Collaborative Parallel Local Search for Simplified Protein Structure Prediction

Protein structure prediction is a challenging optimisation problem to the computer scientists. A large number of existing single-point search algorithms attempt to solve the problem by exploring possible structures and finding the one with the minimum free energy. However, these algorithms perform poorly on large sized proteins due to an astronomically wide search space. In this paper, we present a multi-point local search framework that uses parallel processing techniques to expedite exploration by starting from different points. In our approach, a set of random initial solutions are generated and distributed to different threads. We allow each thread to run for a pre-defined period of time. The improved solutions are stored thread-wise. When the threads finish, the solutions are merged together and the duplicates are removed. A selected distinct set of solutions are then split to different threads again. We tested our approach on large sized proteins for simplified models. The experimental results show that our new parallel framework significantly improves over the results obtained by the state-of-the-art single-point search approaches for the hydrophobic-polar energy model and the three dimensional face-centred-cubic lattice.

[1]  David Baker,et al.  Protein Structure Prediction Using Rosetta , 2004, Numerical Computer Methods, Part D.

[2]  Kathleen Steinhöfel,et al.  A hybrid approach to protein folding problem integrating constraint programming with local search , 2010, BMC Bioinformatics.

[3]  Abdul Sattar,et al.  Random-walk: a stagnation recovery technique for simplified protein structure prediction , 2012, BCB '12.

[4]  Andrew Lewis,et al.  DFS-generated pathways in GA crossover for protein structure prediction , 2010, Neurocomputing.

[5]  Abdul Sattar,et al.  A New Genetic Algorithm for Simplified Protein Structure Prediction , 2012, Australasian Conference on Artificial Intelligence.

[6]  Sitao Wu,et al.  Ab Initio Protein Structure Prediction , 2009 .

[7]  R Samudrala,et al.  Ab initio construction of protein tertiary structures using a hierarchical approach. , 2000, Journal of molecular biology.

[8]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[9]  Frank Thomson Leighton,et al.  Protein folding in the hydrophobic-hydrophilic (HP) is NP-complete , 1998, RECOMB '98.

[10]  Daniel J. Rigden,et al.  From Protein Structure to Function with Bioinformatics , 2009 .

[11]  Richard Bonneau,et al.  Ab initio protein structure prediction of CASP III targets using ROSETTA , 1999, Proteins.

[12]  El-Ghazali Talbi,et al.  A grid-based genetic algorithm combined with an adaptive simulated annealing for protein structure prediction , 2008, Soft Comput..

[13]  Federico Fogolari,et al.  Amino acid empirical contact energy definitions for fold recognition in the space of contact maps , 2003, BMC Bioinformatics.

[14]  Adam Smith.  Protein misfolding , 2003, Nature.

[15]  Holger H. Hoos,et al.  A replica exchange Monte Carlo algorithm for protein folding in the HP model , 2007, BMC Bioinformatics.

[16]  Pascal Van Hentenryck,et al.  Protein Structure Prediction on the Face Centered Cubic Lattice by Local Search , 2008, AAAI.

[17]  Sue Whitesides,et al.  A complete and effective move set for simplified protein folding , 2003, RECOMB '03.

[18]  Abdul Sattar,et al.  Protein folding prediction in 3D FCC HP lattice model using genetic algorithm , 2007, 2007 IEEE Congress on Evolutionary Computation.

[19]  Ron Unger,et al.  On the applicability of genetic algorithms to protein folding , 1993, [1993] Proceedings of the Twenty-sixth Hawaii International Conference on System Sciences.

[20]  Hans-Joachim Böckenhauer,et al.  A Local Move Set for Protein Folding in Triangular Lattice Models , 2008, WABI.

[21]  Erik D. Goodman,et al.  A Standard GA Approach to Native Protein Conformation Prediction , 1995 .

[22]  T. Hales.  The Kepler conjecture , 1998, math/9811078.

[23]  Yang Zhang,et al.  The protein structure prediction problem could be solved using the current PDB library. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[24]  Abdul Sattar,et al.  Spiral search: a hydrophobic-core directed local search for simplified PSP on 3D FCC lattice , 2013, BMC Bioinformatics.

[25]  Kathleen Steinhöfel,et al.  Protein Folding Simulation by Two-Stage Optimization , 2009 .

[26]  D. Eisenberg,et al.  A method to identify protein sequences that fold into a known three-dimensional structure. , 1991, Science.

[27]  C. Levinthal.  Are there pathways for protein folding , 1968 .

[28]  A. Sali,et al.  Protein Structure Prediction and Structural Genomics , 2001, Science.

[29]  Pascal Van Hentenryck,et al.  On Lattice Protein Structure Prediction Revisited , 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[30]  Fred W. Glover,et al.  Tabu Search - Part I , 1989, INFORMS J. Comput..

[31]  Joe Marks,et al.  Human-guided tabu search , 2002, AAAI/IAAI.

[32]  M. Stefani,et al.  Protein Folding and Misfolding on Surfaces , 2008, International journal of molecular sciences.

[33]  Abdul Sattar,et al.  Memory-based local search for simplified protein structure prediction , 2012, BCB.

[34]  C. Anfinsen.  Principles that govern the folding of protein chains. , 1973, Science.

[35]  Songde Ma,et al.  Protein folding simulations of the hydrophobic–hydrophilic model by combining tabu search with genetic algorithms , 2003 .

[36]  Yue,et al.  Sequence-structure relationships in proteins and copolymers. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[37]  Charles Seife,et al.  What Is the Universe Made Of? , 2005, Science.

[38]  Richard Bonneau,et al.  Ab initio protein structure prediction: progress and prospects. , 2001, Annual review of biophysics and biomolecular structure.

[39]  Andrew Lewis,et al.  Twin Removal in Genetic Algorithms for Protein Structure Prediction Using Low-Resolution Model , 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[40]  Christian Blum,et al.  Ant colony optimization: Introduction and recent trends , 2005 .

[41]  Ron Unger,et al.  Genetic Algorithm for 3D Protein Folding Simulations , 1993, ICGA.

[42]  Vincenzo Cutello,et al.  An Immune Algorithm for Protein Structure Prediction on Lattice Models , 2007, IEEE Transactions on Evolutionary Computation.

[43]  K. Dill,et al.  A lattice statistical mechanics model of the conformational and sequence spaces of proteins , 1989 .

[44]  So Much More to Know … , 2005, Science.