Minimum Population Search, an Application to Molecular Docking

Antonio Bolufé-Röhler; Alex Coto Santiesteban; Marta Rosa Soto; Stephen Chen

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Minimum Population Search, an Application to Molecular Docking

Antonio Bolufé-Röhler ^[1] ; Alex Coto-Santiesteban ^[1] ; Marta Rosa Soto ^[2] ; Stephen Chen ^[3]
1. [1] Universidad de La Habana
  
  Universidad de La Habana
  
  Cuba
2. [2] Instituto de Cibernética Matemática y Física
  
  Instituto de Cibernética Matemática y Física
  
  Cuba
3. [3] York University (Canadá)
  
  York University (Canadá)
  
  Canadá
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Localización: GECONTEC: revista Internacional de Gestión del Conocimiento y la Tecnología, ISSN-e 2255-5684, Vol. 2, Nº. 3, 2014, págs. 1-16
Idioma: inglés
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Resumen
- Computer modeling of protein-ligand interactions is one of the most important phases in a drug design process. Part of the process involves the optimization of highly multi-modal objective (scoring) functions. This research presents the Minimum Population Search heuristic as an alternative for solving these global unconstrained optimization problems. To determine the effectiveness of Minimum Population Search, a comparison with seven state-of-the-art search heuristics is performed. Being specifically designed for the optimization of large scale multi-modal problems, Minimum Population Search achieves excellent results on all of the tested complexes, especially when the amount of available function evaluations is strongly reduced. A first step is also made toward the design of hybrid algorithms based on the exploratory power of Minimum Population Search. Computational results show that hybridization leads to a further improvement in performance.
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