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Field theory of enzyme-substrate systems with restricted long-range interactions.
Olmeda, Fabrizio; Rulands, Steffen.
Affiliation
  • Olmeda F; <a href="https://ror.org/01bf9rw71">Max Planck Institute for the Physics of Complex Systems</a>, D-01138 Dresden, Germany and <a href="https://ror.org/03gnh5541">Institute of Science and Technology Austria</a>, 3400 Klosterneuberg, Austria.
  • Rulands S; Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Department of Physics, <a href="https://ror.org/05591te55">Ludwig-Maximilians-Universität München</a>, D-80333 Munich, Germany and <a href="https://ror.org/01bf9rw71">Max Planck Institute for the Physics of Complex Systems</a>, D-01138 Dresden, Germany.
Phys Rev E ; 110(2-1): 024404, 2024 Aug.
Article in En | MEDLINE | ID: mdl-39294986
ABSTRACT
Enzyme-substrate kinetics form the basis of many biomolecular processes. The interplay between substrate binding and substrate geometry can give rise to long-range interactions between enzyme binding events. Here we study a general model of enzyme-substrate kinetics with restricted long-range interactions described by an exponent -γ. We employ a coherent-state path integral and renormalization group approach to calculate the first moment and two-point correlation function of the enzyme-binding profile. We show that starting from an empty substrate the average occupancy follows a power law with an exponent 1/(1-γ) over time. The correlation function decays algebraically with two distinct spatial regimes characterized by exponents -γ on short distances and -(2/3)(2-γ) on long distances. The crossover between both regimes scales inversely with the average substrate occupancy. Our work allows associating experimental measurements of bound enzyme locations with their binding kinetics and the spatial conformation of the substrate.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Enzymes Language: En Journal: Phys Rev E Year: 2024 Document type: Article Affiliation country: Austria Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Enzymes Language: En Journal: Phys Rev E Year: 2024 Document type: Article Affiliation country: Austria Country of publication: United States