The EFI is formed from five Scientific Cores that provide essential intellectual, computational, and experimental infrastructure. The Scientific Cores are the intellectual and technological center of the EFI in developing a general, sequence/structure‑based strategy for functional assignment.
(Patsy Babbitt, Director)
The Superfamily/Genome Core is responsible for identification and regular sequence updates for the AH, EN, GST, HAD, and IS superfamilies. Curated sequences are maintained in the Structure Function Linkage Database (SFLD), which is a tool for investigating protein sequence, structure, and function by providing explicit information concerning how a given protein, or family of proteins, delivers chemical functionality. The SFLD was created in the Babbitt Laboratory with the resources and aid of the UCSF Resource for Biocomputing, Visualization, and Informatics (RBVI). The EFI uses the SFLD as an analysis and archive site for EFI superfamilies. The resources therein are used to identify and prioritize targets for functional assignment in the EFI as well as assist the other Cores and Bridging Projects in their studies.
(Steve Almo, Director)
The Protein Core performs high throughput cloning, protein expression, and protein purification for targets from all five EFI superfamilies. Samples of purified protein are provided for x‑ray crystallography in the Structure Core as well as enzymatic assay and library screening by the Bridging Projects. In collaboration with the Structure Core, the Protein Core screens proteins for ligand binding using thermal denaturation‑based approaches to provide additional clues for functional characterization.
(Steve Almo, Director)
The Structure Core determines high resolution structures of EFI targets. When possible and necessary, liganded structures with substrates and substrate analogues are also pursued. Not only do these structures provide suitable templates for in silico ligand docking by the Computation Core, they are critical for understanding the bases for substrate specificity and thereby evaluating the accuracy of the computationally generated poses.
(Matt Jacobson, Director; Andrej Sali and Brian Shoichet co-PIs)
The Computation Core uses both homology modeled and x-ray structures for in silico ligand docking to predict functions for EFI targets. This requires significant advances in methodology in order to redesign virtual screening tools originally developed for drug discovery. Approaches for allowing and predicting conformational changes (loop closure and flexibility) is also under development. The functional predictions in the Computational Core made guide syntheses of focused libraries and enzymatic assays by the Bridging Projects.
(John Cronan, Director; Jonathan Sweedler, co-PI)
The Microbiology Core examines in vitro assigned functions on a case-by-case basis using genetic, phenotypic, and metabolomic approaches. As available for a given organism, strategies include phenotypic evaluation of knockout and overexpression mutants under variable conditions, transcriptome analyses, and mass spectrometry based identification of substrates/products and pathway metabolites through comparison of wild-type and mutant metabolomes.
Data and Dissemination Core
(Patsy Babbitt and Wladek Minor, co-Directors)
The Data and Dissemination Core is responsible for data gathering/coordination, information dissemination, and bioinformatics. Four primary resources have been established: 1) the EFI website serves as the main resource for general information on development of the integrated strategy as well as a portal to the EFI’s targets, data, and tools; 2) the public EFI-DB database for access to experimental data gathered on each target as it becomes available; 3) an internal LabDB database for semi-automated recording and analysis of experimental data; and 4) the SFLD database which provides highly curated sequence information, links to external databases, and computationally-derived information for the EFI superfamilies as well as an expanding number of other superfamilies.