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Reliable target ligand detection by noise-induced receptor cluster formation.
Kajita, Masashi K; Aihara, Kazuyuki; Kobayashi, Tetsuya J.
Afiliação
  • Kajita MK; Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan.
  • Aihara K; Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan.
  • Kobayashi TJ; Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan.
Chaos ; 30(1): 011104, 2020 Jan.
Article em En | MEDLINE | ID: mdl-32013460
ABSTRACT
Intracellular reactions are intrinsically stochastic. Nonetheless, cells can reliably respond to the changing environment by sensing their target molecules sensitively and specifically, even with the existence of abundant structurally-similar non-target molecules. The mechanism of how the cells can balance and achieve such different characteristics is not yet fully understood. In this work, we demonstrate that these characteristics can be attained by a ligand-induced stochastic cluster formation of receptors via the noise-induced symmetry breaking, in which the intrinsic stochasticity works to enhance sensitivity and specificity. We also show that the noise-induced cluster formation enables cells to detect the target ligand reliably by compensating the abundant non-target ligands in the environment. The proposed mechanism may lead to a deeper understanding of a biological function of the receptor clustering and provide an alternative candidate for the reliable ligand detection to the kinetic proofreading.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Simulação por Computador / Receptores de Superfície Celular / Modelos Biológicos Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals / Humans Idioma: En Revista: Chaos Assunto da revista: CIENCIA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Japão

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Simulação por Computador / Receptores de Superfície Celular / Modelos Biológicos Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Animals / Humans Idioma: En Revista: Chaos Assunto da revista: CIENCIA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Japão