On the fitting of binding data when receptor dimerization is suspected

Mechanistic and empirical modelling are compared in context of dimeric receptors. In particular, the supposed advantages of the two-state dimer model for fitting of binding data with respect to classical approaches such as the two-independent sites model are investigated. The two models are revisited from both the mechanistic and empirical point of views. The problem of overparameterized models and the benefits of the concurrent use of mechanistic and empirical models for mechanism analysis are discussed. The pros and cons of mathematical models are examined with special emphasis given to the interpretation of the connection between the shapes of the curves and receptor cooperativity. It is shown that a given pharmacological phenotype (curve shape) can be obtained from different receptor genotypes (as, for instance, non-interconvertible monomeric receptor species, receptor-G protein interactions and dimeric receptors), though values of the Hill coefficient greater than one are indicative of receptor oligomerization. The existence of a relationship between the recently defined dimer cooperativity index and the more familiar Hill coefficient is proven.