Automatic and accurate ligand structure determination guided by cryo-electron microscopy maps

Abstract

Advances in cryo-electron microscopy (cryoEM) and deep-learning guided protein structure prediction have expedited structural studies of protein complexes. However, methods for accurately determining ligand conformations are lacking. In this manuscript, we develop a tool for automatically determining ligand structures guided by medium-resolution cryoEM density. We show this method is robust at predicting ligands in maps as low as 6[A] resolution, and is able to correct receptor sidechain errors. Combining this with a measure of placement confidence, and running on all protein/ligand structures in EMDB, we show that 58% of ligands replicate the deposited model, 16% confidently find alternate conformations, 22% have ambiguous density where multiple conformations might be present, and 4% are incorrectly placed. For five cases where our approach finds an alternate conformation with high confidence, high-resolution crystal structures validate our placement. This tool and the resulting analysis should prove critical in using cryoEM to investigate protein-ligand complexes.