Minimum Population Search, an Application to Molecular Docking


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

Palabras clave:

Minimum Population Search, Molecular Docking, Heuristic Algorithms, Optimization, Multi-modality


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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Cómo citar

Bolufé-Röhler, A., Coto-Santiesteban, A., Soto, M. R., & Chen, S. (2014). Minimum Population Search, an Application to Molecular Docking. GECONTEC: Revista Internacional De Gestión Del Conocimiento Y La Tecnología, 2(3), 1–16. Recuperado a partir de