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Allosteric regulation plays a crucial role in modulating protein functions and represents a promising strategy in drug development, offering enhanced specificity and reduced toxicity compared to traditional active site inhibition. Existing computational methods for predicting allosteric sites on proteins often rely on static protein surface pocket features, normal mode analysis or extensive molecular dynamics simulations encompassing both the protein function modulator and the protein itself. In this study, we introduce an innovative methodology that employs a per amino acid residue classifier to distinguish allosteric site-forming residues (AFRs) from non-allosteric, or free residues (FRs). Our model, STINGAllo, exhibits robust performance, achieving Distance Center Center (DCC) success rate when all AFRs were predicted within pockets identified by FPocket, overall DCC, F1 score and a Matthews correlation coefficient (MCC) of 78 %, 60 %, 64 % and 64 % respectively. Furthermore, we identified key descriptors that characterize the internal protein nanoenvironment of AFRs, setting them apart from FRs. These descriptors include the sponge effect, distance to the protein centre of geometry (cg), hydrophobic interactions, electrostatic potentials, eccentricity, and graph bottleneck features.

The evolutionary conserved Notch signaling pathway functions as a mediator of direct cell–cell communication between neighboring cells during development. Notch plays a crucial role in various fundamental biological processes in a wide range of tissues. Accordingly, the aberrant signaling of this pathway underlies multiple genetic pathologies such as developmental syndromes, congenital disorders, neurodegenerative diseases, and cancer. Over the last two decades, significant data have shown that the Notch signaling pathway displays a significant function in the mature brains of vertebrates and invertebrates beyond neuronal development and specification during embryonic development. Neuronal connection, synaptic plasticity, learning, and memory appear to be regulated by this pathway. Specific mutations in human Notch family proteins have been linked to several neurodegenerative diseases including Alzheimer's disease, CADASIL, and ischemic injury. Neurodegenerative diseases are incurable disorders of the central nervous system that cause the progressive degeneration and/or death of brain nerve cells, affecting both mental function and movement (ataxia). There is currently a lot of study being conducted to better understand the molecular mechanisms by which Notch plays an essential role in the mature brain. In this study, an in silico analysis of polymorphisms and mutations in human Notch family members that lead to neurodegenerative diseases was performed in order to investigate the correlations among Notch family proteins and neurodegenerative diseases. Particular emphasis was placed on the study of mutations in the Notch3 protein and the structure analysis of the mutant Notch3 protein that leads to the manifestation of the CADASIL syndrome in order to spot possible conserved mutations and interpret the effect of these mutations in the Notch3 protein structure. Conserved mutations of cysteine residues may be candidate pharmacological targets for the potential therapy of CADASIL syndrome. [ABSTRACT FROM AUTHOR]

Research background. Peanut allergy poses a significant threat to human health due to the increased risk of long-term morbidity at low doses. Modifying protein structure to affect sensitization is a popular topic. Experimental approach. In this study, the purified peanut allergen Ara h 1 was enzymatically hydrolysed using Flavourzyme, alkaline protease or a combination of both. The binding ability of Ara h 1 to antibodies, gene expression and secretion levels of the proinflammatory factors interleukin-5 and interleukin-6 in Caco-2 cells was measured. Changes in the secondary and tertiary structures before and after treatment with Ara h 1 were analysed by circular dichroism and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Results and conclusions. The results indicated a decrease of the allergenicity and proinflammatory ability of Ara h 1. The evaluation showed that the Flavourzyme and alkaline protease treatments caused particle shortening and aggregation. The fluorescence emission peak increased by 3.4-fold after the combined treatment with both proteases. Additionally, the secondary structure underwent changes and the hydrophobicity also increased 8.95-fold after the combined treatment. Novelty and scientific contribution. These findings partially uncover the mechanism of peanut sensitization and provide an effective theoretical basis for the development of a new method of peanut desensitization.

Abstract Regulation of amino acid’s biosynthetic pathway is of significant importance to maintain homeostasis and cell functions. Amino acids regulate their biosynthetic pathway by end-product feedback inhibition of enzymes catalyzing committed steps of a pathway. Discovery of new feedback resistant enzyme variants to enhance industrial production of amino acids is a key objective in industrial biotechnology. Deregulation of feedback inhibition has been achieved for various enzymes using in vitro and in silico mutagenesis techniques. As enzyme’s function, its substrate binding capacity, catalysis activity, regulation and stability are dependent on its structural characteristics, here, we provide detailed structural analysis of all feedback sensitive enzyme targets in amino acid biosynthetic pathways. Current review summarizes information regarding structural characteristics of various enzyme targets and effect of mutations on their structures and functions especially in terms of deregulation of feedback inhibition. Furthermore, applicability of various experimental as well as computational mutagenesis techniques to accomplish feedback resistance has also been discussed in detail to have an insight into various aspects of research work reported in this particular field of study.

Regulation of amino acid's biosynthetic pathway is of significant importance to maintain homeostasis and cell functions. Amino acids regulate their biosynthetic pathway by end-product feedback inhibition of enzymes catalyzing committed steps of a pathway. Discovery of new feedback resistant enzyme variants to enhance industrial production of amino acids is a key objective in industrial biotechnology. Deregulation of feedback inhibition has been achieved for various enzymes using in vitro and in silico mutagenesis techniques. As enzyme's function, its substrate binding capacity, catalysis activity, regulation and stability are dependent on its structural characteristics, here, we provide detailed structural analysis of all feedback sensitive enzyme targets in amino acid biosynthetic pathways. Current review summarizes information regarding structural characteristics of various enzyme targets and effect of mutations on their structures and functions especially in terms of deregulation of feedback inhibition. Furthermore, applicability of various experimental as well as computational mutagenesis techniques to accomplish feedback resistance has also been discussed in detail to have an insight into various aspects of research work reported in this particular field of study. [ABSTRACT FROM AUTHOR]

Proteins are essential macromolecules that carry out a plethora of biological functions. The thermal stability of proteins is an important property that affects their function and determines their suitability for various applications. However, current experimental approaches, primarily thermal proteome profiling, are expensive, labor-intensive, and have limited proteome and species coverage. To close the gap between available experimental data and sequence information, a novel protein thermal stability predictor called DeepSTABp has been developed. DeepSTABp uses a transformer-based protein language model for sequence embedding and state-of-the-art feature extraction in combination with other deep learning techniques for end-to-end protein melting temperature prediction. DeepSTABp can predict the thermal stability of a wide range of proteins, making it a powerful and efficient tool for large-scale prediction. The model captures the structural and biological properties that impact protein stability, and it allows for the identification of the structural features that contribute to protein stability. DeepSTABp is available to the public via a user-friendly web interface, making it accessible to researchers in various fields. [ABSTRACT FROM AUTHOR]

ABSTRACT Viruses with large, double-stranded DNA genomes captured the majority of their genes from their hosts at different stages of evolution. The origins of many virus genes are readily detected through significant sequence similarity with cellular homologs. In particular, this is the case for virus enzymes, such as DNA and RNA polymerases or nucleotide kinases, that retain their catalytic activity after capture by an ancestral virus. However, a large fraction of virus genes have no readily detectable cellular homologs, meaning that their origins remain enigmatic. We explored the potential origins of such proteins that are encoded in the genomes of orthopoxviruses, a thoroughly studied virus genus that includes major human pathogens. To this end, we used AlphaFold2 to predict the structures of all 214 proteins that are encoded by orthopoxviruses. Among the proteins of unknown provenance, structure prediction yielded clear indications of origin for 14 of them and validated several inferences that were previously made via sequence analysis. A notable emerging trend is the exaptation of enzymes from cellular organisms for nonenzymatic, structural roles in virus reproduction that is accompanied by the disruption of catalytic sites and by an overall drastic divergence that precludes homology detection at the sequence level. Among the 16 orthopoxvirus proteins that were found to be inactivated enzyme derivatives are the poxvirus replication processivity factor A20, which is an inactivated NAD-dependent DNA ligase; the major core protein A3, which is an inactivated deubiquitinase; F11, which is an inactivated prolyl hydroxylase; and more similar cases. For nearly one-third of the orthopoxvirus virion proteins, no significantly similar structures were identified, suggesting exaptation with subsequent major structural rearrangement that yielded unique protein folds. IMPORTANCE Protein structures are more strongly conserved in evolution than are amino acid sequences. Comparative structural analysis is particularly important for inferring the origins of viral proteins that typically evolve at high rates. We used a powerful protein structure modeling method, namely, AlphaFold2, to model the structures of all orthopoxvirus proteins and compared them to all available protein structures. Multiple cases of recruitment of host enzymes for structural roles in viruses, accompanied by the disruption of catalytic sites, were discovered. However, many viral proteins appear to have evolved unique structural folds.

The identification and characterization of the structural sites which contribute to protein function are crucial for understanding biological mechanisms, evaluating disease risk, and developing targeted therapies. However, the quantity of known protein structures is rapidly outpacing our ability to functionally annotate them. Existing methods for function prediction either do not operate on local sites, suffer from high false positive or false negative rates, or require large site‐specific training datasets, necessitating the development of new computational methods for annotating functional sites at scale. We present COLLAPSE (Compressed Latents Learned from Aligned Protein Structural Environments), a framework for learning deep representations of protein sites. COLLAPSE operates directly on the 3D positions of atoms surrounding a site and uses evolutionary relationships between homologous proteins as a self‐supervision signal, enabling learned embeddings to implicitly capture structure–function relationships within each site. Our representations generalize across disparate tasks in a transfer learning context, achieving state‐of‐the‐art performance on standardized benchmarks (protein–protein interactions and mutation stability) and on the prediction of functional sites from the Prosite database. We use COLLAPSE to search for similar sites across large protein datasets and to annotate proteins based on a database of known functional sites. These methods demonstrate that COLLAPSE is computationally efficient, tunable, and interpretable, providing a general‐purpose platform for computational protein analysis. [ABSTRACT FROM AUTHOR]

The mammalian target of rapamycin (mTOR) is an important biological target for development of novel anticancer drugs and potential antiageing agents. Therefore, many scientific groups search for mTOR kinase inhibitors. Herein, we present structure‐based approach which could be helpful in the studies on new bioactive compounds. Method validation was preceded by structural analysis of ATP catalytic cleft and FRB domain. In silico studies allowed us to point crucial amino acid residues for ligand binding and develop optimal docking protocols. The presented methodology could be applied for design and development of potential mTOR kinase inhibitors. [ABSTRACT FROM AUTHOR]

The protein vitellogenin (Vg) plays a central role in lipid transportation in most egg‐laying animals. High Vg levels correlate with stress resistance and lifespan potential in honey bees (Apis mellifera). Vg is the primary circulating zinc‐carrying protein in honey bees. Zinc is an essential metal ion in numerous biological processes, including the function and structure of many proteins. Measurements of Zn2+ suggest a variable number of ions per Vg molecule in different animal species, but the molecular implications of zinc‐binding by this protein are not well‐understood. We used inductively coupled plasma mass spectrometry to determine that, on average, each honey bee Vg molecule binds 3 Zn2+‐ions. Our full‐length protein structure and sequence analysis revealed seven potential zinc‐binding sites. These are located in the β‐barrel and α‐helical subdomains of the N‐terminal domain, the lipid binding site, and the cysteine‐rich C‐terminal region of unknown function. Interestingly, two potential zinc‐binding sites in the β‐barrel can support a proposed role for this structure in DNA‐binding. Overall, our findings suggest that honey bee Vg bind zinc at several functional regions, indicating that Zn2+‐ions are important for many of the activities of this protein. In addition to being potentially relevant for other egg‐laying species, these insights provide a platform for studies of metal ions in bee health, which is of global interest due to recent declines in pollinator numbers. [ABSTRACT FROM AUTHOR]

PDBsum1 is a standalone set of programs to perform the same structural analyses as provided by the PDBsum web server (https://www.ebi.ac.uk/pdbsum). The server has pages for every entry in the Protein Data Bank (PDB) and can also process user‐uploaded PDB files, returning a password‐protected set of pages that are retained for around 3 months. The standalone version described here allows for in‐house processing and indefinite retention of the results. All data files and images are pre‐generated, rather than on‐the‐fly as in the web version, so can be easily accessed. The program runs on Linux, Windows, and mac operating systems and is freely available for academic use at https://www.ebi.ac.uk/thornton-srv/software/PDBsum1. [ABSTRACT FROM AUTHOR]

DNA damage repair (DDR) pathways modulate cancer risk, progression, and therapeutic response. We systematically analyzed somatic alterations to provide a comprehensive view of DDR deficiency across 33 cancer types. Mutations with accompanying loss of heterozygosity were observed in over 1/3 of DDR genes, including TP53 and BRCA1/2. Other prevalent alterations included epigenetic silencing of the direct repair genes EXO5, MGMT, and ALKBH3 in ∼20% of samples. Homologous recombination deficiency (HRD) was present at varying frequency in many cancer types, most notably ovarian cancer. However, in contrast to ovarian cancer, HRD was associated with worse outcomes in several other cancers. Protein structure-based analyses allowed us to predict functional consequences of rare, recurrent DDR mutations. A new machine-learning-based classifier developed from gene expression data allowed us to identify alterations that phenocopy deleterious TP53 mutations. These frequent DDR gene alterations in many human cancers have functional consequences that may determine cancer progression and guide therapy.

SUMMARY: Large enzyme families catalyze metabolic diversification by virtue of their ability to use diverse chemical scaffolds. How enzyme families attain such functional diversity is not clear. Furthermore, duplication and promiscuity in such enzyme families limits their functional prediction, which has produced a burgeoning set of incompletely annotated genes in plant genomes. Here, we address these challenges using BAHD acyltransferases as a model. This fast‐evolving family expanded drastically in land plants, increasing from one to five copies in algae to approximately 100 copies in diploid angiosperm genomes. Compilation of >160 published activities helped visualize the chemical space occupied by this family and define eight different classes based on structural similarities between acceptor substrates. Using orthologous groups (OGs) across 52 sequenced plant genomes, we developed a method to predict BAHD acceptor substrate class utilization as well as origins of individual BAHD OGs in plant evolution. This method was validated using six novel and 28 previously characterized enzymes and helped improve putative substrate class predictions for BAHDs in the tomato genome. Our results also revealed that while cuticular wax and lignin biosynthetic activities were more ancient, anthocyanin acylation activity was fixed in BAHDs later near the origin of angiosperms. The OG‐based analysis enabled identification of signature motifs in anthocyanin‐acylating BAHDs, whose importance was validated via molecular dynamic simulations, site‐directed mutagenesis and kinetic assays. Our results not only describe how BAHDs contributed to evolution of multiple chemical phenotypes in the plant world but also propose a biocuration‐enabled approach for improved functional annotation of plant enzyme families. Significance Statement: Large enzyme families contribute significantly to the metabolic diversity observed in plants, but our knowledge about how these families attain such functional diversity and whether we can predict their functions is limited. To address these challenges, we used an orthology‐based approach coupled with extensive curation of functional data from literature, using the BAHD acyltransferase family as a model. This approach helped predict BAHD substrate class use and provided insights into the family's functional diversification during the evolution of the plant kingdom. [ABSTRACT FROM AUTHOR]

Allosteric regulation plays a crucial role in modulating protein functions and represents a promising strategy in drug development, offering enhanced specificity and reduced toxicity compared to traditional active site inhibition. Existing computational methods for predicting allosteric sites on proteins often rely on static protein surface pocket features, normal mode analysis or extensive molecular dynamics simulations encompassing both the protein function modulator and the protein itself. In this study, we introduce an innovative methodology that employs a per amino acid residue classifier to distinguish allosteric site-forming residues (AFRs) from non-allosteric, or free residues (FRs). Our model, STINGAllo, exhibits robust performance, achieving Distance Center Center (DCC) success rate when all AFRs were predicted within pockets identified by FPocket, overall DCC, F1 score and a Matthews correlation coefficient (MCC) of 78 %, 60 %, 64 % and 64 % respectively. Furthermore, we identified key descriptors that characterize the internal protein nanoenvironment of AFRs, setting them apart from FRs. These descriptors include the sponge effect, distance to the protein centre of geometry (cg), hydrophobic interactions, electrostatic potentials, eccentricity, and graph bottleneck features., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Exogenous exposure to high concentrations of microplastics (MPs) cause oxidative damage to freshwater food chains (FFCs). Thus, the patterns and mechanisms of oxidative stress responses (OSRs) induced by MPs in FFC organisms were investigated using theoretical simulation methods. Results showed an increasing (reduced) OSR was found in lower trophic levels (higher trophic levels). Besides, polycarbonate (polyvinyl chloride) causes the most (least) significant OSRs in FFC organisms, respectively. The impacts of MP additives were also analyzed using the full factorial experimental design, revealing flame retardants significantly influence oxidative stress variability. A constructive solution of "restriction-control-focus" is proposed for different types of MPs by the coefficient of variation-corrected CRITIC and the nested mean classification method. The mechanism analysis revealed a positive correlation between protein secondary structure orderliness and OSRs. Proteins in organisms that contain a high proportion of hydrophobic non-polar amino acids are more likely to bind to MP and enhance OSRs. This is the first study assessing the OSR patterns and ecological risks of MPs and their additives in FFCs with a proposed priority list, providing theoretical support for risk assessments and management strategies in freshwater environments., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

We demonstrate the usage of Bio3D-web for the interactive analysis of biomolecular structure data. The Bio3D-web application provides online functionality for: (1) The identification of related protein structure sets to user specified thresholds of similarity; (2) Their multiple alignment and structure superposition; (3) Sequence and structure conservation analysis; (4) Inter-conformer relationship mapping with principal component analysis, and (5) comparison of predicted internal dynamics via ensemble normal mode analysis. This integrated functionality provides a complete online workflow for investigating sequence-structure-dynamic relationships within protein families and superfamilies.

Coiled-coils are essential components of many protein complexes. First discovered in structural proteins such as keratins, they have since been found to figure largely in the assembly and dynamics required for diverse functions, including membrane fusion, signal transduction and motors. Coiled-coils have a characteristic repeating seven-residue geometric and sequence motif, which is sometimes interrupted by the insertion of one or more residues. Such insertions are often highly conserved and critical to interdomain communication in signaling proteins such as bacterial histidine kinases. Here we develop the "accommodation index" as a parameter that allows automatic detection and classification of insertions based on the three dimensional structure of a protein. This method allows precise identification of the type of insertion and the "accommodation length" over which the insertion is structurally accommodated. A simple theory is presented that predicts the structural perturbations of 1, 3, 4 residue insertions as a function of the length over which the insertion is accommodated. Analysis of experimental structures is in good agreement with theory, and shows that short accommodation lengths give rise to greater perturbation of helix packing angles, changes in local helical phase, and increased structural asymmetry relative to long accommodation lengths. Cytoplasmic domains of histidine kinases in different signaling states display large changes in their accommodation lengths, which can now be seen to underlie diverse structural transitions including symmetry/asymmetry and local variations in helical phase that accompany signal transduction.

ABSTRACT Hepatitis-hydropericardium syndrome (HHS) induced by fowl adenovirus serotype 4 (FAdV-4) has caused huge economic losses to poultry industries. The key genes responsible for different virulence of FAdV-4 strains are not fully elucidated. Previous studies indicated that hexon of pathogenic FAdV-4 has a conserved arginine (R) at position 188, and a conserved isoleucine (I) is present at this position in reported nonpathogenic FAdV-4. Recently, it was reported that R188 of hexon is the determinant site for pathogenicity of the emerging Chinese FAdV-4 strain. However, the role of hexon amino acid 188 (aa188) has not been examined in the nonpathogenic FAdV-4 strain. In this study, three recombinant FAdV-4 viruses, H/H/R188I, O/O/I188R, and H/O/I188R, were constructed by mutating hexon aa188 of FAdV-4 pathogenic strain CH/HNJZ/2015 (H) and nonpathogenic strain ON1 (O), and pathogenicity was assessed in specific-pathogen-free (SPF) chickens. Consistent with previous findings, H/O/I188R exhibited pathogenicity similar to that of CH/HNJZ/2015, yet H/H/R188I induced no mortality. Unexpectedly, all chickens infected with O/O/I188R survived. Postmortem examination of O/O/I188R-infected chickens showed typical lesions of inclusion body hepatitis rather than HHS. Expression of proinflammatory cytokines in CH/HNJZ/2015- and H/O/I188R-infected chickens was significantly higher than that in H/H/R188I-, ON1-, and O/O/I188R-infected chickens. Analysis of predicted hexon protein structures indicated that aa188 mutation leads to conformational changes in the L1 loop of HNJZ-hexon but not in ON1-hexon. In summary, the present study demonstrated that the role of hexon aa188 in the virulence of FAdV-4 varies between different strains. Induction of HHS requires factors aside from hexon aa188 in the emerging Chinese FAdV-4 strain. IMPORTANCE HHS induced by FAdV-4 has caused huge economic losses to the poultry industry. The key determinants for the different virulence of FAdV-4 have not been fully elucidated. Here, we investigated the role of hexon aa188 in FAdV-4 strains with different virulence and showed that the role of hexon aa188 varies in FAdV-4 strains with different genetic contents. The hexon R188 may be the key amino acid for causing inclusion body hepatitis by the pathogenic FAdV-4 strain, and induction of HHS by FAdV-4 may need other viral cofactors. Moreover, the hexon R188I mutation greatly affected the expression of proinflammatory cytokines induced by the pathogenic strain CH/HNJZ/2015, but no significant difference was observed between the nonpathogenic strain ON1 and ON1 with hexon I188R mutation. We found that hexon aa188 mutation induced conformational changes to hexon protein in CH/HNJZ/2015 but not in ON1, which might be the underlying reason for the changing virulence.

Recent advances in the field of protein structure determination using liquid-state NMR enable the elucidation of multi-state protein conformations that can provide insight into correlated and non-correlated protein dynamics at atomic resolution. So far, NMR-derived multi-state structures were typically evaluated by means of visual inspection of structure superpositions, target function values that quantify the violation of experimented restraints and root-mean-square deviations that quantify similarity between conformers. As an alternative or complementary approach, we present here the use of a recently introduced structural correlation measure, PDBcor, that quantifies the clustering of protein states as an additional measure for multi-state protein structure analysis. It can be used for various assays including the validation of experimental distance restraints, optimization of the number of protein states, estimation of protein state populations, identification of key distance restraints, NOE network analysis and semiquantitative analysis of the protein correlation network. We present applications for the final quality analysis stages of typical multi-state protein structure calculations. [ABSTRACT FROM AUTHOR]

The PDBsum web server provides structural analyses of the entries in the Protein Data Bank (PDB). Two recent additions are described here. The first is the detailed analysis of the SARS‐CoV‐2 virus protein structures in the PDB. These include the variants of concern, which are shown both on the sequences and 3D structures of the proteins. The second addition is the inclusion of the available AlphaFold models for human proteins. The pages allow a search of the protein against existing structures in the PDB via the Sequence Annotated by Structure (SAS) server, so one can easily compare the predicted model against experimentally determined structures. The server is freely accessible to all at http://www.ebi.ac.uk/pdbsum. [ABSTRACT FROM AUTHOR]

[Display omitted] High hydrostatic pressure treatment causes structural changes in interfacial-active β-lactoglobulin (β-lg). We hypothesized that the pressure-induced structural changes affect the intra- and intermolecular interactions which determine the interfacial activity of β-lg. The conducted experimental and numerical investigations could contribute to the mechanistic understanding of the adsorption behavior of proteins in food-related emulsions. We treated β-lg in water at pH 7 with high hydrostatic pressures up to 600 MPa for 10 min at 20 °C. The secondary structure was characterized with Fourier-transform infrared spectroscopy (FTIR) and circular dichroism (CD), the surface hydrophobicity and charge with fluorescence-spectroscopy and ζ-potential, and the quaternary structure with membrane-osmometry, analytical ultracentrifugation (AUC) and mass spectrometry (MS). Experimental analyses were supported through molecular dynamic (MD) simulations. The adsorption behavior was investigated with pendant drop analysis. MD simulation revealed a pressure-induced molten globule state of β-lg, confirmed by an unfolding of β-sheets with FTIR, a stabilization of α-helices with CD and loss in tertiary structure induced by an increase in surface hydrophobicity. Membrane-osmometry, AUC and MS indicated the formation of non-covalently linked dimers that migrated slower through the water phase, adsorbed more quickly due to hydrophobic interactions with the oil, and lowered the interfacial tension more strongly than reference β-lg. [ABSTRACT FROM AUTHOR]

Abstract Background Glomerulopathy with fibronectin deposits is an autosomal dominant disease associated with proteinuria, hematuria, hypertension and renal function decline. Forty percent of the cases are caused by mutations in FN1, the gene that encodes fibronectin. Case presentation This report describes two cases of Glomerulopathy with fibronectin deposits, involving a 47-year-old father and a 14-year-old son. The renal biopsies showed glomeruli with endocapillary hypercellularity and large amounts of mesangial and subendothelial eosinophilic deposits. Immunohistochemistry for fibronectin was markedly positive. Whole exome sequencing identified a novel FN1 mutation that leads to an amino-acid deletion in both patients (Ile1988del), a variant that required primary amino-acid sequence analysis for assessment of pathogenicity. Our primary sequence analyses revealed that Ile1988 is very highly conserved among relative sequences and is positioned in a C-terminal FN3 domain containing heparin- and fibulin-1-binding sites. This mutation was predicted as deleterious and molecular mechanics simulations support that it can change the tertiary structure and affect the complex folding and its molecular functionality. Conclusion The current report not only documents the occurrence of two GFND cases in an affected family and deeply characterizes its anatomopathological features but also identifies a novel pathogenic mutation in FN1, analyzes its structural and functional implications, and supports its pathogenicity.

Research Background: Peanut allergy poses a significant threat to human health due to the increased risk of long-term morbidity at low doses. Modifying protein structure to affect sensitization is a popular topic., Experimental Approach: In this study, the purified peanut allergen Ara h 1 was enzymatically hydrolysed using Flavourzyme, alkaline protease or a combination of both. The binding ability of Ara h 1 to antibodies, gene expression and secretion levels of the proinflammatory factors interleukin-5 and interleukin-6 in Caco-2 cells was measured. Changes in the secondary and tertiary structures before and after treatment with Ara h 1 were analysed by circular dichroism and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE)., Results and Conclusions: The results indicated a decrease of the allergenicity and proinflammatory ability of Ara h 1. The evaluation showed that the Flavourzyme and alkaline protease treatments caused particle shortening and aggregation. The fluorescence emission peak increased by 3.4-fold after the combined treatment with both proteases. Additionally, the secondary structure underwent changes and the hydrophobicity also increased 8.95-fold after the combined treatment., Novelty and Scientific Contribution: These findings partially uncover the mechanism of peanut sensitization and provide an effective theoretical basis for the development of a new method of peanut desensitization., Competing Interests: CONFLICT OF INTEREST This article is an original work and no portion of the study has been published or is under consideration for publication elsewhere. None of the authors has any potential conflicts of interest related to this manuscript. All authors have contributed to the work and have agreed to submit the manuscript., (Authors.)

The native structure of a protein is important for its function, and therefore methods for exploring protein structures have attracted much research. However, rather few methods are sensitive to topologic-geometric features, the examples being knots, slipknots, lassos, links, and pokes, and with each method aimed only for a specific set of such configurations. We here propose a general method which transforms a structure into a ”fingerprint of topological-geometric values” consisting in a series of real-valued descriptors from mathematical Knot Theory. The extent to which a structure contains unusual configurations can then be judged from this fingerprint. The method is not confined to a particular pre-defined topology or geometry (like a knot or a poke), and so, unlike existing methods, it is general. To achieve this our new algorithm, GISA, as a key novelty produces the descriptors, so called Gauss integrals, not only for the full chains of a protein but for all its sub-chains. This allows fingerprinting on any scale from local to global. The Gauss integrals are known to be effective descriptors of global protein folds. Applying GISA to sets of several thousand high resolution structures, we first show how the most basic Gauss integral, the writhe, enables swift identification of pre-defined geometries such as pokes and links. We then apply GISA with no restrictions on geometry, to show how it allows identifying rare conformations by finding rare invariant values only. In this unrestricted search, pokes and links are still found, but also knotted conformations, as well as more highly entangled configurations not previously described. Thus, an application of the basic scan method in GISA’s tool-box revealed 10 known cases of knots as the top positive writhe cases, while placing at the top of the negative writhe 14 cases in cis-trans isomerases sharing a spatial motif of little secondary structure content, which possibly has gone unnoticed. Possible general applications of GISA are fold classification and structural alignment based on local Gauss integrals. Others include finding errors in protein models and identifying unusual conformations that might be important for protein folding and function. By its broad potential, we believe that GISA will be of general benefit to the structural bioinformatics community. GISA is coded in C and comes as a command line tool. Source and compiled code for GISA plus read-me and examples are publicly available at GitHub (https://github.com).

The native structure of a protein is important for its function, and therefore methods for exploring protein structures have attracted much research. However, rather few methods are sensitive to topologic-geometric features, the examples being knots, slipknots, lassos, links, and pokes, and with each method aimed only for a specific set of such configurations. We here propose a general method which transforms a structure into a ''fingerprint of topological-geometric values'' consisting in a series of real-valued descriptors from mathematical Knot Theory. The extent to which a structure contains unusual configurations can then be judged from this fingerprint. The method is not confined to a particular pre-defined topology or geometry (like a knot or a poke), and so, unlike existing methods, it is general. To achieve this our new algorithm, GISA, as a key novelty produces the descriptors, so called Gauss integrals, not only for the full chains of a protein but for all its sub-chains. This allows fingerprinting on any scale from local to global. The Gauss integrals are known to be effective descriptors of global protein folds. Applying GISA to sets of several thousand high resolution structures, we first show how the most basic Gauss integral, the writhe, enables swift identification of pre-defined geometries such as pokes and links.Wethen apply GISA with no restrictions on geometry, to show how it allows identifying rare conformations by finding rare invariant values only. In this unrestricted search, pokes and links are still found, but also knotted conformations, as well as more highly entangled configurations not previously described. Thus, an application of the basic scan method in GISA's tool-box revealed 10 known cases of knots as the top positive writhe cases, while placing at the top of the negative writhe 14 cases in cis-trans isomerases sharing a spatial motif of little secondary structure content, which possibly has gone unnoticed. Possible general applications of GISA are fold classification and structural alignment based on local Gauss integrals. Others include finding errors in protein models and identifying unusual conformations that might be important for protein folding and function. By its broad potential, we believe that GISA will be of general benefit to the structural bioinformatics community. GISA is coded in C and comes as a command line tool. Source and compiled code for GISA plus read-me and examples are publicly available at GitHub [ABSTRACT FROM AUTHOR]

Large language models (LLMs) are proving to be very useful in many fields, especially chemistry and biology, because of their amazing capabilities. Biomolecular data is often represented sequentially, much like textual data used to train LLMs. However, developing LLMs from scratch requires a substantial amount of data and computational resources, which may not be feasible for most researchers. A more workable solution to this problem is to change the inputs or parameters so that the previously trained general LLMs can pick up the specific knowledge needed for biomolecular analysis. These adaption strategies lower the amount of data and hardware needed, providing a more affordable option. This review provides the introduction of two popular LLM adaptation techniques: fine-tuning and prompt engineering, along with their uses in the analysis of molecules, proteins, and genes. A thorough overview of current common datasets and pre-trained models is also provided. This review outlines the possible advantages and difficulties of LLMs for biomolecular analysis, opening the door for chemists and biologists to effectively utilize LLMs in their future studies. • A thorough summary of the use of large language models in biomolecular analysis. • Lists of models and datasets in analyzing molecules, proteins, and genes. • Future directions on improving large language models for biomolecular analysis. [ABSTRACT FROM AUTHOR]

We previously found that circulating β2‐glycoprotein I inhibits human endothelial cell migration, proliferation, and angiogenesis by diverse mechanisms. In the present study, we investigated the antitumor activities of β2‐glycoprotein I using structure‐function analysis and mapped the critical region within the β2‐glycoprotein I peptide sequence that mediates anticancer effects. We constructed recombinant cDNA and purified different β2‐glycoprotein I polypeptide domains using a baculovirus expression system. We found that purified β2‐glycoprotein I, as well as recombinant β2‐glycoprotein I full‐length (D12345), polypeptide domains I‐IV (D1234), and polypeptide domain I (D1) significantly inhibited melanoma cell migration, proliferation and invasion. Western blot analyses were used to determine the dysregulated expression of proteins essential for intracellular signaling pathways in B16‐F10 treated with β2‐glycoprotein I and variant recombinant polypeptides. Using a melanoma mouse model, we found that D1 polypeptide showed stronger potency in suppressing tumor growth. Structural analysis showed that fragments A and B within domain I would be the critical regions responsible for antitumor activity. Annexin A2 was identified as the counterpart molecule for β2‐glycoprotein I by immunofluorescence and coimmunoprecipitation assays. Interaction between specific amino acids of β2‐glycoprotein I D1 and annexin A2 was later evaluated by the molecular docking approach. Moreover, five amino acid residues were selected from fragments A and B for functional evaluation using site‐directed mutagenesis, and P11A, M42A, and I55P mutations were shown to disrupt the anti‐melanoma cell migration ability of β2‐glycoprotein I. This is the first study to show the therapeutic potential of β2‐glycoprotein I D1 in the treatment of melanoma progression. [ABSTRACT FROM AUTHOR]

Proteins play a major role in biosensors in which they provide catalytic activity and specificity in molecular recognition. However, the immobilization process is far from straightforward as it often affects the protein functionality. Extensive interaction of the protein with the surface or significant surface crowding can lead to changes in the mobility and conformation of the protein structure. This review will provide insights as to how an analysis of the physico-chemical features of the protein surface before the immobilization process can help to identify the optimal immobilization approach. Such an analysis can help to preserve the functionality of the protein when on a biosensor surface. [ABSTRACT FROM AUTHOR]

PDBsum is a web server providing structural information on the entries in the Protein Data Bank (PDB). The analyses are primarily image-based and include protein secondary structure, protein-ligand and protein-DNA interactions, PROCHECK analyses of structural quality, and many others. The 3D structures can be viewed interactively in RasMol, PyMOL, and a JavaScript viewer called 3Dmol.js. Users can upload their own PDB files and obtain a set of password-protected PDBsum analyses for each. The server is freely accessible to all at: . [ABSTRACT FROM AUTHOR]

Previously we showed that constant current chronopotentiometric stripping (CPS) is convenient for protein analysis based on the ability of some amino acid residues to catalyze hydrogen evolution on mercury-containing electrodes. This method showed a remarkable sensitivity to changes in protein structures, including protein denaturation and even small protein damage. Here we used normal pulse voltammetric stripping (NPVS) with bare and dithiothreitol-modified hanging mercury drop electrode. We found that NPV pulses denatured the surface-attached protein but we showed conditions under which this method was able to distinguish native and denatured proteins with sensitivity approaching that of CPS. Using NPVS it was possible to follow bovine serum albumin (BSA) thermal denaturation as well as to investigate the effect of NPV pulses on the structure of the surface-attached protein. In addition to BSA we studied several proteins, such as human serum albumin, ovalbumin, urease, aldolase, concanavalin A, histone and vasopressin peptide. Our results suggest that CPS remains the method-of-choice for studies of changes in protein structure and of biochemical processes, such as DNA-protein specific binding, lectin-glycoprotein interactions, detection of protein damage, etc., while voltammetric methods, such as NPVS may suit better for investigation of the processes which proteins undergo at the electrode surface. [ABSTRACT FROM AUTHOR]

Lipid oxidation can produce lipid oxidation products (LOPs), which further react with proteins and affect their structure and digestibility, although the underlying mechanism remains unclear. Herein, we investigated the conformation and digestibility of proteins induced by LOPs after thermal treatment. Digestibility of myoglobin (Mb) affected by trans , trans ,-2,4-decadienal (2,4-Dec) was significantly reduced under high temperature (100-180 °C). The peptides digested from Mb modified with 2,4-Dec during thermal processing revealed that the quantity of peptides decreased with increasing 2,4-Dec concentrations. Proteomic analysis showed that 2,4-Dec covalently binds to Mb, and the extent of modification was in the following order: lysine > histidine > arginine. Moreover, the secondary structure, intrinsic fluorescence, and surface hydrophobicity results suggested that 2,4-Dec induced changes in Mb, leading to a tighter spatial structure and aggregation, and exposure of fewer recognition sites of the enzyme and thermal treatment assisted these changes in the structure. Meanwhile, molecular dynamics simulations elucidated the molecular mechanisms underlying the effect of 2,4-Dec and temperature on the digestion and structure of Mb.

Flavonoid glycosides are required for a number of crucial roles in planta and have the potential for development in a variety of agricultural, medicinal, and biotechnological applications. A number of recent advancements have been made in characterizing glycosyltransferases, the enzymes that are responsible for the synthesis of these important molecules. In this review, glycosyltransferases are considered with regard to biochemical properties, expression patterns, levels of enzyme activity during development, and structure/function relationships. This is presented with historical context to highlight critical findings, particularly with regard to the innovative work that has come from research on citrus species. The plant glycosyltransferase crystal structures that have been solved over the past decade, either alone or in complex with sugar donor and/or acceptor molecules, are discussed. The application of results from these structures to inform current structure/function work as well as implications and goals for future crystallography and tertiary modeling studies are considered. A thorough understanding of the properties of glycosyltransferases will be a critical step in any future biotechnological application of these enzymes in areas such as crop improvement and custom design of enzymes to produce desired compounds for nutritional and/or medicinal usage. [ABSTRACT FROM AUTHOR]

Proteins play a major role in biosensors in which they provide catalytic activity and specificity in molecular recognition. However, the immobilization process is far from straightforward as it often affects the protein functionality. Extensive interaction of the protein with the surface or significant surface crowding can lead to changes in the mobility and conformation of the protein structure. This review will provide insights as to how an analysis of the physico-chemical features of the protein surface before the immobilization process can help to identify the optimal immobilization approach. Such an analysis can help to preserve the functionality of the protein when on a biosensor surface.

Viruses with large, double-stranded DNA genomes captured the majority of their genes from their hosts at different stages of evolution. The origins of many virus genes are readily detected through significant sequence similarity with cellular homologs. In particular, this is the case for virus enzymes, such as DNA and RNA polymerases or nucleotide kinases, that retain their catalytic activity after capture by an ancestral virus. However, a large fraction of virus genes have no readily detectable cellular homologs, meaning that their origins remain enigmatic. We explored the potential origins of such proteins that are encoded in the genomes of orthopoxviruses, a thoroughly studied virus genus that includes major human pathogens. To this end, we used AlphaFold2 to predict the structures of all 214 proteins that are encoded by orthopoxviruses. Among the proteins of unknown provenance, structure prediction yielded clear indications of origin for 14 of them and validated several inferences that were previously made via sequence analysis. A notable emerging trend is the exaptation of enzymes from cellular organisms for nonenzymatic, structural roles in virus reproduction that is accompanied by the disruption of catalytic sites and by an overall drastic divergence that precludes homology detection at the sequence level. Among the 16 orthopoxvirus proteins that were found to be inactivated enzyme derivatives are the poxvirus replication processivity factor A20, which is an inactivated NAD-dependent DNA ligase; the major core protein A3, which is an inactivated deubiquitinase; F11, which is an inactivated prolyl hydroxylase; and more similar cases. For nearly one-third of the orthopoxvirus virion proteins, no significantly similar structures were identified, suggesting exaptation with subsequent major structural rearrangement that yielded unique protein folds. IMPORTANCE Protein structures are more strongly conserved in evolution than are amino acid sequences. Comparative structural analysis is particularly important for inferring the origins of viral proteins that typically evolve at high rates. We used a powerful protein structure modeling method, namely, AlphaFold2, to model the structures of all orthopoxvirus proteins and compared them to all available protein structures. Multiple cases of recruitment of host enzymes for structural roles in viruses, accompanied by the disruption of catalytic sites, were discovered. However, many viral proteins appear to have evolved unique structural folds.

Earlier we showed that constant current chronopotentiometric stripping (CPS) at mercury-containing electrodes reflects changes in proteins, such as denaturation, single amino acid exchange or protein damage by physical and chemical agents. Here we attempted to compare performance of the galvanostatic CPS with the potentiostatic normal pulse voltammetry (NPV). We have found that repeated 50 ms or longer NPV pulses denature the surface-attached protein. Using shorter pulses and adapting other NPV settings we have been able to obtain a good resolution of native (folded) and denatured (unfolded) bovine serum albumin. On the other hand, partial denaturation of the surface-attached native bovine serum albumin during the potential scanning may prevent detection of small conformational changes in the protein. [ABSTRACT FROM AUTHOR]