PROBABILITY MODEL FOR MOLECULAR RECOGNITION IN BIOLOGICAL RECEPTOR REPERTOIRES - SIGNIFICANCE TO THE OLFACTORY SYSTEM
PROBABILITY MODEL FOR MOLECULAR RECOGNITION IN BIOLOGICAL RECEPTOR REPERTOIRES - SIGNIFICANCE TO THE OLFACTORY SYSTEM
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DOI：
10.1073/pnas.90.8.3715
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发表时间：
1993-04-15
影响因子：
11.1
通讯作者：
SEIDEMANN, E
中科院分区：
文献类型：
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作者：
LANCET, D;SADOVSKY, E;SEIDEMANN, E
提出了生物受体与配体立体专一性识别的广义唯象模型。我们问什么是任意配体和一个大的受体库，如免疫球蛋白或嗅觉受体的成员之间的结合常数PSI（K）的分布。对于具有B势亚位和S种不同亚位构型的结合表面，成功的基元相互作用的数目服从二项分布。离散概率函数PSI（K），然后推导出假设的α，每个基本相互作用的自由能贡献。PSI（K）的函数形式可以是通用的，尽管参数值可以针对不同的配体类型而变化。碘香草醛，气味剂和免疫半抗原的类似物，PSI（K）的参数值的估计，获得了平衡透析实验与非免疫抗体。基于一个简单的关系，预测的模型，受体库的大小和其对任意配体的平均最大亲和力之间，嗅觉受体库的大小（N（olf））计算为300-1000，在最近的分子生物学研究非常好的协议。通过将PSI（K）的最大值的理论分布与公开的人类嗅觉阈值变化相关联，独立地导出非常类似的估计N（olf）= 500。本模型也有影响的问题，嗅觉编码和分析特定的嗅觉缺失，遗传缺陷，在感知特定的气味。更一般地说，所提出的模型提供了一个更好的理解生物受体中的配体特异性，并可能有助于理解它们的进化。
A generalized phenomenological model is presented for stereospecific recognition 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 immunoglobulins or olfactory receptors. For binding surfaces with B potential subsite and S different types of subsite configurations, the number of successful elementary interactions obeys a binomial distribution. The discrete probability function PSI(K) is then derived with assumptions on alpha, the free energy contribution per elementary interaction. The functional form of PSI(K) may be universal, although the parameter values could vary for different ligand types. An estimate of the parameter values of PSI(K) for iodovanillin, an analog of odorants and immunological haptens, is obtained by equilibrium dialysis experiments with nonimmune antibodies. Based on a simple relationship, predicted by the model, between the size of a receptor repertoire and its average maximal affinity toward an arbitrary ligand, the size of the olfactory receptor repertoire (N(olf)) is calculated as 300-1000, in very good agreement with recent molecular biological studies. A very similar estimate, N(olf) = 500, is independently derived by relating a theoretical distribution of maxima for PSI(K) with published human olfactory threshold variations. The present model also has implications to the question of olfactory coding and to the analysis of specific anosmias, genetic deficits in perceiving particular odorants. More generally, the proposed model provides a better understanding of ligand specificity in biological receptors and could help in understanding their evolution.