Atomic-accuracy models from 4.5-Å cryo-electron microscopy data with density-guided iterative local refinement

New detector technology has improved the resolution of cryo-electron microscopy (cryo-EM), but tools for structure determination from high-resolution maps have lagged behind. DiMaio et al . report structure determination from high-resolution cryo-EM maps using a homologous structure as a starting model. Also in this issue, Wang et al . describe a de novo approach for structure determination that does not require a starting model. We describe a general approach for refining protein structure models on the basis of cryo-electron microscopy maps with near-atomic resolution. The method integrates Monte Carlo sampling with local density-guided optimization, Rosetta all-atom refinement and real-space B -factor fitting. In tests on experimental maps of three different systems with 4.5-Å resolution or better, the method consistently produced models with atomic-level accuracy largely independently of starting-model quality, and it outperformed the molecular dynamics–based MDFF method. Cross-validated model quality statistics correlated with model accuracy over the three test systems.