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Updated: Jun 21, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Iterative refinement of structure-based sequence alignments by Seed Extension.

Changhoon Kim¹, Chin-Hsien Tai, Byungkook Lee

¹Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA. kimchan@mail.nih.gov

BMC Bioinformatics

|July 11, 2009

Summary

This summary is machine-generated.

Refinement with Seed Extension (RSE) improves structure-based sequence alignment accuracy, especially for low sequence similarity. This computationally inexpensive method enhances existing bioinformatics tools with negligible added time.

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Area of Science:

Bioinformatics
Computational Biology
Structural Bioinformatics

Background:

Accurate sequence alignment is crucial for bioinformatics, but low sequence similarity poses a challenge.
Current structure-based methods still have significant residue misalignments.
Previous work explored Seed Extension (SE) to overcome limitations of gap penalties in dynamic programming.

Purpose of the Study:

To introduce and evaluate Refinement with Seed Extension (RSE), a novel iterative refinement procedure for structure-based sequence alignment.
To assess RSE's ability to correct errors in alignments generated by popular existing software.

Main Methods:

RSE utilizes the Seed Extension (SE) algorithm at its core.
The procedure iteratively refines structure-based sequence alignments.
Evaluated RSE by comparing alignment accuracy before and after refinement using established programs and reference datasets.

Main Results:

RSE significantly improved the average accuracy of structure-based sequence alignments across multiple tested programs.
Improvements were observed even when shift errors were disallowed.
The computational overhead of RSE was negligible compared to the primary structure alignment programs.

Conclusions:

RSE offers a computationally inexpensive method to enhance structure-based sequence alignment accuracy.
It can be applied as a post-processing step or integrated to replace traditional dynamic programming refinement.
The RSE procedure shows potential for broad application in improving bioinformatics analyses reliant on sequence alignment.