The frequency-dependent signal to noise ratio of cryo-electron microscopy data varies dramatically with the frequency and with the type of the data. During different steps of data processing, data with distinct SNR are used for calculations. Thus, specific weighting function based on the particular SNR should be designed to optimize the corresponding calculation. Here, we deduced these weighting functions by maximizing the signal to noise ratio of cross correlated coefficients. Some of our weighting functions for refinement resemble that used in the existing software packages. However, weighting functions we deduced for motion correction, particle picking and the refinement with overlapping densities differ from those employed by existing programs. Our new weighting functions may improve the calculation in these steps.

Drug discovery is a crucial part of human healthcare and has dramatically benefited human lifespan and life quality in recent centuries, however, it is usually time- and effort-consuming. Structural biology has been demonstrated as a powerful tool to accelerate drug development. Among different techniques, cryo-electron microscopy (cryo-EM) is emerging as the mainstream of structure determination of biomacromolecules in the past decade and has received increasing attention from the pharmaceutical industry. Although cryo-EM still has limitations in resolution, speed and throughput, a growing number of innovative drugs are being developed with the help of cryo-EM. Here, we aim to provide an overview of how cryo-EM techniques are applied to facilitate drug discovery. The development and typical workflow of cryo-EM technique will be briefly introduced, followed by its specific applications in structure-based drug design, fragment-based drug discovery, proteolysis targeting chimeras, antibody drug development and drug repurposing. Besides cryo-EM, drug discovery innovation usually involves other state-of-the-art techniques such as artificial intelligence (AI), which is increasingly active in diverse areas. The combination of cryo-EM and AI provides an opportunity to minimize limitations of cryo-EM such as automation, throughput and interpretation of medium-resolution maps, and tends to be the new direction of future development of cryo-EM. The rapid development of cryo-EM will make it as an indispensable part of modern drug discovery.

Amyloid peptide (AP) self-assembly is a hierarchical process. However, the mechanistic rule of guiding peptides to organize well-ordered nanostructure in a clear and precise manner remains poorly understood. Herein we explored the molecular insight of AP motif aggregates underlying hierarchical process with helical fibrillar structure by atomic force microscope, cryo-electron microscopy (cryo-EM), and molecular dynamics simulation. AP assembly encompasses well-ordered twisted fibrils with uniform morphology, size, and periodicity. More importantly, a heterozipper β-sheet was identified in a protofilament of AP assembly determined by cryo-EM with a high resolution of 3.5 Å. Each peptide heterozipper was further composed of two antiparallel β strands and arranged by an alternative manner in a protofilament. The hydrophobic core and hydrophilic area in each zipper played the significant role for peptide assembling. This work proposed and verified the rule facilitating the basic building unit to form twisted fibrils and gave the explanation of peptide hierarchical assembling.

Single-particle cryo-electron microscopy (cryo-EM) has become one of the mainstream technologies in the field of structural biology to determine the three-dimensional (3D) structures of biological macromolecules. Heterogeneous cryo-EM projection image classification is an effective way to discover conformational heterogeneity of biological macromolecules in different functional states. However, due to the low signal-to-noise ratio of the projection images, the classification of heterogeneous cryo-EM projection images is a very challenging task. In this paper, two novel distance measures between projection images integrating the reliability of common lines, pixel intensity and class averages are designed, and then a two-stage spectral clustering algorithm based on the two distance measures is proposed for heterogeneous cryo-EM projection image classification. In the first stage, the novel distance measure integrating common lines and pixel intensities of projection images is used to obtain preliminary classification results through spectral clustering. In the second stage, another novel distance measure integrating the first novel distance measure and class averages generated from each group of projection images is used to obtain the final classification results through spectral clustering. The proposed two-stage spectral clustering algorithm is applied on a simulated and a real cryo-EM dataset for heterogeneous reconstruction. Results show that the two novel distance measures can be used to improve the classification performance of spectral clustering, and using the proposed two-stage spectral clustering algorithm can achieve higher classification and reconstruction accuracy than using RELION and XMIPP.

Cryo-electron microscopy (cryo-EM) has become one of important experimental methods in structure determination. However, despite the rapid growth in the number of deposited cryo-EM maps motivated by advances in microscopy instruments and image processing algorithms, building accurate structure models for cryo-EM maps remains a challenge. Protein secondary structure information, which can be extracted from EM maps, is beneficial for cryo-EM structure modeling. Here, we present a novel secondary structure annotation framework for cryo-EM maps at both intermediate and high resolutions, named EMNUSS. EMNUSS adopts a three-dimensional (3D) nested U-net architecture to assign secondary structures for EM maps. Tested on three diverse datasets including simulated maps, middle resolution experimental maps, and high-resolution experimental maps, EMNUSS demonstrated its accuracy and robustness in identifying the secondary structures for cyro-EM maps of various resolutions. The EMNUSS program is freely available at http://huanglab.phys.hust.edu.cn/EMNUSS.

Antibodies play critical roles in neutralizing viral infections and are increasingly used as therapeutic drugs and diagnostic tools. Structural studies on virus-antibody immune complexes are important for better understanding the molecular mechanisms of antibody-mediated neutralization and also provide valuable information for structure-based vaccine design. Cryo-electron microscopy (cryo-EM) has recently matured as a powerful structural technique for studying bio-macromolecular complexes. When combined with X-ray crystallography, cryo-EM provides a routine approach for structurally characterizing the immune complexes formed between icosahedral viruses and their antibodies. In this review, recent advances in the structural understanding of virus-antibody interactions are outlined for whole virions with icosahedral T = pseudo 3 (picornaviruses) and T = 3 (flaviviruses) architectures, focusing on the dynamic nature of viral shells in different functional states. Glycoprotein complexes from pleomorphic enveloped viruses are also discussed as immune complex antigens. Improving our understanding of viral epitope structures using virus-based platforms would provide a fundamental road map for future vaccine development.

Advanced scanning transmission electron microscopy (STEM) and its associated instruments have made significant contributions to the characterization of all-solid-state (ASS) Li batteries, as these tools provide localized information on the structure, morphology, chemistry, and electronic state of electrodes, electrolytes, and their interfaces at the nano- and atomic scale. Furthermore, the rapid development of in situ techniques has enabled a deep understanding of interfacial dynamic behavior and heterogeneous characteristics during the cycling process. However, due to the beam-sensitive nature of light elements in the interphases, e.g., Li and O, thorough and reliable studies of the interfacial structure and chemistry at an ultrahigh spatial resolution without beam damage is still a formidable challenge. Herein, the following points are discussed: (1) the recent contributions of advanced STEM to the study of ASS Li batteries; (2) current challenges associated with using this method; and (3) potential opportunities for combining cryo-electron microscopy and the STEM phase contrast imaging techniques.

As we know more about Zika virus (ZIKV), as well as its linkage to birth defects (microcephaly) and autoimmune neurological syndromes, we realize the importance of developing an efficient vaccine against it. Zika virus disease has affected many countries and is becoming a major public health concern. To deal with the infection of ZIKV, plenty of experiments have been done on selection of neutralizing antibodies that can target the envelope (E) protein on the surface of the virion. However, the existence of antibody-dependent enhancement (ADE) effect might limit the use of them as therapeutic candidates. In this review, we classify the neutralizing antibodies against ZIKV based on the epitopes and summarize the resolved structural information on antibody/antigen complex from X-ray crystallography and cryo-electron microscopy (cryo-EM), which might be useful for further development of potent neutralizing antibodies and vaccines toward clinical use.

The human Shwachman-Diamond syndrome (SDS) is an autosomal recessive disease caused by mutations in a highly conserved ribosome assembly factor SBDS. The functional role of SBDS is to cooperate with another assembly factor, elongation factor 1-like (Efl1), to promote the release of eukaryotic initiation factor 6 (eIF6) from the late-stage cytoplasmic 60S precursors. In the present work, we characterized, both biochemically and structurally, the interaction between the 60S subunit and SBDS protein (Sdo1p) from yeast. Our data show that Sdo1p interacts tightly with the mature 60S subunit in vitro through its domain I and II, and is capable of bridging two 60S subunits to form a stable 2:2 dimer. Structural analysis indicates that Sdo1p bind to the ribosomal P-site, in the proximity of uL16 and uL5, and with direct contact to H69 and H38. The dynamic nature of Sdo1p on the 60S subunit, together with its strategic binding position, suggests a surveillance role of Sdo1p in monitoring the conformational maturation of the ribosomal P-site. Altogether, our data support a conformational signal-relay cascade during late-stage 60S maturation, involving uL16, Sdo1p, and Efl1p, which interrogates the functional P-site to control the departure of the anti-association factor eIF6.