DocumentCode
55821
Title
Studying the Role of Lipid Rafts on Protein Receptor Bindings with Cellular Automata
Author
Haack, Fiete ; Burrage, Kevin ; Redmer, Ronald ; Uhrmacher, Adelinde M.
Author_Institution
Modeling & Simulation Group, Univ. of Rostock, Rostock, Germany
Volume
10
Issue
3
fYear
2013
fDate
May-June 2013
Firstpage
760
Lastpage
770
Abstract
It is widely accepted that lipid rafts promote receptor clustering and thereby facilitate signaling transduction. The role of lipid rafts in inducing and promoting receptor accumulation within the cell membrane has been explored by several computational and experimental studies. However, it remains unclear whether lipid rafts influence the recruitment and binding of proteins from the cytosol as well. To provide an answer to this question a spatial membrane model has been developed based on cellular automata. Our results indicate that lipid rafts indeed influence protein receptor bindings. In particular processes with slow dissociation and binding kinetics are promoted by lipid rafts, whereas fast binding processes are slightly hampered. However, the impact depends on a variety of parameters, such as the size and mobility of the lipid rafts, the induced slow down of receptors within rafts, and also the dissociation and binding kinetics of the cytosolic proteins. Thus, for any individual signaling pathway the influence of lipid rafts on protein binding might be different. To facilitate analyzing this influence given a specific pathway, our approach has been generalized into LiRaM, a modeling and simulation tool for lipid rafts models.
Keywords
biochemistry; biology computing; biomembranes; cellular automata; cellular biophysics; dissociation; molecular biophysics; physiological models; proteins; LiRaM; binding kinetics; cell membrane; cellular automata; cytosolic proteins; dissociation; fast binding processes; individual signaling pathway; lipid raft mobility; lipid raft model; lipid raft size; modeling tool; protein receptor bindings; protein recruitment; receptor accumulation; receptor clustering; signaling transduction; simulation tool; spatial membrane model; specific pathway; Automata; Biological system modeling; Biomembranes; Computational modeling; Kinetic theory; Lipidomics; Proteins; Modeling and simulation; cellular automata; lipid rafts; receptor protein binding; spatial membrane dynamics;
fLanguage
English
Journal_Title
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher
ieee
ISSN
1545-5963
Type
jour
DOI
10.1109/TCBB.2013.40
Filename
6515125
Link To Document