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  • 1
    Online Resource
    Online Resource
    Genetic Risk Score for Intracranial Aneurysms: Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity
    Ovid Technologies (Wolters Kluwer Health) ; 2023
    In:  Stroke Vol. 54, No. 3 ( 2023-03), p. 810-818
    Details
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 54, No. 3 ( 2023-03), p. 810-818
    Abstract: Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. Methods: A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. Results: Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20–1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01–1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59–0.67) to 0.65 (95% CI, 0.62–0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (β=−4.82×10 −3 per year [95% CI, −6.49×10 −3 to −3.14×10 −3 ]; P =1.82×10 −8 ), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86–0.98]; P =0.0041). Conclusions: The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    URL: Article
    DOI: 10.1161/STROKEAHA.122.040715
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2023
    detail.hit.zdb_id: 1467823-8
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  • 2
    Online Resource
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    Cell-Penetrating Milk-Derived Peptides with a Non-Inflammatory Profile
    MDPI AG ; 2023
    In:  Molecules Vol. 28, No. 19 ( 2023-10-09), p. 6999-
    Details
    In: Molecules, MDPI AG, Vol. 28, No. 19 ( 2023-10-09), p. 6999-
    Abstract: Milk-derived peptides are known to confer anti-inflammatory effects. We hypothesised that milk-derived cell-penetrating peptides might modulate inflammation in useful ways. Using computational techniques, we identified and synthesised peptides from the milk protein Alpha-S1-casein that were predicted to be cell-penetrating using a machine learning predictor. We modified the interpretation of the prediction results to consider the effects of histidine. Peptides were then selected for testing to determine their cell penetrability and anti-inflammatory effects using HeLa cells and J774.2 mouse macrophage cell lines. The selected peptides all showed cell penetrating behaviour, as judged using confocal microscopy of fluorescently labelled peptides. None of the peptides had an effect on either the NF-κB transcription factor or TNFα and IL-1β secretion. Thus, the identified milk-derived sequences have the ability to be internalised into the cell without affecting cell homeostatic mechanisms such as NF-κB activation. These peptides are worthy of further investigation for other potential bioactivities or as a naturally derived carrier to promote the cellular internalisation of other active peptides.
    Type of Medium: Online Resource
    ISSN: 1420-3049
    URL: Article
    DOI: 10.3390/molecules28196999
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2008644-1
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  • 3
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    Modelling the Transitioning of SARS-CoV-2 nsp3 and nsp4 Lumenal Regions towards a More Stable State on Complex Formation
    MDPI AG ; 2022
    In:  International Journal of Molecular Sciences Vol. 24, No. 1 ( 2022-12-31), p. 720-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 24, No. 1 ( 2022-12-31), p. 720-
    Abstract: During coronavirus infection, three non-structural proteins, nsp3, nsp4, and nsp6, are of great importance as they induce the formation of double-membrane vesicles where the replication and transcription of viral gRNA takes place, and the interaction of nsp3 and nsp4 lumenal regions triggers membrane pairing. However, their structural states are not well-understood. We investigated the interactions between nsp3 and nsp4 by predicting the structures of their lumenal regions individually and in complex using AlphaFold2 as implemented in ColabFold. The ColabFold prediction accuracy of the nsp3–nsp4 complex was increased compared to nsp3 alone and nsp4 alone. All cysteine residues in both lumenal regions were modelled to be involved in intramolecular disulphide bonds. A linker region in the nsp4 lumenal region emerged as crucial for the interaction, transitioning to a structured state when predicted in complex. The key interactions modelled between nsp3 and nsp4 appeared stable when the transmembrane regions of nsp3 and nsp4 were added to the modelling either alone or together. While molecular dynamics simulations (MD) demonstrated that the proposed model of the nsp3 lumenal region on its own is not stable, key interactions between nsp and nsp4 in the proposed complex model appeared stable after MD. Together, these observations suggest that the interaction is robust to different modelling conditions. Understanding the functional importance of the nsp4 linker region may have implications for the targeting of double membrane vesicle formation in controlling coronavirus infection.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms24010720
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    Short linear motif candidates in the cell entry system used by SARS-CoV-2 and their potential therapeutic implications
    American Association for the Advancement of Science (AAAS) ; 2021
    In:  Science Signaling Vol. 14, No. 665 ( 2021-01-12)
    Details
    In: Science Signaling, American Association for the Advancement of Science (AAAS), Vol. 14, No. 665 ( 2021-01-12)
    Abstract: The first reported receptor for SARS-CoV-2 on host cells was the angiotensin-converting enzyme 2 (ACE2). However, the viral spike protein also has an RGD motif, suggesting that cell surface integrins may be co-receptors. We examined the sequences of ACE2 and integrins with the Eukaryotic Linear Motif (ELM) resource and identified candidate short linear motifs (SLiMs) in their short, unstructured, cytosolic tails with potential roles in endocytosis, membrane dynamics, autophagy, cytoskeleton, and cell signaling. These SLiM candidates are highly conserved in vertebrates and may interact with the μ2 subunit of the endocytosis-associated AP2 adaptor complex, as well as with various protein domains (namely, I-BAR, LC3, PDZ, PTB, and SH2) found in human signaling and regulatory proteins. Several motifs overlap in the tail sequences, suggesting that they may act as molecular switches, such as in response to tyrosine phosphorylation status. Candidate LC3-interacting region (LIR) motifs are present in the tails of integrin β 3 and ACE2, suggesting that these proteins could directly recruit autophagy components. Our findings identify several molecular links and testable hypotheses that could uncover mechanisms of SARS-CoV-2 attachment, entry, and replication against which it may be possible to develop host-directed therapies that dampen viral infection and disease progression. Several of these SLiMs have now been validated to mediate the predicted peptide interactions.
    Type of Medium: Online Resource
    ISSN: 1945-0877 , 1937-9145
    URL: Article
    DOI: 10.1126/scisignal.abd0334
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2021
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  • 5
    Online Resource
    Online Resource
    Prediction of polyproline II secondary structure propensity in proteins
    The Royal Society ; 2020
    In:  Royal Society Open Science Vol. 7, No. 1 ( 2020-01), p. 191239-
    Details
    In: Royal Society Open Science, The Royal Society, Vol. 7, No. 1 ( 2020-01), p. 191239-
    Abstract: Background: The polyproline II helix (PPIIH) is an extended protein left-handed secondary structure that usually but not necessarily involves prolines. Short PPIIHs are frequently, but not exclusively, found in disordered protein regions, where they may interact with peptide-binding domains. However, no readily usable software is available to predict this state. Results: We developed PPIIPRED to predict polyproline II helix secondary structure from protein sequences, using bidirectional recurrent neural networks trained on known three-dimensional structures with dihedral angle filtering. The performance of the method was evaluated in an external validation set. In addition to proline, PPIIPRED favours amino acids whose side chains extend from the backbone (Leu, Met, Lys, Arg, Glu, Gln), as well as Ala and Val. Utility for individual residue predictions is restricted by the rarity of the PPIIH feature compared to structurally common features. Conclusion: The software, available at http://bioware.ucd.ie/PPIIPRED , is useful in large-scale studies, such as evolutionary analyses of PPIIH, or computationally reducing large datasets of candidate binding peptides for further experimental validation.
    Type of Medium: Online Resource
    ISSN: 2054-5703
    URL: Article
    DOI: 10.1098/rsos.191239
    Language: English
    Publisher: The Royal Society
    Publication Date: 2020
    detail.hit.zdb_id: 2787755-3
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  • 6
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    Resolving the Interactome of the Human Macrophage Immunometabolism Regulator (MACIR) with Enhanced Membrane Protein Preparation and Affinity Proteomics
    Wiley ; 2020
    In:  PROTEOMICS Vol. 20, No. 19-20 ( 2020-10)
    Details
    In: PROTEOMICS, Wiley, Vol. 20, No. 19-20 ( 2020-10)
    Abstract: Expression of the macrophage immunometabolism regulator gene (MACIR) is associated with severity of autoimmune disease pathology and with the regulation of macrophage biology through unknown mechanisms. The encoded 206 amino acid protein lacks homology to any characterized protein sequence and is a disordered protein according to structure prediction algorithms. To identify interactions of MACIR with proteins from all subcellular compartments, a membrane solubilization buffer is employed, that together with a high affinity EF hand based pull down method, increases the resolution of quantitative mass spectrometry analysis with significant enrichment of interactions from membrane bound nuclear and mitochondrial compartments compared to samples prepared with radioimmunoprecipitation assay buffer. A total of 63 significant interacting proteins are identified and interaction with the nuclear transport receptor TNPO1 and the trafficking proteins UNC119 homolog A and B are validated by immunoprecipitation. Mutational analysis in two candidate nuclear localization signal motifs in the MACIR amino acid sequence shows the interaction with TNPO1 is likely via a non‐classical proline/tyrosine‐nuclear localization signal motif (aa98‐117). It is shown that employing a highly specific and high affinity pull down method that performs efficiently in this glycerol and detergent rich buffer is a powerful approach for the analysis of uncharacterized protein interactomes.
    Type of Medium: Online Resource
    ISSN: 1615-9853 , 1615-9861
    URL: Issue
    URL: Article
    DOI: 10.1002/pmic.v20.19-20
    DOI: 10.1002/pmic.202000062
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2037674-1
    SSG: 12
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  • 7
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    Enriching antimicrobial peptides from milk hydrolysates using pectin/alginate food-gels
    Elsevier BV ; 2021
    In:  Food Chemistry Vol. 352 ( 2021-08), p. 129220-
    Details
    In: Food Chemistry, Elsevier BV, Vol. 352 ( 2021-08), p. 129220-
    Type of Medium: Online Resource
    ISSN: 0308-8146
    URL: Article
    DOI: 10.1016/j.foodchem.2021.129220
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 1483647-6
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  • 8
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    Computational modelling of chromosomally clustering protein domains in bacteria
    Springer Science and Business Media LLC ; 2021
    In:  BMC Bioinformatics Vol. 22, No. 1 ( 2021-12)
    Details
    In: BMC Bioinformatics, Springer Science and Business Media LLC, Vol. 22, No. 1 ( 2021-12)
    Abstract: In bacteria, genes with related functions—such as those involved in the metabolism of the same compound or in infection processes—are often physically close on the genome and form groups called clusters. The enrichment of such clusters over various distantly related bacteria can be used to predict the roles of genes of unknown function that cluster with characterised genes. There is no obvious rule to define a cluster, given their variability in size and intergenic distances, and the definition of what comprises a “gene”, since genes can gain and lose domains over time. Protein domains can cluster within a gene, or in adjacent genes of related function, and in both cases these are chromosomally clustered. Here, we model the distances between pairs of protein domain coding regions across a wide range of bacteria and archaea via a probabilistic two component mixture model, without imposing arbitrary thresholds in terms of gene numbers or distances. Results We trained our model using matched gene ontology terms to label functionally related pairs and assess the stability of the parameters of the model across 14,178 archaeal and bacterial strains. We found that the parameters of our mixture model are remarkably stable across bacteria and archaea, except for endosymbionts and obligate intracellular pathogens. Obligate pathogens have smaller genomes, and although they vary, on average do not show noticeably different clustering distances; the main difference in the parameter estimates is that a far greater proportion of the genes sharing ontology terms are clustered. This may reflect that these genomes are enriched for complexes encoded by clustered core housekeeping genes, as a proportion of the total genes. Given the overall stability of the parameter estimates, we then used the mean parameter estimates across the entire dataset to investigate which gene ontology terms are most frequently associated with clustered genes. Conclusions Given the stability of the mixture model across species, it may be used to predict bacterial gene clusters that are shared across multiple species, in addition to giving insights into the evolutionary pressures on the chromosomal locations of genes in different species.
    Type of Medium: Online Resource
    ISSN: 1471-2105
    URL: Article
    DOI: 10.1186/s12859-021-04512-x
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2041484-5
    SSG: 12
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  • 9
    Online Resource
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    Relationship between Protein Digestibility and the Proteolysis of Legume Proteins during Seed Germination
    MDPI AG ; 2023
    In:  Molecules Vol. 28, No. 7 ( 2023-04-04), p. 3204-
    Details
    In: Molecules, MDPI AG, Vol. 28, No. 7 ( 2023-04-04), p. 3204-
    Abstract: Legume seed protein is an important source of nutrition, but generally it is less digestible than animal protein. Poor protein digestibility in legume seeds and seedlings may partly reflect defenses against herbivores. Protein changes during germination typically increase proteolysis and digestibility, by lowering the levels of anti-nutrient protease inhibitors, activating proteases, and breaking down storage proteins (including allergens). Germinating legume sprouts also show striking increases in free amino acids (especially asparagine), but their roles in host defense or other processes are not known. While the net effect of germination is generally to increase the digestibility of legume seed proteins, the extent of improvement in digestibility is species- and strain-dependent. Further research is needed to highlight which changes contribute most to improved digestibility of sprouted seeds. Such knowledge could guide the selection of varieties that are more digestible and also guide the development of food preparations that are more digestible, potentially combining germination with other factors altering digestibility, such as heating and fermentation. Techniques to characterize the shifts in protein make-up, activity and degradation during germination need to draw on traditional analytical approaches, complemented by proteomic and peptidomic analysis of mass spectrometry-identified peptide breakdown products.
    Type of Medium: Online Resource
    ISSN: 1420-3049
    URL: Article
    DOI: 10.3390/molecules28073204
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2008644-1
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  • 10
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    Continent-wide declines in shallow reef life over a decade of ocean warming
    Springer Science and Business Media LLC ; 2023
    In:  Nature Vol. 615, No. 7954 ( 2023-03-30), p. 858-865
    Details
    In: Nature, Springer Science and Business Media LLC, Vol. 615, No. 7954 ( 2023-03-30), p. 858-865
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
    URL: Article
    DOI: 10.1038/s41586-023-05833-y
    RVK:
    TA 1000
    RVK:
    UA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 120714-3
    detail.hit.zdb_id: 1413423-8
    SSG: 11
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