Structure

Background: Comparisons between independently predicted wild-type and missense-variant protein structures can generate mechanistic hypotheses, but small apparent differences may reflect model-selection variability rather than mutation-specific effects. Methods: Human mitochondrial DNA polymerase gamma (POLG; UniProt P54098) variants p.Arg627Gln (R627Q) and p.Trp748Ser (W748S) were evaluated using five AlphaFold2-PTM network-model outputs per condition generated with one random seed under matched ColabFold settings. Ten pairwise wild type comparisons at each site described between-network model-selection variability. Variant effects were summarized across five within-network wild-type-versus-variant comparisons using rotation-invariant local C-alpha pair distances and local displacement after global and local alignment. Because these comparison designs differ, the wild-type distribution was used as context rather than a mutation-effect null. Wild-type cryo-EM structure 9GGF was used for contact and interface mapping. Experimental A467T and G848S structures 9GGE and 9GGC provided contextual benchmarks. Results: R627Q measurements fell within the range of between-network wild-type differences: its median mean local pair-distance change was 0.170 angstrom, compared with a wild-type median of 0.170 angstrom, and its locally aligned displacement was 0.265 versus 0.248 angstrom. W748S showed higher median values (0.168 versus 0.132 angstrom for pair-distance change; 0.236 versus 0.182 angstrom for locally aligned displacement), but the ranges overlapped and the comparison-design asymmetry precluded a calibrated mutation-effect percentile. Experimental A467T and G848S comparisons produced local changes of similar magnitude. In 9GGF, R627 and W748 directly shared a local microenvironment, with a minimum heavy-atom distance of 3.53 angstrom. R627 also formed short polar-contact candidates with D629 and D743, whereas W748 occupied a hydrophobic packing environment containing Y622 and F750. Both sites were more than 18 angstrom from nucleic acid, more than 30 angstrom from POLG2, and more than 33 angstrom from PZL-A in a ligand-bound structure. Conclusions: Available AlphaFold2 comparisons do not establish a mutation-specific structural deformation for either variant. Experimental-structure mapping supports testable physicochemical hypotheses involving a shared R627-W748 microenvironment - loss of an arginine-centered polar network for R627Q and disruption of a buried aromatic environment for W748S - but not direct DNA, POLG2, or PZL-A contact mechanisms. Matched control substitutions and independent seeds are required to calibrate small mutation-associated structural deltas.

In molluscs, chitin synthases are essential for biologically controlled biomineralization, with some variants possessing a myosin motor domain that may link polymer synthesis to the cytoskeleton. Experimentally, we established a reliable workflow for expressing ArCS1_E22TM in Dictyostelium discoideum and developed effective purification methods to reconstitute ArCS1_E22TM in nanodiscs using MSPs and specific lipid composition. MSP1D1deltaH5 proved optimal for nanodisc formation, yielding homogeneous, monodisperse discs (~8.2 nm). Lipids were refined to POPC:POPE:POPG (3:1:1) with 20% cholesterol, improving nanodisc quality and uniformity as observed by negative-stain EM. The full-length ArCS1 and its subdomains were modeled using AlphaFold3; the myosin motor, glycosyltransferase, and transmembrane regions are well-defined internally but loosely constrained relative to one another, suggesting flexible linking and conformational coupling. Modelling with Mg2+ and oleic acid as ligands and comparative analyses with bacterial cellulose synthase and yeast chitin synthase 1 provided insights into substrate binding and a potential mechanism for chitin polymerization and translocation. This research establishes a standard procedure for comprehensive structural analyses of recombinant molluscan chitin synthase in near-native or biomimetic membranes. This sets the stage for high-resolution cryo-electron microscopy to determine the first experimentally resolved structure of a molluscan chitin synthase and to provide insight into the enzyme's architecture and the regulatory mechanisms of biomineralization.

Single-particle cryo-electron microscopy (cryo-EM) plays an increasingly important role in structure-based drug discovery (SBDD) by revealing target protein-ligand interactions at the molecular level, but its application has largely focused on large- and medium-sized protein complexes. Many therapeutically important targets are smaller than 50 kDa and remain highly challenging for cryo-EM analysis because of low signal-to-noise ratios and difficulties in particle alignment. Here, we describe cryoFAST, an integrated workflow that couples ligand-compatible Fab discovery and structure-guided computational maturation with biochemical triage, fiducial-complex assembly, and single-particle cryo-EM. Through phage-display screening and/or AI-guided design, we developed high-affinity Fab binders of approximately 50 kDa that stabilize the target without disrupting ligand-target interactions and then assembled Fab-target complexes for cryo-EM analysis. Using the therapeutically relevant extracellular domain (~20 kDa) of interleukin-4 receptor (IL-4R) as a proof of concept, we determined its cryo-EM structure at 2.74 Angstrom resolution and established a framework for elucidating ligand-binding modes. This workflow provides a practical, efficient, and potentially broadly applicable route to the structural characterization of small protein targets that are otherwise challenging to study. By extending the applicability of cryo-EM to high-value but technically challenging small targets, cryoFAST may open new opportunities for structure-based drug discovery.

Dynamics in proteins occur on a wide range of timescales and are crucial for protein function. On the fast end of that timescale, pico- to nanosecond dynamics have been extensively employed as proxies for entropy and their amplitude can be described by order parameters. Experimentally, NMR can be used to determine order parameters of the protein backbone and, via deuterium relaxation, of methyl groups, yet such experiments cannot be applied to large protein assemblies. In contrast, relaxation-violated coherence transfer experiments, that allow for the determination of side chain order parameters in highly deuterated, methyl-labeled proteins, are more sensitive. Here, we demonstrate that such experiments can be applied to very large, asymmetric protein assemblies by determining axial methyl order parameters for the 300 kDa fully asymmetric core of the eukaryotic RNA exosome complex. Ile-{delta}1[13CH3] methyl groups adopt a wide range of order parameters but highly flexible side chains are infrequent. High quality data, which we obtain for flexible regions, is required to observe subtle effects of RNA binding on order parameters. Local cryo-EM Q-scores correlate moderately with order parameters suggesting that Q-scores contain information on nanosecond motions. AF2{chi}, a recently described prediction tool for side-chain variability, provides good estimates of methyl order parameters, which are, in favorable cases, strongly correlated with experimental values. We thus demonstrate that relaxation-violated coherence transfer experiments can be employed to determine order parameters in large, asymmetric protein complexes that are difficult to capture by other methods, yet are crucial for the understanding of protein function. SignificanceNanosecond side chain dynamics contribute to the entropy of proteins and are therefore proxies for protein stability and binding. Here, we demonstrate that NMR can be employed to experimentally quantify nanosecond dynamics in large, asymmetric proteins paving the way to assess contributions of fast dynamics to the quality of static protein structures. Furthermore, we employ the experimental data to validate computational methods that provide structural insights into nanosecond dynamics.

Cryogenic electron microscopy (cryo-EM) has enabled rapid progress in structural biology throughout the last decade. However, cryo-EM sample preparation still represents a major bottleneck in high-resolution structure determination. Many proteins and macromolecular complexes interact with the air-water interface during sample preparation, which can cause protein denaturation, complex disassembly, and preferred particle orientation. Development of methods to alleviate these issues is an active field of investigation. However, a universally applicable solution to this problem has not been found so far. Here, we describe the simple and cost-effective usage of synthetic peptides with defined amino acid sequence to protect cryo-EM samples from complex disassembly and reduce preferred orientation. We show benefits during cryo-EM grid preparation of a large E3 ubiquitin ligase termed the anaphase-promoting complex (APC/C), and the small CDK11:cyclin L:SAP30BP complex.

Proteins naturally adopt multiple conformations in mediating cellular processes, and ensemble models are used to fit X-ray crystallography data that captures this heterogeneity. In practice, ensemble refinement produces only minor improvements in agreement with experimental data (R-free) over single-conformation models. It has recently been shown that ensemble models are universally trapped, or "tangled"; refinement algorithms strain each individual conformation in the model to fit the electron density in its immediate vicinity, missing more harmonious ways to arrange the collection of protein conformations to fit the electron density. Here, we demonstrate that this type of trap may be escaped by formulating the construction of low-energy conformations from individual conformer coordinates as an integer linear programming problem. The method successfully recovered the two original protein conformations from a previously published synthetic dataset that traps current refinement methods. Inclusion of the method in an automated refinement procedure with real data is shown to improve R-free and reduce geometric strain in a four-conformation model by comparison with controls. Applying this method in combination with human input and fitting low-occupancy waters to density features in the bulk solvent, we produce models for deposited datasets of three separate 14-19 kDa proteins with greatly improved geometry and R-factors. This includes a 0.77 [A] six-conformation model of the SARS-CoV-2 macrodomain Mac1 (PDB ID: 44PS) with an R-work of 4.7% and an R-free of 6.4%.

TWIK-related halothane-inhibited potassium channel 1 (THIK1) is a two-pore domain potassium (K2P) channel highly expressed in microglia that contributes to microglial homeostasis and neuroinflammatory responses. Pharmacological inhibition of THIK1 suppresses tonic K+ currents and attenuates NLRP3-dependent IL-1{beta} release, highlighting THIK1 as a potential therapeutic target for neuroinflammatory disorders. However, the structural basis of THIK1 inhibition remains unclear. Here we report cryo-electron microscopy (cryo-EM) structures of full-length human THIK1 in complex with C101248, a commercially available tool compound, and CVN293, a clinical-stage inhibitor that has completed Phase I evaluation. The two inhibitors occupy a similar site within the inner vestibule formed by TM2 and TM4 beneath the selectivity filter. Consistent with their closely related chemical scaffolds and shared binding site, both inhibitors remodel the Y273 inner gate but differ in their effects on the C-terminal gate. Electrophysiological analyses further demonstrate that the C-terminal gate contributes differently to inhibition by the two compounds. Together, our findings show how chemically related inhibitors exert different effects on THIK1 despite engaging a common binding site.

Cryo-electron microscopy (cryo-EM) has become a central tool for structure-based drug discovery, yet ligand-binding sites often remain substantially less well resolved than the surrounding protein, limiting reliable atomic interpretation. Although deep-learning methods have substantially improved overall cryo-EM map quality, their predominantly protein-focused training limits their ability to recover ligand density. Here we present CryoLigATE, a deep learning framework specifically designed to enhance densities associated with protein-bound ligands in cryo-EM maps. We curated a chemically and structurally diverse dataset of more than 6,000 protein-ligand complexes from the EMDB and PDB, encompassing drug-like molecules, lipids, steroids, carbohydrates and other ligand classes, and trained a hybrid convolutional-transformer network to enhance local density around binding pockets. During inference, CryoLigATE automatically extracts the target region from a preliminary atomic model, requiring no manual map preparation and completing localized refinement in seconds on a desktop GPU. Evaluation on an independent test set of 649 complexes demonstrates substantial improvements in ligand resolvability, particularly for maps with poorly resolved binding sites, while preserving high-quality experimental densities. The enhanced maps recover chemically meaningful features, including ligand functional groups and topological continuity, enabling more confident atomic modeling. By learning the structural diversity of ligand features, CryoLigATE addresses a longstanding limitation of cryo-EM map enhancement and provides a useful framework for improving structural interpretation and structure-guided drug discovery.

Disulfide-rich peptides possess exceptional potency and selectivity but are often limited by the instability and synthetic challenges associated with native disulfide bonds. Here, we report the design, synthesis, pharmacological evaluation, and structural characterisation of triazole-based peptidomimetics of the -GI conotoxin, a selective antagonist of the muscle-type nicotinic acetylcholine receptor (nAChR). A series of 1,4- and 1,5-disubstituted triazole analogues were prepared entirely on resin using CuAAC and RuAAC chemistry to replace the native Cys3/13 disulfide bridge. Functional evaluation against human muscle nAChRs revealed that 1,5-triazole analogues retained low-nanomolar potency, with the lead mimetic exhibiting activity comparable to native -GI. Cryo-electron microscopy of the lead compound bound to the muscle-type nAChR provided the first structure of a disulfide-isostere peptidomimetic in complex with a membrane receptor. The structure demonstrates that the 1,5-triazole reproduces the native peptide fold with high fidelity while contributing receptor-facing interactions not available to the native disulfide bridge. Molecular dynamics simulations further revealed conserved hydration networks and similar conformational sampling between the native peptide and lead mimetic. Together, these findings establish triazoles as effective disulfide surrogates and provide a structural framework for the rational design of stabilised conotoxin therapeutics.

G protein-coupled receptors (GPCRs) often engage multiple intracellular transducers, yet the structural basis by which endogenous ligands influence G protein selectivity remains poorly understood. GPR119 is a lipid-activated receptor expressed in pancreatic {beta}-cells and enteroendocrine L-cells, where it regulates glucose-dependent insulin and incretin secretion, making it a promising therapeutic target for metabolic disease. Here, we present cryo-electron microscopy structures of GPR119 bound to its endogenous lipid agonist oleoylethanolamide (OEA) in complex with Gs and Gq proteins. These structures reveal that OEA occupies a deeply buried orthosteric pocket but adopts distinct conformations in the two signaling states. Structural and functional analyses further identify an extended TM5 helix that stabilizes the receptor-Gs interface and acts as a key determinant of G-protein subtype selectivity. Together, these findings provide mechanistic insights into endogenous lipid-driven multi-transducer signaling and establish a structural framework for the development of pathway-selective GPR119 therapeutics.

While cryogenic electron microscopy (cryo-EM) has transformed structural biology, sample preparation remains a major determinant of success. Specifically, the air-water interface (AWI) can damage complexes, impose preferred orientation, and reduce particle density. Here, we introduce cryoSHIELDs, a chemically diverse library of peptide additives designed to passivate the AWI and improve cryo-EM grid preparation. Across 24 protein systems spanning GPCRs, ABC and SLC transporters, soluble and Fab-containing complexes, and enzymes, cryoSHIELDs increased the success rate of structure determination. Individual cryoSHIELDs improved particle density, angular sampling, complex stability, and, for routine targets, map quality and resolution. This toolkit enabled the structural characterization of important targets, including the ABCC6 transporter, revealing unique TMD0-mediated stabilization, and DAMGO-bound -opioid receptor-Gi complex using substantially lower protein concentration. CryoSHIELDs provide a simple, tunable, and broadly applicable platform for more reliable cryo-EM in discovery biology and structure-based drug development.

Microtubules are cytoskeletal filaments that are involved in intracellular transport, cell division, and motility. Despite their biological importance, determining their high-resolution structures via cryo-electron microscopy remains a significant technical challenge due to their polymorphisms and pseudo-helical assembly. Current processing workflows are complex, often requiring the integration of multiple software packages and custom scripts, which creates a steep learning curve for many research groups. To address these limitations, we introduce CsMT, a streamlined workflow implemented entirely within the CryoSPARC environment and using synthetic references. CsMT simplifies microtubule reconstruction by utilizing a novel protofilament-pair classification approach, which effectively handles the inherent pseudo-symmetry and structural heterogeneity of microtubules with minimal manual intervention. Our workflow is versatile, capable of processing both undecorated and decorated microtubules while accurately determining seams and performing high-resolution refinement. We demonstrate the efficacy of this workflow by achieving a 2.3 and 2.7 [A] resolution reconstruction of homotypic and heterotypic maps of undecorated microtubules, matching the best-resolved microtubule structures in the field. By unifying the pipeline into a single and portable workflow, CsMT enhances reproducibility and accessibility, empowering more laboratories to explore the structural biology of microtubules and associated proteins, yielding new insights into their function.

Proteins in solution often populate conformational ensembles that differ from the static states captured by crystallography or AI-based structure prediction. Conventional molecular dynamics (MD) simulations often fail to cross the energy barriers separating these states on accessible timescales, and statistical reweighting cannot recover conformations never sampled. Here we present Carbonara, a framework that uses experimental small-angle X-ray scattering (SAXS) data to predict alternative physically plausible protein conformations. Carbonara builds on Wiggle, a standalone C-based SAXS forward model validated against explicit-solvent calculations and experimental benchmarks. Using two case studies, an AI-predicted multi-domain helicase (SMAR-CAL1) and a crystallographic antibody fragment (ChiLob7/4 IgG2), we show how seeding MD simulations from Carbonara conformations enables efficient exploration of solution-state conformational landscapes. In both cases, MD ensembles initiated from available models either fail to match the SAXS data or do so only after discarding nearly all sampled conformations, whereas Carbonara-seeded ensembles reach agreement while retaining the majority of conformations. Our modelling framework provides a route from static structural models of flexible multi-domain proteins and multimeric assemblies to solution-state ensembles.

The facilitative transport of hexose through the GLUcose Transporter type 4 (GLUT4) is essential for cellular metabolism and is regulated by allosteric nucleotide interactions. In this study, we conducted a comparative biophysical analysis of glucose translocation using both the native Cryo-EM structure (7WSN) and the AI-predicted AlphaFold model using Steered Molecular Dynamics (SMD) at physiological (310.15 K) and attenuated (303.15 K) temperatures with two different allosteric modulators, ATP and ADP. While the AlphaFold model managed to capture baseline static topologies, dynamic profiling revealed that it intrinsically over-optimizes for static stability, immediately collapsing into a sterically occluded, hyper-packed artifact. Translocation through this constricted geometry forces severe steric solvent exclusion, abruptly stripping the substrates hydration shell and resulting in immediate and immense thermodynamic friction (>300 kJ/mol). Under ATP-bound physiological strain, this hyper-bonded structural clamp prevents functional relaxation, ultimately inducing a catastrophic kinematic failure. Furthermore, ensemble Dynamic Cross-Correlation Matrix (DCCM) analysis demonstrates that the AI-predicted model suffers from persistent rigid-body locking, forcing the transmembrane domain to behave as a kinetically trapped conformation. In contrast, the functionally hydrated Cryo-EM architecture actively maintains a dual-gating pore and successfully isolates the exact mechanical lever driving transport: a native Proline hinge (PRO379) that seamlessly routes allosteric signals from the nucleotide anchor to the pore gate. Within the AlphaFold model, this critical allosteric wiring is disrupted, forcing mechanical coupling through an unphysiological, hyper-correlated aromatic pathway. These findings yield novel atomistic insights into GLUT4 gating mechanics, while definitively establishing that rigid AI-generated architectures lack the essential internal free volume and conformational plasticity required to sustain accurate thermodynamic profiling of dynamic membrane transporters.

Cytochrome P450 3A4 (CYP3A4) metabolizes roughly half of all marketed drugs, and its inhibition can cause clinically significant drug-drug interactions. The enzyme accommodates chemically diverse ligands, making binding modes and metabolic outcomes difficult to predict. Previous X-ray crystallography efforts have leveraged a truncated construct without the N-terminal segment that tethers CYP3A4 to the membrane. Here we show that the same construct assembles into a symmetric trimer that can be resolved by cryo-EM and determine structures of both unliganded and ligand-bound CYP3A4. Multiple ligands are resolved with density consistent with several mutually exclusive conformations. Protein remodeling to reshape the binding pocket is concentrated in the F/G loop, which is poorly resolved and unmodeled in many X-ray structures. These features likely underlie the poor predictive performance of co-folding methods on this target. The routine use of cryo-EM to resolve CYP3A4 ligand-bound complexes will provide the ground truth data needed to make predictive models of drug metabolism useful in practice.

AMP-activated protein kinase (AMPK) regulates metabolism in response to metabolic stress that includes stimulating glucose uptake in skeletal muscle independently of the canonical insulin signalling pathway, positioning it as an attractive therapeutic target for insulin resistance and type 2 diabetes mellitus (T2DM). AMPK is an {beta}{gamma} heterotrimer, with multiple isoforms for each subunit enabling the formation of 12 different complexes with distinct tissue expression profiles. Among these, the 2{beta}2{gamma}3 complex is predominantly expressed in skeletal muscle, the major site of glucose disposal and a highly desirable therapeutic target for T2DM. Here, we characterise the functional role of a unique, 182 residue N-terminal extension (NTE) within {gamma}3 subunit. Deletion of the {gamma}3-NTE from 2{beta}2{gamma}3 complex increases basal AMPK activity without affecting activation by AMP or pharmacological AMPK activators, demonstrating the {gamma}3-NTE performs an autoinhibitory function. Using complementary biophysical techniques, including hydrogen-deuterium exchange-mass spectrometry, surface plasmon resonance, chemical crosslinking and co-pulldowns, we identified a 39-residue sequence in the {gamma}3-NTE (residues 129-168), that directly interacts with the C-helix of the AMPK kinase domain small lobe, a key regulatory element in many protein kinases. Using AlphaFold3, we probe the interaction predicted to take place between a {gamma}3-NTE -helix ({gamma}3-iHelix; [~]T142-E154) and the C-helix in the 2{beta}2{gamma}3 complex. These findings provide the groundwork for developing novel T2DM therapies that target AMPK activation selectively in skeletal muscle involving reversal of the {gamma}3 autoinhibition.

Respiratory complex I is a large redox-driven proton pump and contributes to the proton motive force required for ATP generation in mitochondria and bacteria. It has been extensively studied with structural and biochemical approaches leading to enhanced understanding of its three- dimensional architecture. Despite significant progress in deciphering its catalytic function, the redox-coupled proton pumping mechanism remains unclear and extensively debated. The three membrane-bound antiporter-like subunits ND2, ND4 and ND5 are responsible for pumping protons from the negatively charged side (N-side) of the membrane to the positively charged side (P-side). Emerging evidence supports the role of ND5 subunit in releasing pumped protons to the P-side of the membrane, but the question whether ND2 and ND4 also contribute to proton release remains unanswered. Here, we performed atomistic molecular dynamics (MD) simulations of an intact and a truncated model of complex I in which ND5 and ND4 subunits are removed in-silico. The simulation data reveals a previously unobserved conformational change in the P-side region of ND2 subunit that occurs much more easily in a truncated model of complex I, as also estimated based on free energy calculations. The conformational change, in part triggered by the artificial exposure of ND2 subunit to lipid bilayer, results in a local hydration of the region, similar to what has been observed in recent cryo-EM structure of plant CI:CIII2 supercomplex. We discuss the functional relevance of observed conformational transitions and identify residues that can be manipulated with biochemical approaches to shed light on proton pumping by complex I.

Tuberculosis is a leading cause of death globally due to an infectious agent. There is ongoing need for novel mechanisms to inhibit M. tuberculosis (Mtb) growth and infection to improve patient outcomes. FtsZ, a GTPase that assembles into protofilaments at the division site of a replicating cell to produce two individual cells, is an attractive target as an essential protein in bacterial cell division. Here we describe a crystallographic fragment screening campaign of MtbFtsZ. 1,070 crystals were soaked with fragments and 714 datasets were used for downstream PanDDA analysis. 149 datasets exhibited PanDDA-generated event map density to support modeling of fragment binding. 15 novel sites are described. Both the ON and the OFF conformations of FtsZ are found in the asymmetric unit. Asymmetric binding of fragments to each chain in the model is observed. These crystallographic fragment screening results additionally provide opportunities for fragment growing and merging to develop FtsZ binders into drug-like molecules or conformation specific chemical probes.

The ability of cryo-electron microscopy (cryo-EM) to interrogate the atomic structure and motion of biomolecules has motivated the development of a wide range of algorithms for heterogeneity analysis. However, evaluating and comparing these methods remains challenging because ground-truth structures are generally unknown for experimental samples. Here, we introduce the 2026 Community-Wide Assessment of Heterogeneous Reconstruction Algorithms (CAHRA), a community-wide challenge centered on three benchmark datasets that probe distinct tasks in heterogeneity analysis. These include (1) compositional heterogeneity arising from mixtures of distinct protein complexes, (2) continuous conformational variability and atomic modeling, and (3) entanglement between molecular conformation and particle pose. We describe the design, construction, and validation of these datasets, as well as their use in the recently completed CAHRA Challenge.

In-cell protein crystallization (ICPC) produces ordered protein crystals within living cells, but the mechanisms used by proteins to acquire long-range crystalline order in the cellular environment remains poorly understood. Here, we define the assembly pathway of CipB, a crystalline inclusion protein from Photorhabdus luminescens. CipB crystals formed in cells dissolve under mild acidic conditions into a predominant 24-mer species, supporting a model in which an in-cell crystal is built from a discrete 24-mer assembly precursor rather than through direct packing of smaller oligomeric states. Structural analysis of recrystallized CipB shows that the same 24-mer architecture packs into a body-centered cubic lattice, consistent with the lattice observed for the in-cell crystals. Cryo-EM and molecular dynamics analyses indicate that the 24-mer assembly precursor preserves its overall architecture while retaining local conformational flexibility at the N-terminal and surface-loop regions. Mutation analyses further link the N-terminal region to the formation of the 24-mer precursor and surface residues to lattice assembly. These observations support a stepwise crystallization model in which N-terminal flexibility facilitates the formation of an assembly-competent 24-mer precursor, whereas defined hydrophobic surface contacts subsequently organize these precursors into a long-range-ordered lattice.