PROBABILITY MODEL FOR MOLECULAR RECOGNITION IN BIOLOGICAL RECEPTOR REPERTOIRES - SIGNIFICANCE TO THE OLFACTORY SYSTEM

Citation
D. Lancet et al., PROBABILITY MODEL FOR MOLECULAR RECOGNITION IN BIOLOGICAL RECEPTOR REPERTOIRES - SIGNIFICANCE TO THE OLFACTORY SYSTEM, Proceedings of the National Academy of Sciences of the United Statesof America, 90(8), 1993, pp. 3715-3719
Citations number
34
ISSN journal
00278424
Volume
90
Issue
8
Year of publication
1993
Pages
3715 - 3719
Database
ISI
SICI code
0027-8424(1993)90:8<3715:PMFMRI>2.0.ZU;2-Y
Abstract
A generalized phenomenological model is presented for stereospecific r ecognition between biological receptors and their ligands. We ask what is the distribution of binding constants PSI(K) between an arbitrary ligand and members of a large receptor repertoire, such as immunoglobu lins or olfactory receptors. For binding surfaces with B potential sub site and S different types of subsite configurations, the number of su ccessful elementary interactions obeys a binomial distribution. The di screte probability function PSI(K) is then derived with assumptions on alpha, the free energy contribution per elementary interaction. The f unctional form of PSI(K) may be universal, although the parameter valu es could vary for different ligand types. An estimate of the parameter values of PSI(K) for iodovanillin, an analog of odorants and immunolo gical haptens, is obtained by equilibrium dialysis experiments with no nimmune antibodies. Based on a simple relationship, predicted by the m odel, between the size of a receptor repertoire and its average maxima l affinity toward an arbitrary ligand, the size of the olfactory recep tor repertoire (N(olf)) is calculated as 300-1000, in very good agreem ent with recent molecular biological studies. A very similar estimate, N(olf) = 500, is independently derived by relating a theoretical dist ribution of maxima for PSI(K) with published human olfactory threshold variations. The present model also has implications to the question o f olfactory coding and to the analysis of specific anosmias, genetic d eficits in perceiving particular odorants. More generally, the propose d model provides a better understanding of ligand specificity in biolo gical receptors and could help in understanding their evolution.