title: 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 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 EdaRosecis able to provide predictions with lower C αRMSD to the native structure than EdaRoseenand 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.
authors.affiliation: INRA MIAT, UR 875, Castanet-Tolosan Cedex, 31326, France.|Structural Bioinformatics Team, Division of Structural and Synthetic Biology, Center for Life Science Technologies, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa, 230-0045, Japan.
authors.forename: David
authors.initials: D
authors.lastname: Simoncini
authors.affiliation: INRA MIAT, UR 875, Castanet-Tolosan Cedex, 31326, France.
authors.forename: Thomas
authors.initials: T
authors.lastname: Schiex
authors.affiliation: Structural Bioinformatics Team, Division of Structural and Synthetic Biology, Center for Life Science Technologies, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa, 230-0045, Japan.
authors.forename: Kam Y J
authors.initials: KY
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D019985:Benchmarking; D016000:Cluster Analysis; D020407:Internet; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D040901:Proteomics / Q000379:methods / Q000706:statistics & numerical data*; D012984:Software; D013816:Thermodynamics
chemical_list: D011506:Proteins
keywords: Edafold; Rosetta; estimation of distribution; protein structure prediction; sampling