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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Extended experimental inferential structure determination method in determining the structural ensembles of disordered protein states

Proteins with intrinsic or unfolded state disorder comprise a new frontier in structural biology, requiring the characterization of diverse and dynamic structural ensembles. Here we introduce a comprehensive Bayesian framework, the Extended Experimental Inferential Structure Determination (X-EISD) method, which calculates the maximum log-likelihood of a disordered protein ensemble. X-EISD accounts for the uncertainties of a range of experimental data and back-calculation models from structures, including NMR chemical shifts, J-couplings, Nuclear Overhauser Effects (NOEs), paramagnetic relaxation enhancements (PREs), residual dipolar couplings (RDCs), hydrodynamic radii (R h ), single molecule fluorescence Förster resonance energy transfer (smFRET) and small angle X-ray scattering (SAXS). We apply X-EISD to the joint optimization against experimental data for the unfolded drkN SH3 domain and find that combining a local data type, such as chemical shifts or J-couplings, paired with long-ranged restraints such as NOEs, PREs or smFRET, yields structural ensembles in good agreement with all other data types if combined with representative IDP conformers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Protein Data Bank (PDB): Fifty-three years young and having a transformative impact on science and society

This review article describes the co-evolution of structural biology as a discipline and the Protein Data Bank (PDB), established in 1971 as the first open-access data resource in biology by like-minded structural scientists. As the PDB archive grew in size and scope to encompass macromolecular crystallography, NMR spectroscopy, and cryo-electron microscopy, new technologies were developed to ingest, validate, curate, store, and distribute the information. Community engagement ensured that the needs of structural biologists (data depositors) and data consumers were met. Today, the archive houses more than 230,000 experimentally determined structures of proteins, nucleic acids, and macromolecular machines and their complexes with one another and small-molecule ligands. Aggregate costs of PDB data preservation are ~1% of the cost of structure determination. The enormous impact of PDB data on basic and applied research and education across the natural and medical sciences is presented and highlighted with illustrative examples. Enablement of de novo protein structure prediction (AlphaFold2, RoseTTAfold, OpenFold, etc.) is the most widely appreciated benefit of having a corpus of rigorously validated, expertly curated 3D biostructure data.

bioinformatics↗
DOE OSTI2022

RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning

Abstract The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a ‘living data resource.’ Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Ion-selective conformational stabilization of a disordered repeats-in-toxin protein domain

Ion-binding intrinsically disordered proteins (IDPs) recruit and bind to specific metal ions to perform critical biological functions. In proteins where ion binding and structural transitions are coupled, interactions with off-target toxic metals can dramatically disrupt protein structure and function, exemplified by lead and mercury poisoning. Understanding the complex mechanisms underlying how IDPs exclude or allow binding to different ionic species is crucial for addressing the origins of metal toxicity in biological systems. Here, we elucidate mechanisms of ion selectivity in an IDP that adopts a structure upon Ca 2+ binding. We probed ion-induced conformational changes of a repeats-in-toxin (RTX) protein domain in the presence of different ion ligands—Mg 2+ , Ca 2+ , Sr 2+ , and Ba 2+ —with chemical similarities but drastically different ionic radii. RTX adopts ion-selective conformations measured by x-ray crystallography, small-angle x-ray scattering, and circular dichroism. High-resolution x-ray structures reveal that Sr 2+ induces a nearly identical RTX structure as natively binding Ca 2+ , enabled by the intrinsic flexibility and disorder of the protein. Small-angle x-ray scattering and circular dichroism indicate that smaller Mg 2+ does not induce a significant conformational change in RTX, whereas larger Ba 2+ induces a partially folded structure. These results highlight the importance of geometric constraints imposed by protein structure in determining metal ion selectivity, yielding insights into how off-target ion binding may result in protein misfolding and malfunction.

Gudinas, Alana P. [Stanford Univ., CA (United Stat↗
DOE OSTI2020

Graph-Directed Approach for Downselecting Toxins for Experimental Structure Determination

Conotoxins are short, cysteine-rich peptides of great interest as novel therapeutic leads and of great concern as lethal biological agents due to their high affinity and specificity for various receptors involved in neuromuscular transmission. Currently, of the approximately 6000 known conotoxin sequences, only about 3% have associated structural characterization, which leads to a bottleneck in rapid high-throughput screening (HTS) for identification of potential leads or threats. In this work, we combine a graph-based approach with homology modeling to expand the library of conotoxin structures and to identify those conotoxin sequences that are of the greatest value for experimental structural characterization. The latter would allow for the rapid expansion of the known structural space for generating high quality template-based models. Our approach generalizes to other evolutionarily-related, short, cysteine-rich venoms of interest. Overall, we present and validate an approach for venom structure modeling and experimental guidance and employ it to produce a 290%-larger library of approximate conotoxin structures for HTS. We also provide a set of ranked conotoxin sequences for experimental structure determination to further expand this library.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Structure and identification of the native PLP synthase complex from Methanosarcina acetivorans lysate

Many protein-protein interactions behave differently in biochemically purified forms as compared to their in vivo states. As such, determining native protein structures may elucidate structural states previously unknown for even well-characterized proteins. Here, we apply the bottom-up structural proteomics method, cryoID , toward a model methanogenic archaeon. While they are keystone organisms in the global carbon cycle and active members of the human microbiome, there is a general lack of characterization of methanogen enzyme structure and function. Through the cryoID approach, we successfully reconstructed and identified the native Methanosarcina acetivorans pyridoxal 5′-phosphate (PLP) synthase (PdxS) complex directly from cryogenic electron microscopy (cryo-EM) images of fractionated cellular lysate. We found that the native PdxS complex exists as a homo-dodecamer of PdxS subunits, and the previously proposed supracomplex containing both the synthase (PdxS) and glutaminase (PdxT) was not observed in cellular lysate. Our structure shows that the native PdxS monomer fashions a single 8α/8β TIM-barrel domain, surrounded by seven additional helices to mediate solvent and interface contacts. A density is present at the active site in the cryo-EM map and is interpreted as ribose 5-phosphate. In addition to being the first reconstruction of the PdxS enzyme from a heterogeneous cellular sample, our results reveal a departure from previously published archaeal PdxS crystal structures, lacking the 37-amino-acid insertion present in these prior cases. This study demonstrates the potential of applying the cryoID workflow to capture native structural states at atomic resolution for archaeal systems, for which traditional biochemical sample preparation is nontrivial.

Methanosarcina acetivorans↗
DOE OSTI2021

Development of a universal nanobody-binding Fab module for fiducial-assisted cryo-EM studies of membrane proteins

Structural studies of membrane proteins by cryogenic electron microscopy (cryo-EM) often require antibody fragments (Fabs) to facilitate particle alignments and achieve high resolution. While conformational nanobodies have been developed to lock specific states of many membrane proteins, they only add 15 kDa of mass to the complex. We developed a synthetic Fab (NabFab) that rigidly binds the conserved scaffold of nanobodies, providing a universally applicable fiducial for cryo-EM studies of protein–nanobody complexes. Additionally, we demonstrate the concept by determining two high-resolution structures of membrane proteins bound to specific nanobodies and NabFab. As the structural epitope for NabFab can be incorporated into the scaffold of virtually any nanobody, this raises the prospect of facile structure determination of many nanobody–protein complexes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Cryo-EM, Protein Engineering, and Simulation Enable the Development of Peptide Therapeutics against Acute Myeloid Leukemia

Cryogenic electron microscopy (cryo-EM) has emerged as a viable structural tool for molecular therapeutics development against human diseases. However, it remains a challenge to determine structures of proteins that are flexible and smaller than 30 kDa. The 11 kDa KIX domain of CREB-binding protein (CBP), a potential therapeutic target for acute myeloid leukemia and other cancers, is a protein which has defied structure-based inhibitor design. Here, we develop an experimental approach to overcome the size limitation by engineering a protein double-shell to sandwich the KIX domain between apoferritin as the inner shell and maltose-binding protein as the outer shell. To assist homogeneous orientations of the target, disulfide bonds are introduced at the target–apoferritin interface, resulting in a cryo-EM structure at 2.6 Å resolution. We used molecular dynamics simulations to design peptides that block the interaction of the KIX domain of CBP with the intrinsically disordered pKID domain of CREB. The double-shell design allows for fluorescence polarization assays confirming the binding between the KIX domain in the double-shell and these interacting peptides. Further cryo-EM analysis reveals a helix–helix interaction between a single KIX helix and the best peptide, providing a possible strategy for developments of next-generation inhibitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

rcsb-api : Python Toolkit for Streamlining Access to RCSB Protein Data Bank APIs

The Protein Data Bank (PDB) was founded in 1971 as the first open-access digital data resource in biology to serve as the single global archive for three-dimensional (3D) macromolecular structure data. Current PDB holdings exceed 230,000 experimentally determined structures of proteins, nucleic acids, viruses, and macromolecular machines. The RCSB Protein Data Bank RCSB.org research-focused web portal facilitates search, analyses, and visualization of every PDB structure along with more than one million Computed Structure Models from AlphaFold DB and the ModelArchive. It is powered by a set of publicly available Application Programming Interfaces (APIs) that both support RCSB.org users and provide programmatic access to PDB data. Given the breadth and levels of granularity encompassed in this rich data collection, efficiently accessing the information programmatically may be challenging for new users. RCSB PDB has developed a Python software package, rcsb-api , that facilitates easy and efficient use of RCSB PDB APIs within a Python environment. This software tool is designed to streamline access to the extensive corpus of data housed within the PDB, enabling researchers to search, retrieve, and analyze 3D biostructure data seamlessly. Its use will accelerate research in structural biology, molecular biology and biochemistry, drug discovery, and bioinformatics by providing more efficient tools for data integration and analysis. The new toolkit is available on GitHub (github.com/rcsb/py-rcsb-api) and published to the public Python package repository (PyPI) to foster wider usage and support basic and applied research in fundamental biology, biomedicine, and the energy sciences.

FAIR principles↗
DOE OSTI2023

Crystal structure of the Arabidopsis SPIRAL2 C-terminal domain reveals a p80-Katanin-like domain

Epidermal cells of dark-grown plant seedlings reorient their cortical microtubule arrays in response to blue light from a net lateral orientation to a net longitudinal orientation with respect to the long axis of cells. The molecular mechanism underlying this microtubule array reorientation involves katanin, a microtubule severing enzyme, and a plant-specific microtubule associated protein called SPIRAL2. Katanin preferentially severs longitudinal microtubules, generating seeds that amplify the longitudinal array. Upon severing, SPIRAL2 binds nascent microtubule minus ends and limits their dynamics, thereby stabilizing the longitudinal array while the lateral array undergoes net depolymerization. To date, no experimental structural information is available for SPIRAL2 to help inform its mechanism. To gain insight into SPIRAL2 structure and function, we determined a 1.8 Å resolution crystal structure of the Arabidopsis thaliana SPIRAL2 C-terminal domain. The domain is composed of seven core α-helices, arranged in an α-solenoid. Amino-acid sequence conservation maps primarily to one face of the domain involving helices α1, α3, α5, and an extended loop, the α6-α7 loop. The domain fold is similar to, yet structurally distinct from the C-terminal domain of Ge-1 (an mRNA decapping complex factor involved in P-body localization) and, surprisingly, the C-terminal domain of the katanin p80 regulatory subunit. The katanin p80 C-terminal domain heterodimerizes with the MIT domain of the katanin p60 catalytic subunit, and in metazoans, binds the microtubule minus-end factors CAMSAP3 and ASPM. Structural analysis predicts that SPIRAL2 does not engage katanin p60 in a mode homologous to katanin p80. The SPIRAL2 structure highlights an interesting evolutionary convergence of domain architecture and microtubule minus-end localization between SPIRAL2 and katanin complexes, and establishes a foundation upon which structure-function analysis can be conducted to elucidate the role of this domain in the regulation of plant microtubule arrays.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Serial crystallography using automated drop dispensing

Automated, pulsed liquid-phase sample delivery has the potential to greatly improve the efficiency of both sample and photon use at pulsed X-ray facilities. In this work, an automated drop on demand (DOD) system that accelerates sample exchange for serial femtosecond crystallography (SFX) is demonstrated. Four different protein crystal slurries were tested, and this technique is further improved here with an automatic sample-cycling system whose effectiveness was verified by the indexing results. Here, high-throughput SFX screening is shown to be possible at free-electron laser facilities with very low risk of cross contamination and minimal downtime. The development of this technique will significantly reduce sample consumption and enable structure determination of proteins that are difficult to crystallize in large quantities. This work also lays the foundation for automating sample delivery.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination

Abstract Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Observation of substrate diffusion and ligand binding in enzyme crystals using high-repetition-rate mix-and-inject serial crystallography

Here, we illustrate what happens inside the catalytic cleft of an enzyme when substrate or ligand binds on single-millisecond timescales. The initial phase of the enzymatic cycle is observed with near-atomic resolution using the most advanced X-ray source currently available: the European XFEL (EuXFEL). The high repetition rate of the EuXFEL combined with our mix-and-inject technology enables the initial phase of ceftriaxone binding to the Mycobacterium tuberculosis β-lactamase to be followed using time-resolved crystallography in real time. It is shown how a diffusion coefficient in enzyme crystals can be derived directly from the X-ray data, enabling the determination of ligand and enzyme–ligand concentrations at any position in the crystal volume as a function of time. In addition, the structure of the irreversible inhibitor sulbactam bound to the enzyme at a 66 ms time delay after mixing is described. This demonstrates that the EuXFEL can be used as an important tool for biomedically relevant research.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ig-VAE: Generative modeling of protein structure by direct 3D coordinate generation

While deep learning models have seen increasing applications in protein science, few have been implemented for protein backbone generation—an important task in structure-based problems such as active site and interface design. We present a new approach to building class-specific backbones, using a variational auto-encoder to directly generate the 3D coordinates of immunoglobulins. Our model is torsion- and distance-aware, learns a high-resolution embedding of the dataset, and generates novel, high-quality structures compatible with existing design tools. We show that the Ig-VAE can be used with Rosetta to create a computational model of a SARS-CoV2-RBD binder via latent space sampling. We further demonstrate that the model’s generative prior is a powerful tool for guiding computational protein design, motivating a new paradigm under which backbone design is solved as constrained optimization problem in the latent space of a generative model.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

In Situ Proteolysis Condition-Induced Crystallization of the XcpVWX Complex in Different Lattices

Although prevalent in the determination of protein structures; crystallography always has the bottleneck of obtaining high-quality protein crystals for characterizing a wide range of proteins; especially large protein complexes. Stable fragments or domains of proteins are more readily to crystallize; which prompts the use of in situ proteolysis to remove flexible or unstable structures for improving crystallization and crystal quality. In this work; we investigated the effects of in situ proteolysis by chymotrypsin on the crystallization of the XcpVWX complex from the Type II secretion system of Pseudomonas aeruginosa. Different proteolysis conditions were found to result in two distinct lattices in the same crystallization solution. With a shorter chymotrypsin digestion at a lower concentration; the crystals exhibited a P3 hexagonal lattice that accommodates three complex molecules in one asymmetric unit. By contrast; a longer digestion with chymotrypsin of a 10-fold higher concentration facilitated the formation of a compact P212121 orthorhombic lattice with only one complex molecule in each asymmetric unit. The molecules in the hexagonal lattice have shown high atomic displacement parameter values compared with the ones in the orthorhombic lattice. Taken together; our results clearly demonstrate that different proteolysis conditions can result in the generation of distinct lattices in the same crystallization solution; which can be exploited in order to obtain different crystal forms of a better quality

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Complementarity of neutron, XFEL and synchrotron crystallography for defining the structures of metalloenzymes at room temperature

Room-temperature macromolecular crystallography allows protein structures to be determined under close-to-physiological conditions, permits dynamic freedom in protein motions and enables time-resolved studies. In the case of metalloenzymes that are highly sensitive to radiation damage, such room-temperature experiments can present challenges, including increased rates of X-ray reduction of metal centres and site-specific radiation-damage artefacts, as well as in devising appropriate sample-delivery and data-collection methods. It can also be problematic to compare structures measured using different crystal sizes and light sources. In this study, structures of a multifunctional globin, dehaloperoxidase B (DHP-B), obtained using several methods of room-temperature crystallographic structure determination are described and compared. Here, data were measured from large single crystals and multiple microcrystals using neutrons, X-ray free-electron laser pulses, monochromatic synchrotron radiation and polychromatic (Laue) radiation light sources. These approaches span a range of 18 orders of magnitude in measurement time per diffraction pattern and four orders of magnitude in crystal volume. The first room-temperature neutron structures of DHP-B are also presented, allowing the explicit identification of the hydrogen positions. The neutron data proved to be complementary to the serial femtosecond crystallography data, with both methods providing structures free of the effects of X-ray radiation damage when compared with standard cryo-crystallography. Comparison of these room-temperature methods demonstrated the large differences in sample requirements, data-collection time and the potential for radiation damage between them. With regard to the structure and function of DHP-B, despite the results being partly limited by differences in the underlying structures, new information was gained on the protonation states of active-site residues which may guide future studies of DHP-B.

36 MATERIALS SCIENCE↗