Sign in
Systems BiologyPLoS ONE
Peer-reviewed journal article

Biodynamics: A novel quasi-first principles theory on the fundamental mechanisms of cellular function/dysfunction and the pharmacological modulation thereof

Gianluca SelvaggioiD, Robert A. PearlsteiniD

Abstract

Cellular function depends on heterogeneous dynamic intra-, inter-, and supramolecular structure-function relationships. However, the specific mechanisms by which cellular function is transduced from molecular systems, and by which cellular dysfunction arises from molecular dysfunction are poorly understood. We proposed previously that cellular function manifests as a molecular form of analog computing, in which specific time-dependent state transition fluxes within sets of molecular species (\"molecular differential equations\" (MDEs)) are sped and slowed in response to specific perturbations (inputs). In this work, we offer a theoretical treatment of the molecular mechanisms underlying cellular analog computing (which we refer to as \"biodynamics\"), focusing primarily on non-equilibrium (dynamic) intermolecular state transitions that serve as the principal means by which MDE systems are solved (the molecular equivalent of mathematical \"integration\"). Under these conditions, bound state occupancy is governed by kon and koff, together with the rates of binding partner buildup and decay. Achieving constant fractional occupancy over time depends on: 1) equivalence between kon and the rate of binding site buildup); 2) equivalence between koff and the rate of binding site decay; and 3) free ligand concentration relative to koff/k0n (n {middle dot} Kd, where n is the fold increase in binding partner concentration needed to achieve a given fractional occupancy). Failure to satisfy these conditions results in fractional occupancy well below that corresponding to n {middle dot} Kd. The implications of biodynamics for cellular function/dysfunction and drug discovery are discussed.

02 /Specification & Classification

Click any tag to browse matching papers
Citations
13
FWCI
0.71
Field percentile
top 32%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISJohnson '20Pearlstein '22Sun '26Tuyéras '26Chang '19Arias '24
56% semantic matchSystems Biology
Margaret E. Johnson, Athena Chen, James R. Faeder+7 more·bioRxiv·Jul 2, 2020