Publication:
Minimum Population Search, an Application to Molecular Docking

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

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Universidad Pablo de Olavide
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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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GECONTEC: Revista Internacional de Gestión del Conocimiento y la Tecnología

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