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Related Concept Videos

Protein Families02:47

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key locations, protein...
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A Protocol for Computer-Based Protein Structure and Function Prediction
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Published on: November 3, 2011

Algorithm for predicting functionally equivalent proteins from BLAST and HMMER searches.

Dong Su Yu1, Dae-Hee Lee, Seong Keun Kim

  • 1Systems and Synthetic Biology Research Center, Korea Research Institute of Bioscience and Biotechnology, 125 Gwahak-ro, Yuseong-gu, Daejeon 305-806, Korea.

Journal of Microbiology and Biotechnology
|June 21, 2012
PubMed
Summary
This summary is machine-generated.

Predicting protein function is challenging. The new FEP-BH algorithm accurately identifies functionally equivalent proteins from sequence similarity searches (BLAST) and domain predictions (HMMER), outperforming existing methods.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Protein Science

Background:

  • Predicting protein function from sequence is crucial for biological research.
  • BLAST and HMMER are standard tools for identifying homologous proteins and domains.
  • Functional equivalence is not guaranteed by sequence similarity or shared domains alone.

Purpose of the Study:

  • To develop a novel algorithm, FEP-BH, for accurate prediction of functionally equivalent proteins.
  • To improve upon existing methods for functional prediction based on BLAST and HMMER outputs.

Main Methods:

  • The FEP-BH algorithm was developed to analyze protein-protein pairs from BLAST and protein-domain pairs from HMMER.
  • The algorithm's performance was evaluated against the Pfam-A seed database domain classes.

Main Results:

  • FEP-BH achieved 71.53% accuracy in predicting functionally equivalent proteins.
  • This accuracy significantly surpassed BLAST (57.72%) and HMMER (36.62%) in the same evaluation.

Conclusions:

  • The FEP-BH algorithm offers a more accurate approach to identifying functionally equivalent proteins compared to traditional methods.
  • This tool is expected to be valuable for biologists seeking to determine protein function from sequence and domain data.