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Towards a full quantitative description of single-molecule reaction kinetics in biological cells.
Grebenkov, Denis S; Metzler, Ralf; Oshanin, Gleb.
Afiliação
  • Grebenkov DS; Laboratoire de Physique de la Matière Condensée (UMR 7643), CNRS - Ecole Polytechnique, University Paris-Saclay, 91128 Palaiseau, France. denis.grebenkov@polytechnique.edu.
Phys Chem Chem Phys ; 20(24): 16393-16401, 2018 Jun 20.
Article em En | MEDLINE | ID: mdl-29873351
The first-passage time (FPT), i.e., the moment when a stochastic process reaches a given threshold value for the first time, is a fundamental mathematical concept with immediate applications. In particular, it quantifies the statistics of instances when biomolecules in a biological cell reach their specific binding sites and trigger cellular regulation. Typically, the first-passage properties are given in terms of mean first-passage times. However, modern experiments now monitor single-molecular binding-processes in living cells and thus provide access to the full statistics of the underlying first-passage events, in particular, inherent cell-to-cell fluctuations. We here present a robust explicit approach for obtaining the distribution of FPTs to a small partially reactive target in cylindrical-annulus domains, which represent typical bacterial and neuronal cell shapes. We investigate various asymptotic behaviours of this FPT distribution and show that it is typically very broad in many biological situations, thus, the mean FPT can differ from the most probable FPT by orders of magnitude. The most probable FPT is shown to strongly depend only on the starting position within the geometry and to be almost independent of the target size and reactivity. These findings demonstrate the dramatic relevance of knowing the full distribution of FPTs and thus open new perspectives for a more reliable description of many intracellular processes initiated by the arrival of one or few biomolecules to a small, spatially localised region inside the cell.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Células / Modelos Químicos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Células / Modelos Químicos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article