dorsal/arxiv
View SchemaEquations for Stochastic Macromolecular Mechanics of Single Proteins: Equilibrium Fluctuations, Transient Kinetics and Nonequilibrium Steady-State
| Authors | Hong Qian |
|---|---|
| Categories | |
| ArXiv ID | physics/0007017 |
| URL | https://arxiv.org/abs/physics/0007017 |
| DOI | 10.1021/jp013143w |
| Journal | Journal of Physical Chemistry, B. Vol. 106, pp. 2065-2073 (2002) |
Abstract
A modeling framework for the internal conformational dynamics and external mechanical movement of single biological macromolecules in aqueous solution at constant temperature is developed. Both the internal dynamics and external movement are stochastic; the former is represented by a master equation for a set of discrete states, and the latter is described by a continuous Smoluchowski equation. Combining these two equations into one, a comprehensive theory for the Brownian dynamics and statistical thermodynamics of single macromolecules arises. This approach is shown to have wide applications. It is applied to protein-ligand dissociation under external force, unfolding of polyglobular proteins under extension, movement along linear tracks of motor proteins against load, and enzyme catalysis by single fluctuating proteins. As a generalization of the classic polymer theory, the dynamic equation is capable of characterizing a single macromolecule in aqueous solution, in probabilistic terms, (1) its thermodynamic equilibrium with fluctuations, (2) transient relaxation kinetics, and most importantly and novel (3) nonequilibrium steady-state with heat dissipation. A reversibility condition which guarantees an equilibrium solution and its thermodynamic stability is established, an H-theorem like inequality for irreversibility is obtained, and a rule for thermodynamic consistency in chemically pumped nonequilibrium steady-state is given.
{
"annotation_id": "ac2ca9b9-8810-44f0-a6f8-915ee8650934",
"date_created": "2026-03-02T18:00:32.657000Z",
"date_modified": "2026-03-02T18:00:32.657000Z",
"file_hash": "df879b53c6901eb8cefb2dbfa95a1ecec624bbde1ad288f19cd9a092c66f64b0",
"private": false,
"record": {
"abstract": "A modeling framework for the internal conformational dynamics and external\nmechanical movement of single biological macromolecules in aqueous solution at\nconstant temperature is developed. Both the internal dynamics and external\nmovement are stochastic; the former is represented by a master equation for a\nset of discrete states, and the latter is described by a continuous\nSmoluchowski equation. Combining these two equations into one, a comprehensive\ntheory for the Brownian dynamics and statistical thermodynamics of single\nmacromolecules arises. This approach is shown to have wide applications. It is\napplied to protein-ligand dissociation under external force, unfolding of\npolyglobular proteins under extension, movement along linear tracks of motor\nproteins against load, and enzyme catalysis by single fluctuating proteins. As\na generalization of the classic polymer theory, the dynamic equation is capable\nof characterizing a single macromolecule in aqueous solution, in probabilistic\nterms, (1) its thermodynamic equilibrium with fluctuations, (2) transient\nrelaxation kinetics, and most importantly and novel (3) nonequilibrium\nsteady-state with heat dissipation. A reversibility condition which guarantees\nan equilibrium solution and its thermodynamic stability is established, an\nH-theorem like inequality for irreversibility is obtained, and a rule for\nthermodynamic consistency in chemically pumped nonequilibrium steady-state is\ngiven.",
"arxiv_id": "physics/0007017",
"authors": [
"Hong Qian"
],
"categories": [
"physics.bio-ph",
"q-bio"
],
"doi": "10.1021/jp013143w",
"journal_ref": "Journal of Physical Chemistry, B. Vol. 106, pp. 2065-2073 (2002)",
"title": "Equations for Stochastic Macromolecular Mechanics of Single Proteins: Equilibrium Fluctuations, Transient Kinetics and Nonequilibrium Steady-State",
"url": "https://arxiv.org/abs/physics/0007017"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "e7ef7c8e-f2e7-4855-9458-d3e7ef21657e",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}