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Structure-based evaluation of sequence comparison and fold recognition alignment accuracy.

F S Domingues1, P Lackner, A Andreeva

  • 1Center for Applied Molecular Engineering, Institute for Chemistry and Biochemistry, University of Salzburg, Jakob Haringer Strasse 3, Salzburg, A-5020, Austria.

Journal of Molecular Biology
|March 29, 2000
PubMed
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This study introduces a benchmark protocol for assessing protein sequence alignment accuracy. The findings suggest combining substitution matrices and knowledge-based potentials yields the best results for distant relationships.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Inferring protein function and structure relies on sequence similarity to known proteins.
  • Accurate protein sequence alignment is crucial for detecting distant evolutionary relationships.
  • Reliable benchmarks are needed to evaluate and improve alignment methods.

Purpose of the Study:

  • To develop and describe a benchmark protocol for estimating sequence-to-sequence and sequence-to-structure alignment accuracy.
  • To create a challenging dataset of structurally related proteins with low sequence similarity.
  • To evaluate the accuracy of different alignment algorithms.

Main Methods:

  • Constructed a benchmark set of structurally related protein pairs covering all known fold types.

Related Experiment Videos

  • Derived accurate target alignments using rigid body superposition of 3D protein structures.
  • Developed an evaluation engine to quantify alignment accuracy against structure-derived alignments.

    • Main Results:

    • The benchmark effectively assesses alignment accuracy for proteins lacking clear sequence similarity.
    • Evaluated alignment accuracy by measuring shifts relative to structure-derived alignments.
    • Identified that a combination of amino acid residue substitution matrices and knowledge-based potentials provides optimal results.

    Conclusions:

    • The developed benchmark protocol is a valuable tool for assessing protein sequence alignment accuracy.
    • The findings highlight the effectiveness of integrating substitution matrices and knowledge-based potentials for challenging alignment tasks.
    • This approach enhances the reliability and accuracy of detecting distant protein relationships.