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Search strategies in structural bioinformatics.

Mark T Oakley¹, Daniel Barthel, Yuri Bykov

¹School of Chemistry, University of Nottingham, University Park, Nottingham NG7 2RD, UK.

Current Protein & Peptide Science

|June 10, 2008

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This review explores optimization in structural bioinformatics, highlighting Kolmogorov complexity for protein structure comparison and advanced algorithms like the great deluge and memetic algorithms for de novo protein structure prediction.

Area of Science:

Structural Bioinformatics
Computational Biology

Background:

Optimization problems are central to structural bioinformatics.
Recent advancements address key challenges in the field.

Purpose of the Study:

To review recent work on structural bioinformatics challenges.
To highlight novel methods in protein structure comparison and prediction.

Main Methods:

Kolmogorov complexity for protein structure comparison.
De novo protein structure prediction from first principles.
Off-lattice prediction using the great deluge algorithm.
Memetic algorithms for lattice-based protein models.

Main Results:

Kolmogorov complexity proves useful for assessing structural similarity.

Related Experiment Videos

The great deluge algorithm aids in off-lattice structure prediction.

Memetic algorithms enhance the study of lattice-based protein models.

Conclusions:

Optimization techniques are crucial for advancing structural bioinformatics.
Novel algorithms offer improved approaches to protein structure comparison and prediction.