scholarly journals An analytical coarse-graining method which preserves the free energy, structural correlations, and thermodynamic state of polymer melts from the atomistic to the mesoscale

2014 ◽  
Vol 140 (20) ◽  
pp. 204913 ◽  
Author(s):  
J. McCarty ◽  
A. J. Clark ◽  
J. Copperman ◽  
M. G. Guenza
2020 ◽  
Vol 16 (4) ◽  
pp. 557-580
Author(s):  
S.A. Rashkovskiy ◽  

It is believed that thermodynamic laws are associated with random processes occurring in the system and, therefore, deterministic mechanical systems cannot be described within the framework of the thermodynamic approach. In this paper, we show that thermodynamics (or, more precisely, a thermodynamically-like description) can be constructed even for deterministic Hamiltonian systems, for example, systems with only one degree of freedom. We show that for such systems it is possible to introduce analogs of thermal energy, temperature, entropy, Helmholtz free energy, etc., which are related to each other by the usual thermodynamic relations. For the Hamiltonian systems considered, the first and second laws of thermodynamics are rigorously derived, which have the same form as in ordinary (molecular) thermodynamics. It is shown that for Hamiltonian systems it is possible to introduce the concepts of a thermodynamic state, a thermodynamic process, and thermodynamic cycles, in particular, the Carnot cycle, which are described by the same relations as their usual thermodynamic analogs.


2009 ◽  
Vol 11 (12) ◽  
pp. 1942 ◽  
Author(s):  
T. Strauch ◽  
L. Yelash ◽  
W. Paul

1990 ◽  
Vol 42 (6) ◽  
pp. 3196-3206 ◽  
Author(s):  
Brad Lee Holian ◽  
Harald A. Posch ◽  
William G. Hoover

2019 ◽  
Author(s):  
Griffin Chure ◽  
Manuel Razo-Mejia ◽  
Nathan M. Belliveau ◽  
Tal Einav ◽  
Zofii A. Kaczmarek ◽  
...  

Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring changes in the free energy of the system to link individual mutations in an allosteric transcriptional repressor to the parameters which govern its response. We find the energetic effects of the mutations can be categorized into several classes which have characteristic curves as a function of the inducer concentration. We experimentally test these diagnostic predictions using the well-characterized LacI repressor of Escherichia coli, probing several mutations in the DNA binding and inducer binding domains. We find that the change in gene expression due to a point mutation can be captured by modifying only a subset of the model parameters that describe the respective domain of the wild-type protein. These parameters appear to be insulated, with mutations in the DNA binding domain altering only the DNA affinity and those in the inducer binding domain altering only the allosteric parameters. Changing these subsets of parameters tunes the free energy of the system in a way that is concordant with theoretical expectations. Finally, we show that the induction profiles and resulting free energies associated with pairwise double mutants can be predicted with quantitative accuracy given knowledge of the single mutants, providing an avenue for identifying and quantifying epistatic interactions.SummaryWe present a biophysical model of allosteric transcriptional regulation that directly links the location of a mutation within a repressor to the biophysical parameters that describe its behavior. We explore the phenotypic space of a repressor with mutations in either the inducer binding or DNA binding domains. Using the LacI repressor in E. coli, we make sharp, falsifiable predictions and use this framework to generate a null hypothesis for how double mutants behave given knowledge of the single mutants. Linking mutations to the parameters which govern the system allows for quantitative predictions of how the free energy of the system changes as a result, permitting coarse graining of high-dimensional data into a single-parameter description of the mutational consequences.


1998 ◽  
Vol 49 (2-3) ◽  
pp. 61-74 ◽  
Author(s):  
W. Tschöp ◽  
K. Kremer ◽  
J. Batoulis ◽  
T. Bürger ◽  
O. Hahn

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