Enzyme Function Initiative

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Enzyme Function Initiative (EFI)
Formation 2010
Purpose/focus develop and disseminate a robust strategy to determine enzyme function
Headquarters University of Illinois, Urbana-Champaign
Principal Investigator John A. Gerlt, Ph.D.
Budget 5 year NIGMS Glue Grant
Website www.enzymefunction.org

The Enzyme Function Initiative (EFI) is a large scale collaborative project aiming to develop and disseminate a robust strategy to determine enzyme function through an integrated sequence-structure based approach.[1] The project was funded in May 2010 by the National Institute of General Medical Sciences as a Glue Grant which supports the research of complex biological problems that cannot be solved by a single research group.[2][3] The EFI was largely spurred by the need to develop methods to identify the functions of the enormous number proteins discovered through genomic sequencing projects.[4]

Motivation

The dramatic increase in genome sequencing technology has caused the number of protein sequences deposited into public databases to grow apparently exponentially.[5] To cope with the influx of sequences, databases use computational predictions to auto-annotate individual protein's functions. While these computational methods offer the advantages of being extremely high-throughput and generally provide accurate broad classifications, exclusive use has led to a significant level of misannotation of enzyme function in protein databases.[6] Thus although the information now available represents an unprecedented opportunity to understand cellular metabolism across a wide variety of organisms, which includes the ability to identify molecules and/or reactions that may benefit human quality of life, the potential has not been fully actualized.[7] The biological community's ability to characterize newly discovered proteins has been outstripped by the rate of genome sequencing, and the task of assigning function is now considered the rate-limiting step in understanding biological systems in detail.[8]

Integrated Strategy for Functional Assignment

The EFI is developing an integrated sequence-structure based strategy for functional assignment by predicting the substrate specificities of unknown members of mechanistically diverse enzyme superfamilies.[9] The approach leverages conserved features within a given superfamily such as known chemistry, identity of active site functional groups, and composition of specificity-determining residues, motifs, or structures to predict function but relies on multidisciplinary expertise to streamline, refine, and test the predictions.[10][11][12] The integrated sequence-strategy under development will be generally applicable to deciphering the ligand specificities of any functionally unknown protein.[9]

Organization

By NIGMS program mandate, Glue Grant consortia must contain Core Resources and Bridging Projects.[3] The EFI consists of six Scientific Cores which provide bioinformatic, structural, computational, and data management expertise to facilitate functional predictions for enzymes of unknown function targeted by the EFI. These predictions are then tested by five Bridging Projects representing the amidohydrolase, enolase, GST, HAD, and isoprenoid synthase enzyme superfamilies.[9]

Scientific Cores

The Superfamily/Genome Core contributes bioinformatic analysis by collecting and curating complete sequence data sets, generating sequence similarity networks, and classification of superfamily members into subgroups and families for subsequent annotation transfer and evaluation as targets for functional characterization.

The Protein Core develops cloning, expression, and protein purification strategies for the enzymes targeted for study.

The Structure Core fulfills the structural biology component for EFI by providing high resolution structures of targeted enzymes.

The Computation Core performs in silico docking to generate rank-ordered lists of predicted substrates for targeted enzymes using both experimentally determined and/or homology modeled protein structures.

The Microbiology Core examines in vivo functions using genetic techniques and metabolomics to compliment in vitro functions determined by the Bridging Projects.

The Data and Dissemination Core maintains two complementary public databases for bioinformatic (Structure-Function Linkage Database) and experimental data (EFI-DB).[13][14]

Bridging Projects

The amidohydrolase superfamily contains evolutionarily related enzymes with a distorted (β/α)8 barrel fold which primarily catalyze metal-assisted deamination, decarboxylation, isomerization, hydration, or retroaldol cleavage reactions.[15]

The enolase superfamily contains evolutionarily related enzymes with a (β/α)7β‑barrel (TIM‑barrel) fold which primarily catalyze metal-assisted epimerization/racemization or β-elimination of carboxylate substrates.[16]

The GST superfamily contains evolutionarily related enzymes with a modified thioredoxin fold and an additional all α-helical domain which primarily catalyze nucleophilic attack of reduced glutathione (GSH) on electrophlic substrates.[17]

The HAD superfamily contains evolutionarily related enzymes with a Rosmmannoid α/β fold with an inserted "cap" region which primarily catalyze metal-assisted nucleophilic catalysis, most frequently resulting in phosphoryl group transfer.[18]

The isoprenoid synthase (I) superfamily contains evolutionarily related enzymes with a mostly all α-helical fold and primarily catalyze trans-prenyl transfer reactions to form elongated or cyclized isoprene products.[19]

Participating Investigators

Fourteen investigators with expertise in various disciplines make up the EFI.[20]

Name Institution Role
Gerlt, John A. University of Illinois, Urbana-Champaign EFI Director, Director of the Enolase Bridging Project
Allen, Karen N. Boston University Co-Director of the HAD Bridging Project
Almo, Steven C. Albert Einstein College of Medicine Director of the Protein, Director of the Structure Core
Armstrong, Richard N. Vanderbilt University School of Medicine Director of the GST Bridging Project
Babbitt, Patricia C. University of California, San Francisco Director of the Superfamily/Genome Core, Co-Director of the Data and Dissemination Core
Cronan, John E. University of Illinois, Urbana-Champaign Co-Director of the Microbiology Core
Dunaway‑Mariano, Debra University of New Mexico Co-Director of the HAD Bridging Project
Jacobson, Matthew P. University of California, San Francisco Co-Director of the Computation Core
Minor, Wladek University of Virginia Co-Director of Data and Dissemination Core
Poulter, C. Dale University of Utah Director of the Isoprenoid Synthase Bridging Project
Raushel, Frank M. Texas A&M University Director of the Amidohydrolase Bridging Project
Sali, Andrej University of California, San Francisco Co-Director of the Computation Core
Shoichet, Brian K. University of California, San Francisco Co-Director of the Computation Core
Sweedler, Jonathan V. University of Illinois, Urbana-Champaign Co-Director of the Microbiology Core

Deliverables

The EFI's primary deliverable is development and dissemination of an integrated sequence/structure strategy for functional assignment. As the strategy is developed, data and clones generated by the EFI are made freely available via several online resources.[9]

Funding

The EFI was established in May 2010 with $33.9 million in funding over a 5-year period (grant number GM093342). Pending project success and assessment of the Glue Grant funding mechanism, the grant may be renewed for an additional 5 years in 2014.[21]

References

  1. ↑ "New NIGMS ‘Glue Grant’ Takes Aim at Unknown Enzymes" (Press release). NIGMS. 2010-05-20. Retrieved 2012-04-27. 
  2. ↑ "Glue Grants". NIGMS. Retrieved 2012-04-27. 
  3. ↑ 3.0 3.1 "PAR-07-412: Large-Scale Collaborative Project Awards (R24/U54)". NIH/NIGMS. Retrieved 2012-04-27. 
  4. ↑ "Researchers Awarded $33.9 Million Grant to Study Enzyme Functions" (Press release). UIUC News Bureau. 2010-05-20. Retrieved 2012-04-27. 
  5. ↑ "UniProtKB/TrEMBL Protein Database Release Statistics". UniProtKB/TrEMBL Protein Database. Retrieved 2012-04-27. 
  6. ↑ Schnoes, Alexandra M.; Brown, Shoshana D.; Dodevski, Igor; Babbitt, Patricia C. (2009). "Annotation Error in Public Databases: Misannotation of Molecular Function in Enzyme Superfamilies". In Valencia, Alfonso. PLoS Computational Biology 5 (12): e1000605. doi:10.1371/journal.pcbi.1000605. PMC 2781113. PMID 20011109. 
  7. ↑ Saghatelian, Alan; Cravatt, Benjamin F (2005). "Assignment of protein function in the postgenomic era". Nature Chemical Biology 1 (3): 130–42. doi:10.1038/nchembio0805-130. PMID 16408016. 
  8. ↑ Brown, Shoshana; Gerlt, John; Seffernick, Jennifer; Babbitt, Patricia (2006). "A gold standard set of mechanistically diverse enzyme superfamilies". Genome Biology 7 (1): R8. doi:10.1186/gb-2006-7-1-r8. PMC 1431709. PMID 16507141. 
  9. ↑ 9.0 9.1 9.2 9.3 Gerlt, JA; Allen, KN, Almo, SC, Armstrong, RN, Babbitt, PC, Cronan, JE, Dunaway-Mariano, D, Imker, HJ, Jacobson, MP, Minor, W, Poulter, CD, Raushel, FM, Sali, A, Shoichet, BK, Sweedler, JV (Nov 22, 2011). "The Enzyme Function Initiative.". Biochemistry 50 (46): 9950–62. doi:10.1021/bi201312u. PMC 3238057. PMID 21999478. 
  10. ↑ Song, Ling; Kalyanaraman, Chakrapani; Fedorov, Alexander A; Fedorov, Elena V; Glasner, Margaret E; Brown, Shoshana; Imker, Heidi J; Babbitt, Patricia C; Almo, Steven C (2007). "Prediction and assignment of function for a divergent N-succinyl amino acid racemase". Nature Chemical Biology 3 (8): 486–91. doi:10.1038/nchembio.2007.11. PMID 17603539. 
  11. ↑ Hermann, Johannes C.; Marti-Arbona, Ricardo; Fedorov, Alexander A.; Fedorov, Elena; Almo, Steven C.; Shoichet, Brian K.; Raushel, Frank M. (2007). "Structure-based activity prediction for an enzyme of unknown function". Nature 448 (7155): 775–779. doi:10.1038/nature05981. PMC 2254328. PMID 17603473. 
  12. ↑ Kalyanaraman, C; Imker, H; Fedorov, A; Fedorov, E; Glasner, M; Babbitt, P; Almo, S; Gerlt, J; Jacobson, M (2008). "Discovery of a Dipeptide Epimerase Enzymatic Function Guided by Homology Modeling and Virtual Screening". Structure 16 (11): 1668–77. doi:10.1016/j.str.2008.08.015. PMC 2714228. PMID 19000819. 
  13. ↑ Pegg, Scott C.-H.; Brown, Shoshana D.; Ojha, Sunil; Seffernick, Jennifer; Meng, Elaine C.; Morris, John H.; Chang, Patricia J.; Huang, Conrad C.; Ferrin, Thomas E. (2006). "Leveraging Enzyme Structure−Function Relationships for Functional Inference and Experimental Design:  The Structure−Function Linkage Database†". Biochemistry 45 (8): 2545–55. doi:10.1021/bi052101l. PMID 16489747. 
  14. ↑ "EFI-DB Experimental Database". Enzyme Function Initiative. Retrieved 2012-04-27. 
  15. ↑ Seibert, Clara M.; Raushel, Frank M. (2005). "Structural and Catalytic Diversity within the Amidohydrolase Superfamily". Biochemistry 44 (17): 6383–91. doi:10.1021/bi047326v. PMID 15850372. 
  16. ↑ Gerlt, John A.; Babbitt, Patricia C.; Rayment, Ivan (2005). "Divergent evolution in the enolase superfamily: The interplay of mechanism and specificity". Archives of Biochemistry and Biophysics 433 (1): 59–70. doi:10.1016/j.abb.2004.07.034. PMID 15581566. 
  17. ↑ Armstrong, Richard N. (1997). "Structure, Catalytic Mechanism, and Evolution of the Glutathione Transferases". Chemical Research in Toxicology 10 (1): 2–18. doi:10.1021/tx960072x. PMID 9074797. 
  18. ↑ Burroughs, A. Maxwell; Allen, Karen N.; Dunaway-Mariano, Debra; Aravind, L. (2006). "Evolutionary Genomics of the HAD Superfamily: Understanding the Structural Adaptations and Catalytic Diversity in a Superfamily of Phosphoesterases and Allied Enzymes". Journal of Molecular Biology 361 (5): 1003–34. doi:10.1016/j.jmb.2006.06.049. PMID 16889794. 
  19. ↑ Christianson, David W. (2006). "Structural Biology and Chemistry of the Terpenoid Cyclases". Chemical Reviews 106 (8): 3412–42. doi:10.1021/cr050286w. PMID 16895335. 
  20. ↑ "People". Enzyme Function Initiative. Retrieved 2012-04-27. 
  21. ↑ "NIGMS Glue Grants Outcomes Assessment". NIGMS. Retrieved 2012-04-27. 

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