Abstract
Producing an accurate atomic model of biomolecule-ligand interactions from maps generated by cryoelectron microscopy (cryo-EM) often presents challenges inherent to the methodology and the dynamic nature of ligand binding. Here, we present GemSpot, an automated pipeline of computational chemistry methods that take into account EM map potentials, quantum mechanics energy calculations, and water molecule site prediction to generate candidate poses and provide a measure of the degree of confidence. The pipeline is validated through several published cryo-EM structures of complexes in different resolution ranges and various types of ligands. In all cases, at least one identified pose produced both excellent interactions with the target and agreement with the map. GemSpot will be valuable for the robust identification of ligand poses and drug discovery efforts through cryo-EM.
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