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Related Experiment Videos

Sequence to structure alignment in comparative modeling using PrISM.

A S Yang1, B Honig

  • 1Columbia Genome Center, Columbia University, New York, New York 10032, USA. yanga@cumbih.bioc.columbia.edu

Proteins
|October 20, 1999
PubMed
Summary
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The Protein Informatics System for Modeling (PrISM) aids protein analysis and modeling. Advanced alignment methods in PrISM show promise but face challenges with distantly related protein sequences.

Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Protein modeling

Background:

  • Protein structure prediction is crucial for understanding protein function.
  • Comparative modeling relies on accurate sequence-template alignments.
  • Existing alignment methods can struggle with distantly related sequences.

Purpose of the Study:

  • To evaluate the performance of the PrISM system in comparative protein modeling.
  • To highlight the challenges and successes of sequence-template alignment methods.
  • To assess PrISM's utility in the CASP3 experiment.

Main Methods:

  • Utilized the integrated informatics, alignment, modeling, and assessment modules of PrISM.
  • Applied various sequence-template alignment methods and parameter sets.

Related Experiment Videos

  • Employed a model ranking system for selecting the best alignment.

    • Main Results:

    • PrISM successfully predicted models for 13 comparative modeling targets in CASP3.
    • Advanced alignment procedures in PrISM improved results when standard methods failed.
    • PrISM's advanced methods encountered difficulties with targets involving significant insertions/deletions.

    Conclusions:

    • PrISM offers an integrated environment for interactive and automated protein analysis and modeling.
    • Sequence-template alignment remains a critical challenge, especially for distantly related proteins.
    • PrISM's alignment strategies show potential but require further refinement for complex cases.