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Related Experiment Videos

PALSSE: a program to delineate linear secondary structural elements from protein structures.

Indraneel Majumdar1, S Sri Krishna, Nick V Grishin

  • 1Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, USA. indraneel@chop.swmed.edu

BMC Bioinformatics
|August 13, 2005
PubMed
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A new method, Predictive Assignment of Linear Secondary Structure Elements (PALSSE), accurately identifies protein secondary structures for improved vector-based comparisons. PALSSE assigns more residues to structures than other methods, enhancing protein similarity searches.

Area of Science:

  • Structural Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Protein structures predominantly feature alpha-helices and beta-strands.
  • Accurate identification of secondary structure elements is vital for protein structure comparison.
  • Vector-based methods rely on precise delineation of these elements.

Purpose of the Study:

  • To develop a novel method for delineating secondary structure elements (SSEs) from protein Calpha coordinates.
  • To specifically address the needs of vector-based protein similarity searches.
  • To improve the accuracy and coverage of secondary structure assignment.

Main Methods:

  • Developed Predictive Assignment of Linear Secondary Structure Elements (PALSSE).
  • Identifies helices and beta-strands representable by vectors.

Related Experiment Videos

  • Assigns residues to linear SSEs, allowing for overlapping elements.

    • Main Results:

    • PALSSE assigns approximately 80% of protein chains to SSEs, surpassing DSSP (53%) and P-SEA (57%).
    • The method aligns with human judgment and DSSP.
    • Results are robust to coordinate errors, applicable to low-resolution structures.

    Conclusions:

    • PALSSE offers a more comprehensive assignment of residues to SSEs for structural comparisons.
    • The method is reliable and effective for diverse protein structure quality.
    • The PALSSE program and its results are publicly available.