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Computational methods for protein secondary structure prediction using multiple sequence alignments.

J Heringa1

  • 1Division of Mathematical Biology, National Institute of Medical Research (NIMR), The Ridgeway, Mill Hill, London, NW7 1AA, United Kingdom. jhering@nimr.mrc.ac.uk

Current Protein & Peptide Science
|October 9, 2002
PubMed
Summary
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Predicting protein secondary structure computationally has advanced significantly. Modern methods, using multiple sequence alignments, now enable reliable 3D protein modeling.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Science

Background:

  • Early computational methods for protein secondary structure prediction showed promise but lacked accuracy for reliable 3D modeling.
  • Recent advancements in computational techniques and the incorporation of multiple sequence information have dramatically improved prediction success rates.

Purpose of the Study:

  • To provide an overview of protein secondary structure prediction challenges and historical computational approaches.
  • To describe methods for accurate multiple protein sequence alignments, crucial for modern prediction strategies.
  • To briefly cover trans-membrane segment prediction in addition to globular proteins.

Main Methods:

  • Review of historical and contemporary computational methods for protein secondary structure prediction.

Related Experiment Videos

  • Description of techniques for generating accurate multiple protein sequence alignments.
  • Introduction to an integrated iterative approach combining secondary structure prediction and multiple alignment.

    • Main Results:

    • Significant increase in the accuracy of protein secondary structure prediction methods over the last decade.
    • Feasibility of successful 3D protein modeling based on predicted secondary structures.
    • Development of strategies leveraging multiple sequence information for enhanced prediction.

    Conclusions:

    • Computational protein secondary structure prediction has evolved substantially, becoming a reliable tool for structural biology.
    • Multiple sequence alignment is a key component of successful modern prediction methods.
    • Integrated approaches offer promising avenues for future advancements in protein structure prediction and modeling.