Pub Date : 2023-07-07DOI: 10.1107/s2053273323097036
Joseph Davis, Barratt Powell, S. Mosalaganti
Compositional and conformational dynamics are integral to the assembly and function of macromolecular complexes. Fueled by deep learning, new single -particle cryo-EM image analysis tools have revealed these structural dynamics in isolated samples. However, a key goal of structural biology is to interrogate these dynamic structures in their native cellular environment, which would reveal how distinct structural states are partitioned throughout the cell, how they uniquely interact with other cellular components, and how they respond to genetic and environmental perturbations. Cryo-electron tomography (cryo-ET), which has the potential for high -resolution imaging directly in flash - frozen cells, represents a promising path toward achieving this goal. Indeed, modern cryo-ET workflows have revealed molecularly interpretable, sub-nm structures of key complexes, including the ribosome. To date, most cryo - ET processing algorithms aim to increase resolution by relying on expert-guided classification of structures into a discrete set of approximately homogeneous classes. Such discrete classification models scale poorly to highly heterogeneous ensembles and are inherently ill-match to molecules undergoing continuous motion. To analyze such complex structural ensembles in situ, we developed tomoDRGN, which employs a modified variational autoencoder to embed individual particles in a continuous latent space and to reconstruct unique volumes informed by the latent. Here, we describe the tomoDRGN model architecture, which was purpose - built for tomographic datasets; we detail its performance on simulated and exemplar experimental datasets, and we highlight tools built to aid in interpreting tomoDRGN outputs in the context of a cellular tomogram. Additionally, we showcase its application to the process of bacterial ribosome biogenesis - specifically comparing the structural ensembles observed in situ with those observed in isolated samples.
{"title":"TomoDRGN: resolving structural heterogeneity in situ","authors":"Joseph Davis, Barratt Powell, S. Mosalaganti","doi":"10.1107/s2053273323097036","DOIUrl":"https://doi.org/10.1107/s2053273323097036","url":null,"abstract":"Compositional and conformational dynamics are integral to the assembly and function of macromolecular complexes. Fueled by deep learning, new single -particle cryo-EM image analysis tools have revealed these structural dynamics in isolated samples. However, a key goal of structural biology is to interrogate these dynamic structures in their native cellular environment, which would reveal how distinct structural states are partitioned throughout the cell, how they uniquely interact with other cellular components, and how they respond to genetic and environmental perturbations. Cryo-electron tomography (cryo-ET), which has the potential for high -resolution imaging directly in flash - frozen cells, represents a promising path toward achieving this goal. Indeed, modern cryo-ET workflows have revealed molecularly interpretable, sub-nm structures of key complexes, including the ribosome. To date, most cryo - ET processing algorithms aim to increase resolution by relying on expert-guided classification of structures into a discrete set of approximately homogeneous classes. Such discrete classification models scale poorly to highly heterogeneous ensembles and are inherently ill-match to molecules undergoing continuous motion. To analyze such complex structural ensembles in situ, we developed tomoDRGN, which employs a modified variational autoencoder to embed individual particles in a continuous latent space and to reconstruct unique volumes informed by the latent. Here, we describe the tomoDRGN model architecture, which was purpose - built for tomographic datasets; we detail its performance on simulated and exemplar experimental datasets, and we highlight tools built to aid in interpreting tomoDRGN outputs in the context of a cellular tomogram. Additionally, we showcase its application to the process of bacterial ribosome biogenesis - specifically comparing the structural ensembles observed in situ with those observed in isolated samples.","PeriodicalId":6903,"journal":{"name":"Acta Crystallographica Section A Foundations and Advances","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-07DOI: 10.1107/s2053273323097978
Melissa Carrillo, Thomas James Manson, John H Beale, C. Padeste
Serial crystallography at X - ray free electron lasers (XFELs) and synchrotron light sources, called serial femto -second crystallography (SFX) and serial synchrotron crystallography (SSX), respectively, has proved to be a successful and robust methodology for determining the structures of macromolecules at near physiological temperatures and with minimal radiation damage. To cater for these different experiments, a wide variety of delivery methods have been developed [1, 2]. Amongst these, fi xed-targets, based on micro-pattern solid-supports or chips [3] and precise stage-motion [4], have proved to be a strong and dependable approach. Fixed - target sample delivery methods allow for a reduction of sample consumption, rapid optimization of sample loading parameters and are generally easy to use, making them user friendly. Fixed -targets also lend themselves to high throughput technologies and an increased ability to locate and position crystals. Of these currently, only silicon offers the ability to perform an aperture-aligned data collection were crystals are loaded into cavities in precise locations and sequentially rastered through in step with the X -ray pulses [5]. However, the silicon wafers are highly brittle, hugely expensive, prone to fracture and are opaque, making it difficult to know a priori how well crystals have been loaded into the apertures. The polymer based fixed - targets have lacked the precision fabrication to enable this type of data - collection strategy and have been limited to directed raster-scans with crystals randomly distributed across the polymer surface. Here we present a new aperture -aligned polymer-based fixed - target, the Micro - Structured Polymer fixed - targets (MISP-chips) developed for TR - SFX using the SwissMX endstation at the Cristallina experimental station of SwissFEL [Fig. 1]. The MISP-chips, like those made from silicon, have a precise array of cavities and fiducial markers. Using silicon microfabrication and polymer replication technologies, we have designed inverted pyramidal shaped wells in membranes of 50 µm in thickness. This design enables crystals to funnel into predefined positions, optimizing the hit-rate of the probing X -ray beam. The polymer-based fi lm provides low x-ray absorption and scattering background, high design fl exibility and the potential for mass-fabrication at low cost. Here we present the methodology for the manufacture of these fixed -targets and a summary of their use at Cristallina for both standard SFX and time-resolved experiments.
在X射线自由电子激光器（XFEL）和同步辐射光源下进行的串行晶体学研究（分别称为串行飞秒晶体学研究（SFX）和串行同步辐射晶体学研究（SSX））已被证明是在接近生理温度和辐射损伤最小的条件下确定大分子结构的一种成功而稳健的方法。为了满足这些不同实验的需要，人们开发了多种传输方法[1, 2]。其中，基于微图案固体支架或芯片[3]的固定靶和精确的阶段运动[4]已被证明是一种强大而可靠的方法。固定靶样品输送方法可以减少样品消耗，快速优化样品装载参数，而且通常易于使用，对用户非常友好。固定靶还适用于高通量技术，并提高了晶体定位的能力。目前，只有硅能够进行孔径对齐数据采集，即晶体被装入精确定位的空腔中，并与 X 射线脉冲同步依次通过[5]。然而，硅晶片脆性高、价格昂贵、易断裂，而且不透明，因此很难事先知道晶体装入孔中的情况。基于聚合物的固定靶缺乏精确的制造工艺，因此无法采用这种数据收集策略，只能进行定向光栅扫描，晶体随机分布在聚合物表面。在这里，我们介绍一种新的孔径对齐聚合物固定靶，即微结构聚合物固定靶（MISP-chips），它是利用瑞士激光发射台 Cristallina 实验站的 SwissMX 端站为 TR - SFX 开发的[图 1]。MISP 芯片与用硅制成的芯片一样，具有精确的空腔阵列和关键标记。利用硅微加工和聚合物复制技术，我们在厚度为 50 微米的薄膜上设计了倒金字塔形的孔。这种设计使晶体能够漏斗状地进入预设位置，优化了探测 X 射线束的命中率。基于聚合物的薄膜具有低 X 射线吸收和散射背景、高设计灵活性和低成本大规模制造的潜力。在此，我们介绍了制造这些固定靶的方法，并总结了这些靶在克里斯塔利纳用于标准 SFX 和时间分辨实验的情况。
{"title":"Micro-structured polymer fixed targets (MISP-chips) for serial crystallography at synchrotrons and XFELs","authors":"Melissa Carrillo, Thomas James Manson, John H Beale, C. Padeste","doi":"10.1107/s2053273323097978","DOIUrl":"https://doi.org/10.1107/s2053273323097978","url":null,"abstract":"Serial crystallography at X - ray free electron lasers (XFELs) and synchrotron light sources, called serial femto -second crystallography (SFX) and serial synchrotron crystallography (SSX), respectively, has proved to be a successful and robust methodology for determining the structures of macromolecules at near physiological temperatures and with minimal radiation damage. To cater for these different experiments, a wide variety of delivery methods have been developed [1, 2]. Amongst these, fi xed-targets, based on micro-pattern solid-supports or chips [3] and precise stage-motion [4], have proved to be a strong and dependable approach. Fixed - target sample delivery methods allow for a reduction of sample consumption, rapid optimization of sample loading parameters and are generally easy to use, making them user friendly. Fixed -targets also lend themselves to high throughput technologies and an increased ability to locate and position crystals. Of these currently, only silicon offers the ability to perform an aperture-aligned data collection were crystals are loaded into cavities in precise locations and sequentially rastered through in step with the X -ray pulses [5]. However, the silicon wafers are highly brittle, hugely expensive, prone to fracture and are opaque, making it difficult to know a priori how well crystals have been loaded into the apertures. The polymer based fixed - targets have lacked the precision fabrication to enable this type of data - collection strategy and have been limited to directed raster-scans with crystals randomly distributed across the polymer surface. Here we present a new aperture -aligned polymer-based fixed - target, the Micro - Structured Polymer fixed - targets (MISP-chips) developed for TR - SFX using the SwissMX endstation at the Cristallina experimental station of SwissFEL [Fig. 1]. The MISP-chips, like those made from silicon, have a precise array of cavities and fiducial markers. Using silicon microfabrication and polymer replication technologies, we have designed inverted pyramidal shaped wells in membranes of 50 µm in thickness. This design enables crystals to funnel into predefined positions, optimizing the hit-rate of the probing X -ray beam. The polymer-based fi lm provides low x-ray absorption and scattering background, high design fl exibility and the potential for mass-fabrication at low cost. Here we present the methodology for the manufacture of these fixed -targets and a summary of their use at Cristallina for both standard SFX and time-resolved experiments.","PeriodicalId":6903,"journal":{"name":"Acta Crystallographica Section A Foundations and Advances","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, an increasing number of protein and nucleotide structures have been modeled from cryo -electron microscopy (cryo-EM) maps. However, even though the EM map resolution has generally improved steadily over the past years, there are still many situations where modeling errors occur in high-resolution EM maps, or modelers face difficulties in modeling biomolecular structures due to locally low resolution in the map. To address such challenges, we have applied deep learning to three tasks: model quality assessment, protein structure modeling, and DNA/RNA structure modeling in cryo-EM maps. 1: Model Quality Assessment Modeling a protein structure into a cryo-EM map is a challenging task. One of the main difficulties is assigning the correct amino acids to their corresponding positions. Moreover, even with high-quality maps, there is always a risk of human error in the modeling process. To ensure the resulting atomic model is as accurate as possible, it's essential to perform rigorous validation using appropriate methods. To validate protein structure models in cryo-EM maps, our group developed a novel method based on the Deep -learning-based Amino-acid-wise model Quality (DAQ) score. In the DAQ score, the neural network detects specific map features for protein amino acid residue types, Cα atoms, and secondary structures, and computes the likelihood that each residue assignment is correct. By quantifying the incompatibilities between the protein model and the EM map at the amino acid level, the DAQ score provides a more accurate and sensitive measure of model quality compared to other methods [1]. Overall, the DAQ score offers a powerful tool for assessing protein structure models in EM maps and advancing cryo-EM research. The DAQ score can be computed on the Google Colab site (https://bit.ly/daq - score) or local machine by installing the code from ( https://github.com/kiharalab/DAQ). Our group has also recently released the DAQ -Score Database [2] (https
{"title":"Quality assessment and biomolecular structure modeling for cryo-EM using deep learning","authors":"Genki Terashi, Xiao Wang, Tsukasa Nakamura, Devashish Prasad, Daisuke Kihara","doi":"10.1107/s2053273323099473","DOIUrl":"https://doi.org/10.1107/s2053273323099473","url":null,"abstract":"In recent years, an increasing number of protein and nucleotide structures have been modeled from cryo -electron microscopy (cryo-EM) maps. However, even though the EM map resolution has generally improved steadily over the past years, there are still many situations where modeling errors occur in high-resolution EM maps, or modelers face difficulties in modeling biomolecular structures due to locally low resolution in the map. To address such challenges, we have applied deep learning to three tasks: model quality assessment, protein structure modeling, and DNA/RNA structure modeling in cryo-EM maps. 1: Model Quality Assessment Modeling a protein structure into a cryo-EM map is a challenging task. One of the main difficulties is assigning the correct amino acids to their corresponding positions. Moreover, even with high-quality maps, there is always a risk of human error in the modeling process. To ensure the resulting atomic model is as accurate as possible, it's essential to perform rigorous validation using appropriate methods. To validate protein structure models in cryo-EM maps, our group developed a novel method based on the Deep -learning-based Amino-acid-wise model Quality (DAQ) score. In the DAQ score, the neural network detects specific map features for protein amino acid residue types, Cα atoms, and secondary structures, and computes the likelihood that each residue assignment is correct. By quantifying the incompatibilities between the protein model and the EM map at the amino acid level, the DAQ score provides a more accurate and sensitive measure of model quality compared to other methods [1]. Overall, the DAQ score offers a powerful tool for assessing protein structure models in EM maps and advancing cryo-EM research. The DAQ score can be computed on the Google Colab site (https://bit.ly/daq - score) or local machine by installing the code from ( https://github.com/kiharalab/DAQ). Our group has also recently released the DAQ -Score Database [2] (https","PeriodicalId":6903,"journal":{"name":"Acta Crystallographica Section A Foundations and Advances","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-07DOI: 10.1107/s2053273323097607
M. Mazzorana, David Aragao, Neil Paterson, Elliot Nelson, Felicity Bertram, Dave Hall
The MX group at Diamond Light Source offers a suite of seven macromolecular crystallography (MX) beamlines covering a variety of setups and techniques to meet the demands of the user community. This selection of instruments allows access to a wide range of focusing, energy, throughput capabilities as well as numerous approaches including in-situ , serial crystallography, and fragment - based drug discovery.
{"title":"Improving access and throughput of the MX beamlines at Diamond Light Source, UK","authors":"M. Mazzorana, David Aragao, Neil Paterson, Elliot Nelson, Felicity Bertram, Dave Hall","doi":"10.1107/s2053273323097607","DOIUrl":"https://doi.org/10.1107/s2053273323097607","url":null,"abstract":"The MX group at Diamond Light Source offers a suite of seven macromolecular crystallography (MX) beamlines covering a variety of setups and techniques to meet the demands of the user community. This selection of instruments allows access to a wide range of focusing, energy, throughput capabilities as well as numerous approaches including in-situ , serial crystallography, and fragment - based drug discovery.","PeriodicalId":6903,"journal":{"name":"Acta Crystallographica Section A Foundations and Advances","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-07DOI: 10.1107/s2053273323099047
Martina Maritan
Structural biology enables scientists to examine molecular structures in exceptional detail, including at the atomic level. This knowledge of molecular anatomy is crucial for understanding how molecules function and for guiding structure-based drug discovery. Visualizing and manipulating molecular structures is an essential step in this process, and advances in technology are providing increasingly sophisticated methods for doing so. The very process of visual exploration can be a moment for creativity and lead to unexpected ideas. Nanome has developed a platform that utilizes virtual and mixed reality to enable scientists to brainstorm in front of 3D structures and use the platform as a sandbox for visually testing hypotheses. The intuitive interaction with molecules offered by the virtual reality environment makes it a powerful tool for promoting creativity and unlocking unforeseen inspirations. Research groups have used this virtual environment to freely explore structures and molecular designs in real-time, leading to the ideation of completely novel compounds and gaining new structural insights.
{"title":"Virtual reality as a thinking tool for structural investigation","authors":"Martina Maritan","doi":"10.1107/s2053273323099047","DOIUrl":"https://doi.org/10.1107/s2053273323099047","url":null,"abstract":"Structural biology enables scientists to examine molecular structures in exceptional detail, including at the atomic level. This knowledge of molecular anatomy is crucial for understanding how molecules function and for guiding structure-based drug discovery. Visualizing and manipulating molecular structures is an essential step in this process, and advances in technology are providing increasingly sophisticated methods for doing so. The very process of visual exploration can be a moment for creativity and lead to unexpected ideas. Nanome has developed a platform that utilizes virtual and mixed reality to enable scientists to brainstorm in front of 3D structures and use the platform as a sandbox for visually testing hypotheses. The intuitive interaction with molecules offered by the virtual reality environment makes it a powerful tool for promoting creativity and unlocking unforeseen inspirations. Research groups have used this virtual environment to freely explore structures and molecular designs in real-time, leading to the ideation of completely novel compounds and gaining new structural insights.","PeriodicalId":6903,"journal":{"name":"Acta Crystallographica Section A Foundations and Advances","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-07DOI: 10.1107/s2053273323098145
Hideki Shigematsu, Christoph Gerle, Chai Gopalasingam
Since October 2021, we have started public use of CryoTEM as an ancillary facility for structural biology beamlines at SPring-8. We have set up a facility with two CryoTEMs, EM01CT for high -resolution data collection and EM02CT for screening, user training, and general purpose. EM01CT produces high-resolution data in a high-throughput manner for single particle analysis by using a CRYO ARM 300 (JEM - Z300FSC, JEOL) which has a cold - field emission gun, an in-column energy filter, a cryo -supporter system and is coupled with a K3 camera (Gatan). EM02CT is a CRYO ARM 200 (JEM-Z200FSC, JEOL) equipped with a K2 summit camera (Gatan). We provide a training course for all new users of the facility to enable them to have an easy start with structural analysis projects by using our CryoTEMs and continue to provide advice throughout their projects to provide the best possible environment for the successful completion of projects. We have been able to continuously provide productive machine time to the users of SPring-8 resulting in many high-resolution solution structures in the range of 2 ~ 2.5 Å. The first paper was published by one of our users in June 2022[1]. The authors tried to obtain structures of the gastric proton pump with its known inhibitors to understand its inhibitory mechanism by using X -ray crystallography. In this paper, they succeeded in obtaining the crystal structures with three compounds but could not obtain good crystals with another compound. It was crucial to obtain structures with compounds to comp are the interactions between compounds and the protein, therefore they switched to using CryoEM for the complex with the other compound, for which it was difficult to obtain good crystals. This is exactly the situation in which we set up our CryoTEMs as an ancillary facility for structural biology beamlines. In addition to the CryoTEMs
{"title":"Public use cryo-EM at Spring-8","authors":"Hideki Shigematsu, Christoph Gerle, Chai Gopalasingam","doi":"10.1107/s2053273323098145","DOIUrl":"https://doi.org/10.1107/s2053273323098145","url":null,"abstract":"Since October 2021, we have started public use of CryoTEM as an ancillary facility for structural biology beamlines at SPring-8. We have set up a facility with two CryoTEMs, EM01CT for high -resolution data collection and EM02CT for screening, user training, and general purpose. EM01CT produces high-resolution data in a high-throughput manner for single particle analysis by using a CRYO ARM 300 (JEM - Z300FSC, JEOL) which has a cold - field emission gun, an in-column energy filter, a cryo -supporter system and is coupled with a K3 camera (Gatan). EM02CT is a CRYO ARM 200 (JEM-Z200FSC, JEOL) equipped with a K2 summit camera (Gatan). We provide a training course for all new users of the facility to enable them to have an easy start with structural analysis projects by using our CryoTEMs and continue to provide advice throughout their projects to provide the best possible environment for the successful completion of projects. We have been able to continuously provide productive machine time to the users of SPring-8 resulting in many high-resolution solution structures in the range of 2 ~ 2.5 Å. The first paper was published by one of our users in June 2022[1]. The authors tried to obtain structures of the gastric proton pump with its known inhibitors to understand its inhibitory mechanism by using X -ray crystallography. In this paper, they succeeded in obtaining the crystal structures with three compounds but could not obtain good crystals with another compound. It was crucial to obtain structures with compounds to comp are the interactions between compounds and the protein, therefore they switched to using CryoEM for the complex with the other compound, for which it was difficult to obtain good crystals. This is exactly the situation in which we set up our CryoTEMs as an ancillary facility for structural biology beamlines. In addition to the CryoTEMs","PeriodicalId":6903,"journal":{"name":"Acta Crystallographica Section A Foundations and Advances","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-07DOI: 10.1107/s2053273323099126
Robert P. Hayes, Edward DiNunzio, Mahdieh Yazdani, Justyna Sikorska, Yili Chen, S. Tyagarajan, Younghee Park, Amy Lee, Cesar Reyes, Daniel Burschowsky, Matthias Zebisch, Yangsi Ou, Marina Bukhtiyarova, Shahriar Niroomand, Yuan Tian, Shawn J. Stachel, Hua Su, Jacqueline D. Hicks, Daniel F. Wyss
,
,
{"title":"Fragment-based screening approach reveals non-orthosteric pockets in the search for allosteric inhibitors of tau-tubulin kinase 1","authors":"Robert P. Hayes, Edward DiNunzio, Mahdieh Yazdani, Justyna Sikorska, Yili Chen, S. Tyagarajan, Younghee Park, Amy Lee, Cesar Reyes, Daniel Burschowsky, Matthias Zebisch, Yangsi Ou, Marina Bukhtiyarova, Shahriar Niroomand, Yuan Tian, Shawn J. Stachel, Hua Su, Jacqueline D. Hicks, Daniel F. Wyss","doi":"10.1107/s2053273323099126","DOIUrl":"https://doi.org/10.1107/s2053273323099126","url":null,"abstract":",","PeriodicalId":6903,"journal":{"name":"Acta Crystallographica Section A Foundations and Advances","volume":"88 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-07DOI: 10.1107/s2053273323099576
Kristin M. Hutchins
{"title":"The dynamic side of crystals: how structure influences function in the solid state","authors":"Kristin M. Hutchins","doi":"10.1107/s2053273323099576","DOIUrl":"https://doi.org/10.1107/s2053273323099576","url":null,"abstract":"","PeriodicalId":6903,"journal":{"name":"Acta Crystallographica Section A Foundations and Advances","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-07DOI: 10.1107/s205327332309664x
Sujeong Byun, Sangkee Rhee
{"title":"Structure studies of IMP-specific phosphatase ISN1 from Saccharomyces cerevisiae","authors":"Sujeong Byun, Sangkee Rhee","doi":"10.1107/s205327332309664x","DOIUrl":"https://doi.org/10.1107/s205327332309664x","url":null,"abstract":"","PeriodicalId":6903,"journal":{"name":"Acta Crystallographica Section A Foundations and Advances","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-07DOI: 10.1107/s2053273323097875
Shi Feng, Cody Aplin, Thuy-Tien T. Nguyen, R. Cerione
{"title":"Filament formation drives catalysis of glutaminase","authors":"Shi Feng, Cody Aplin, Thuy-Tien T. Nguyen, R. Cerione","doi":"10.1107/s2053273323097875","DOIUrl":"https://doi.org/10.1107/s2053273323097875","url":null,"abstract":"","PeriodicalId":6903,"journal":{"name":"Acta Crystallographica Section A Foundations and Advances","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：