This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The Enzyme Function Initiative (EFI) is a large, multi-center, NIH Glue grant funded project that is a major driving biological problem motivating the development of resources and tools at the RBVI. The mission of the EFI is to develop a robust sequence/structure-based strategy for facilitating discovery of in vitro enzymatic and in vivo metabolic/physiological functions of unknown enzymes discovered in genome projects, a crucial limitation in genomic biology. This goal will be accomplished by integrating bioinformatics, structural biology, and computation with enzymology, genetics, and metabolomics. The EFI is composed of five scientific cores and five bridging projects in addition to some administrative and data encapsulation cores. The scientific cores (Superfamily (SF)/Genome, Protein, Computation, Structure and Microbiology Core) are tasked with being central resources for data analysis, structure determination, high-throughput experimentation and data storage. The five bridging projects (Amidohydrolase, Enolase, Glutathione Transferase, Haloacid Dehalogenase and Isoprenoid Synthase Project), named for the enzyme superfamilies they each study, provide in depth experimentation and scientific expertise in these complex enzyme systems that make up the large test set of enzyme functions examined in the EFI. For the EFI, the Babbitt lab directs the SF/Genome core. The role of the SF/Genome Core is to contribute to the development of a general strategy for assignment of reaction and substrate specificity for enzymes of unknown function, aka “unknowns,”in functionally diverse superfamilies. The core has three aims: 1) Serve as an archive resource, maintaining sequence, structural and functional data. 2) In collaboration with the Bridging Projects and the other Scientific Cores, computationally analyze these SFs to aid in target identification, function prediction, and validation by EFI investigators and collaborators. 3) For enzymes for which the functions have been experimentally established by EFI investigators, annotate uncharacterized orthologs in each of these proteins by annotation transfer. Currently, the SF/Genome core is focused principally on identification of superfamily members and curation into subgroups and families. This work provides a large-scale context useful for informing a strategy for function prediction in collaboration with the Bridging Projects and other Scientific Cores. The Babbitt lab is also co-directs the Data and Dissemination Core. For the Babbitt lab this work focuses mostly on the dissemination mission of the core through the lab’s web accessible database, the Structure Function Linkage Database (SFLD). Many of the computational resources underpinning the work of both the SF/Genome Core and the Data and Dissemination Core are supplied by or supported by the RBVI and are not funded through the EFI grant, for example: the use of the RBVI’s high performance computation cluster;the storage, maintenance, and development of the SFLD;and the development of the Cytoscape program used extensively for sequence analysis and annotation by currators in the Babbitt lab for EFI proteins. Recent progress of this work is presented in the updates for the Cytoscape and the SFLD projects within this annual report.
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