Cryo-EM combined with image deconvolution to determine ZIF-8 crystal structure

Metal–organic frameworks(MOFs) are crystalline porous materials with tunable properties, exhibiting great potential in gas adsorption, separation and catalysis.[1,2]It is challenging to visualize MOFs with transmission electron microscopy(TEM) due to their inherent instability under electron beam irradiation. Here, we employ cryo-electron microscopy(cryoEM) to capture images of MOF ZIF-8, revealing inverted-space structural information at a resolution of up to about 1.7A and enhancing its critical electron dose to around 20 e^(-)/A^(2). In addition, it is confirmed by electron-beam irradiation experiments that the high voltage could effectively mitigate the radiolysis, and the structure of ZIF-8 is more stable along the [100] direction under electron beam irradiation. Meanwhile, since the high-resolution electron microscope images are modulated by contrast transfer function(CTF) and it is difficult to determine the positions corresponding to the atomic columns directly from the images. We employ image deconvolution to eliminate the impact of CTF and obtain the structural images of ZIF-8. As a result, the heavy atom Zn and the organic imidazole ring within the organic framework can be distinguished from structural images.

Applications and prospects of cryo-EM in drug discovery

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 mediumresolution 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.

Cryo-EM Data Statistics and Theoretical Analysis of KaiC Hexamer

Cryo-electron microscopy(cryo-EM) provides a powerful tool to resolve the structure of biological macromolecules in natural state. One advantage of cryo-EM technology is that different conformation states of a protein complex structure can be simultaneously built, and the distribution of different states can be measured. This provides a tool to push cryo-EM technology beyond just to resolve protein structures, but to obtain the thermodynamic properties of protein machines. Here, we used a deep manifold learning framework to get the conformational landscape of Kai C proteins, and further obtained the thermodynamic properties of this central oscillator component in the circadian clock by means of statistical physics.

A Noise Extraction Method for Cryo-EM Single-Particle Denoising

Cryo-Electron Microscopy(cryo-EM)has become a powerful method to study the structure and function of biological macromolecules.However,in clustering tasks based on the projection angle of particles in cryoEM,the noise considerably affects the clustering results.Existing denoising algorithms are ineffective due to the extremely low signal-to-noise ratio(SNR)of cryo-EM images and the complexity of noise types.The noise of a single particle greatly influences the orientation estimation of the subsequent clustering task,and the result of the clustering task directly affects the accuracy of the 3D reconstruction.In this paper,we propose a construction method of cryo-EM denoising dataset that uses U-Net to extract noise blocks from cryoEM images,superimpose the noise block with the projected pure particles to construct our simulated dataset.Then we adopt a supervised generative adversarial network(GAN)with perceptual loss to train on our simulated dataset and denoise the real cryo-EM single particle.The method can solve the problem of poor denoising performance caused by assuming that the noise of the Gaussian distribution does not conform to the noise distribution of cryo-EM,and it can retain the useful information of particles to a great extent.We compared traditional image filtering methods and the classic deep learning denoising algorithm DnCNN on the simulated and real datasets.Experiment results show that the method based on deep learning has more advantages than traditional image denoising methods.It is worth mentioning that our method achieves a competitive peak signal to noise ratio(PSNR)and structural similarity(SSIM).Moreover,visualization results,indicate that our method can retain the structure information and orientation information of particles to a greater extent compared with other state-of-the-art image denoising methods.It means that our denoising task can provide considerable help for subsequent cryo-EM clustering tasks.

Research on Denoising of Cryo-em Images Based on Deep Learning

Cryo-em(Cryogenic electron microscopy)is a technology this can build bio-macromolecule of three-dimensional structure.Under the condition of now,the projection image of the biological macromolecule which is collected by the Cryo-em technology that the contrast is low,the signal to noise is low,image blurring,and not easy to distinguish single particle from background,the corresponding processing technology is lagging behind.Therefore,make Cryo-em image denoising useful,and maintaining bio-macromolecule of contour or signal of function-construct improve Cryo-em image quality or resolution of Cryo-em three-dimensional structure have important effect.This paper researched a denoising function base on GANs(generative adversarial networks),purpose an improved discriminant model base on Wasserstein distance and an improved image denoising model by add gray constraint.Our model turn discriminant model’s training process from binary classification’s training process into regression task training process,it make GANs in training process more stable,more reasonable parameter passing.Meantime,we also propose an improved generative model by add gray constraint.The experimental results show that our model can increase the peak signal-to-noise ratio of the Cryo-em simulation image by 10.3 dB and improve SSIM(Structural Similarity Index)of the denoised image results by 0.43.Compared with traditional image denoising algorithms such as BM3D(Block Matching 3D),our model can better save the model structure and the vein signal in the original image and the operation speed is faster.

Subtraction of liposome signals in cryo-EM structural determination of protein-liposome complexes

Reconstituting membrane proteins in liposomes and determining their structure is a common method for determining membrane protein structures using single-particle cryo-electron microscopy(cryo-EM).However,the strong signal of liposomes under cryo-EM imaging conditions often interferes with the structural determination of the embedded membrane proteins.Here,we propose a liposome signal subtraction method based on single-particle two-dimensional(2D)classification average images,aimed at enhancing the reconstruction resolution of membrane proteins.We analyzed the signal distribution characteristics of liposomes and proteins within the 2D classification average images of protein–liposome complexes in the frequency domain.Based on this analysis,we designed a method to subtract the liposome signals from the original particle images.After the subtraction,the accuracy of single-particle three-dimensional(3D)alignment was improved,enhancing the resolution of the final 3D reconstruction.We demonstrated this method using a PIEZO1-proteoliposome dataset by improving the resolution of the PIEZO1 protein.

冷冻电镜观察固态锂电池界面

固态锂电池(SSLBs)有望兼顾高能量密度和高安全性,是未来电池领域的重要发展方向。固态电解质(SSE)与电极材料之间存在界面阻抗大、相容性差等问题,严重地制约着它的发展。然而,由于辐照敏感特性,难以直接采用常规透射电子显微镜(TEM)观察界面结构。冷冻电镜(Cryo⁃EM)可以有效地缓解辐照损伤,提供更准确、真实的结构信息,有助于深入理解界面微观结构与SSLBs电化学性能之间的构效关系。本文综述了Cryo⁃EM用于观测SSLBs界面的晶体结构和化学组成,揭示了界面形成和演化机制以及SSLBs的失效机制。最后展望了Cryo⁃EM在表征SSLBs界面所面临的挑战和未来的研究方向。Cryo⁃EM在SSLBs界面研究中发挥越来越重要的作用,逐渐成为推动高性能SSLBs发展的必备技术。

岩土材料中冰分布状态的冷冻电镜表征方法

为从微观角度定量描述冰在岩土材料中的分布特征,基于冷冻电镜技术提出了一种微观尺度的实验表征方法。针对不同冰饱和度人造岩芯样品的二次电子图像和能谱分析图,通过元素含量分布、升华前后图像对比确认了冰在岩土材料中的分布状态。随着冰饱和度的增加,骨架孔隙被冰填充、骨架颗粒表面被冰包裹区域增大,样品断面更密实平整,岩土骨架的堆积结构特征变弱。在背散射电子图像中,冰的图像比岩土骨架亮度低、灰度高,基于此构建了冰饱和度的数字图像计算方法。该方法计算的升华前冰饱和度与样品预制冰饱和度偏差小于5%,验证了其可靠性。

Emerging structures and dynamic mechanisms ofγ-secretase for Alzheimer’s disease

γ-Secretase,called“the proteasome of the membrane,”is a membrane-embedded protease complex that cleaves 150+peptide substrates with central roles in biology and medicine,including amyloid precursor protein and the Notch family of cell-surface receptors.Mutations inγ-secretase and amyloid precursor protein lead to early-onset familial Alzheimer’s disease.γ-Secretase has thus served as a critical drug target for treating familial Alzheimer’s disease and the more common late-onset Alzheimer’s disease as well.However,critical gaps remain in understanding the mechanisms of processive proteolysis of substrates,the effects of familial Alzheimer’s disease mutations,and allosteric modulation of substrate cleavage byγ-secretase.In this review,we focus on recent studies of structural dynamic mechanisms ofγ-secretase.Different mechanisms,including the“Fit-Stay-Trim,”“Sliding-Unwinding,”and“Tilting-Unwinding,”have been proposed for substrate proteolysis of amyloid precursor protein byγ-secretase based on all-atom molecular dynamics simulations.While an incorrect registry of the Notch1 substrate was identified in the cryo-electron microscopy structure of Notch1-boundγ-secretase,molecular dynamics simulations on a resolved model of Notch1-boundγ-secretase that was reconstructed using the amyloid precursor protein-boundγ-secretase as a template successfully capturedγ-secretase activation for proper cleavages of both wildtype and mutant Notch,being consistent with biochemical experimental findings.The approach could be potentially applied to decipher the processing mechanisms of various substrates byγ-secretase.In addition,controversy over the effects of familial Alzheimer’s disease mutations,particularly the issue of whether they stabilize or destabilizeγ-secretase-substrate complexes,is discussed.Finally,an outlook is provided for future studies ofγ-secretase,including pathways of substrate binding and product release,effects of modulators on familial Alzheimer’s disease mutations of theγ-secretase-substrate complexes.Comprehensive understanding of the functional mechanisms ofγ-secretase will greatly facilitate the rational design of effective drug molecules for treating familial Alzheimer’s disease and perhaps Alzheimer’s disease in general.

SARS⁃CoV⁃2免疫逃逸NTD中和抗体的分子机制

针对严重急性呼吸综合征冠状病毒2(Severe acute respiratory syndrome coronavirus 2,SARS-CoV-2)中和抗体的开发,主要针对SARS-CoV-2表面的刺突(Spike,S)蛋白。大多数中和SARS-CoV-2的单克隆抗体(MAbs)可结合S蛋白的受体结合结构域(receptor-binding domain,RBD),从而阻断病毒与血管紧张素转化酶2(Angiotensin-converting enzyme 2,ACE2)的相互作用。作者早期通过SARS-CoV-2原型株S蛋白免疫小鼠,筛选得到S2G4,S2H5,S4D4,S5B84株与S蛋白氮末端结构域(N-terminal domain,NTD)不同表位结合的单克隆抗体,其中S2H5活病毒中和能力最强。本研究利用冷冻电镜技术解析了S2H5的抗原结合片段(Fab)结合SARS-CoV-2原型株S蛋白复合体的结构,共获得六种构象,其中S2H5 Fab结合在S蛋白的NTD上,结构模拟完整S2H5抗体结合S蛋白可以空间上阻碍S蛋白与ACE2相互作用,揭示了S2H5中和SARS-CoV-2原型株的结构基础。此外,作者应用假病毒中和实验,分析了上述四种抗体对SARS-CoV-2多种突变株的中和能力,显示了其突变株对NTD抗体的免疫逃逸,并从结构生物学角度对各突变株表现出的免疫逃逸提供了可能的解释。

Cryo-EM structures reveal the dynamic transformation of human alpha-2-macroglobulin working as a protease inhibitor

Human alpha-2-macroglobulin is a well-known inhibitor of a broad spectrum of proteases and plays important roles in immunity,inflammation,and infections.Here,we report the cryo-EM structures of human alpha-2-macroglobulin in its native state,induced state transformed by its authentic substrate,human trypsin,and serial intermediate states between the native and fully induced states.These structures exhibit distinct conformations,which reveal the dynamic transformation of alpha-2-macroglobulin that acts as a protease inhibitor.The results shed light on the molecular mechanism of alpha-2-macroglobulin in entrapping substrates.

8 Å structure of the outer rings of the Xenopus laevis nuclear pore complex obtained by cryo-EM and AI

The nuclear pore complex(NPC),one of the largest protein complexes in eukaryotes,serves as a physical gate to regulate nucleocytoplasmic transport.Here,we determined the 8Åresolution cryo-electron microscopic(cryo-EM)structure of the outer rings containing nuclear ring(NR)and cytoplasmic ring(CR)from the Xenopus laevis NPC,with local resolutions reaching 4.9Å.With the aid of AlphaFold2,we managed to build a pseudoatomic model of the outer rings,including the Y complexes and flanking components.In this most comprehensive and accurate model of outer rings to date,the almost complete Y complex structure exhibits much tighter interaction in the hub region.In addition to two copies of Y complexes,each asymmetric subunit in CR contains five copies of Nup358,two copies of the Nup214 complex,two copies of Nup205 and one copy of newly identified Nup93,while that in NR contains one copy of Nup205,one copy of ELYS and one copy of Nup93.These in-depth structural features represent a great advance in understanding the assembly of NPCs.

I型组蛋白去乙酰化酶复合物结构生物学研究进展

I型组蛋白去乙酰化酶复合物是从酵母到人所有真核生物中都保守的依赖于锌离子的组蛋白修饰酶。酿酒酵母Rpd3S和裂殖酵母来源同系物Clr6S包含多个亚基,可以被甲基化修饰的组蛋白H3第36位赖氨酸招募到相关核小体位点,随后对组蛋白H3和H4上的乙酰化修饰位点进行去除,以防止隐匿转录的发生。文章总结了近期关于I型组蛋白去乙酰化酶复合物结构生物学及生化方面的研究进展,对I型组蛋白去乙酰化酶复合物识别核小体底物并对其乙酰化位点进行特异性去除的分子机制进行了讨论。

Cryo-EM structure of L-fucokinase/GDP-fucose pyrophosphorylase(FKP)in Bacteroides fragilis

Dear Editor,L-Fucose(6-deoxy-L-galactose,fucose)is the basic compone nt of a variety of glyca n structures.The fucosylated oligosaccharides participate in a variety of cellular activities,like the cell-cell recognition,selectin-mediated leukocyteendothelial adhesion and the formation of Lewis blood group antigens(Ma et al.,2006).GDP-fucose is an important fucose donor in the process of fucosylated oligosaccharides formation.Two pathways of GDP-fucose synthesis are present in the cytosol of mammalian cells,including the de novo pathway and the salvage pathway(Becker et al.,2003).In the salvage pathway,cells use fucose from the extracellular or lysosomal sources to synthesize GDP-fucose.

Cryo-EM Studies of Virus-Antibody Immune Complexes

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.

Cryo-EM structure of an early precursor of large ribosomal subunit reveals a half-assembled intermediate

Assembly of eukaryotic ribosome is a complicated and dynamic process that involves a series of intermediates.It is unknown how the highly intertwined structure of 60S large ribosomal subunits is established.Here,we report the structure of an early nucleolar pre-60S ribosome determined by cryo-electron microscopy at 3.7 A resolution,revealing a half-assembled subunit.DomainsⅠ,ⅡandⅣof 25S/5.8S rRNA pack tightly into a native-like substructure,but domains Ⅲ,ⅣandⅤare not assembled.The structure contains 12 assembly factors and 19 ribosomal proteins,many of which are required for early processing of large subunit rRNA.The Brx1-Ebp2 complex would interfere with the assembly of domains Ⅳ and Ⅴ.Rpf1,Mak16,Nsa1 and Rrp1 form a cluster that consolidates the joining of domainsⅠandⅡ.Our structure reveals a key intermediate on the path to establishing the global architecture of 60S subunits.

Cryo-EM snapshots of mycobacterial arabinosyltransferase complex EmbB2-AcpM2

Inhibition of Mycobacterium tuberculosis(Mtb)cell wall assembly is an established strategy for anti-TB chemotherapy.Arabinosyltransferase EmbB,which catalyzes the transfer of arabinose from the donor decaprenyl-phosphate-arabinose(DPA)to its arabinosyl acceptor is an essential enzyme for Mtb cell wall synthesis.Analysis of drug resistance mutations suggests that EmbB is the main target of the front-line anti-TB drug,ethambutol.Herein,we report the cryo-EM structures of Mycobacterium smegmatis EmbB in its"resting state"and DPA-bound"active state".EmbB is a fifteen-transmembrane-spanning protein,assembled as a dimer.Each protomer has an associated acyl-carrier-protein(AcpM)on their cytoplasmic surface.Confor-mational changes upon DPA binding indicate an asym-metric movement within the EmbB dimer during catalysis.Functional studies have identified critical residues in substrate recognition and catalysis,and demonstrated that ethambutol inhibits transferase activity of EmbB by competing with DPA.The structures represent the first step directed towards a rational approach for anti-TB drug discovery.

Accelerating the cryo-EM structure determination in RELION on GPU cluster

The cryo-electron microscopy(cryo-EM)is one of the most powerful technologies available today for structural biology.The RELION(Regularized Likelihood Optimization)implements a Bayesian algorithm for cryo-EM structure determination,which is one of the most widely used software in this field.Many researchers have devoted effort to improve the performance of RELION to satisfy the analysis for the ever-increasing volume of datasets.In this paper,we focus on performance analysis of the most time-consuming computation steps in RELION and identify their performance bottlenecks for specific optimizations.We propose several performance optimization strategies to improve the overall performance of RELION,including optimization of expectation step,parallelization of maximization step,accelerating the computation of symmetries,and memory affinity optimization.The experiment results show that our proposed optimizations achieve significant speedups of RELION across representative datasets.In addition,we perform roofline model analysis to understand the effectiveness of our optimizations.

Cryo-EM structure of a tetrameric photosystem I from Chroococcidiopsis TS-821, a thermophilic, unicellular, non-heterocyst-forming cyanobacterium

Photosystem I(PSI)is one of two photosystems involved in oxygenic photosynthesis.PSI of cyanobacteria exists in monomeric,trimeric,and tetrameric forms,in contrast to the strictly monomeric form of PSI in plants and algae.The tetrameric organization raises questions about its structural,physiological,and evolutionary significance.Here we report the3.72 A˚resolution cryo-electron microscopy structure of tetrameric PSI from the thermophilic,unicellular cyanobacterium Chroococcidiopsis sp.TS-821.The structure resolves 44 subunits and 448 cofactor molecules.We conclude that the tetramer is arranged via two different interfaces resulting from a dimer-of-dimers organization.The localization of chlorophyll molecules permits an excitation energy pathway within and between adjacent monomers.Bioinformatics analysis reveals conserved regions in the PsaL subunit that correlate with the oligomeric state.Tetrameric PSI may function as a key evolutionary step between the trimeric and monomeric forms of PSI organization in photosynthetic organisms.

Cryo-EM structure of the plant 26S proteasome

Targeted proteolysis is a hallmark of life.It is especially important in long-lived cells that can be found in higher eukaryotes,like plants.This task is mainly fulfilled by the ubiquitin–proteasome system.Thus,proteolysis by the 26S proteasome is vital to development,immunity,and cell division.Although the yeast and animal proteasomes are well characterized,there is only limited information on the plant proteasome.We determined the first plant 26S proteasome structure from Spinacia oleracea by single-particle electron cryogenic microscopy at an overall resolution of 3.3 A°.We found an almost identical overall architecture of the spinach proteasome compared with the known structures from mammals and yeast.Nevertheless,we noticed a structural difference in the proteolytic active b1 subunit.Furthermore,we uncovered an unseen compression state by characterizing the proteasome’s conformational landscape.We suspect that this new conformation of the 20S core protease,in correlation with a partial opening of the unoccupied gate,may contribute to peptide release after proteolysis.Our data provide a structural basis for the plant proteasome,which is crucial for further studies.