Abstract
The catalytic activities of enzymes can be described using Gene Ontology (GO) terms and Enzyme Commission (EC) numbers. These annotations are available from numerous biological databases and are routinely accessed by researchers and bioinformaticians to direct their work. However, enzyme data may not be congruent between different resources, while the origin, quality and genomic coverage of these data within any one resource are often unclear. GO/EC annotations are assigned either manually by expert curators or inferred computationally, and there is potential for errors in both types of annotation. If such errors remain unchecked, false positive annotations may be propagated across multiple resources, significantly degrading the quality and usefulness of these data. Similarly, the absence of annotations (false negatives) from any one resource can lead to incorrect inferences or conclusions. We are systematically reviewing and enhancing the functional annotation of the enzymes of Drosophila melanogaster, focusing on improvements within the FlyBase (www.flybase.org) database. We have reviewed four major enzyme groups to date: oxidoreductases, lyases, isomerases and ligases. Herein, we describe our review workflow, the improvement in the quality and coverage of enzyme annotations within FlyBase and the wider impact of our work on other related databases.
Highlights
Enzymes are biocatalysts that greatly enhance the rate of specific chemical reactions without being consumed in the process—without enzymatic catalysis, most reactions would be too slow to sustain life
Experimental evidence codes Inferred from direct assay (IDA) Inferred from mutant phenotype (IMP) Inferred from genetic interaction (IGI)
Computational analysis evidence codes Inferred from sequence or structural similarity (ISS)a Inferred from biological aspect of ancestor (IBA)
Summary
Enzymes are biocatalysts that greatly enhance the rate of specific chemical reactions without being consumed in the process—without enzymatic catalysis, most reactions would be too slow to sustain life. Metabolic pathways are built from enzymes acting sequentially to perform chemical conversions such as the breakdown of glucose to lactate. The classical and prominent example is phenylketonuria, an inborn error of metabolism, caused by mutations in the phenylalanine hydroxylase enzyme [3] Another example is the RAS GTPase: mutated H-RAS, NRAS or K-RAS is found in >20% of all human cancers and are among the most important drug targets in oncology [4]. Determining and cataloging the biological activities of enzymes helps us better understand metabolic systems and provides important insights on disease mechanisms, detection and potential therapies
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