Gpathfinder: Identification of ligand-binding pathways by a multi-objective genetic algorithm

José Emilio Sánchez-Aparicio, Giuseppe Sciortino, Daniel Viladrich Herrmannsdoerfer, Pablo Orenes Chueca, Jaime Rodríguez Guerra Pedregal, Jean Didier Maréchal

Research output: Contribution to journalArticleResearch

3 Citations (Scopus)


Protein-ligand docking is a widely used method to generate solutions for the binding of a small molecule with its target in a short amount of time. However, these methods provide identification of physically sound protein-ligand complexes without a complete view of the binding process dynamics, which has been recognized to be a major discriminant in binding affinity and ligand selectivity. In this paper, a novel piece of open-source software to approach this problem is presented, called GPathFinder. It is built as an extension of the modular GaudiMM platform and is able to simulate ligand diffusion pathways at atomistic level. The method has been benchmarked on a set of 20 systems whose ligand-binding routes were studied by other computational tools or suggested from experimental “snapshots”. In all of this set, GPathFinder identifies those channels that were already reported in the literature. Interestingly, the low-energy pathways in some cases indicate novel possible binding routes. To show the usefulness of GPathFinder, the analysis of three case systems is reported. We believe that GPathFinder is a software solution with a good balance between accuracy and computational cost, and represents a step forward in extending protein-ligand docking capacities, with implications in several fields such as drug or enzyme design.
Original languageEnglish
Article number3155
Number of pages18
JournalInternational Journal of Molecular Sciences
Issue number13
Publication statusPublished - 1 Jul 2019


  • Computational chemistry
  • Drug design
  • Ligand diffusion
  • Molecular docking
  • Molecular modeling
  • Multi-objective genetic algorithm


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