Intracellular biochemical networks often display large fluctuations in the molecule numbers or the concentrations of reactive species, making molecular approaches necessary for system descriptions. For Markovian reaction networks, the fluctuation-dissipation theorem (FDT) has been well established and extensively used in fast evaluation of fluctuations in reactive species. For non-Markovian reaction networks, however, the similar FDT has not been established so far. Here, we present a generalized FDT (gFDT) for a large class of non-Markovian reaction networks where general intrinsic-event waiting-time distributions account for the effect of intrinsic noise and general stochastic reaction delays represent the impact of extrinsic noise from environmental perturbations. The starting point is a generalized chemical master equation (gCME), which describes the probabilistic behavior of an equivalent Markovian reaction network and identifies the structure of the original non-Markovian reaction network in terms of stoichiometries and effective transition rates (extensions of common reaction propensity functions). From this formulation follows directly the solution of the linear noise approximation of the stationary gCME for all the components in the non-Markovian reaction network. While the gFDT can quickly trace noisy sources in non-Markovian reaction networks, example analysis verifies its effectiveness.
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http://dx.doi.org/10.1103/PhysRevE.105.064409 | DOI Listing |
Phys Rev E
October 2024
Racah Institute of Physics, The Hebrew University of Jerusalem, Jerusalem 91904, Israel.
Phys Rev Lett
November 2024
Freie Universität Berlin, Fachbereich Physik, 14195 Berlin, Germany.
Protein folding is an intrinsically multitimescale problem. While it is accepted that non-Markovian effects are present on short timescales, it is unclear whether memory-dependent friction influences long-timescale protein folding reaction kinetics. We combine friction memory-kernel extraction techniques with recently published extensive all-atom simulations of the α3D protein under neutral and reduced pH conditions, and we show that the pH reduction modifies the friction acting on the folding protein by dramatically decreasing the friction memory decay time.
View Article and Find Full Text PDFPhys Rev Lett
September 2024
Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA.
Directional chemosensing is ubiquitous in cell biology, but some cells such as mating yeast paradoxically degrade the signal they aim to detect. While the data processing inequality suggests that such signal modification cannot increase the sensory information, we show using a reaction-diffusion model and an exactly solvable discrete-state reduction that it can. We identify a non-Markovian step in the information chain allowing the system to evade the data processing inequality, reflecting the nonlocal nature of diffusion.
View Article and Find Full Text PDFAcc Chem Res
November 2024
Beijing National Laboratory for Molecular Sciences, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Zhongguancun, Beijing 100190, China.
ConspectusQuantum effects are critical to understanding many chemical dynamical processes in condensed phases, where interactions between molecules and their environment are usually strong and non-Markovian. In this Account, we review recent progress from our group in development and application of the hierarchical equations of motion (HEOM) method, highlighting its ability to address some challenging problems in quantum chemical dynamics.In the HEOM method, the bath degrees of freedom are represented using effective modes from exponential decomposition of the bath correlation function.
View Article and Find Full Text PDFJ Chem Phys
September 2024
Fachbereich Physik, Freie Universität Berlin, 14195 Berlin, Germany.
By simulation and asymptotic theory, we investigate the transition-path time of a one-dimensional finite-mass reaction coordinate crossing a double-well potential in the presence of non-Markovian friction. First, we consider single-exponential memory kernels and demonstrate that memory accelerates transition paths compared to the Markovian case, especially in the low-mass/high-friction limit. Then, we generalize to multi-exponential kernels and construct an asymptotic formula for the transition-path time that compares well with simulation data.
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