key: cord-0860885-79ye2zm4 authors: Yan, Renhong; Zhang, Yuanyuan; Li, Yaning; Ye, Fangfei; Guo, Yingying; Xia, Lu; Zhong, Xinyue; Chi, Ximin; Zhou, Qiang title: Structural basis for the different states of the spike protein of SARS-CoV-2 in complex with ACE2 date: 2021-03-18 journal: Cell Res DOI: 10.1038/s41422-021-00490-0 sha: 463160367b48c9193f63f15ba3d97153fd06e983 doc_id: 860885 cord_uid: 79ye2zm4 nan nominal magnification of 81,000×. Each stack was exposed for 2.56 s with an exposure time of 0.08 s per frame, resulting in a total of 32 frames per stack. The total dose rate was approximately 50 e -/Å 2 for each stack. The stacks were motion corrected with MotionCor2 4 and binned 2-fold, resulting in a pixel size of 1.087 Å/pixel. Meanwhile, dose weighting was performed 5 . The defocus values were estimated with Gctf 6 . Cryo-EM data was processed similarly for all S-related samples. Particles were automatically picked using Relion 3.0.6 7-10 from manually selected micrographs. After 2D classification with Relion, good particles were selected and subject to one cycle of heterogeneous refinement without symmetry using cryoSPARC 11 .The good particles were selected and subject to homogeneous refinement with C1 symmetry, resulting in the 3D reconstruction for the whole structures. The map quality of overall structure was improved by 3D refinement with Relion. Then, these particles were subject to 3D classification, 3D refinement and post-processing to catch the different conformations. For the S-ACE2-B 0 AT1 complex, the methods for particle picking and 2D classification are same to that for the S protein, but the box size is 480 pixel. The good particles selected from 2D classification were subject to multiple heterogeneous refinement without symmetry using cryoSPARC, the last run of which resulted in two good classes. They were subject to non-uniform refinement (Legacy) without symmetry resulting in two conformations for the S-ACE2-B 0 AT1 ternary complex. To further improve the map quality, the particles which contributed to the above two conformations, were reextracted at the location of recognizable S protein and ACE2 and subjected to nonuniform refinement (Legacy) as the processing of the whole structure. The resolution was estimated with the gold-standard Fourier sFhell correlation 0.143 criterion 12 with high-resolution noise substitution 13 . Refer to Supplemental information, Fig. S1 , S2, S3, S4, S10, S11, S12, S13 and Table S1 for details of data collection and processing. Model building of the S protein of SARS-CoV-2 and PD of ACE2 were performed by molecular dynamics flexible fitting (MDFF) 14 of the published structure (PDB ID: 7C2L) and (PDB ID: 6M18) for majority. And the other parts were performed in the cryo-EM map with Phenix 15 and Coot 16 based on the focused-refined cryo-EM maps of all models with aromatic residues as landmarks, most of which were clearly visible in the cryo-EM map. Each residue was manually checked with the chemical properties taken into consideration during model building. Several segments, whose corresponding densities were invisible, were not modeled. Structural refinement was performed in Phenix with secondary structure and geometry restraints to prevent overfitting. To monitor the potential overfitting, the model was refined against one of the two independent half maps from the gold-standard 3D refinement approach. Then, the refined model was tested against the other map. Statistics associated with data collection, 3D reconstruction and model building were summarized in Supplemental information, Table S1 . A neutralizing human antibody binds to the N-terminal domain of the Spike protein of SARS-CoV-2 Structural basis for the recognition of SARS-CoV-2 by full-length human ACE2 Automated acquisition of cryo-electron micrographs for single particle reconstruction on an FEI Tecnai electron microscope MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy Measuring the optimal exposure for single particle cryo-EM using a 2.6 A reconstruction of rotavirus VP6 Real-time CTF determination and correction New tools for automated high-resolution cryo-EM structure determination in RELION-3 Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2 RELION: implementation of a Bayesian approach to cryo-EM structure determination A Bayesian view on cryo-EM structure determination cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy High-resolution noise substitution to measure overfitting and validate resolution in 3D structure determination by single particle electron cryomicroscopy Flexible fitting of atomic structures into electron microscopy maps using molecular dynamics PHENIX: a comprehensive Python-based system for macromolecular structure solution