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Accuracy of structure-based sequence alignment of automatic methods.

Changhoon Kim1, Byungkook Lee

  • 1Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute National Institutes of Health, Bethesda, Maryland, USA. kimchan@mail.nih.gov

BMC Bioinformatics
|September 22, 2007
PubMed
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Structure-based methods improve protein sequence alignment accuracy, especially for low sequence similarity. However, current methods still misalign 11-19% of conserved residues, with alignment quality varying by protein type and similarity. DaliLite shows the most agreement with curated alignments.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Bioinformatics

Background:

  • Accurate protein sequence alignments are crucial for homology searches and 3D model construction.
  • Protein structure is more conserved than sequence, making structure alignments a gold standard for evaluating sequence alignments.
  • Systematic evaluations of pairwise structure alignment programs for sequence alignment accuracy are lacking.

Purpose of the Study:

  • To systematically evaluate the sequence alignment accuracy of seven pairwise structure alignment programs: CE, DaliLite, FAST, LOCK2, MATRAS, SHEBA, and VAST.
  • To compare the accuracy of structure-based sequence alignments against human-curated alignments from the Conserved Domain Database (CDD).

Main Methods:

  • Evaluated seven structure alignment programs (CE, DaliLite, FAST, LOCK2, MATRAS, SHEBA, VAST).

Related Experiment Videos

  • Used sequence alignments from NCBI's Conserved Domain Database (CDD) as the ground truth.
  • Analyzed alignment accuracy based on residue alignment, shift error, sequence similarity, RMSD, and protein structural classes (SCOP).

    • Main Results:

    • 4-19% of residues were misaligned or had significant shift errors, depending on the program and dataset.
    • Alignment accuracy decreased with lower sequence similarity and higher structural divergence (RMSD).
    • Alignment quality varied across protein superfamilies and structural classes, with specific programs showing weaknesses (e.g., CE for beta-sheet structures, DaliLite for 'others', LOCK2/VAST for all-beta/others).

    Conclusions:

    • Structure-based methods outperform sequence-only methods for low sequence similarity but still have limitations.
    • 11-19% of conserved core residues are misaligned compared to CDD, highlighting room for improvement.
    • DaliLite demonstrated the highest agreement with CDD alignments on average, indicating its robustness across different protein types.