T1 Minimum Population Search, an Application to Molecular Docking
A1 Bolufé-Röhler, Antonio
A1 Coto-Santiesteban, Alex
A1 Soto, Marta Rosa
A1 Chen, Stephen
K1 Minimum Population Search
K1 Molecular Docking
K1 Heuristic Algorithms
K1 Optimization
K1 Multi-modality
AB 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.
PB Universidad Pablo de Olavide
SN 2255-5684
YR 2014
FD 2014
LK http://hdl.handle.net/10433/2778
UL http://hdl.handle.net/10433/2778
LA en
NO GECONTEC: Revista Internacional de Gestión del Conocimiento y la Tecnología
DS RIO
RD May 9, 2026