title: Evolution of complex probability distributions in enzyme cascades.
abstract: Unusual probability distribution profiles, including transient multi-peak distributions, have been observed in computer simulations of cell signaling dynamics. The emergence of these complex distributions cannot be explained using either deterministic chemical kinetics or simple Gaussian noise approximation. To develop physical insights into the origin of complex distributions in stochastic cell signaling, we compared our approximate analytical solutions of signaling dynamics with the exact numerical simulations. Our results are based on studying signaling in 2-step and 3-step enzyme amplification cascades that are among the most common building blocks of cellular protein signaling networks. We have found that while the multi-peak distributions are typically transient, and eventually evolve into single peak distributions, in certain cases these distributions may be stable in the limit of long times. We also have shown that introducing positive feedback loops results in diminution of the probability distribution complexity.
authors.affiliation: Department of Chemistry, University of North Carolina, Chapel Hill, USA.
authors.forename: Yueheng
authors.initials: Y
authors.lastname: Lan
authors.forename: Garegin A
authors.initials: GA
authors.lastname: Papoian
mesh_terms: D000465:Algorithms; D000818:Animals; D002477:Cells / Q000201:enzymology*; D004798:Enzymes / Q000493:pharmacokinetics*; D005246:Feedback; D008954:Models, Biological; D011336:Probability; D011506:Proteins / Q000378:metabolism; D015398:Signal Transduction / Q000502:physiology*; D013269:Stochastic Processes; D013997:Time Factors
chemical_list: D004798:Enzymes; D011506:Proteins