The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS-CoV-2 ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. We found that (1) the quality of submitted ligand models and surrounding atoms varied, as judged by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics, and contact scores, and (2) a composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

The use of transgenic mice displaying amyloid-β (Aβ) brain pathology has been essential for the preclinical assessment of new treatment strategies for Alzheimer’s disease. However, the properties of Aβ in such mice have not been systematically compared to Aβ in the brains of patients with Alzheimer’s disease. Here, we determined the structures of nine ex vivo Aβ fibrils from six different mouse models by cryogenic-electron microscopy. We found novel Aβ fibril structures in the APP/PS1, ARTE10 and tg-SwDI models, whereas the human type II filament fold was found in the ARTE10, tg-APP Swe and APP23 models. The tg-APP ArcSwe mice showed an Aβ fibril whose structure resembles the human type I filament found in patients with sporadic Alzheimer’s disease. A detailed assessment of the Aβ fibril structure is key to the selection of adequate mouse models for the preclinical development of novel plaque-targeting therapeutics and positron emission tomography imaging tracers in Alzheimer’s disease.

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density.

Heart contraction depends on a complicated array of interactions between sarcomeric proteins required to convert chemical energy into mechanical force. Cyclic interactions between actin and myosin molecules, controlled by troponin and tropomyosin, generate the sliding force between the actin-based thin and myosin-based thick filaments. Alterations in this sophisticated system due to missense mutations can lead to cardiovascular diseases. Numerous structural studies proposed pathological mechanisms of missense mutations at the myosin-myosin, actin-tropomyosin, and tropomyosin-troponin interfaces. However, despite the central role of actomyosin interactions a detailed structural description of the cardiac actomyosin interface remained unknown. Here, we report a cryo-EM structure of a cardiac actomyosin complex at 3.8 A resolution. The structure reveals the molecular basis of cardiac diseases caused by missense mutations in myosin and actin proteins.

A critical role of the hormone islet amyloid polypeptide (IAPP) is vividly discussed for Type 2 Diabetes (T2D), where amyloid deposits in pancreatic islets consisting of fibrillar IAPP have been associated with beta cell loss. Here, we applied cryo-electron microscopy to elucidate the structure of IAPP fibrils prepared at physiological pH and reconstructed densities of three dominant polymorphs. An atomic model of the main polymorph comprising residues 13 – 37 in a density map of 4.2 Å resolution reveals two S-shaped, intertwined protofilaments. The segment 21-NNFGAIL-27, which is essential for IAPP amyloidogenicity, forms the protofilament interface together with tyrosine 37 and the amidated C-terminus. The main IAPP fibril polymorph resembles polymorphs of the Alzheimer disease (AD)-associated amyloid-β peptide (Aβ), which is striking in light of the epidemiological link between T2D and AD and reports on IAPP-Aβ cross-seeding in vivo . The results structurally link the early-onset T2D IAPP genetic polymorphism S20G with the early-onset AD Arctic mutation E22G of Aβ, rationalize previous data on IAPP fibrils, help to elucidate mechanisms of amyloid formation and toxicity, and support the design of fibril growth inhibitors as well as imaging probes for early detection of IAPP fibrils.

This paper describes outcomes of the 2019 Cryo-EM Map-based Model Metrics Challenge sponsored by EMDataResource ( www.emdataresource.org ). The goals of this challenge were (1) to assess the quality of models that can be produced using current modeling software, (2) to check the reproducibility of modeling results from different software developers and users, and (3) compare the performance of current metrics used for evaluation of models. The focus was on near-atomic resolution maps with an innovative twist: three of four target maps formed a resolution series (1.8 to 3.1 Å) from the same specimen and imaging experiment. Tools developed in previous challenges were expanded for managing, visualizing and analyzing the 63 submitted coordinate models, and several novel metrics were introduced. The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual laboratory experiments and holdings of structure data archives such as the Protein Data Bank. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived from these benchmark maps by 13 participating teams, representing both widely used and novel modeling approaches. We also evaluate the pros and cons of the commonly used metrics to assess model quality and recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed density in the cryo-EM map.