New Journal publication: Bio-inspired optimization for the molecular docking problem: State of the art, recent results and perspectives

Javier Del Ser, coordinator and member of the Joint Research Lab, has authored the paper “Bio-inspired optimization for the molecular docking problem: State of the art, recent results and perspectives”, a joint work with collaborators from the University of Malaga (Spain) that has been published in the Applied Soft Computing journal (Q1 JCR). The paper can be retrieved at:

Summary: Molecular docking is a Bioinformatics method based on predicting the position and orientation of a small molecule or ligand when it is bound to a target macromolecule. This method can be modeled as an optimization problem where one or more objectives can be defined, typically around an energy scoring function. This paper reviews developments in the field of single- and multi-objective meta-heuristics for efficiently addressing molecular docking optimization problems. We comprehensively analyze both problem formulations and applied techniques from Evolutionary Computation and Swarm Intelligence, jointly referred to as Bio-inspired Optimization. Our prospective analysis is supported by an experimental study dealing with a molecular docking problem driven by three conflicting objectives, which is tackled by using different multi-objective heuristics. We conclude that genetic algorithms are the most widely used techniques by far, with a noted increasing prevalence of particle swarm optimization in the last years, being these last techniques particularly adequate when dealing with multi-objective formulations of molecular docking problems. We end this experimental survey by outlining future research paths that should be under target in this vibrant area.


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