Probability model for molecular recognition in biological receptor repertoires: significance to the olfactory system.
Open accessAbstract
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 (Nolf) is calculated as 300-1000, in very good agreement with recent molecular biological studies. A very similar estimate, Nolf = 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.
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The receptor affinity distribution (RAD) inferred via string matching is broadly applicable to the immune and olfactory systems and portrays a Poisson distribution, approximated by a lognormal distribution in GARD applications.
“Along these lines, we have inferred a receptor affinity distribution (RAD) broadly applicable to the immune and olfactory systems via a close analogue of string matching [65,79]. This portrayed a Poisson distribution, which in GARD applications [54] was approximated by a lognormal distribution [80].”
From Systems protobiology: origin of life in lipid catalytic networks (2018) · cites this paper as [65]
Stronger and more selective interactions come via a relationship between affinity and selectivity known to exist in ligand-target interactions in general.
“Along with that, come stronger and more selective interactions, via a relationship between affinity and selectivity known to exist in ligand–target interactions in general [65,226].”
From Systems protobiology: origin of life in lipid catalytic networks (2018) · cites this paper as [65]
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- Authors
- Lancet, D., Sadovsky, E., & Seidemann, E.
- Affiliations
- Weizmann Institute of Science (IL)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 1993-04-15
- Volume
- 90
- Issue
- 8
- Pages
- 3715-3719
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC46372
- OpenAlex
- W1975934174
- Cited by
- 160
- References
- 1
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 4 · 2022: 1 · 2021: 2 · 2019: 4 · 2018: 1 · 2017: 1 · 2016: 3 · 2015: 3 · 2014: 2 · 2013: 6 · 2012: 10
- FWCI
- 1.97
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Sensory Systems › Olfactory and Sensory Function Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
- Health Sciences › Nursing › Nutrition and Dietetics › Biochemical Analysis and Sensing Techniques
- Keywords
- molecular recognition, ligand-receptor interactions, olfactory receptors, immunoglobulins, binomial distribution, aroma compounds, odor threshold, odor coding, anosmia, receptor evolution
- MeSH terms
- Animals, Benzaldehydes, Cattle, Humans, Immunoglobulins, Iodine Radioisotopes, Kinetics, Mathematics, Models, Biological, Probability, Sensory Receptor Cells, Sensory Thresholds, Smell, Thermodynamics, Models, Statistical
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