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TRIAL: a tool for finding distant structural similarities.

Jayendra Gnanaskandan Venkateswaran1, Bin Song, Tamer Kahveci

  • 1Epic Systems Corporation, 221 S High Point Rd., Apt# 115, Madison, WI 53717, USA. jgvenkat@cise.ufl.edu

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|March 12, 2011
PubMed
Summary
This summary is machine-generated.

A new algorithm, TRiplet-based Iterative ALignment (TRIAL), enhances protein structural alignment for distantly related proteins. TRIAL improves accuracy and alignment length, outperforming existing methods in identifying functional relationships.

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Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Protein structure analysis

Background:

  • Sequence comparison often fails to identify functional relationships in distantly related proteins.
  • Existing structural alignment algorithms struggle with proteins exhibiting low primary sequence similarity.

Purpose of the Study:

  • To develop an algorithm for robust protein structural alignment, particularly for proteins with low sequence similarity.
  • To improve the identification of functional relationships through enhanced structural comparison.

Main Methods:

  • Developed the TRiplet-based Iterative ALignment (TRIAL) algorithm.
  • TRIAL computes transformations to maximize aligned residues within a specified root mean square deviation (RMSD) threshold (ε Å).
  • Algorithm specifically designed to handle proteins with low primary structure similarity.

Main Results:

  • TRIAL outperforms existing methods in protein structural alignment.
  • Achieved up to 63% better classification accuracy compared to methods like CE and DALI.
  • Successfully aligns 83% of residues from smaller proteins, significantly more than other methods (29-65%).
  • TRIAL alignment results in similar orientations of secondary structures and increased alignment lengths at lower RMSD values.

Conclusions:

  • TRIAL is an effective algorithm for structural alignment of distantly related proteins.
  • The method enhances the discovery of functional relationships missed by sequence-based approaches.
  • TRIAL offers significant improvements in accuracy, alignment length, and residue coverage over existing algorithms.