Molecular modeling of muscarinic acetylcholine receptors: Structural basis of ligand-receptor interactions / Chin Sek Peng
Muscarinic acetylcholine receptors (mAChRs), specifically of the M1 subtype, have been the focus of significant drug discovery and development due to their potential roles in the pathophysiology of several central nervous system disorders, such as, Alzheimer’s disease. Because of the conserved or...
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| Format: | Thesis |
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2015
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| Online Access: | http://studentsrepo.um.edu.my/7048/ http://studentsrepo.um.edu.my/7048/7/sek_peng.pdf |
| Summary: | Muscarinic acetylcholine receptors (mAChRs), specifically of the M1 subtype, have
been the focus of significant drug discovery and development due to their potential roles
in the pathophysiology of several central nervous system disorders, such as,
Alzheimer’s disease. Because of the conserved orthosteric binding pocket of mAChRs,
identification of the selective activators/modulators have not been realized, and this
often lead to undesired side effects from off-target activation. In this thesis, structural
and dynamics studies of the M1 mAChR using computational approaches are presented.
Homology models of the M1 mAChR were constructed and virtual screening
experiments showed that the models could efficiently differentiate agonists from
decoys, with the TM5-modified models also giving good agonist/antagonist selectivity.
Molecular dynamics simulations further allowed the characterization of the dynamics
profiles of different mAChR subtypes, bound to an agonist or antagonist and in apo
form, leading to the elucidation of ligand affinity, selectivity, and possible allosteric
pocket formation. Lastly, the models together with the crystal structures of the M2 and
M3 mAChRs were used in virtual screening to identify potential selective M1 mAChR
binders. Of the 19 hits identified, 11 ligands targeted the orthosteric cavity, 7 portray
bitopic characteristic, and 1 was found to preferentially sit on top of the orthosteric site.
Together, this study demonstrates that computational tools can be applied to provide
insight in understanding the structural basis of ligand-receptor interactions and the
dynamics patterns of different mAChR subtypes, and can aid the discovery of potential M1 mAChR selective hits. |
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