Balancing exploration and exploitation in population‐based sampling improves fragment‐based de novo protein structure prediction

ABSTRACT Conformational search space exploration remains a major bottleneck for protein structure prediction methods. Population‐based meta‐heuristics typically enable the possibility to control the search dynamics and to tune the balance between local energy minimization and search space exploratio...

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Published in:Proteins, structure, function, and bioinformatics structure, function, and bioinformatics, 2017-05, Vol.85 (5), p.852-858
Main Authors: Simoncini, David, Schiex, Thomas, Zhang, Kam Y.J.
Format: Article
Language:English
Subjects:
Algorithms
Benchmarking
Cluster Analysis
Edafold
estimation of distribution
Internet
Life Sciences
Protein Conformation
protein structure prediction
Proteins - chemistry
Proteomics - methods
Proteomics - statistics & numerical data
Rosetta
sampling
Software
Thermodynamics
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Summary:ABSTRACT Conformational search space exploration remains a major bottleneck for protein structure prediction methods. Population‐based meta‐heuristics typically enable the possibility to control the search dynamics and to tune the balance between local energy minimization and search space exploration. EdaFold is a fragment‐based approach that can guide search by periodically updating the probability distribution over the fragment libraries used during model assembly. We implement the EdaFold algorithm as a Rosetta protocol and provide two different probability update policies: a cluster‐based variation (EdaRosec) and an energy‐based one (EdaRoseen). We analyze the search dynamics of our new Rosetta protocols and show that EdaRosec is able to provide predictions with lower C αRMSD to the native structure than EdaRoseen and Rosetta AbInitio Relax protocol. Our software is freely available as a C++ patch for the Rosetta suite and can be downloaded from http://www.riken.jp/zhangiru/software/. Our protocols can easily be extended in order to create alternative probability update policies and generate new search dynamics. Proteins 2017; 85:852–858. © 2016 Wiley Periodicals, Inc.
ISSN:0887-3585
1097-0134
1097-0134
DOI:10.1002/prot.25244