title: A mathematical model for dynamics of CD40 clustering.
abstract: Ligand bound-receptors in a signalosome complex trigger signals to determine cellular functions. Upon ligand binding, the ligand-receptor complexes form clusters on cell membrane. Guided by the previous experimental reports on the cluster formation of CD40, a trans membrane receptor for CD40-ligand, we built a minimal model of the receptor cluster formation. In this model, we studied co-operative and non-co-operative clustering of a maximum of four CD40 molecules assuming a positive mediator of clustering such as cholesterol to be present in both cases. We observed that co-operative interactions between CD40 molecules resulted in more of the largest CD40 clusters than that observed with the non-co-operatively interacting CD40 molecules. We performed global sensitivity analysis on the model parameters and the analyses suggested that cholesterol influenced only the initial stage of the co-operatively clustering CD40 molecules but it affects both the initial and the final stages in case of the non-co-operatively clustering CD40 molecules. Robustness analyses revealed that in both co-operative and non-co-operative interactions, the higher order clusters beyond a critical size are more robust with respect to alterations in the environmental parameters including the cholesterol. Thus, the role of co-operative and non-co-operative interactions in environment-influenced receptor clustering is reported for the first time.
authors.affiliation: National Centre for Cell Science, Ganeshkhind, Pune, 411007 India.
authors.forename: Uddipan
authors.initials: U
authors.lastname: Sarma
authors.affiliation: PG Department of Physics, RTM Nagpur University, Campus Nagpur, Nagpur, 440033 India.
authors.forename: Prashant M
authors.initials: PM
authors.lastname: Gade
authors.affiliation: National Centre for Cell Science, Ganeshkhind, Pune, 411007 India.
authors.forename: Bhaskar
authors.initials: B
authors.lastname: Saha
keywords: CD40; Cholesterol in receptor clustering; Clustering dynamics; Co-operativity in receptor clustering and robustness; Kinetic model for receptor clustering