UC San Diego

Rosetta is one of the prime tools for high resolution protein structure refinement. While its scoring function can distinguish native-like from non-native-like conformations 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 conformational 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 refinement protocol. Molecular dynamics is most efficient in applying subtle but important rearrangements within secondary structure elements and is thus highly complementary to the Rosetta refinement, which focuses on side chains and loop regions.