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Prediction of protein–ligand binding poses is an essential component for understanding protein–ligand interactions and computer‐aided drug design. Various proteins involve prosthetic groups such as heme for their functions, and adequate consideration of the prosthetic groups is vital for protein–ligand docking. Here, we extend the GalaxyDock2 protein–ligand docking algorithm to handle ligand docking to heme proteins. Docking to heme proteins involves increased complexity because the interaction of heme iron and ligand has covalent nature. GalaxyDock2‐HEME, a new protein–ligand docking program for heme proteins, has been developed based on GalaxyDock2 by adding an orientation‐dependent scoring term to describe heme iron‐ligand coordination interaction. This new docking program performs better than other noncommercial docking programs such as EADock with MMBP, AutoDock Vina, PLANTS, LeDock, and GalaxyDock2 on a heme protein–ligand docking benchmark set in which ligands are known to bind iron. In addition, docking results on two other sets of heme protein–ligand complexes in which ligands do not bind iron show that GalaxyDock2‐HEME does not have a high bias toward iron binding compared to other docking programs. This implies that the new docking program can distinguish iron binders from noniron binders for heme proteins. [ABSTRACT FROM AUTHOR]

Predicting conformational changes of both the protein and the ligand is a major challenge when a protein–ligand complex structure is predicted from the unbound protein and ligand structures. Herein, we introduce a new protein–ligand docking program called GalaxyDock3 that considers the full ligand conformational flexibility by explicitly sampling the ligand ring conformation and allowing the relaxation of the full ligand degrees of freedom, including bond angles and lengths. This method is based on the previous version (GalaxyDock2) which performs the global optimization of a designed score function. Ligand ring conformation is sampled from a ring conformation library constructed from structure databases. The GalaxyDock3 score function was trained with an additional bonded energy term for the ligand on a large set of complex structures. The performance of GalaxyDock3 was improved compared to GalaxyDock2 when predicted ligand conformation was used as the input for docking, especially when the input ligand conformation differs significantly from the crystal conformation. GalaxyDock3 also compared favorably with other available docking programs on two benchmark tests that contained diverse ligand rings. The program is freely available at http://galaxy.seoklab.org/softwares/galaxydock.html. © 2019 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]