Decoys Reveal Multiple Basins of Attraction for Cryo-Electron-Microscopy Flexible Fitting

This study explored the robustness and uniqueness of the flexible fitting of atomic structures against cryo-electron microscopy (cryo-EM) maps using elastic network motion models. The success of flexible fitting is based on the optimistic expectation of a single optimum fit that can be reached from a wide range of start conformations. We revisited this assumption for four AlphaFold models that deviated from corresponding medium-resolution cryo-EM maps but benefitted from flexible fitting. To test the dependence of the flexible fitting performance on the start structures, we systematically generated decoys using normal modes, offering a broader sampling of the conformational space compared to a single start structure. This strategy allowed exploration of the global properties of the cross-correlation (CC) scoring function landscape. Statistical analysis using multidimensional scaling revealed that the initial decoy ensembles collapsed into multiple basins of attraction in three of the four cases. The results demonstrate that a single start structure can be trapped in the local maxima of the CC during flexible fitting (spurious fits), but the decoys increase the likelihood of finding a correct fit. More precisely, there is a "winning" cluster of closely related structures that exhibit high template modeling (TM)-scores with the known true structures. Comparison of the CC and the TM-scores showed that the winning cluster can be identified by high CC values, further demonstrating the utility of cryo-EM maps as filters for screening candidate structures.