Nicotinic receptors: From protein allostery to computational neuropharmacology.
Allosteric regulation
Binding affinity calculations
Brain disease
Efficacy
MWC theory
Modeling
Molecular dynamics
Neuropharmacology
Nicotinic acetylcholine receptor
Potency
Selectivity
Synaptic receptors
Thermodynamic modeling
Journal
Molecular aspects of medicine
ISSN: 1872-9452
Titre abrégé: Mol Aspects Med
Pays: England
ID NLM: 7603128
Informations de publication
Date de publication:
04 2022
04 2022
Historique:
received:
27
07
2021
revised:
28
09
2021
accepted:
30
09
2021
pubmed:
18
10
2021
medline:
15
3
2022
entrez:
17
10
2021
Statut:
ppublish
Résumé
We propose an extension and further development of the Monod-Wyman-Changeux model for allosteric transitions of regulatory proteins to brain communications and specifically to neurotransmitters receptors, with the nicotinic acetylcholine receptor (nAChR) as a model of ligand-gated ion channels. The present development offers an expression of the change of the gating isomerization constant caused by pharmacological ligand binding in terms of its value in the absence of ligands and several "modulation factors", which vary with orthosteric ligand binding (agonists/antagonists), allosteric ligand binding (positive allosteric modulators/negative allosteric modulators) and receptor desensitization. The new - explicit - formulation of such "modulation factors", provides expressions for the pharmacological attributes of potency, efficacy, and selectivity for the modulatory ligands (including endogenous neurotransmitters) in terms of their binding affinity for the active, resting, and desensitized states of the receptor. The current formulation provides ways to design neuroactive compounds with a controlled pharmacological profile, opening the field of computational neuro-pharmacology.
Identifiants
pubmed: 34656371
pii: S0098-2997(21)00104-7
doi: 10.1016/j.mam.2021.101044
pii:
doi:
Substances chimiques
Ligands
0
Receptors, Nicotinic
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
101044Informations de copyright
Copyright © 2021. Published by Elsevier Ltd.