Open AccessLightDock goes information-driven
Author(s) -
Jorge RoelTouris,
Alexandre M. J. J. Bonvin,
Brian JiménezGarcía
Publication year - 2019
Publication title -
bioinformatics
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btz642
Subject(s) - docking (animal) , computer science , benchmark (surveying) , software , data mining , filter (signal processing) , programming language , medicine , nursing , geodesy , computer vision , geography
The use of experimental information has been demonstrated to increase the success rate of computational macromolecular docking. Many methods use information to post-filter the simulation output while others drive the simulation based on experimental restraints, which can become problematic for more complex scenarios such as multiple binding interfaces.
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