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Related Concept Videos

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Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
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A Protocol for Computer-Based Protein Structure and Function Prediction
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Fold-specific sequence scoring improves protein sequence matching.

Sumudu P Leelananda1,2,3,4, Andrzej Kloczkowski4,5, Robert L Jernigan6,7

  • 1Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, 112 Office and Lab Building, Ames, IA, 50011-3020, USA.

BMC Bioinformatics
|September 1, 2016
PubMed
Summary
This summary is machine-generated.

Novel amino acid substitution matrices incorporating topology-specific structural information significantly improve sequence matching and homology detection. These structure-based matrices outperform traditional methods, enhancing biological data analysis.

Keywords:
Blosom62CATH topologiesDistant homologiesHMMProtein fold familiesPsi-blastSequence matchingStructure alignment

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Accurate sequence matching is crucial for understanding biological functions, evolutionary relationships, and identifying disease-related gene mutations.
  • Current universal amino acid substitution matrices (e.g., Blosum62) lack protein structural topology information, limiting their effectiveness in identifying distant homologues.
  • Previous attempts to integrate structural information into sequence matching have yielded limited success.

Purpose of the Study:

  • To develop novel amino acid substitution matrices that combine general sequence information with topology-specific structural data.
  • To enhance the accuracy and effectiveness of sequence matching and homology detection by leveraging protein structural topology.

Main Methods:

  • Development of novel substitution matrices incorporating both sequence and CATH topology-specific information.
  • Utilized a multi-structure alignment method to extract topological information across different homology levels within the CATH classification.
  • Integrated these structure-based matrices into sequence matching algorithms like Psi-blast.

Main Results:

  • Statistically significant improvements in sequence matching scores observed for 73% of alpha-helical test cases.
  • On average, 61% of test cases showed improved homology detection with structure-informed matrices.
  • Average z-scores for homology detection improved by over 54%, with some cases doubling compared to generic matrices; outperforming Psi-blast and HMM profiles.

Conclusions:

  • Incorporating topology-specific structural information into amino acid substitution matrices significantly enhances sequence matching and homology detection.
  • The developed topology-specific matrices demonstrate superior performance compared to traditional matrices, single-matrix structure methods, Psi-blast, and HMM profiles.
  • These matrices effectively discriminate between distant homologs and structurally dissimilar protein pairs.