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Related Experiment Videos

Predicting reliable regions in protein alignments from sequence profiles.

Michael L Tress1, David Jones, Alfonso Valencia

  • 1Protein Design Group, Centro Nacional de Biotechnologia, CNB-CSIC, Cantoblanco, 28049 Madrid, Spain. mtress@cnb.uam.es

Journal of Molecular Biology
|July 10, 2003
PubMed
Summary
This summary is machine-generated.

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Predicting reliable protein sequence alignment regions is crucial for comparative modeling. This study demonstrates that profile-derived alignment scores effectively identify these reliable regions, improving alignment quality assessment and binding site prediction.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Sequence alignment reliability is critical for comparative modeling.
  • Current methods for predicting reliable alignment regions have limitations.

Purpose of the Study:

  • To develop and validate a novel method for predicting reliable regions in protein sequence alignments using multiple sequence profile information.
  • To assess the accuracy of this method in predicting reliably aligned residues within secondary structures and loops.
  • To explore the utility of this method for predicting conserved binding sites.

Main Methods:

  • Generated alignments for remotely related protein pairs using five different methods.
  • Scored aligned positions using information from amino acid residue frequencies in pre-generated sequence profiles.

Related Experiment Videos

  • Assessed alignment quality using structural alignments.
  • Evaluated the prediction accuracy for residues in secondary structures and loops.

    • Main Results:

    • Profile-derived alignment scores accurately predicted reliably aligned regions.
    • High-scoring regions of these scores correlated well with structurally verified reliable alignments.
    • The method achieved high accuracy (92-97.4%) for residues in secondary structures and just under 92% for loop regions.
    • Predicted reliable regions for helix residues ranged from 32.1% to 52.8% for strand residues.
    • Identified conserved binding sites in over 80% of cases within highly conserved, high-scoring regions.

    Conclusions:

    • Profile-derived alignment scores offer a robust and broadly applicable method for assessing protein sequence alignment quality.
    • This approach enhances the reliability of comparative modeling by identifying trustworthy alignment regions.
    • The method shows promise for predicting conserved binding sites from sequence alignments, facilitating functional site identification.