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An iterative structure-assisted approach to sequence alignment and comparative modeling.

D F Burke1, C M Deane, H A Nagarajaram

  • 1Department of Biochemistry, University of Cambridge, United Kingdom.

Proteins
|October 20, 1999
PubMed
Summary
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Accurate protein sequence alignment is crucial for comparative modeling. This study presents an iterative method using structural alignment databases and the JOY program to optimize protein models and sequence alignments.

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein modeling

Background:

  • Comparative protein modeling relies on accurate sequence alignment with homologous proteins of known 3D structure.
  • Iterative approaches considering local and global structural features are typically required for optimal alignment.

Purpose of the Study:

  • To describe an iterative approach for protein sequence alignment in comparative modeling.
  • To exploit structural alignment databases (HOMSTRAD, CAMPASS) and the JOY program for enhanced alignment and model validation.
  • To evaluate the use of multiple homologous structures versus a single parent structure for improved modeling.

Main Methods:

  • Utilized HOMSTRAD and CAMPASS databases for structure-based alignments.
  • Employed the JOY program to analyze and format alignments, revealing conserved local structural features.

Related Experiment Videos

  • Implemented an iterative refinement process: model construction, JOY reformatting, and realignment with parent structures.
  • Assessed the method using targets from the CASP3 experiment.

    • Main Results:

    • Databases and JOY facilitate recognition of protein families/superfamilies, selection of parent structures, and alignment refinement.
    • The iterative approach optimizes both sequence alignment and the resulting protein model.
    • Using multiple homologous structures can be advantageous over relying on a single parent structure.

    Conclusions:

    • The described iterative method, leveraging structural databases and JOY, enhances the accuracy of protein sequence alignment for comparative modeling.
    • This approach aids in selecting appropriate templates and validating models, particularly when multiple related structures are available.