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  • 1
    Online Resource
    Online Resource
    Amino acid sensor conserved from bacteria to humans
    Proceedings of the National Academy of Sciences ; 2022
    In:  Proceedings of the National Academy of Sciences Vol. 119, No. 10 ( 2022-03-08)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 10 ( 2022-03-08)
    Abstract: Amino acids are the building blocks of life, and they are also recognized as signals by various receptors in bacteria, archaea, and eukaryotes. Despite their common basic structure, no universal mechanism for amino acid recognition is currently known. Here, we show that a subclass of dCache_1 (double domain found in calcium channels and chemotaxis receptors, family 1), a ubiquitous extracellular sensory domain, contains a simple motif, which recognizes the amino and carboxyl groups of amino acid ligands. We found this motif throughout the Tree of Life. In bacteria and archaea, this motif exclusively binds amino acids, including γ-aminobutyric acid (GABA), and it is present in all major receptor types. In humans, this motif is found in α2δ-subunits of voltage-gated calcium channels that are implicated in neuropathic pain and neurodevelopmental disorders and in a recently characterized CACHD1 protein. Our findings suggest that GABA-derived drugs bind to the same motif in human α2δ-subunits that binds natural GABA ligands in bacterial chemoreceptors. The exact location on the target protein and the mechanism of binding may enable future improvements of drugs targeting pain and neurobiological disorders.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2110415119
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Evolutionary history of MEK1 illuminates the nature of deleterious mutations
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 34 ( 2023-08-22)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 34 ( 2023-08-22)
    Abstract: Mutations in signal transduction pathways lead to various diseases including cancers. MEK1 kinase, encoded by the human MAP2 K1 gene, is one of the central components of the MAPK pathway and more than a hundred somatic mutations in the MAP2 K1 gene were identified in various tumors. Germline mutations deregulating MEK1 also lead to congenital abnormalities, such as the cardiofaciocutaneous syndrome and arteriovenous malformation. Evaluating variants associated with a disease is a challenge, and computational genomic approaches aid in this process. Establishing evolutionary history of a gene improves computational prediction of disease-causing mutations; however, the evolutionary history of MEK1 is not well understood. Here, by revealing a precise evolutionary history of MEK1, we construct a well-defined dataset of MEK1 metazoan orthologs, which provides sufficient depth to distinguish between conserved and variable amino acid positions. We matched known and predicted disease-causing and benign mutations to evolutionary changes observed in corresponding amino acid positions and found that all known and many suspected disease-causing mutations are evolutionarily intolerable. We selected several variants that cannot be unambiguously assessed by automated prediction tools but that are confidently identified as “damaging” by our approach, for experimental validation in Drosophila . In all cases, evolutionary intolerant variants caused increased mortality and severe defects in fruit fly embryos confirming their damaging nature. We anticipate that our analysis will serve as a blueprint to help evaluate known and novel missense variants in MEK1 and that our approach will contribute to improving automated tools for disease-associated variant interpretation.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2304184120
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
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