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The '''Enzyme Function Initiative (EFI)''' is a large scale collaborative project which aims to develop and disseminate a robust strategy to determine [[Enzyme|enzyme]] function through an integrated sequence-structure based approach.<ref>{{cite press release |title=New NIGMS ‘Glue Grant’ Takes Aim at Unknown Enzymes |publisher=NIGMS |date=2010-05-20 |url=http://www.nigms.nih.gov/News/Results/gluegrant_051510.htm |format= |language= |accessdate=2011-05-04 |quote= }}</ref> The project was funded in May 2010 by the [[National_Institute_of_General_Medical_Sciences|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.<ref>{{cite web |url=http://www.nigms.nih.gov/Research/FeaturedPrograms/Collaborative/GlueGrants/ |title=Glue Grants |accessdate=2011-05-04 |work= |publisher=NIGMS |date= }}</ref><ref>{{cite web |url=http://grants.nih.gov/grants/guide/pa-files/PAR-07-412.html|title=PAR-07-412: Large-Scale Collaborative Project Awards (R24/U54) |accessdate=2011-05-04 |work= |publisher=NIH/NIGMS |date= }}</ref> The EFI was largely spurred by the need to develop methods to identify the functions of the enormous number proteins discovered through [[Genomics|genomic]] sequencing projects.<ref>{{cite press release |title=Researchers Awarded $33.9 Million Grant to Study Enzyme Functions |publisher=UIUC News Bureau |date=2010-05-20 |url=http://news.illinois.edu/news/10/0520gerlt.html |format= |language= |accessdate=2011-05-04 |quote= }}</ref>
The '''Enzyme Function Initiative (EFI)''' is a large scale collaborative project which aims to develop and disseminate a robust strategy to determine [[Enzyme|enzyme]] function through an integrated sequence-structure based approach.<ref>{{cite press release |title=New NIGMS ‘Glue Grant’ Takes Aim at Unknown Enzymes |publisher=NIGMS |date=2010-05-20 |url=http://www.nigms.nih.gov/News/Results/gluegrant_051510.htm |format= |language= |accessdate=2011-05-04 |quote= }}</ref> The project was funded in May 2010 by the [[National_Institute_of_General_Medical_Sciences|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.<ref>{{cite web |url=http://www.nigms.nih.gov/Research/FeaturedPrograms/Collaborative/GlueGrants/ |title=Glue Grants |accessdate=2011-05-04 |work= |publisher=NIGMS |date= }}</ref><ref>{{cite web |url=http://grants.nih.gov/grants/guide/pa-files/PAR-07-412.html|title=PAR-07-412: Large-Scale Collaborative Project Awards (R24/U54) |accessdate=2011-05-04 |work= |publisher=NIH/NIGMS |date= }}</ref> The EFI was largely spurred by the need to develop methods to identify the functions of the enormous number proteins discovered through [[Genomics|genomic]] sequencing projects.<ref>{{cite press release |title=Researchers Awarded $33.9 Million Grant to Study Enzyme Functions |publisher=UIUC News Bureau |date=2010-05-20 |url=http://news.illinois.edu/news/10/0520gerlt.html |format= |language= |accessdate=2011-05-04 |quote= }}</ref>


== Motivation ==
== Motivation ==
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== Organization ==
== Organization ==
The EFI is comprised 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|amidohydrolase]], [[Enolase_superfamily|enolase]], [[Glutathione_S-transferase|GST]], HAD, and isoprenoid synthase enzyme superfamilies.
The EFI is comprised 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|amidohydrolase]], [[Enolase_superfamily|enolase]], [[Glutathione_S-transferase|GST]], HAD, and isoprenoid synthase enzyme superfamilies.


=== Scientific Cores ===
=== Scientific Cores ===

Revision as of 20:45, 4 May 2011

Enzyme Function Initiative (EFI)
Formation2010
Purposedevelop and disseminate a robust strategy to determine enzyme function
HeadquartersUniversity of Illinois, Urbana-Champaign
Principal Investigator
John A. Gerlt, Ph.D.
Budget
5 year NIGMS Glue Grant
Websitehttp://enzymefunction.org

The Enzyme Function Initiative (EFI) is a large scale collaborative project which aims 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 genomic sequencing projects has caused the number of protein sequences deposited into public databases to grow 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 lead 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 replies 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.

Organization

By NIGMS program mandate, Glue Grant consortia must contain Core Resources and Bridging Projects.[3] The EFI is comprised 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.

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 : the Structure-Function Linkage Database (SFLD) which houses bioinformatic data for targeted EFI enzymes and the EFI-DB which houses experimental data for targeted EFI enzymes.

Bridging Projects

The Amidohydrolase Superfamily (> 20,000 enzymes) 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.[13]

The Enolase Superfamily (> 8,000 enzymes) 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.[14]

The GST Superfamily (> 10,000 enzymes) 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.[15]

The HAD Superfamily (> 40,000 enzymes) 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.[16]

The Isoprenoid Synthase (I) Superfamily (> 9,000 enzymes) 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.

Participating Investigators

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.[17] As the strategy is developed, data on gene cloning, protein purification, and crystallization is made freely available via the EFI-DB, and bioinformatic data is available in the SFLD. Clones may be obtained from the materials repository PSI-MR. Protocols for gene cloning, protein purification, and crystallography are available via PepcDB while protocols for substrate library synthesis and enzyme assays will be made available via the EFI website as will any other tools developed.

Funding

The EFI was established in May of 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. [18]

References

  1. ^ "New NIGMS 'Glue Grant' Takes Aim at Unknown Enzymes" (Press release). NIGMS. 2010-05-20. Retrieved 2011-05-04.
  2. ^ "Glue Grants". NIGMS. Retrieved 2011-05-04.
  3. ^ a b "PAR-07-412: Large-Scale Collaborative Project Awards (R24/U54)". NIH/NIGMS. Retrieved 2011-05-04.
  4. ^ "Researchers Awarded $33.9 Million Grant to Study Enzyme Functions" (Press release). UIUC News Bureau. 2010-05-20. Retrieved 2011-05-04.
  5. ^ "UniProtKB/TrEMBL Protein Database Release 2011_04 Statistics". UniProtKB/TrEMBL Protein Database. Retrieved 2011-05-04. {{cite web}}: Cite has empty unknown parameter: |1= (help)
  6. ^ Schnoes, Alexandra M.; Brown, Shoshana D.; Dodevski, Igor; Babbitt, Patricia C. (2009). Valencia, Alfonso (ed.). "Annotation Error in Public Databases: Misannotation of Molecular Function in Enzyme Superfamilies". PLoS Computational Biology. 5 (12): e1000605. doi:10.1371/journal.pcbi.1000605. PMC 2781113. PMID 20011109.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  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, Shoshanad; Gerlt, Johna; Seffernick, Jenniferl; Babbitt, Patriciac (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.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  9. ^ "Integrated Strategy". Enzyme Function Initiative. Retrieved 2011-04-05. {{cite web}}: Cite has empty unknown parameter: |1= (help)
  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. ^ 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.
  14. ^ 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.
  15. ^ 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.
  16. ^ 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.
  17. ^ "Problems to be Solved". Enzyme Function Initiative. Retrieved 2011-04-05. {{cite web}}: Cite has empty unknown parameter: |1= (help)
  18. ^ "NIGMS Glue Grants Outcomes Assessment". NIGMS. Retrieved 2011-05-04.
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