BER launches Environmental System Science Program. Visit our new website under construction!

U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights

Evaluating Methods for Predicting Protein Functions
Published: January 27, 2013
Posted: February 13, 2019

International teams assess computational tools to speed up annotations.

The Science
The accurate annotation of protein function from genomic sequences is key to understanding biological processes at the molecular level. However, experimental characterization of protein function is challenging and costly and thus cannot keep pace with the amount of sequencing data being produced.

The Impact
Numerous computational methods to predict protein function have been developed over the past decade to address the growing divide between sequence data and protein functional annotations. Recently, the scientific community came together to provide an unbiased evaluation of these new methods. This effort, named Critical Assessment of Protein Function Annotation (CAFA), consisted of 30 international teams of scientists who evaluated various computational methods on a target set of 866 protein sequences from 11 species, both eukaryotic and prokaryotic.

The organizers gave the research community four months to provide computational predictions of protein function, and then CAFA assessors obtained experimental validations of the targeted protein functions. The results suggest that predicting protein function is difficult because proteins can behave differently depending on environmental factors, such as pH, temperature, or the presence of interacting partners. This was evident across all targets studied, although predictions of molecular function (e.g., protein binding) outperformed predictions of biological processes (e.g., dynamics as a function of temperature). The CAFA community concluded that one way to improve annotation would be to integrate a variety of experimental evidence and data into new computational methods.

Predrag Radivojac
School of Informatics and Computing, Indiana University
Bloomington, Indiana

The CAFA activity and Automated Function Prediction Special Interest Group meeting at the ISMB 2011 conference were supported jointly by the U.S. National Institutes of Health (grant R13 HG006079-01A1) and the Office of Biological and Environmental Research within the U.S. Department of Energy’s Office of Science (grant DE-SC0006807TDD).

Radivojac, P., et al. “A large-scale evaluation of computational protein function prediction,” Nature Methods 10(3), 221-227 (2013). [DOI: 10.1038/nmeth.2340]

Topic Areas:

  • Research Area: Genomic Analysis and Systems Biology
  • Research Area: Computational Biology, Bioinformatics, Modeling
  • Research Area: Structural Biology, Biomolecular Characterization and Imaging

Division: SC-33.2 Biological Systems Science Division, BER


BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

Mar 23, 2021
Molecular Connections from Plants to Fungi to Ants
Lipids transfer energy and serve as an inter-kingdom communication tool in leaf-cutter ants&rsqu [more...]

Mar 19, 2021
Microbes Use Ancient Metabolism to Cycle Phosphorus
Microbial cycling of phosphorus through reduction-oxidation reactions is older and more widespre [more...]

Feb 22, 2021
Warming Soil Means Stronger Microbe Networks
Soil warming leads to more complex, larger, and more connected networks of microbes in those soi [more...]

Jan 27, 2021
Labeling the Thale Cress Metabolites
New data pipeline identifies metabolites following heavy isotope labeling.

Analysis [more...]

Aug 31, 2020
Novel Bacterial Clade Reveals Origin of Form I Rubisco

  • All plant biomass is sourced from the carbon-fixing enzyme Rub [more...]

List all highlights (possible long download time)