Iterative Molecular DynamicsRosetta Protein Structure Refinement Protocol to Improve Model Quality

ABSTRACT: Rosetta is one of the prime tools for high resolution protein structure refinement. While its scoring func-tion can distinguish native-like from non-native-like conforma-tions in many cases, the method is limited by conformational sampling for larger proteins, that is, leaving a local energy minimum in which the search algorithm may get stuck. Here, we test the hypothesis that iteration of Rosetta with an orthogonal sampling and scoring strategy might facilitate exploration of conformational space. Specifically, we run short molecular dynamics (MD) simulations on models created by de novo folding of large proteins into cryoEM density maps to enable sampling of conformational space not directly accessible to Rosetta and thus provide an escape route from the conforma-tional traps. We present a combined MD−Rosetta protein structure refinement protocol that can overcome some of these sampling limitations. Two of four benchmark proteins showed incremental improvement through all three rounds of the iterative refinemen