title: Consensus among multiple approaches as a reliability measure for flexible fitting into cryo-EM data.
abstract: Cryo-electron microscopy (cryo-EM) can provide low-resolution density maps of large macromolecular assemblies. As the number of structures deposited in the Protein Data Bank by fitting a high-resolution structure into a low-resolution cryo-EM map is increasing, there is a need to revise the protocols and improve the measures for fitting. A recent study suggested using a combination of multiple automated flexible fitting approaches to improve the interpretation of cryo-EM data. The current work further explores the use of multiple approaches by validating this "consensus" fitting approach and deriving a local reliability measure. Here four different flexible fitting approaches are applied for fitting an initial structure into a simulated density map of known target structure from a dataset of proteins. It is found that the models produced from different approaches often have a consensus in conformation and are also near to the target structure, whereas cases not showing consensus are away from the target. A high correlation is also observed between the RMSF profiles calculated with respect to the average and the target structures, which indicates that the relation between consensus and accuracy can also be extended to a per-residue level. Therefore, the RMSF among the fitted models is proposed as a local reliability measure, which can be used to assess the reliability of the fit at specific regions. Hence, we encourage the community to use consensus flexible fitting with different methods to report on local reliability of the resulting models and improve the interpretation of cryo-EM data.
authors: Department of Chemistry and Biochemistry, The University of Arizona, 1041 E. Lowell Street, Tucson, AZ 85721, USA. ahmedaq@umich.edu
authors: Aqeel
authors: A
authors: Ahmed
authors: Florence
authors: F
authors: Tama
mesh_terms: D020285:Cryoelectron Microscopy / Q000379:methods*; D030562:Databases, Protein; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D046911:Macromolecular Substances / Q000648:ultrastructure*; D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D011487:Protein Conformation
chemical_list: D046911:Macromolecular Substances