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Curr Med Chem. 2011;18(9):1339-52.

Bio-inspired algorithms applied to molecular docking simulations.

Author information

1
Faculdade de Biociências, Laboratório de Bioquímica Estrutural, Programa de Pós-Graduação em Biologia Celular e Molecular, Instituto Nacional de Ciência e Tecnologia em Tuberculose-Pontifícia Universidade Católica do Rio Grande do Sul, CEP 90619-900, Porto Alegre - RS, Brazil.

Abstract

Nature as a source of inspiration has been shown to have a great beneficial impact on the development of new computational methodologies. In this scenario, analyses of the interactions between a protein target and a ligand can be simulated by biologically inspired algorithms (BIAs). These algorithms mimic biological systems to create new paradigms for computation, such as neural networks, evolutionary computing, and swarm intelligence. This review provides a description of the main concepts behind BIAs applied to molecular docking simulations. Special attention is devoted to evolutionary algorithms, guided-directed evolutionary algorithms, and Lamarckian genetic algorithms. Recent applications of these methodologies to protein targets identified in the Mycobacterium tuberculosis genome are described.

PMID:
21366530
[Indexed for MEDLINE]

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