Cryo-EM Map–Based Model Validation Using the False Discovery Rate Approach - Olek, Mateusz; Joseph, Agnel Praveen (Frontiers in Molecular Biosciences, 2021)
Significant technological developments and increasing scientific interest in cryogenic Electron Microscopy (cryo-EM) has resulted in a rapid increase in the amount of data generated by these experiments and the derived atomic models. Robust measures for validation of 3D reconstructions and atomic models are essential for appropriate interpretation of the data. The resolution of data and availability of software tools that work across a range of resolutions, often limit the quality of derived models. Hence, the final atomic model is often incomplete or contains regions where atomic positions are less reliable or incorrectly built. Extensive manual pruning and local adjustments or rebuilding are usually required to address these issues. The presented research introduces a software tool for the validation of the backbone trace of atomic models built in the cryoEM density maps. In this study, we use the False Discovery Rate analysis which can be used to segregate molecular signal from the background. Each atomic position in the model can be associated with a FDR backbone validation score which can be used to identify potential mis-traced residues. We demonstrated that the proposed validation score is complementary to existing validation metrics and is especially useful in the cases where the model is built in the maps which have varying local resolution. We also discuss the application of the score for automated pruning of atomic models built ab-initio during the iterative model building process in Buccaneer. We have implemented our score in the CCP-EM software suite.