title: Quantifying biological specificity: the statistical mechanics of molecular recognition.
abstract: The Random Energy Model of statistical physics is applied to the problem of the specificity of recognition between two biological (macro)molecules forming a non-covalent complex. In this model, the native mode of association is separated by an energy gap from a large body of non-native modes. Whereas the native mode is unique, the non-native modes form an energy spectrum which is approximated by a gaussian distribution. Specificity can then be estimated by writing the partition function and calculating the ratio r of non-native to native modes at thermodynamic equilibrium. We examine three situations: (i) recognition in the absence of a competitor; (ii) recognition in the presence of a competing ligand; (iii) recognition in a heterogeneous mixture. We derive the dependence of the ratio r on temperature and on the concentration of competing ligands, and we estimate the effect of a local perturbation such as can result from a point mutation. Cases (i) and (iii) are modeled by docking experiments in the computer. In case (iii), which is representative of a wide variety of biological situations, we show that increasing the heterogeneity of a mixture affects the specificity of recognition, even when the concentration of competing species is kept constant.
authors.affiliation: Laboratoire d'Enzymologie et Biochimie Structurales, CNRS, Gif-sur-Yvette, France. janin@lebs.cn2s-gif.fr
authors.forename: J
authors.initials: J
authors.lastname: Janin
mesh_terms: D001665:Binding Sites; D004268:DNA-Binding Proteins / Q000737:chemistry* / Q000378:metabolism; D008024:Ligands; D008956:Models, Chemical; D013816:Thermodynamics
chemical_list: D004268:DNA-Binding Proteins; D008024:Ligands