Acta Crystallographica. Section D, Structural Biology最新文献

{"title":"CryoLike: a Python package for cryo-electron microscopy image-to-structure likelihood calculations.","authors":"Wai Shing Tang, Jeff Soules, Aaditya Rangan, Pilar Cossio","doi":"10.1107/S2059798325009350","DOIUrl":"10.1107/S2059798325009350","url":null,"abstract":"<p><p>Extracting conformational heterogeneity from cryo-electron microscopy (cryo-EM) images is particularly challenging for flexible biomolecules, where traditional 3D classification approaches often fail. Over the past few decades, advancements in experimental and computational techniques have been made to tackle this challenge, especially Bayesian-based approaches that provide physically interpretable insights into cryo-EM heterogeneity. To reduce the computational cost for Bayesian approaches, and building upon previously developed Fourier-Bessel image-representation methods, we created CryoLike, computationally efficient software for evaluating image-to-structure (or image-to-volume) likelihoods across large image data sets, packaged in a user-friendly Python workflow.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"660-667"},"PeriodicalIF":3.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145547591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydrogen density mapping in biomolecular crystals through dynamic nuclear polarization.","authors":"Khadiza Begam, Zachary Morgan, Dean A A Myles, Jens Glaser","doi":"10.1107/S2059798325009520","DOIUrl":"10.1107/S2059798325009520","url":null,"abstract":"<p><p>Many fundamental biological processes, including those in photosynthetic reaction centers and enzyme active sites, involve charge and energy transfer, bond cleavage, protonation and hydrogen bonding. Because H atoms play such central roles in these reactions, accurately determining their positions is essential. Yet, conventional X-ray crystallography primarily resolves the heavy atoms in biological structures and provides limited insight into hydrogen, even at atomic resolution. Neutron macromolecular crystallography (NMC) overcomes this limitation by offering exceptional sensitivity to hydrogen and deuterium. Here, we present a theoretical framework for the development of dynamic nuclear polarization NMC (DNP-NMC) techniques, which exploit the alignment of neutron and proton nuclear spins to enhance and tune the hydrogen signal contribution. The DNP-NMC approach advances the resolution of H atoms within biomolecular crystals, whether bound to protein residues or present in solvent. The method establishes key relationships for the coherent structure factor of polarized neutron scattering from hydrogenous matter. It theoretically achieves full accuracy in phase reconstruction and offers a path to improve neutron structure determination, achieving accuracies exceeding ≳80% by incorporating titration states. Using a variant of the hybrid input/output phase-retrieval algorithm, it allows recovery of the hydrogen density with ≳90% phase accuracy. We further discuss sources of experimental uncertainty for the upcoming DNP-enabled, quasi-Laue IMAGINE-X experiment at Oak Ridge National Laboratory's High Flux Isotope Reactor.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"758-768"},"PeriodicalIF":3.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145595696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploration of questionable backbone conformations in crystallographic structure models using a structural alphabet.","authors":"Clémence Sarrau, Marine Baillif, Lucas Mantel, Dounia Benyakhlaf, Shamima Peerbux, Leslie Regad","doi":"10.1107/S2059798325009301","DOIUrl":"10.1107/S2059798325009301","url":null,"abstract":"<p><p>More than 80% of protein structure models in the Protein Data Bank have been solved using X-ray crystallography. Despite continuous improvements in this experimental technique, crystallographic structure models may still present artifacts related to the crystallization process as well as errors introduced during model building and refinement, even in high-resolution cases. Such limitations can alter atomic or residue positions, leading to local misconformations, local or domain rearrangements, and occasionally global distortions. In this study, we developed a protocol to locate residues with questionable conformations, where conformations may be uncertain, atypical or influenced by crystallographic modeling and refinement. To do so, we started from a set of 826 nonredundant X-ray protein structure models. Each X-ray model underwent an energy-minimization step that relaxes atomic geometry by reducing potential energy. Residues that exhibited different local conformations between the X-ray and minimized models were therefore considered as having questionable conformations. To identify them, we compared the X-ray and minimized models of each protein using the HMM-SA structural alphabet. Our results revealed that over 18% of the residues in the protein set have questionable conformations in their backbone. These conformations can occur either as isolated events within the protein sequence or can form patterns. Moreover, we observed that the frequency of questionable conformations per X-ray model was independent of factors such as the date of deposition, resolution or crystal system. Analysis of the properties of residues associated with questionable conformations revealed that they do not specifically occur in flexible or accessible regions. However, there is a correlation between questionable conformations and secondary structures, with a particular overrepresentation of residues with questionable conformations in α-helices. We then further investigated questionable conformations in the structure model of ligand-free HIV-2 protease (PR2). By combining our questionable conformation-detection protocol with molecular-dynamics simulation, we demonstrated that approximately half of the questionable conformations in PDB entry 1hsi correspond to local conformations that are sparsely sampled by PR2 during the molecular-dynamics simulation or are structural outliers detected by the wwPDB report. In addition, our results suggested that these questionable conformations may affect the position of the flaps, two β-sheets forming the top of the binding site. In PDB entry 1hsi, their relative arrangement appears atypical compared with MD simulations, raising questions about the biological relevance of this conformation. To conclude, we have developed a protocol to quantify and localize questionable backbone conformations in X-ray structure models, which can affect the interpretation of structural data.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"734-757"},"PeriodicalIF":3.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12809442/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145595656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Xtricorder: a likelihood-enhanced self-rotation function and application to a machine learning-enhanced Matthews prediction of asymmetric unit copy number.","authors":"Airlie J McCoy, Randy J Read","doi":"10.1107/S2059798325009647","DOIUrl":"10.1107/S2059798325009647","url":null,"abstract":"<p><p>Analysis of crystallographic diffraction data after collection and integration but before phasing gives the crystallographer a `first-look' assessment of data quality and flags potential challenges in subsequent structure determination. We here report the development of Xtricorder, a `first-look' application specifically targeted at likelihood-based phasing. Xtricorder incorporates the full array of analyses previously available in the Phaser codebase, with some enhancements and updates, in a more streamlined and accessible implementation. In addition, Xtricorder offers a likelihood-enhanced self-rotation function. A novel graphical representation of the self-rotation function, the `composite-section diagram', presents the results for user inspection and has the added advantage that, in an adapted form, it is appropriate for training a convolutional neural network to enhance the standard Matthews analysis and double the accuracy of asymmetric unit copy-number prediction. We investigate the usefulness of the likelihood-enhanced self-rotation function in `first-look' analyses, exploring the circumstances under which the self-rotation function results are useful, and discuss the application to AI-generated structure prediction.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"678-692"},"PeriodicalIF":3.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12809497/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145601705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Polo-like kinase 1-inhibitor co-complex structures via the surface-entropy reduction approach and a DARPin-assisted approach.","authors":"Uwe Eberspaecher, Arndt A Schmitz, Gerhard Siemeister, Ulf Bömer, Tiago M Bandeiras, Pedro M Matias, Volker K Schulze, Roman C Hillig","doi":"10.1107/S2059798325009325","DOIUrl":"10.1107/S2059798325009325","url":null,"abstract":"<p><p>Polo-like kinase 1 (PLK1) is a major regulator of cell division and has been pursued as a drug target for cancer therapy for a long time. Crystallization of the kinase domain has proven to be exceptionally challenging. Previously, we published a crystallization approach using a PLK1-specific designed ankyrin-repeat protein (DARPin) as a crystallization facilitator. Here, we report an alternative route: crystallization was successful after the introduction of a double mutation which reduced surface entropy and enabled the formation of a new crystal contact. This new PLK1 crystallization system was used to determine the first co-complex crystal structure of the Bayer thiazolidinone lead series, as well as crystal structures with representatives of two competitor inhibitor series. The molecular binding modes of these three inhibitors are analysed and discussed, and the surface-entropy reduction approach is compared with the surface modifications employed by us and others to enable the crystallization of PLK1.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"718-733"},"PeriodicalIF":3.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12809504/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145538570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Completion of partial structures using Patterson maps with the CrysFormer machine-learning model.","authors":"Tom Pan, Evan Dramko, Mitchell D Miller, Anastasios Kyrillidis, George N Phillips","doi":"10.1107/S2059798325009659","DOIUrl":"10.1107/S2059798325009659","url":null,"abstract":"<p><p>Protein structure determination has long been one of the primary challenges of structural biology, to which deep machine learning (ML)-based approaches have increasingly been applied. However, these ML models generally do not directly incorporate the experimental measurements, such as X-ray crystallographic diffraction data. To this end, we explore an approach that more tightly couples these traditional crystallographic and recent ML-based methods by training a hybrid 3D vision transformer and convolutional network on inputs from both domains. We make use of two distinct input constructs: Patterson maps, which are directly obtainable from crystallographic data, and `partial structure' template maps derived from predicted structures deposited in the AlphaFold Protein Structure Database with subsequently omitted residues. With these, we predict electron-density maps that are then post-processed into atomic models through standard crystallographic refinement processes. Introducing an initial data set of small protein fragments taken from Protein Data Bank entries and placing them in hypothetical crystal settings, we demonstrate that our method is effective at both improving the phases of the crystallographic structure factors and completing the regions missing from partial structure templates, as well as improving the agreement of the electron-density maps with the ground-truth atomic structures.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"668-677"},"PeriodicalIF":3.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12809498/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145595633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rescaling FSC curves.","authors":"Alexandre G Urzhumtsev","doi":"10.1107/S2059798325008526","DOIUrl":"10.1107/S2059798325008526","url":null,"abstract":"<p><p>Similarity between two periodic functions is commonly assessed by comparing their Fourier coefficients within resolution shells. In particular, this approach is widely used in both crystallography and cryo-electron microscopy (cryoEM). The definition of these shells, that is the choice of resolution scale for their boundaries, can be guided by the specific goals of the analysis, by the expected features of the studied functions or simply by convention. In cryoEM, shell boundaries are traditionally defined uniformly in inverse resolution. This convention results in a vast imbalance in the number of Fourier coefficients per shell, which may bias statistical comparisons and can make function plots misleading. Constructing resolution shells with approximately equal numbers of Fourier coefficients can be achieved automatically by defining shell boundaries uniformly on the inverse cubic resolution scale. This transformation effectively zooms into the high-resolution region, which is typically the primary focus of analysis. For Fourier shell correlation (FSC) calculations between half-maps, the characteristic sigmoidal curves were observed to transform into profiles that permit piecewise linear interpolation, which may make FSC analysis more robust.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"621-629"},"PeriodicalIF":3.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12576846/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145249268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconstructing biological molecules with help from video gamers.","authors":"Andreas C Petrides, Robbie P Joosten, Firas Khatib, Scott Horowitz","doi":"10.1107/S2059798325008149","DOIUrl":"10.1107/S2059798325008149","url":null,"abstract":"<p><p>Foldit is a citizen science video game in which players tackle a variety of complex biochemistry puzzles. Here, we describe a new series of puzzles in which Foldit players improve the accuracy of models in the public repository of experimental protein structure models, the Protein Data Bank (PDB). Analyzing the results of these puzzles showed that the Foldit players were able to considerably improve the deposited structures. We describe a mechanism by which the efforts of the Foldit players can be fed back into the structural biology scientific record by using Foldit results as improved input for the PDB-REDO databank. These efforts highlight the continued need for the engagement of the lay population in science.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"598-604"},"PeriodicalIF":3.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12576847/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145249280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Off-target structural insights: ArnA and AcrB in bacterial membrane-protein cryo-EM analysis.","authors":"Mehmet Caliseki, Ufuk Borucu, Sathish K N Yadav, Christiane Schaffitzel, Burak Veli Kabasakal","doi":"10.1107/S2059798325007089","DOIUrl":"10.1107/S2059798325007089","url":null,"abstract":"<p><p>Membrane-protein quality control in Escherichia coli involves coordinated actions of the AAA+ protease FtsH, the insertase YidC and the regulatory complex HflKC. These systems maintain proteostasis by facilitating membrane-protein insertion, folding and degradation. To gain structural insights into a putative complex formed by FtsH and YidC, we performed single-particle cryogenic electron microscopy on detergent-solubilized membrane samples, from which FtsH and YidC were purified using Ni-NTA affinity and size-exclusion chromatography. Although SDS-PAGE analysis indicated high purity of these proteins, cryo-EM data sets unexpectedly yielded high-resolution structures of ArnA and AcrB at 4.0 and 2.9 Å resolution, respectively. ArnA is a bifunctional enzyme involved in lipid A modification and polymyxin resistance, while AcrB is a multidrug efflux transporter of the AcrAB-TolC system. ArnA and AcrB, known Ni-NTA purification contaminants, were also consistently detected by mass spectrometry in Strep-Tactin affinity-purified samples, validating their presence independently of affinity-tag selection. ArnA, which is typically cytoplasmic, was consistently found in membrane-isolated samples, indicating an association with membrane components. Only 2D class averages corresponding to the cytoplasmic AAA+ domain of FtsH were observed; neither side views of full-length FtsH nor densities corresponding to an intact FtsH-YidC complex could be identified, due to the conformational flexibility of the FtsH complex and its transient interaction with YidC, which limited particle alignment and stable classification in cryo-EM data sets. Two-dimensional class averages revealed additional particles resembling GroEL and cytochrome bo₃ oxidase. These results underscore the utility of cryo-EM in uncovering off-target yet structurally well defined complexes, which may reflect physiologically relevant interactions or purification biases during membrane-protein overexpression.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"545-557"},"PeriodicalIF":3.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485490/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145028756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of helical symmetry parameters in the EMDB.","authors":"Daoyi Li, María Muñoz Pérez, Xiaoqi Zhang, Jiaqing Li, Wen Jiang","doi":"10.1107/S2059798325007260","DOIUrl":"10.1107/S2059798325007260","url":null,"abstract":"<p><p>Helical symmetry is a structural feature of many biological assemblies, including cytoskeletons, viruses and pathological amyloid fibrils. The helical parameters twist and rise are unique metadata for helical structures. With the increasing number of helical structures being resolved through cryo-EM and deposited in the EMDB, there is a growing possibility of errors in the metadata associated with these entries. During our cryo-EM analysis of protein amyloids and the development of helical analysis tools, we realized that many deposited helical parameters appear to be inconsistent with the associated density maps. Here, we have developed a comprehensive validation process that examines the consistency of these parameters by combining high-throughput computational evaluation with manual verification. Multiple errors were identified and corrected for ∼14% of the total entries, including missing parameters, swapped twist and rise values, incorrect sign of twist angles, partial symmetries and bona fide errors. Our validation code, workflow and the validated parameters are publicly available.</p>","PeriodicalId":7116,"journal":{"name":"Acta Crystallographica. Section D, Structural Biology","volume":" ","pages":"527-534"},"PeriodicalIF":3.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485488/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144991244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}