Reconfigurable Hardware Computing for Accelerating Protein Folding Simulations Using the Harmony Search Algorithm and the 3D-HP-Side Chain Model

Proteins are essentials to life and they have countless biological functions. They are synthesized in the ribosome of cells following a template given by the messenger RNA (mRNA). During the synthesis, the protein folds into an unique three-dimensional structure, known as native conformation. This process is called protein folding. Several diseases are believed to be result of the accumulation of ill-formed proteins.Therefore, understanding the folding process can lead to important medical advancements and development of new drugs.

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

[2]  Giovanni Ulivi,et al.  Combinatorial analysis and algorithms for quasispecies reconstruction using next-generation sequencing , 2011, BMC Bioinformatics.

[3]  T. Ramdas,et al.  A Survey of FPGAs for Acceleration of High Performance Computing and their Application to Computational Molecular Biology , 2005, TENCON 2005 - 2005 IEEE Region 10 Conference.

[4]  Heitor Silvério Lopes,et al.  Preliminary Steps Towards Protein Folding Prediction Using Reconfigurable Computing , 2006, 2006 IEEE International Conference on Reconfigurable Computing and FPGA's (ReConFig 2006).

[5]  Heitor Silvério Lopes,et al.  Hierarchical Parallel Genetic Algorithm applied to the three-dimensional HP Side-chain Protein Folding Problem , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[6]  Wen-Tsai Sung.  Efficiency Enhancement of Protein Folding for Complete Molecular Simulation via Hardware Computing , 2009, 2009 Ninth IEEE International Conference on Bioinformatics and BioEngineering.

[7]  Jens Gottlieb,et al.  Evolutionary Computation in Combinatorial Optimization , 2006, Lecture Notes in Computer Science.

[8]  Mai Suan Li,et al.  Folding in lattice models with side chains , 2002, cond-mat/0211348.

[9]  Yong Dou,et al.  FPGA accelerator for protein secondary structure prediction based on the GOR algorithm , 2011, BMC Bioinformatics.

[10]  Aboul Ella Hassanien,et al.  Computational Intelligence in Biomedicine and Bioinformatics, Current Trends and Applications , 2008, Computational Intelligence in Biomedicine and Bioinformatics.

[11]  Yoginder S. Dandass,et al.  Accelerating String Set Matching in FPGA Hardware for Bioinformatics Research , 2008, BMC Bioinformatics.

[12]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[13]  Heitor Silvério Lopes.  Evolutionary Algorithms for the Protein Folding Problem: A Review and Current Trends , 2008, Computational Intelligence in Biomedicine and Bioinformatics.

[14]  Heitor Silvério Lopes,et al.  Self-Adapting Evolutionary Parameters: Encoding Aspects for Combinatorial Optimization Problems , 2005, EvoCOP.

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

[16]  D. Yee,et al.  Principles of protein folding — A perspective from simple exact models , 1995, Protein science : a publication of the Protein Society.