Acta Crystallographica Section D Structural Biology

Cryogenic electron microscopy (cryoEM) is now routinely used for high-resolution structure determination of biological macromolecules. However, many biological specimens exhibit varying degrees of preferred orientation on cryoEM grids, resulting in uneven sampling of three-dimensional Fourier space. This orientation bias produces anisotropic reconstruction artifacts and, in severe cases, can exacerbate particle misalignment during iterative refinement, thereby limiting the success rate of near-atomic resolution cryoEM structure determination. This protocol provides a practical guide for applying spIsoNet, a self-supervised deep-learning method, to mitigate preferred-orientation issues in cryoEM reconstructions. We describe two complementary workflows: (1) map Anisotropy Correction to correct anisotropic artifacts of cryoEM maps and (2) particle Misalignment Correction, which integrates spIsoNet with RELION external reconstruction to improve particle-pose estimation. We demonstrate these workflows using two influenza hemagglutinin (HA) trimer datasets representing moderate and severe degrees of preferred-orientation bias. The protocol includes installation instructions, parameter-selection guidance, quality-control checkpoints and troubleshooting advice, and can typically be completed in ~7 hours on a workstation equipped with four NVIDIA A100 GPUs. Together, these workflows provide step-by-step guidance for using the open-source spIsoNet software to mitigate the preferred-orientation problem directly from experimental data.

Cryogenic-electron microscopy (cryo-EM) has revolutionized the field of protein structural biology. The structures of large membrane proteins are now routinely determined by cryo-EM to near atomic resolution. However, in the medium resolution range of cryo-EM maps (>[~]2 [A]), negatively charged sidechains of acidic residues are not well-resolved due to the negative electrostatic potential of the region. This may lead to incorrect sidechain models for residues like glutamic acid or aspartic acid that are central for proton transfer activity in various respiratory and photosynthetic enzymes. We previously proposed that the acidic residues with weak or non-existent cryo-EM density can be modeled to represent their low proton affinity conformations. Here, we tested this hypothesis on a larger data set of acidic amino acid residues in two high-resolution respiratory complex I structures. By using faster sidechain modeling and proton affinity prediction tools, we created a workflow that generates sidechain conformations of selected amino acid residues. We validated the sidechain conformation predictions by Q-score analysis and atomistic molecular dynamics simulations in different charged states. The proposed workflow provides a way to rapidly obtain sidechain conformations of acidic residues with weak cryo-EM densities and can be integrated into the existing cryo-EM modeling pipelines to speed up sidechain rotamer prediction.

In single particle cryo-EM, analysis of continuous conformational heterogeneity has always been challenging. Both linear and deep learning-based methods treat conformational heterogeneity as perturbations to the consensus average conformation, limiting their capability in analyzing large protein motions. While classic conformational classifications are capable of handling large domain motion, they bin continuous protein dynamics into discrete static substates. Here, we present cryoROLE, a computational tool that extracts the continuous conformational dynamics embedded in the static composite map constructed from multi-body refinement into a landscape of relative orientation between the moving domains. Depicted in real space, the landscape allows intuitive interpretations of domain motion and the population of poses in the conformational space. Applying it to various biological systems reveals hidden conformational dynamics that are relevant to protein functions.

Bovine ephemeral fever virus (BEFV), a member of the Rhabdoviridae family, is an arthropod-borne pathogen that causes acute febrile disease in cattle. The structural basis of its genome encapsidation and virion assembly remains unexplored, with the current knowledge largely limited to predictions derived from bioinformatic comparisons with other rhabdoviruses. Furthermore, the structural principles that permit the formation of variable-diameter nucleocapsids resulting in the distinctive bullet-shaped morphology of rhabdoviruses remain poorly understood. Here, we report the cryo-electron microscopy structure of the BEFV nucleoprotein (N) in complex with RNA, in the absence of other viral components. The complex predominantly forms circular decameric oligomers that we propose to act as nucleation intermediates during assembly of the bullet-shaped nucleocapsids. Direct subunit interactions are limited to a small polar surface area, with additional intersubunit links mediated by flexible N- and C-terminal loops. These interfaces generate a structurally plastic oligomeric lattice in which neighbouring N subunits can undergo substantial rigid-body rotations and positional rearrangements while preserving conserved local contacts and continuous RNA encapsidation. Such quasi-equivalent interactions provide a plausible mechanism for accommodating the progressive changes in helical diameter required for the transition from the highly curved bullet tip to the wider cylindrical trunk of rhabdovirus nucleocapsids. The assembly is stabilised by the bound RNA molecule, where nine RNA bases are accommodated by each N subunit. The RNA-binding mechanism is consistent with that of VSV, the closest BEFV homologue characterised structurally, but differs at about half of the RNA-binding residues, demonstrating the versatility of the nucleoprotein scaffold in interacting with ssRNA. Comparative analysis with other rhabdoviruses, as well as negative-sense RNA viruses with constant-diameter nucleocapsids, such as Ebola, further confirms the structural features that enable bullet-shaped versus cylindrical nucleocapsid assembly.

Four-dimensional scanning transmission electron microscopy (4D-STEM) enables the acquisition of diffraction patterns at every probe position in a dense array. For imaging applications this approach offers significant benefits in terms of spatial resolution and contrast enhancement. In this work, we present the development of a synchronous scan generator integrated with SerialEM software to enable automation of complex experimental protocols such as tomography. The proposed hardware functions as an interface between SerialEM, the scan controls of the microscope, a fast annular dark-field detector, and a synchronized trigger for a pixelated detector. Our previous implementation, named SavvyScan, relied on a dedicated computer equipped with a multichannel acquisition and signal-generation cards, as well as a separate microcontroller for synchronization. Here, we report a low-cost implementation based on a Red Pitaya board, utilizing direct programming of its embedded FPGA and Linux server components. We provide detailed instructions for system installation and operation, along with practical guidance for modifying the source code. System performance is validated through oscilloscope measurements and imaging of a replica grating sample. The utility of the approach is further demonstrated by generating a 3D electron tomogram of a cryogenic sample of mitochondria from a tilt series of shadow montage projections.

Cryo-electron microscopy (cryo-EM) of biological specimens is limited by radiation damage and a low signal-to-noise ratio (SNR). Here, we show that reducing the illuminated area substantially slows the observed diffraction decay in protein microcrystals. We further show that narrow parallel-beam electron diffraction from thin non-crystalline biological specimens provides substantially higher reciprocal-space SNR than conventional cryo-EM imaging. We developed a multimodal scanning workflow, 4D-para-STEM, that records narrow-beam diffraction patterns together with corresponding images. Using viruses, peptide assemblies, and microtubules, we demonstrate interpretable diffraction signals from both crystalline and non-crystalline biological specimens. Together, these results show that narrow parallel-beam scanning reduces observed radiation damage and improves the SNR in cryo-EM.

Thermostable DNA polymerases are indispensable tools in molecular biology, yet enzymes from the most extreme hyperthermophiles remain largely uncharacterized. Here, we report the biochemical and structural characterization of a family B DNA polymerase from Pyrolobus fumarii A1 (Pyrfu pol), one of the most thermoresistant archaea described to date. The enzyme was efficiently overproduced in E. coli Rosetta 2(DE3)[pLysS] and purified to homogeneity using a two-step protocol that combined heat treatment with immobilized metal affinity chromatography (IMAC). Bioinformatic analysis confirmed the canonical family B architecture, while AlphaFold-based structural modeling and comparative analysis with mesophilic RB69 DNA polymerase revealed a well-conserved structural core alongside thermoadaptive features. Radiolabel incorporation assays demonstrated enzymatic activity over a broad ionic strength range and an absolute requirement for Mg ions. PCR-based optimization confirmed these findings and revealed broad pH tolerance (6.5-11.0). Notably, Tris inhibited radiolabel-based assays (pH 7.0) yet proved essential for efficient PCR amplification (pH 8.5), suggesting a context-dependent role of buffer composition in polymerase activity. Processivity assays confirmed amplification of DNA fragments up to approximately 8,000 bp. Replication fidelity, assessed by the lacZ-based assay, showed a 2.9-fold improvement over Taq polymerase. Urea-nanoDSF yielded an exceptional melting temperature of 105.9 {+/-} 0.08 {degrees}C. Pyrfu pol also demonstrated tolerance to common PCR inhibitors, highlighting its potential utility in molecular biology applications.

Human LonP1 is an ATP-dependent mitochondrial protease that degrades damaged or redundant proteins. Indiscriminate proteolysis by LonP1 is limited through tight coordination of substrate recognition, unfolding, translocation and catalytic cleavage, yet the role of ATP hydrolysis in these individual steps remains unclear. Here, we show that LonP1 binds substrates and cleaves peptide bonds without ATP hydrolysis, whereas degradation of folded proteins strictly depends on ATP-driven unfolding and translocation. Initial substrate binding opens a closed ADP-bound resting state, enabling nucleotide exchange and stimulating ATPase activity. The opening also increases accessibility of the proteolytic chamber, modestly enhancing peptidase activity. Maximal peptidase activity is observed in a transition-state mimic stabilised by ADP{middle dot}AlF, in which substrate is engaged within the translocation channel. Cryo-EM analysis reveals that in this state the proteolytic active sites are no longer occluded, linking ATP-driven substrate translocation to full proteolytic activation. Together, these findings reveal how LonP1 prevents indiscriminate proteolysis during substrate selection by ensuring that efficient proteolysis occurs only in substrate-translocating states. Model of the conformational landscape and functional cycle of LonP1Schematic overview of LonP1 states and their inter-conversion. State transitions are modulated by substrate, nucleotide occupancy, temperature, and inhibitors. Key distinguishing features include the presence or absence of the lateral gap, nucleotide state, substrate engagement within the A-tunnel, and the handedness of the ATPase (A) domains. Additional indicators include the compactness of the proteolytic (P) domain and the presence of substrate density within the N-terminal (N) domain or at the coiled-coil domain (CCD) as well as the position of a loop within the catalytic centre. The depicted cryo-EM structures represent a model of a continuous conformational landscape and correspond to the closest matching biological states and positions within the reaction cycle, but may also capture transient intermediates or conformations stabilised by experimental conditions. The shown atomic models correspond to the states highlighted in larger font (R-state: PDB 7NGL; P1-state: PDB 7NFY; P2-state: PDB 7NGC; closed LonP1-ADP-substrate: PDB 9CC1). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/733973v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@16e0491org.highwire.dtl.DTLVardef@1ee02b1org.highwire.dtl.DTLVardef@f2b47aorg.highwire.dtl.DTLVardef@26f6b2_HPS_FORMAT_FIGEXP M_FIG C_FIG

Microscopes are essential tools for discoveries on a scale invisible to the unaided human eye. The development of immuno-fluorescence followed by molecular biology techniques and fluorescent fusion proteins have revolutionised the use of optical microscopy in bioscience. The quality of the data produced is dependent upon the sample, its preparation and the instrument used. However, instruments can degrade over time without easily visible changes to the produced images and, in turn, negatively impacts results. By testing instruments and doing comparisons between results over time and between different instruments, problems can be highlighted and corrective action can be taken. Using small fluorescent beads the point spread function (PSF) of the microscope can be recorded and the image resolution measured. Beads were prepared in a concentration matched to the field of view size and dried onto coverslips and mounted on slides. The beads were then imaged as 3D Z-stacks of sufficient size to fully enclose the PSF of the system. This data was uploaded to OMERO and processed using OMERO-metrics, an OMERO plugin developed for this purpose. This paper summarizes the development of workflows and protocols to enable this process, presents the results obtained and demonstrates the detection of significant instrument issues.

Chemical imaging is a powerful branch of modern microscopy encumbered by a lack of flexible, high-throughput analysis tools. Bespoke analytical pipelines typically perform ratiometric analysis on two layers in a multispectral image to describe the relative composition of molecules in a sample. This strategy has been implemented across fields, spanning histopathology, cell biology, environmental science, and materials science. The commercialization of chemical imaging microscopes has facilitated the collection of large multispectral datasets, necessitating accessible ways to process them. This paper describes Multispectral Analysis Graphical User Interface (msaGUI), a desktop graphical user interface to analyze individual and batch datasets of multispectral images. Data is loaded as CSV, TSV, or TIFFs and processed through a user-defined sequence of modular image operations that can be flexibly combined, e.g. to reduce spectral crosstalk or background noise. After analysis, data is visualized as exportable images, histograms, and statistics. To yield publication-quality figures, outputted images are fully customizable. Written in Python with open-source libraries, the msaGUI program is packaged into an executable for Windows and Mac for a fully no-code application. Other operating systems are supported via the Python source code. In summary, msaGUI provides a rapid and user-friendly solution for analyzing and visualizing multispectral data.

Small-angle X-ray or neutron scattering (SAXS/SANS) analysis of large unilamellar vesicles (LUVs) is often limited by high-dimensional bilayer models and the lack of dedicated, statistically rigorous workflows. Here, we introduce SAS_MoCa, an open-source Python package that integrates a compositional scattering density profile (SDP) description of lipid bilayers with a separated form factor (SFF) treatment of vesicle size and polydispersity, and couples these highly parameterized models to an adaptive thermodynamic simulated annealing algorithm formulated within a constrained Bayesian framework. SAS_MoCa enables users to incorporate quantitative prior information from, e.g., previous SAXS/SANS studies, dynamic light scattering, NMR, or molecular simulations, and returns full posterior parameter distributions, uncertainties (reported as medians and median absolute deviations) and correlations even from single SAXS curves. Validation on POPC, POPE and DMPC SAXS-only data demonstrates that the method yields reproducible structural parameters with uncertainties comparable to joint SAXS/contrast-variation SANS analyses. The modular architecture of SAS_MoCa facilitates extension to additional lipid systems and future joint SAXS/SANS or SANS-only applications.

Structure prediction models have moved from single proteins to assemblies that include diverse biomolecules and their modifications. AlphaFold3 (AF3) and related models extended structural modelling via an all-atom framework, opening many new potential applications in structural biology. We evaluate how well the new capabilities of AF3 translate into application tasks in diverse areas: prediction of ubiquitinated protein structures, T-cell receptor (TCR)-epitope recognition, antibody-antigen complexes, protein-RNA and protein-lipid interactions. We find that, while AF3 can perform well in favourable settings, this performance is uneven across applications. In RNA-target predictions, the model confidence fails to separate genuine from decoy interaction partners and in several tasks accuracy depends on the presence of related complexes in the training set. Taken together, our assessment is more cautious than for AF2, whose gains in modelling monomers and complexes were clear and broadly generalisable. AF3s extension to new biomolecule types shows less consistent performance and generalisation. AF3 can be a powerful tool for hypothesis generation and prioritisation, but its predictions and use of confidence metrics will depend strongly on the specific application area and must be interpreted with respect to training-set overlap. We expect that the benchmarks provided here will serve for testing of future developments in the structure prediction field.

The human sodium-citrate cotransporter NaCT imports various tri- and dicarboxylates into the cell as TCA cycle intermediates. This substrate uptake process is driven by an inward sodium gradient. The protein is a member of the Divalent Anion-Sodium Symporter (DASS) family. Whereas extensive biochemical and structural studies have been carried out for NaCT, how the substrate binding and translocation is coupled to the sodium gradient remains unclear. Here using single particle cryo-electron microscopy, we determined the structures of the human NaCT protein in three states: sodium-free, in the presence of sodium, and sodium- and substrate-bound. These structures suggest a simultaneous binding mechanism for sodium-substrate coupling, distinct from the sequential binding, conformational selection mechanism previously observed for the bacterial DASS protein VcINDY.

Space biology literature is growing exponentially. Existing infrastructure has not kept pace with organizing, synthesizing, and disseminating this knowledge. We present SpaceBio SpaceBio Knowledge Hub (www.spacebio.space), an integrated digital ecosystem that combines artificial intelligence, real-time data integration, and open-access infrastructure to advance research, education, and collaboration in microgravity, space biology and space exploration. The platform applies AI-driven approaches including natural language processing, machine learning, and automated content generation to construct a semantic atlas of the field. The atlas reveals the hierarchical thematic organization underlying microgravity-induced biological responses, space mission infrastructure, planetary science, and astrobiology. As part of this effort, SpaceBio is moving toward the construction of a LiteratOmics framework for microgravity, and space biology a systematic, AI-enabled approach to mining, integrating, and structuring the primary literature generated by omics-driven spaceflight research, treating the scientific literature itself as a navigable data layer alongside genomic, transcriptomic, and proteomic datasets. Built on a scalable, cloud-based architecture with a user-centered interface, SpaceBio supports literature exploration, data integration, and knowledge discovery for researchers, educators, students, industry partners, and citizen scientists. The platform also functions as a community-building ecosystem. It integrates hands-on research initiatives, AI-generated educational content, pilot data science projects, and social responsibility programs that broaden participation without compromising scientific rigor. AI-enabled digital environments can transform fragmented literature into a navigable knowledge landscape. SpaceBio accelerates research productivity, strengthens STEM education, and supports the global space life sciences community as human space exploration enters in the most ambitious era.

Acetyl-coenzyme A (CoA) is a central metabolic intermediate that links carbon and energy metabolism across all domains of life. The conversion of acetate and acetyl-CoA is carried out by three enzyme pathways: acetate kinase/phosphotransacetylase, ADP-forming acetyl-CoA synthetase, and AMP-forming acetyl-CoA synthetase (Acs). Acs enzymes serve critical physiological roles across diverse organisms generally by catalyzing a reversible two-step reaction forming acetyl-CoA and AMP from acetate and ATP. Isolated from the wastewater reclamation facility in Norman, Oklahoma, Syntrophus aciditrophicus strain SB (Sa) relies on an AMP-forming acetyl-CoA synthetase (SaAcs1) that favors synthesizing acetate and ATP from acetyl-CoA and AMP, in contrast to all previously characterized Acs enzymes. The origin of this preference and the structural determinants of both the thioester-forming step and catalytic directionality remain poorly understood. Here, we report a 2.2 [A] crystal structure of full-length SaAcs1 in the adenylation conformation with acetyl-AMP bound in the active site. Structural comparison to the extensively characterized Acs enzymes from Salmonella enterica (SeAcs) and Cryptococcus neoformans (CnAcs) revealed a displaced CoA-binding loop in SaAcs1. Enzymatic assays confirmed that SaAcs1 preferentially catalyzes the ATP-forming reaction. Site-directed mutagenesis demonstrated that reversion of two residues, G196 and T197, at the beginning of the CoA-binding loop to the consensus sequence repositions the loop and shifts catalytic preference toward the AMP-forming direction. Together, these results establish the CoA-binding loop and G196 and T197 as the primary structural determinants of directional preference in SaAcs1.

Enterovirus D68 (EV-D68) is a non-polio picornavirus that has caused increasing rates of severe respiratory illness and acute flaccid myelitis in children worldwide this century. There are no approved vaccines or antivirals for EV-D68. Thus, we conducted a crystallographic fragment screening (CFS) and a high-throughput screening (HTS) biochemical assay against the EV-D68 RNA-dependent RNA polymerase 3D (3Dpol) to identify ligandable sites and non-nucleoside compounds that can spearhead anti-enteroviral drug discovery. The CFS, involving 650 fragments, identified 68 hit compounds (~10% hit rate) distributed across 3Dpol, including the functionally relevant sites RNA template channel, Active site, and RNA primer channel, and the previously unknown "Thumb site II" and "Index-middle finger pocket". Inhibition assays confirmed that compounds binding to each site can inhibit EV-D68 3Dpol activity. The HTS, a fluorescence-based PicoGreen biochemical assay, permitted screening 50,000 compounds of the ChemBridge Premium Library (0.77% hit rate). After a second-round dose-response screening, we identified 5-aminoindazole as a promising scaffold that inhibits EV-D68 3Dpol, including hit-to-lead compound 727590, which displayed an IC50 value of 25 M and preliminary structure-activity relationships. These hits offer amenable starting points for discovery and development of non-nucleoside inhibitors and provide opportunities for structure-based drug design against enteroviruses. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/737532v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@14a54a6org.highwire.dtl.DTLVardef@fb6621org.highwire.dtl.DTLVardef@ee2e2aorg.highwire.dtl.DTLVardef@118f91d_HPS_FORMAT_FIGEXP M_FIG Created with biorender.com and PyMOL Molecular Graphics System, version 2.5.0. Schrodinger, LLC. C_FIG

Images in the electron microscope are formed by electron scattering and focusing. The spherical geometry of these processes gives rise to two coherent, conjugate spherical wave fronts, known as Ewald spheres. These spheres are associated with the two halves of the contrast transfer function (CTF), and their widths are determined by the focal gradient through the specimen. To properly correct for the CTF, each half of the CTF must be applied to an image individually and integrated into the reconstruction into the corresponding Ewald sphere. Theory indicates that this dual Ewald sphere reconstruction method should recover the maximal amount of information possible. This method was compared to the other reconstruction methods commonly used: the projection approximation (ignoring the Ewald sphere), the simple insertion and the single sideband methods. In simulated reconstructions the dual Ewald sphere method recovered the most information when the correct half of the CTF is matched to the corresponding Ewald sphere. If the wrong half is matched, the result worse than the projection approximation method. Examining reconstructions from real data indicated that the dual Ewald sphere method performs at least as well as the simple insertion method, but not as good as in simulations. The likely reason is the two-fold ambiguity in the assigned orientations of the particle images, which remains an issue to pursue in further studies. In conclusion, the dual Ewald sphere reconstruction method may offer the best way to calculate very high resolution reconstructions when the micrograph quality warrants it. HighlightsO_LIThe dual Ewald sphere reconstruction corrects for the two halves of the CTF. C_LIO_LIThe signs of the two halves of the CTF must correspond to the focal gradient. C_LIO_LIDetermining the focal gradient for individual particle images remains unresolved. C_LIO_LIComplex reconstructions indicate any real space phases are artifacts. C_LI

DnaK, a prokaryotic Hsp70 chaperone, plays a central role in proteostasis by restoring native structures to heat-denatured proteins in an ATP-hydrolysis-dependent manner. While structures of DnaK in complex with nucleotides, co-chaperones, and short peptides have been resolved, structures with larger, stably folded substrates--such as firefly luciferase (Fluc, 61 kDa)--are lacking, limiting mechanistic understanding of how DnaK refolds such proteins. Here, we generated models of the DnaK-Fluc complex using AlphaFold3 and evaluated their mechanistic relevance. In one of three major model clusters, Fluc is unexpectedly immobilized beneath the DnaK -helical lid against the nucleotide-binding domain (NBD), rather than interacting primarily with the substrate-binding domain {beta} (SBD{beta}), as commonly assumed. All-atom molecular dynamics simulations indicate that, in this configuration, the lid can engage a thermally destabilized Fluc helix (residues 405-411), which we recently identified as the first--and likely the only--helix to irreversibly melt at 42 {degrees}C. Upon binding, the lid forms extensive hydrogen-bonding interactions with the melted helix. These interactions persist during lid movement toward SBD{beta} (following ATP hydrolysis), enabling the lid to actively extract the helix from the Fluc surface. In contrast, simulations with the helix in its native folded state show that the lid cannot extract it, leaving the native structure unaffected. Equilibrium simulations further indicate that, once extracted and mechanically stretched, the melted helix can refold to its native conformation. Together, these findings suggest a revised mechanism for DnaK-mediated protein refolding, in which the -helical lid selectively recognizes structurally compromised segments, forms stabilizing hydrogen bonds, and--powered by ATP hydrolysis--mechanically pulls them away from the protein surface to facilitate their refolding. SIGNIFICANCEDnaK is a model chaperone, which can reactivate thermally denatured proteins. Over the span of 40 years, significant findings have been made about DnaKs structure, dynamics and interactions with its co-chaperones, the exact molecular mechanism by which DnaK refolds misfolded proteins remains a mystery. This work exploited Alphafold3 to generate atomistic models of complexes between DnaK and Firefly luciferase. Molecular dynamics simulations directly captured how DnaK may assist thermally denatured proteins by mechanically pulling out their misfolded helices. This study provides a new insight into the DnaK mechanism.

Protein structure predictors achieve high single-state accuracy, but it remains unclear whether they can recover functionally relevant conformational ensembles or account for the presence of ligands and/or binding partners. Here, we benchmark AlphaFold3, Boltz-2, Chai-1, and BioEmu on four canonical multi-state proteins (Pf-MATE, LAO, SecA, and {beta}2AR), quantifying state bias and sampling breadth against experimental reference structures. Models frequently default to a dominant state represented in the PDB; small-molecule ligands have weak or inconsistent effects, while large protein partners drive clear conformational switching between states. Multiple sequence alignment (MSA)-based approaches (AF-Cluster and random subsampling) recapitulate similar biases, indicating that this behavior is not unique to newer architectures. These results underscore current limitations for multi-state protein structure prediction and structure-guided ligand discovery. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/737860v1_ufig1.gif" ALT="Figure 1"> View larger version (12K): org.highwire.dtl.DTLVardef@3bf389org.highwire.dtl.DTLVardef@1f1c436org.highwire.dtl.DTLVardef@188ea8aorg.highwire.dtl.DTLVardef@1de236e_HPS_FORMAT_FIGEXP M_FIG C_FIG

EIF2alpha kinase heme-regulated inhibitor (HRI) is a novel target for haematological malignancies with modulators reported to trigger cell death via the HRI-eIF2alpha-ATF4 pathway. We report a protocol for producing the minimal kinase domain of full-length human HRI, termed HRIKD-delta-KI, where the unstructured 140 amino acid (aa) kinase insert (KI) within HRI kinase domain (HRIKD) is replaced with a 2aa glycine/serine (GS) linker. X-ray crystal structures were determined of apo-HRIKD-delta-KI and of its complex with ATP at 2.1 & 2.5 Angstrom resolution respectively. Both structures display a canonical bi-lobal kinase fold. However, they remain in a non-productive state with a displaced C-helix, disassembled R-spine, and a disordered activation segment hindering the substrate site. Biophysical assays (fluorescence based thermal shift & Synchrotron Radiation Circular Dichroism) demonstrate HRIKD-delta-KI retains its functional ligand-binding conformation. All together, these findings define structural and ligand-binding features of HRI to support ongoing drug discovery efforts in blood cancer.