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At least 415 records · Page 23

Structural analysis of the catalytic domain of Artemis endonuclease/SNM1C reveals distinct structural features

The endonuclease Artemis is responsible for opening DNA hairpins during V(D)J recombination and for processing a subset of pathological DNA double-strand breaks. Artemis is an attractive target for the development of therapeutics to manage various B cell and T cell tumors, because failure to open DNA hairpins and accumulation of chromosomal breaks may reduce the proliferation and viability of pre-T and pre-B cell derivatives. However, structure-based drug discovery of specific Artemis inhibitors has been hampered by a lack of crystal structures. Here, we report the structure of the catalytic domain of recombinant human Artemis. The catalytic domain displayed a polypeptide fold similar overall to those of other members in the DNA cross-link repair gene SNM1 family and in mRNA 3'-end-processing endonuclease CPSF-73, containing metallo-β-lactamase and β-CASP domains and a cluster of conserved histidine and aspartate residues capable of binding two metal atoms in the catalytic site. As in SNM1A, only one zinc ion was located in the Artemis active site. However, Artemis displayed several unique features. Unlike in other members of this enzyme class, a second zinc ion was present in the β-CASP domain that leads to structural reorientation of the putative DNA-binding surface and extends the substrate-binding pocket to a new pocket, pocket III. Moreover, the substrate-binding surface exhibited a dominant and extensive positive charge distribution compared with that in the structures of SNM1A and SNM1B, presumably because of the structurally distinct DNA substrate of Artemis. The structural features identified here may provide opportunities for designing selective Artemis inhibitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

2.7 Å cryo-EM structure of rotavirus core protein VP3, a unique capping machine with a helicase activity

In many viruses, including rotavirus (RV), the major pathogen of infantile gastroenteritis, capping of viral messenger RNAs is a pivotal step for efficient translation of the viral genome. In RV, VP3 caps the nascent transcripts synthesized from the genomic dsRNA segments by the RV polymerase VP1 within the particle core. Here, from cryo–electron microscopy, x-ray crystallography, and biochemical analyses, we show that VP3 forms a stable tetrameric assembly with each subunit having a modular domain organization, which uniquely integrates five distinct enzymatic steps required for capping the transcripts. In addition to the previously known guanylyl- and methyltransferase activities, we show that VP3 exhibits hitherto unsuspected RNA triphosphatase activity necessary for initiating transcript capping and RNA helicase activity likely required for separating the RNA duplex formed transiently during endogenous transcription. From our studies, we propose a new mechanism for how VP3 inside the virion core caps the nascent transcripts exiting from the polymerase.

59 BASIC BIOLOGICAL SCIENCES↗

Preparation of a Deuterated Membrane Protein for Small-Angle Neutron Scattering

This chapter outlines a protocol developed to prepare a purified deuterated membrane protein for a small-angle neutron scattering (SANS) experiment. SANS is a noninvasive technique well suited to studying membrane protein solution structures, and deuteration enhances the signal from the protein over the background (Breyton et al., Eur Phys J E Soft Matter 36 (7):71, 2013; Garg et al., Biophys J 101 (2):370–377, 2011). We present our workflow: transformation of our plasmid into E. coli, cell growth and expression of our deuterated protein, membrane isolation, detergent solubilization, protein purification, purity assessment, and final preparation for SANS.

Wu, Yuqi↗

Molecular-dynamics simulation methods for macromolecular crystallography

It is investigated whether molecular-dynamics (MD) simulations can be used to enhance macromolecular crystallography (MX) studies. Historically, protein crystal structures have been described using a single set of atomic coordinates. Because conformational variation is important for protein function, researchers now often build models that contain multiple structures. Methods for building such models can fail, however, in regions where the crystallographic density is difficult to interpret, for example at the protein–solvent interface. To address this limitation, a set of MD–MX methods that combine MD simulations of protein crystals with conventional modeling and refinement tools have been developed. In an application to a cyclic adenosine monophosphate-dependent protein kinase at room temperature, the procedure improved the interpretation of ambiguous density, yielding an alternative water model and a revised protein model including multiple conformations. The revised model provides mechanistic insights into the catalytic and regulatory interactions of the enzyme. The same methods may be used in other MX studies to seek mechanistic insights.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding protein-complex assembly through grand canonical maximum entropy modeling

Inside a cell, heterotypic proteins assemble in inhomogeneous, crowded systems where the abundance of these proteins vary with cell types. While some protein complexes form putative structures that can be visualized with imaging, there are far more protein complexes that are yet to be solved because of their dynamic associations with one another. Nevertheless, it is possible to infer these protein complexes through a physical model. However, it is often not clear to physicists what kind of data from biology is necessary for such a modeling endeavor. Here, we aim to model these clusters of coarse-grained protein assemblies from multiple subunits through the constraints of interactions among the subunits and the chemical potential of each subunit. We obtained the constraints on the interactions among subunits from the known protein structures. We inferred the chemical potential that dictates the particle number distribution of each protein subunit from the knowledge of protein abundance from experimental data. Guided by the maximum entropy principle, we formulated an inverse statistical mechanical method to infer the distribution of particle numbers from the data of protein abundance as chemical potentials for a grand canonical multicomponent mixture. Using grand canonical Monte Carlo simulations, we captured a distribution of high-order clusters in a protein complex of succinate dehydrogenase with four known subunits. The complexity of hierarchical clusters varies with the relative protein abundance of each subunit in distinctive cell types such as lung, heart, and brain. When the crowding content increases, we observed that crowding stabilizes emergent clusters that do not exist in dilute conditions. We, therefore, proposed a testable hypothesis that the hierarchical complexity of protein clusters on a molecular scale is a plausible biomarker of predicting the phenotypes of a cell.

59 BASIC BIOLOGICAL SCIENCES↗

A Bis(imidazole)-based cysteine labeling tool for metalloprotein assembly

Precise metal-protein coordination by design remains a considerable challenge. Polydentate, high-metal-affinity protein modifications, both chemical and recombinant, can enable metal localization. However, these constructs are often bulky, conformationally and stereochemically ill-defined, or coordinately saturated. Here, we expand the biomolecular metal-coordination toolbox with the irreversible attachment to cysteine of bis(1-methylimidazol-2-yl)ethene (“BMIE”), which generates a compact imidazole-based metal-coordinating ligand. Conjugate additions of small-molecule thiols (thiocresol and N-Boc-Cys) with BMIE confirm general thiol reactivity. The BMIE adducts are shown to complex the divalent metal ions Cu ++ and Zn ++ in bidentate (N 2 ) and tridentate (N 2 S*) coordination geometries. Cysteine-targeted BMIE modification (>90% yield at pH 8.0) of a model protein, the S203C variant of carboxypeptidase G2 (CPG2), measured with ESI-MS, confirms its utility as a site-selective bioconjugation method. ICP-MS analysis confirms mono-metallation of the BMIE-modified CPG2 protein with Zn ++ , Cu ++ , and Co ++ . EPR characterization of the BMIE-modified CPG2 protein reveals the structural details of the site selective 1:1 BMIE-Cu ++ coordination and symmetric tetragonal geometry under physiological conditions and in the presence of various competing and exchangeable ligands (H 2 O/HO – , tris, and phenanthroline). An X-ray protein crystal structure of BMIE-modified CPG2-S203C demonstrates that the BMIE modification is minimally disruptive to the overall protein structure, including the carboxypeptidase active sites, although Zn ++ metalation could not be conclusively discerned at the resolution obtained. The carboxypeptidase catalytic activity of BMIE-modified CPG2-S203C was also assayed and found to be minimally affected. Finally, these features, combined with ease of attachment, define the new BMIE-based ligation as a versatile metalloprotein design tool, and enable future catalytic and structural applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural and spectroscopic characterization of photoactive yellow protein and photoswitchable fluorescent protein constructs containing heavy atoms

Photo-induced structural rearrangements of chromophore-containing proteins are essential for various light-dependent signaling pathways and optogenetic applications. Ultrafast structural and spectroscopic methods have offered insights into these structural rearrangements across many timescales. However, questions still remain about exact mechanistic details, especially regarding photoisomerization of the chromophore within these proteins femtoseconds to picoseconds after photoexcitation. Instrumentation advancements for time-resolved crystallography and ultrafast electron diffraction provide a promising opportunity to study these reactions, but achieving enough signal-to-noise is a constant challenge. In this work, we present four new photoactive yellow protein constructs and one new fluorescent protein construct that contain heavy atoms either within or around the chromophore and can be expressed with high yields. Structural characterization of these constructs, most at atomic resolution, show minimal perturbation caused by the heavy atoms compared to wild-type structures. Spectroscopic studies report the effects of the heavy atom identity and location on the chromophore’s photophysical properties. None of the substitutions prevent photoisomerization, although certain rates within the photocycle may be affected. Overall, these new proteins containing heavy atoms are ideal samples for state-of-the-art time-resolved crystallography and electron diffraction experiments to elucidate crucial mechanistic information of photoisomerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bump-and-Hole Engineering Identifies Specific Substrates of Glycosyltransferases in Living Cells

Studying posttranslational modifications classically relies on experimental strategies that oversimplify the complex biosynthetic machineries of living cells. Protein glycosylation contributes to essential biological processes, but correlating glycan structure, underlying protein, and disease-relevant biosynthetic regulation is currently elusive. Here, we engineer living cells to tag glycans with editable chemical functionalities while providing information on biosynthesis, physiological context, and glycan fine structure. We introduce a non-natural substrate biosynthetic pathway and use engineered glycosyltransferases to incorporate chemically tagged sugars into the cell surface glycome of the living cell. We apply the strategy to a particularly redundant yet disease-relevant human glycosyltransferase family, the polypeptide N-acetylgalactosaminyl transferases. This approach bestows a gain-of-chemical-functionality modification on cells, where the products of individual glycosyltransferases can be selectively characterized or manipulated to understand glycan contribution to major physiological processes.

59 BASIC BIOLOGICAL SCIENCES↗

Predicting receptor-ligand pairing preferences in plant-microbe interfaces via molecular dynamics and machine learning

Microbiome assembly, structure, and dynamics significantly influence plant health. Secreted microbial signaling molecules initiate and mediate symbiosis by binding to structurally compatible plant receptors. For example, lipo-chitooligosaccharides (LCOs), produced by nitrogen-fixing rhizobial bacteria and various fungi, are recognized by plant lysin motif receptor-like kinases (LysM-RLKs), which activate the common symbiotic pathway. Accurately predicting these molecular interactions could reveal complementary signatures underlying the initial stages of endosymbiosis. Despite the breakthrough in protein-ligand structure prediction with deep learning-based tools, such as AlphaFold3, the large size and highly flexible nature of signaling compounds like LCOs present major challenges for detailed structural characterization and binding-affinity prediction. Typical structure-/physics-based methods of ligand virtual screening are designed for small, drug-like molecules, often rely on high-resolution, experimentally determined structures of the protein receptors, and rarely achieve sufficient sampling to obtain converged thermodynamic quantities with large ligands. In this study, we developed a hybrid molecular dynamics/machine learning (MD/ML) approach capable of predicting binding affinity rankings with high accuracy in systems involving large, flexible ligands, despite limited experimental structural information. Using coarse initial structural models, the predictions using the MD/ML workflow achieved strong alignment with experimental trends, particularly in the top-affinity tier for four legume LysM-RLKs (LYR3) binding to LCOs and a chitooligosaccharide. Furthermore, the MD-based conformation selection protocol provided critical structural insights into substrate specificity and binding mechanisms. This study demonstrates a powerful method to screen for challenging cognate ligand-receptors and advance our understanding of the molecular basis of microbial colonization in plants.

Lipo-chitooligosaccharides↗

BIPSPI+: Mining Type-Specific Datasets of Protein Complexes to Improve Protein Binding Site Prediction

Computational approaches for predicting protein-protein interfaces are extremely useful for understanding and modelling the quaternary structure of protein assemblies. In particular, partner-specific binding site prediction methods allow delineating the specific residues that compose the interface of protein complexes. In recent years, new machine learning and other algorithmic approaches have been proposed to solve this problem. However, little effort has been made in finding better training datasets to improve the performance of these methods. With the aim of vindicating the importance of the training set compilation procedure, in this work we present BIPSPI+, a new version of our original server trained on carefully curated datasets that outperforms our original predictor. We show how prediction performance can be improved by selecting specific datasets that better describe particular types of protein interactions and interfaces (e.g. homo/hetero). In addition, our upgraded web server offers a new set of functionalities such as the sequence-structure prediction mode, hetero- or homo-complex specialization and the guided docking tool that allows to compute 3D quaternary structure poses using the predicted interfaces. BIPSPI+ is freely available at https://bipspi.cnb.csic.es.

59 BASIC BIOLOGICAL SCIENCES↗

Facile Labeling of Sieve Element Phloem-Protein Bodies Using the Reciprocal Oligosaccharide Probe OGA488

Sieve elements of many angiosperms contain structural phloem proteins (P-proteins) that can interact to create large P-protein bodies. P-protein bodies can occlude sieve plates upon injury but the range of functional and physiological roles of P-proteins remains uncertain, in part because of challenges in labeling and visualization methods. Here, we show that a reciprocal oligosaccharide probe, OGA 488 , can be used in rapid and sensitive labeling of P-protein bodies in Arabidopsis, poplar, snap bean and cucumber in histological sections. OGA 488 labeling of knockouts of the two Arabidopsis P-protein-encoding genes, AtSEOR1 and AtSEOR2 , indicated that labeling is specific to AtSEOR2. That protein bodies were labeled and visible in Atseor1 knockouts indicates that heterodimerization of AtSEOR1 and AtSEOR2 may not be necessary for P-protein body formation. Double labeling with a previously characterized stain for P-proteins, sulphorhodamine 101, confirmed P-protein labeling and also higher specificity of OGA 488 for P-proteins. OGA 488 is thus robust and easily used to label P-proteins in histological sections of multiple angiosperm species.

59 BASIC BIOLOGICAL SCIENCES↗

Charge Movement and Structural Changes in the Gas-Phase Unfolding of Multimeric Protein Complexes Captured by Native Top-Down Mass Spectrometry

The extent to which noncovalent protein complexes retain native structure in the gas phase is highly dependent on experimental conditions. Energetic collisions with background gas can cause structural changes ranging from unfolding to subunit dissociation. Additionally, recent studies have highlighted the role of charge in such structural changes, but the mechanism is not completely understood. In this study, native top down (native TD) mass spectrometry was used to probe gas-phase structural changes of alcohol dehydrogenase (ADH, 4mer) under varying degrees of in-source activation. Changes in covalent backbone fragments produced by electron capture dissociation (ECD) or 193 nm ultraviolet photodissociation (UVPD) were correlated to structural changes of the ADH 4mer. ECD fragments indicated unfolding started at the N-terminus, and the charge states of UVPD fragments enabled monitoring of charge migration to the unfolded regions. Interestingly, UVPD fragments also indicated that the charge at the “unfolding” N-terminus of ADH decreased at high in-source activation energies after the initial increase. We proposed a possible “refolding-after-unfolding” mechanism, as further supported by monitoring hydrogen elimination from radical a-ions produced by UVPD at the N-terminus of ADH. However, “refolding-after-unfolding” with increasing in-source activation was not observed for charge-reduced ADH, which likely adopted compact structures that are resistant to both charge migration and unfolding. Combined, these results support a charge-directed unfolding mechanism for protein complexes. Overall, an experimental framework was outlined for utilizing native TD to generate structure-informative mass spectral signatures for protein complexes that complement other structure characterization techniques, such as ion mobility spectrometry and computational modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A structural explanation for the mechanism and specificity of plant branching enzymes I and IIb

Branching enzymes (BEs) are essential in the biosynthesis of starch and glycogen and play critical roles in determining the fine structure of these polymers. The substrates of these BEs are long carbohydrate chains that interact with these enzymes via multiple binding sites on the enzyme’s surface. By controlling the branched-chain length distribution, BEs can mediate the physiological properties of starch and glycogen moieties; however, the mechanism and structural determinants of this specificity remain mysterious. In this study, we identify a large dodecaose binding surface on rice BE I (BEI) that reaches from the outside of the active site to the active site of the enzyme. Mutagenesis activity assays confirm the importance of this binding site in enzyme catalysis, from which we conclude that it is likely the acceptor chain binding site. Comparison of the structures of BE from Cyanothece and BE1 from rice allowed us to model the location of the donor-binding site. We also identified two loops that likely interact with the donor chain and whose sequences diverge between plant BE1, which tends to transfer longer chains, and BEIIb, which transfers exclusively much shorter chains. When the sequences of these loops were swapped with the BEIIb sequence, rice BE1 also became a short-chain transferring enzyme, demonstrating the key role these loops play in specificity. Taken together, these results provide a more complete picture of the structure, selectivity, and activity of BEs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combining pairwise structural similarity and deep learning interface contact prediction to estimate protein complex model accuracy in CASP15

Abstract Estimating the accuracy of quaternary structural models of protein complexes and assemblies (EMA) is important for predicting quaternary structures and applying them to studying protein function and interaction. The pairwise similarity between structural models is proven useful for estimating the quality of protein tertiary structural models, but it has been rarely applied to predicting the quality of quaternary structural models. Moreover, the pairwise similarity approach often fails when many structural models are of low quality and similar to each other. To address the gap, we developed a hybrid method (MULTICOM_qa) combining a pairwise similarity score (PSS) and an interface contact probability score (ICPS) based on the deep learning inter‐chain contact prediction for estimating protein complex model accuracy. It blindly participated in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 and performed very well in estimating the global structure accuracy of assembly models. The average per‐target correlation coefficient between the model quality scores predicted by MULTICOM_qa and the true quality scores of the models of CASP15 assembly targets is 0.66. The average per‐target ranking loss in using the predicted quality scores to rank the models is 0.14. It was able to select good models for most targets. Moreover, several key factors (i.e., target difficulty, model sampling difficulty, skewness of model quality, and similarity between good/bad models) for EMA are identified and analyzed. The results demonstrate that combining the multi‐model method (PSS) with the complementary single‐model method (ICPS) is a promising approach to EMA.

59 BASIC BIOLOGICAL SCIENCES↗

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↗