MetaCyc contains manually curated information on thousands of metabolic pathways, reactions, and enzymes from scientific literature, with each entry verified by experts and linked to primary research publications.
MetaCyc serves as the reference database for the Pathway Tools software suite, which enables creation, visualization, and analysis of organism-specific metabolic networks and genome-scale metabolic models.
SmartTables allow users to create, filter, and manipulate custom tables of pathways, reactions, or compounds, then perform operations like comparing across organisms or exporting for further analysis.
MetaCyc data can be used to generate hundreds of organism-specific PGDBs that combine genomic information with metabolic pathway predictions tailored to particular species.
Users can export pathway and compound data in various standard formats including BioPAX, SBML, CSV, and GenBank, facilitating integration with other bioinformatics tools and workflows.
The database includes tools for comparing metabolic pathways across different organisms, identifying conserved and unique metabolic capabilities, and analyzing evolutionary relationships.
Bioinformaticians use MetaCyc to annotate newly sequenced genomes by comparing predicted protein sequences against MetaCyc's enzyme database. The curated pathway information helps assign functional roles to genes and predict metabolic capabilities of organisms. This is essential for understanding the biology of poorly characterized species and for reconstructing metabolic networks from genomic data.
Metabolic engineers utilize MetaCyc to design pathways for producing valuable chemicals in microbial hosts. By searching for known biosynthetic routes and identifying suitable enzymes, researchers can design and optimize metabolic pathways for industrial biotechnology. The database helps identify bottlenecks, predict side reactions, and select optimal enzyme variants for pathway construction.
Pharmaceutical researchers use MetaCyc to identify essential metabolic pathways in pathogens that could serve as drug targets. By comparing human and pathogen metabolism, they can find pathway differences that allow selective inhibition. The detailed enzyme information helps in understanding mechanism of action and predicting potential side effects of candidate drugs.
Systems biologists employ MetaCyc as a reference for building genome-scale metabolic models (GEMs). The curated reaction information, including stoichiometry, directionality, and cofactor requirements, provides essential parameters for constraint-based modeling and flux balance analysis. This enables prediction of metabolic phenotypes under different genetic and environmental conditions.
Educators and students use MetaCyc as a teaching tool for understanding metabolic pathways and their interconnections. The visual pathway diagrams and detailed biochemical information help illustrate complex metabolic concepts. The database serves as a constantly updated reference that reflects current scientific understanding of metabolism across all life forms.
Researchers studying microbial communities use MetaCyc to predict metabolic functions from metagenomic data. By mapping sequenced genes to MetaCyc pathways, they can infer the metabolic capabilities of microbial populations and understand how community metabolism responds to environmental changes. This helps in studying host-microbe interactions, biogeochemical cycles, and ecosystem functioning.
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