Protein Science最新文献

Molecular analysis of interactions between IgE antibody and allergen allows the structural basis of IgE recognition to be defined. Human IgE (hIgE) epitopes of respiratory lipocalin allergens, including Can f 1, remain elusive due to a lack of IgE-allergen complexes. This study aims to map the structure of allergenic epitopes on Can f 1. The fragment antigen-binding (Fab) regions of Can f 1 specific human IgE monoclonal antibodies (hIgE mAb) were used to determine the structures of IgE epitopes. Epitope mutants were designed to target Can f 1 epitopes. Immunoassays and a human FcεRIα transgenic mouse model of passive anaphylaxis in vivo were used to assess the functional activity of epitope mutants. Crystal structures of natural or recombinant Can f 1 complexed with two hIgE mAb 1J11 and 12F3 Fabs, respectively, were determined. The hIgE mAb bound to two partially overlapping epitopes and recognized two different Can f 1 conformations. The hIgE mAb 12F3 showed an unusual mode of binding by protruding its heavy chain CDR3 inside the Can f 1 calyx. Epitope mutants generated based on the structural analyses displayed a 64%-89% reduction in IgE antibody binding and failed to induce passive anaphylaxis in a human FcεRIα transgenic mouse model. In summary, the structures of Can f 1-hIgE Fab complexes revealed two unique and partially overlapping epitopes on Can f 1. The modification of the identified IgE epitopes provides a pathway for the design of hypoallergens to treat dog allergies.

Lectins are proteins or glycoproteins capable of binding specifically and reversibly to carbohydrates, a property that, in itself, gives them great functional versatility in organisms from all kingdoms of nature. A subclass of these proteins, called chimerolectins, is composed of proteins that have at least one lectin domain associated with another functional domain, such as enzymatic domains or modules involved in molecular signaling processes. The emergence of chimerolectins throughout evolution significantly expanded the functional repertoire of lectins, allowing their action to go beyond the interaction with carbohydrates and glycoconjugates. These proteins are involved in the regulation of the immune system in humans and animals, in the defense of plants against pathogens and predators, as well as in the mediation of responses to biotic and abiotic stresses. In addition, they can act as potent lethal toxins or as factors in the infection of several pathogens and are often associated with the manifestation of symptoms of diseases, which makes them therapeutic targets of great interest. Deepening the structural knowledge of these proteins has been essential for understanding their mechanisms of action, in addition to providing solid bases for biotechnological applications and for the rational development of artificial lectins with specific functions. This approach has enabled the creation of chimerolectins with potent antiviral activity, as well as the development of new therapeutic strategies aimed at inducing death in cells of different tumor lineages.

The fra locus of Salmonella enterica encodes five genes for metabolism of fructose-asparagine, an Amadori product formed by condensation of asparagine with glucose. In the last step of this pathway, the FraB deglycase cleaves 6-phospho-fructose-aspartate into glucose-6-phosphate and aspartate. In homology models, FraB forms a homodimer with two equivalent active sites located at the dimer interface. E214 and H230, two invariant residues essential for catalysis, project into each active site cleft from opposing subunits of the dimer. Here, we have determined six crystal structures of FraB, three of a variant containing an N-terminal His₆ tag and two mutations needed for crystallization (hereafter referred to as WT'), two with additional mutations to active site residues (E214A and P232A), and one of a variant with C-terminal residues 313-325 deleted. Surprisingly, in the WT' FraB structure, the two catalytic residues, E214 (general base) and H230 (general acid), are positioned ~22 Å apart. In the E214A and C-terminus-truncated FraB variants, however, a conformational change in the E214-residing helix brings E214 and H230* to ~7 Å (* indicates residue from the second protomer that creates the inter-subunit catalytic center). The loop bearing H230 also exhibits significant variation, ranging from being completely disordered to adopting open or closed states, with the nearby P232* residue being either cis or trans. The C-terminal residues 313-325 form a flexible "C-tail" that can be fully disordered, bind in the active site to block access of substrate, or angle across the active site to wrap across the other subunit of the dimer and potentially close over substrate. Collectively, these structures reveal that FraB is a conformational heterodimer with two chemically identical subunits that are constrained to adopt different structures as they come together for catalysis. This plasticity likely involves correlated opening and closure of the two active sites for their respective binding and release of substrates and ligands.

Despite the vast number of enzymatic kinetic measurements reported across decades of biochemical literature, the majority of relational enzyme kinetic data-linking amino acid sequence, substrate identity, kinetic parameters, and assay conditions-remains uncollected and inaccessible in structured form. This constitutes a significant portion of the "dark matter" of enzymology. Unlocking these hidden data through automated extraction offers an opportunity to expand enzyme dataset diversity and size, critical for building accurate, generalizable models that drive predictive enzyme engineering. To address this limitation, we built EnzyExtract, a large language model-powered pipeline that automates the extraction, verification, and structuring of enzyme kinetics data from scientific literature. By processing 137,892 full-text publications (PDF/XML), EnzyExtract collected more than 218,095 enzyme-substrate-kinetics entries, including 218,095 k_cat and 167,794 K_m values. These entries are mapped to enzymes spanning 3569 unique four-digit EC numbers, with a total of 84,464 entries assigned at least a first-digit EC number. EnzyExtract identified 89,544 unique kinetic entries (k_cat and K_m combined) absent from BRENDA, significantly expanding the known enzymology dataset. The newly curated dataset was compiled into a database named EnzyExtractDB. EnzyExtract demonstrates high accuracy when benchmarked against manually curated datasets and strong consistency with BRENDA-derived data. To create model-ready datasets, enzyme and substrate sequences were aligned to UniProt and PubChem, yielding 92,286 high-confidence, sequence-mapped kinetic entries. To assess the practical utility of our dataset, we retrained several state-of-the-art k_cat predictors (including MESI, DLKcat, and TurNuP) using EnzyExtractDB. Across held-out test sets, all models demonstrate improved predictive performance in terms of RMSE, MAE, and R², highlighting the value of high-quality, large-scale, literature-derived EnzyExtractDB for enhancing predictive modeling of enzyme kinetics. The EnzyExtract source code and the database are openly available at https://github.com/ChemBioHTP/EnzyExtract, and an interactive demo can be accessed via Google Colab at https://colab.research.google.com/drive/1MwKSEZzLPNOseksRshbzkkFoO_cgJhva.

The process of protein phase separation, particularly in the context of intrinsically disordered proteins, has been extensively studied for its implications in several neurodegenerative diseases. Although the mechanism of protein phase separation and the involved molecular grammar have been well explored under in vitro conditions, the focus is now shifting toward developing more complex models of phase separation in order to mimic the biological systems closely. Here, we studied the phase separation of alpha synuclein (α-syn), an intrinsically disordered protein whose aggregation is implicated in the pathology of Parkinson's disease inside yeast cells (Saccharomyces cerevisiae). Using a positively charged polymer, polyethylenimine (PEI), which binds presumably at the negatively charged C-terminal domain of α-syn, we find that the aggregation of α-syn inside yeast can be modulated by at least two pathways: one involving phase separation and the second one without phase separation. We find further that these two pathways lead to varying fibril characteristics and toxicities. We believe that this model can be used as a quick and convenient system to screen novel and repurposed small molecules against toxic protein droplets.

In this study, we analyzed large-scale T-cell receptor (TCR) sequence data to determine whether TCRs preferentially bind to major histocompatibility complex (MHC) class I (CD8+) or class II (CD4+) epitopes. Using the International ImMunoGeneTics information system numbering scheme, we identified specific positions with distinct amino acid enrichment for each MHC class and developed machine learning models for classification. While our frequency-based approach effectively differentiated MHC-I from MHC-II TCRs in cross-validation, performance declined when only beta chain data were used from real-world peripheral blood mononuclear cell samples. However, incorporating the TCR alpha chain significantly improved accuracy, emphasizing its importance for MHC recognition. Overall, we found that V-region loops can signal MHC class bias, aiding in immunotherapy design and TCR repertoire analysis, while highlighting the need for larger, more diverse datasets for reliable predictions.

In this study, we investigate the detergent-induced behavior of the integral membrane protein ShuA in solution, focusing on its interactions with octyl polyoxyethylene (OPOE) and n-dodecyl-β-D-maltoside (DDM). Using a combination of size-exclusion chromatography coupled with multi-angle light scattering (SEC-MALS) and small-angle scattering techniques (SAXS and SANS), we provide a detailed characterization of the protein-detergent complex (PDC) behavior under varying conditions. Our results reveal that ShuA remains monomeric in 1% OPOE, whereas in 0.5 mM DDM, it undergoes a reversible monomer/dimer equilibrium that shifts towards a monodisperse, monomeric state with increasing DDM concentration to 7.5 mM, highlighting the significant influence of detergent type and concentration on protein colloidal stability. These findings have direct implications for membrane protein purification and structural studies, particularly in crystallization and cryo-EM sample preparation. The study emphasizes the necessity of optimizing detergent conditions to ensure monodispersity and structural integrity, preventing detergent-induced artifacts that could affect structural interpretations. Importantly, our results highlight the power of the SEC-MALS technique in determining oligomeric or association equilibrium states, detecting weak intermolecular interactions often overlooked in conventional SEC, and achieving this even in the particularly complex case of MPs. By integrating advanced scattering techniques, this work contributes valuable insights into MP colloidal behavior, refining strategies for structural characterization and providing a framework for optimizing detergent conditions in biochemical and biophysical studies.

A protein's energy landscape, all accessible conformations, their populations, and dynamics of interconversion, is encoded in its primary sequence. While how this sequence encodes a protein's native state is well understood, how it encodes the dynamics, such as the kinetic barriers for unfolding and refolding, is not. Here we have looked at two subtiliase homologs from Bacillus subtilis, Intracellular Subtilisin Protease 1 (ISP1) and Subtilisin E (SbtE), that are expected to have very different dynamics. ISP1, an intracellular protein, has a small pro-domain thought to act simply as a zymogen, whereas the extracellular SbtE has a large pro-domain required for folding. The stability and kinetics of the mature proteins have been previously characterized; here we compare their energy landscapes with and without the pro-domain, examining global and local energetics of the mature proteases and the effect of each pro-domain. We find that ISP1's pro-domain has limited impact on the energy landscape of the mature protein. For SbtE, the protein is thermodynamically unstable and kinetically trapped without the pro-domain. The pro-domains' effects on the flexibility of the core of the proteins are different: in the absence of its pro-domain, ISP1's core becomes more flexible, while SbtE's core becomes more rigid. ISP1 contains a conserved insertion, which points to a potential source for these differences. These homologs show how changes in the primary sequence can dramatically alter a protein's energy landscape and highlight the need for large-scale, high-throughput studies on the relationship between primary sequence and conformational dynamics.

Lanthipeptides are a class of thioether-containing ribosomally synthesized and post-translationally modified peptides, which often have antibiotic activity. As a potential starting point for therapeutics, interest in engineering lanthipeptides is growing. Our inability to computationally model and design lanthipeptides in molecular modeling and design software such as Rosetta limits our ability to rationally design lanthipeptides for drug discovery campaigns. We propose that implementing support for the lanthionine rings and dehydrated amino acids found in lanthipeptides will enable accurate lanthipeptide modeling with Rosetta. We find that when compared to the ensembles of lanthipeptides with NMR-determined structures in the PDB, lanthipeptide ensembles generated with Rosetta have similar experimental agreement, lower Rosetta energy scores, and greater flexibility. Our use of ensemble-averaged NOE distances instead of requiring individual structures to satisfy all NOE restraints was key for revealing the flexibility of these peptides. Our Rosetta lanthipeptide ensembles show increased flexibility in non-cyclized peptide regions as well as increased lanthionine ring flexibility when internal hydrogen bonds are absent and glycine residues are present. Support for lanthipeptides in Rosetta enables the design and modeling of lanthipeptides in Rosetta for therapeutic development.

N6-adenine (6mA) DNA methylation plays an important role in gene regulation and genome stability. The 6mA methylation in Tetrahymena thermophila is mainly mediated by the AMT complex, comprised of the AMT1, AMT7, AMTP1, and AMTP2 subunits. To date, how this complex assembles on the DNA substrate remains elusive. Here we report the structure of the AMT complex bound to the OCR protein from bacteriophage T7, mimicking the AMT-DNA encounter complex. The AMT1-AMT7 heterodimer approaches OCR from one side, while the AMTP1 N-terminal domain, assuming a homeodomain fold, binds to OCR from the other side, resulting in a saddle-shaped architecture reminiscent of what was observed for prokaryotic 6mA writers. Mutation of the AMT1, AMT7, and AMTP1 residues on the OCR-contact points led to impaired DNA methylation activity to various extents, supporting a role for these residues in DNA binding. Furthermore, structural comparison of the AMT1-AMT7 subunits with the evolutionarily related METTL3-METTL14 and AMT1-AMT6 complexes reveals sequence conservation and divergence in the region corresponding to the OCR-binding site, shedding light on the substrate binding of the latter two complexes. Together, this study supports a model in which the AMT complex undergoes a substrate binding-induced open-to-closed conformational transition, with implications in its substrate binding and processive 6mA methylation.