title: Stochastic simulations of ErbB homo and heterodimerisation: potential impacts of receptor conformational state and spatial segregation.
abstract: ErbB overexpression is linked to carcinogenesis. It is hypothesised that this is due to increased receptor density and receptor clustering, leading to increased receptor dimerisation and activation. Herein, spatial stochastic simulations have been performed to shed light receptor dimerisation processes. First, ligand-independent homodimerisation, is considered, based upon constitutive oligomerisation estimates (14%) in A431 cells that overexpress epidermal growth factor receptor (EGFR). When autocrine stimulation is blocked, ligand-independent EGFR activation is demonstrated by persistent, low levels of phosphorylation. The possibility that ligand-independent signalling is due to the fluctuation of EGFR conformation is considered. The agent-based model predicts the frequency (expressed as a probability) that uniformly distributed receptors would need to flux to the open conformation to reach 14% EGFR dimers at high receptor density. Simulations suggest that ligand-independent EGFR homodimerisation is highly density dependent, since collisions between 'open', dimerisation-competent receptors are a rare event at low receptor levels. Simulations that incorporate receptor clustering lower the threshold for homodimerisation of unoccupied receptors as well as the estimate of the probability for fluxing to the dimer-competent conformation. The impact of ErbB receptor clustering patterns on hetero and homodimerisation rates is also considered, using immunoelectron microscopy data derived from SKBR3 breast cancer cells that express ErbB2>>EGFR>ErbB3. Partial spatial segregation of ErbB receptors has a profound effect on simulated heterodimerisation rates. Despite the general assumption that ErbB2 is a preferred heterodimerising partner for other ErbBs, it is predicted that most ErbB2 will form homodimers. Overall, it is proposed that both receptor density and membrane spatial organisation contribute to the carcinogenesis process.
authors.affiliation: University of New Mexico, Department of Electrical and Computer Engineering, Albuquerque, NM, USA.
authors.forename: M-Y
authors.initials: MY
authors.lastname: Hsieh
authors.forename: S
authors.initials: S
authors.lastname: Yang
authors.forename: M A
authors.initials: MA
authors.lastname: Raymond-Stinz
authors.forename: S
authors.initials: S
authors.lastname: Steinberg
authors.forename: D G
authors.initials: DG
authors.lastname: Vlachos
authors.forename: W
authors.initials: W
authors.lastname: Shu
authors.forename: B
authors.initials: B
authors.lastname: Wilson
authors.forename: J S
authors.initials: JS
authors.lastname: Edwards
mesh_terms: D002462:Cell Membrane / Q000737:chemistry* / Q000378:metabolism* / Q000648:ultrastructure; D003198:Computer Simulation; D019281:Dimerization; D008954:Models, Biological; D008956:Models, Chemical; D008958:Models, Molecular; D011487:Protein Conformation; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000737:chemistry / Q000378:metabolism / Q000648:ultrastructure; D013269:Stochastic Processes; D013329:Structure-Activity Relationship
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases