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Generating, Maintaining, and Exploiting Diversity in a Memetic Algorithm for Protein Structure Prediction.

Mario Garza-Fabre1, Shaun M Kandathil2, Julia Handl3

  • 1Decision and Cognitive Sciences Research Centre, University of Manchester, Manchester, M15 6PB, UK mario.garza-fabre@manchester.ac.uk.

Evolutionary Computation
|February 25, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a novel memetic algorithm to improve protein tertiary structure prediction for large proteins. The enhanced algorithm overcomes limitations in fold diversity and energy function deception, leading to more accurate predictions.

Keywords:
Fragment assemblyMemetic algorithms.Protein structure prediction

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Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Protein folding

Background:

  • De novo protein tertiary structure prediction methods, particularly fragment-assembly, struggle with larger proteins (>100 residues).
  • Key challenges include limited exploration of diverse protein folds and deceptive energy functions where low energy does not guarantee native structure.

Purpose of the Study:

  • To address the scaling limitations and deceptive energy functions in protein structure prediction.
  • To improve the diversity of explored protein folds and the accuracy of predicting native structures.

Main Methods:

  • Development of a multistage memetic algorithm.
  • Integration of the Rosetta method as a local search routine.
  • Implementation of specialized genetic operators for enhanced structural diversity.
  • Application of a generalized stochastic ranking procedure for selection to navigate deceptive energy wells.

Main Results:

  • Specialized genetic operators significantly increased structural diversity, aiding in reaching lower energy states.
  • The stochastic ranking procedure effectively handled deceptive energy wells, improving fold diversity.
  • The algorithm demonstrated an improved ability to obtain a diverse range of protein folds.

Conclusions:

  • The developed memetic algorithm offers a tangible improvement for protein structure prediction algorithms.
  • This approach enhances the ability to predict the three-dimensional structures of larger proteins.
  • The findings have implications for improving performance in challenges like CASP and advancing protein structure prediction.