Soft Computing Techniques for the Protein Folding Problem on High Performance Computing Architectures

Title:Soft Computing Techniques for the Protein Folding Problem on High Performance Computing Architectures

Volume: 17 Issue: 14

Author(s): Antonio Llanes, Andrés Muñoz, Andrés Bueno-Crespo, Teresa García-Valverde, Antonia Sánchez, Francisco Arcas-Túnez, Horacio Pérez-Sánchez and José M. Cecilia

Affiliation:

Keywords: Soft computing, protein folding problem, protein structure prediction, parallel computing, distributed computing, metaheuristics, high performance computing.

Abstract: The protein-folding problem has been extensively studied during the last fifty years. The understanding of the dynamics of global shape of a protein and the influence on its biological function can help us to discover new and more effective drugs to deal with diseases of pharmacological relevance. Different computational approaches have been developed by different researchers in order to foresee the threedimensional arrangement of atoms of proteins from their sequences. However, the computational complexity of this problem makes mandatory the search for new models, novel algorithmic strategies and hardware platforms that provide solutions in a reasonable time frame. We present in this revision work the past and last tendencies regarding protein folding simulations from both perspectives; hardware and software. Of particular interest to us are both the use of inexact solutions to this computationally hard problem as well as which hardware platforms have been used for running this kind of Soft Computing techniques.

Cite this article as:

Llanes Antonio, Muñoz Andrés, Bueno-Crespo Andrés, García-Valverde Teresa, Sánchez Antonia, Arcas-Túnez Francisco, Pérez-Sánchez Horacio and Cecilia M. José, Soft Computing Techniques for the Protein Folding Problem on High Performance Computing Architectures, Current Drug Targets 2016; 17 (14) . https://dx.doi.org/10.2174/1389450117666160201114028