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Título del libro: 2010 Ieee World Congress On Computational Intelligence, Wcci 2010 - 2010 Ieee Congress On Evolutionary Computation, Cec 2010
Título del capítulo: Estimation of 3D Protein Structure by means of parallel Particle Swarm Optimization

Autores UNAM:
LUIS GERMAN PEREZ HERNANDEZ; KATYA RODRIGUEZ VAZQUEZ; RAMON GARDUÑO JUAREZ;
Autores externos:

Idioma:
Inglés
Año de publicación:
2010
Palabras clave:

3D Structure; Computational time; Distributed computing environment; Empirical functions; Minimum energy; Parallel particle swarm optimization; Processor communications; Protein 3-D structure; Protein conformation; Protein folding problem; Protein structures; Running-in; Side-chains; Structural restrictions; Torsion angle; Artificial intelligence; Program processors; Protein folding; Proteins; Three dimensional; Particle swarm optimization (PSO)


Resumen:

This paper presents the Algorithm of Particle Swarm Optimization (PSO) implemented in a Distributed Computing Environment. The main objective of this PSO is to calculate the Protein 3D Structure reducing the computational time to carry out this task; this problem is also known as Protein Folding Problem (PFP). The parallel PSO works on a real conformation, considering structural restriction of the protein, where the conformation uses a representation of torsion angles of the skeleton and the side chains, applying the sequence of amino-acid of the protein for the prediction of 3D structure of minimum energy. In order to calculate the energy of the protein conformation, the energy empirical function ECEPP/3 is used. This program was implemented for running in a cluster with the libraries MPI for the processor communication. The quality of the results on the testing peptide (leuenkephalin) is compared with other techniques reported in literature, and also the PSO is used to predict the structure of unknown proteins. © 2010 IEEE.


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