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  1. Article ; Online: Modus operandi: Chromatin recognition by α-helical histone readers.

    Davarinejad, Hossein / Arvanitis-Vigneault, Alexis / Nygard, Dallas / Lavallée-Adam, Mathieu / Couture, Jean-François

    Structure (London, England : 1993)

    2023  Volume 32, Issue 1, Page(s) 8–17

    Abstract: Histone reader domains provide a mechanism for sensing states of coordinated nuclear processes marked by histone proteins' post-translational modifications (PTMs). Among a growing number of discovered histone readers, the 14-3-3s, ankyrin repeat domains ( ...

    Abstract Histone reader domains provide a mechanism for sensing states of coordinated nuclear processes marked by histone proteins' post-translational modifications (PTMs). Among a growing number of discovered histone readers, the 14-3-3s, ankyrin repeat domains (ARDs), tetratricopeptide repeats (TPRs), bromodomains (BRDs), and HEAT domains are a group of domains using various mechanisms to recognize unmodified or modified histones, yet they all are composed of an α-helical fold. In this review, we compare how these readers fold to create protein domains that are very diverse in their tertiary structures, giving rise to intriguing peptide binding mechanisms resulting in vastly different footprints of their targets.
    MeSH term(s) Chromatin ; Histones/metabolism ; Protein Processing, Post-Translational ; Protein Domains
    Chemical Substances Chromatin ; Histones
    Language English
    Publishing date 2023-11-02
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 1213087-4
    ISSN 1878-4186 ; 0969-2126
    ISSN (online) 1878-4186
    ISSN 0969-2126
    DOI 10.1016/j.str.2023.10.008
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  2. Article ; Online: Computational Identification of Human Biological Processes and Protein Sequence Motifs Putatively Targeted by SARS-CoV-2 Proteins Using Protein-Protein Interaction Networks.

    Nadeau, Rachel / Shahryari Fard, Soroush / Scheer, Amit / Hashimoto-Roth, Emily / Nygard, Dallas / Abramchuk, Iryna / Chung, Yun-En / Bennett, Steffany A L / Lavallée-Adam, Mathieu

    Journal of proteome research

    2020  Volume 19, Issue 11, Page(s) 4553–4566

    Abstract: While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a ...

    Abstract While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a better understanding of the mechanisms exploited by the virus and enable the identification of potential drug targets. We therefore performed an in-depth computational analysis of the interactome of SARS-CoV-2 and human proteins in infected HEK 293 cells published by Gordon et al. (
    MeSH term(s) Algorithms ; Amino Acid Motifs ; Betacoronavirus/chemistry ; Betacoronavirus/metabolism ; Betacoronavirus/pathogenicity ; COVID-19 ; Cluster Analysis ; Coronavirus Infections/metabolism ; Coronavirus Infections/virology ; Gene Ontology ; HEK293 Cells ; Host-Pathogen Interactions/genetics ; Humans ; Molecular Sequence Annotation ; Pandemics ; Pneumonia, Viral/metabolism ; Pneumonia, Viral/virology ; Protein Binding ; Protein Interaction Maps/genetics ; Protein Interaction Maps/physiology ; Proteins/chemistry ; Proteins/classification ; Proteins/genetics ; Proteins/metabolism ; SARS-CoV-2 ; Viral Proteins/chemistry ; Viral Proteins/genetics ; Viral Proteins/metabolism
    Chemical Substances Proteins ; Viral Proteins
    Keywords covid19
    Language English
    Publishing date 2020-10-26
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2078618-9
    ISSN 1535-3907 ; 1535-3893
    ISSN (online) 1535-3907
    ISSN 1535-3893
    DOI 10.1021/acs.jproteome.0c00422
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  3. Article ; Online: Computational identification of human biological processes and protein sequence motifs putatively targeted by SARS-CoV-2 proteins using protein-protein interaction networks

    Nadeau, Rachel / Fard, Soroush Shahryari / Scheer, Amit / Roth, Emily / Nygard, Dallas / Abramchuk, Iryna / Chung, Yun-En / Bennett, Steffany A. L. / Lavallée-Adam, Mathieu

    bioRxiv

    Abstract: While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a ...

    Abstract While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a better understanding of the mechanisms exploited by the virus and enable the identification of potential drug targets. We therefore performed an in-depth computational analysis of the interactome of SARS-CoV-2 and human proteins in infected HEK293 cells published by Gordon et al. to reveal processes that are potentially affected by the virus and putative protein binding sites. Specifically, we performed a set of network-based functional and sequence motif enrichment analyses on SARS-CoV-2-interacting human proteins and on a PPI network generated by supplementing viral-host PPIs with known interactions. Using a novel implementation of our GoNet algorithm, we identified 329 Gene Ontology terms for which the SARS-CoV-2-interacting human proteins are significantly clustered in the network. Furthermore, we present a novel protein sequence motif discovery approach, LESMoN-Pro, that identified 9 amino acid motifs for which the associated proteins are clustered in the network. Together, these results provide insights into the processes and sequence motifs that are putatively implicated in SARS-CoV-2 infection and could lead to potential therapeutic targets.
    Keywords covid19
    Publisher BioRxiv; WHO
    Document type Article ; Online
    DOI 10.1101/2020.09.29.318931
    Database COVID19

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  4. Article: Computational Identification of Human Biological Processes and Protein Sequence Motifs Putatively Targeted by SARS-CoV-2 Proteins Using Protein-Protein Interaction Networks

    Nadeau, Rachel / Shahryari Fard, Soroush / Scheer, Amit / Hashimoto-Roth, Emily / Nygard, Dallas / Abramchuk, Iryna / Chung, Yun-En / Bennett, Steffany A L / Lavallée-Adam, Mathieu

    J Proteome Res

    Abstract: While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a ...

    Abstract While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a better understanding of the mechanisms exploited by the virus and enable the identification of potential drug targets. We therefore performed an in-depth computational analysis of the interactome of SARS-CoV-2 and human proteins in infected HEK 293 cells published by Gordon et al. (Nature 2020, 583, 459-468) to reveal processes that are potentially affected by the virus and putative protein binding sites. Specifically, we performed a set of network-based functional and sequence motif enrichment analyses on SARS-CoV-2-interacting human proteins and on PPI networks generated by supplementing viral-host PPIs with known interactions. Using a novel implementation of our GoNet algorithm, we identified 329 Gene Ontology terms for which the SARS-CoV-2-interacting human proteins are significantly clustered in PPI networks. Furthermore, we present a novel protein sequence motif discovery approach, LESMoN-Pro, that identified 9 amino acid motifs for which the associated proteins are clustered in PPI networks. Together, these results provide insights into the processes and sequence motifs that are putatively implicated in SARS-CoV-2 infection and could lead to potential therapeutic targets.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #889122
    Database COVID19

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  5. Article ; Online: Computational identification of human biological processes and protein sequence motifs putatively targeted by SARS-CoV-2 proteins using protein-protein interaction networks

    Nadeau, Rachel / Shahryari Fard, Soroush / Scheer, Amit / Hashimoto-Roth, Emily / Nygard, Dallas / Abramchuk, Iryna / Chung, Yun-En / Bennett, Steffany A. L. / Lavallee-Adam, Mathieu

    bioRxiv

    Abstract: While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a ...

    Abstract While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a better understanding of the mechanisms exploited by the virus and enable the identification of potential drug targets. We therefore performed an in-depth computational analysis of the interactome of SARS-CoV-2 and human proteins in infected HEK293 cells published by Gordon et al. to reveal processes that are potentially affected by the virus and putative protein binding sites. Specifically, we performed a set of network-based functional and sequence motif enrichment analyses on SARS-CoV-2-interacting human proteins and on a PPI network generated by supplementing viral-host PPIs with known interactions. Using a novel implementation of our GoNet algorithm, we identified 329 Gene Ontology terms for which the SARS-CoV-2-interacting human proteins are significantly clustered in the network. Furthermore, we present a novel protein sequence motif discovery approach, LESMoN-Pro, that identified 9 amino acid motifs for which the associated proteins are clustered in the network. Together, these results provide insights into the processes and sequence motifs that are putatively implicated in SARS-CoV-2 infection and could lead to potential therapeutic targets.
    Keywords covid19
    Language English
    Publishing date 2020-09-30
    Publisher Cold Spring Harbor Laboratory
    Document type Article ; Online
    DOI 10.1101/2020.09.29.318931
    Database COVID19

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  6. Article ; Online: Computational Identification of Human Biological Processes and Protein Sequence Motifs Putatively Targeted by SARS-CoV-2 Proteins Using Protein–Protein Interaction Networks

    Nadeau, Rachel / Shahryari Fard, Soroush / Scheer, Amit / Hashimoto-Roth, Emily / Nygard, Dallas / Abramchuk, Iryna / Chung, Yun-En / Bennett, Steffany A. L. / Lavallée-Adam, Mathieu

    Journal of Proteome Research

    2020  Volume 19, Issue 11, Page(s) 4553–4566

    Keywords Biochemistry ; General Chemistry ; covid19
    Language English
    Publisher American Chemical Society (ACS)
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2078618-9
    ISSN 1535-3893
    ISSN 1535-3893
    DOI 10.1021/acs.jproteome.0c00422
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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