metabolites for osteoporosis.Gut microbes · 2025Review
- Machine learning-guided discovery of thermophilic carbonic anhydrases from environmental metagenomes.Scientific reports · 2025Article
- FGeneBERT: function-driven pre-trained gene language model for metagenomics.Briefings in bioinformatics · 2025Article
- Unlocking New Bioactive Peptides from Coffee Pulp: A Metagenomics and AI-Driven Discovery Paradigm.Foods (Basel, Switzerland) · 2025Article
- Of Revolutions and Roadblocks: The Emerging Role of Machine Learning in Biocatalysis.ACS central science · 2025Review
- Wide Diversity and Complex Evolution of M42 Aminopeptidases With Contrasted Functional Properties in Archaea.Molecular biology and evolution · 2025Article
- Recombinant Production and Characterization of a Novel α-L-Fucosidase fromInternational journal of molecular sciences · 2025Article
- Current Approaches and Implications in Discovery of Novel Bioactive Products from Microbial Sources.Current microbiology · 2025Review
- FGeneBERT: function-driven pre-trained gene language model for metagenomics.Briefings in bioinformatics · 2025Article
- Analysis of metagenomic data.Nature reviews. Methods primers · 2025Article
- Shotgun metagenomics reveals antibiotic resistome dynamics and metabolic specialization in fungal-dominated microbiomes.Frontiers in microbiology · 2025Article
- Characterization of mycobacteria isolated from the Brazilian Atlantic Forest: a public health and bioprospection perspective.Frontiers in microbiology · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metagenomics has opened new avenues for exploring the genetic potential of uncultured microorganisms, which may serve as promising sources of enzymes and natural products for industrial applications. Identifying enzymes with improved catalytic properties from the vast amount of available metagenomic data poses a significant challenge that demands the development of novel computational and functional screening tools. The catalytic properties of all enzymes are primarily dictated by their structures, which are predominantly determined by their amino acid sequences. However, this aspect has not been fully considered in the enzyme bioprospecting processes. With the accumulating number of available enzyme sequences and the increasing demand for discovering novel biocatalysts, structural and functional modeling can be employed to identify potential enzymes with novel catalytic properties. Recent efforts to discover new polysaccharide-degrading enzymes from rumen metagenome data using homology-based searches and machine learning-based models have shown significant promise. Here, we will explore various computational approaches that can be employed to screen and shortlist metagenome-derived enzymes as potential biocatalyst candidates, in conjunction with the wet lab analytical methods traditionally used for enzyme characterization.
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Registered trials
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