Coto-Santiesteban, A., et al. “Minimum Population Search, an Application to Molecular Docking”. GECONTEC: Revista Internacional de Gestión del Conocimiento Y la Tecnología, vol. 2, no. 3, 2014, pp. 1-16, https://scholar2.islandarchives.ca/islandora/object/ir%3A24797.

Genre

  • Journal Article
Contributors
Author: Coto-Santiesteban, A.
Author: Bolufé-Röhler, A.
Author: Rosa-Soto, M
Author: Chen, S.
Date Issued
2014
Abstract

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.

Language

  • English
Page range
1-16
Host Title
GECONTEC: Revista Internacional de Gestión del Conocimiento y la Tecnología
Volume
2
Issue
3
ISSN
2255-5684