Carbachol dimers with primary carbamate groups as homobivalent modulators of muscarinic receptors

Matucci, Rosanna; Bellucci, Cristina; Martino, Maria Vittoria; Nesi, Mascia; Manetti, Dina; Welzel, Jessica; Bartz, Ulrike; Holze, Janine; Tränkle, Christian; Mohr, Klaus; Mazzolari, Angelica; Vistoli, Giulio; Dei, Silvia; Teodori, Elisabetta; Romanelli, Maria Novella

doi:10.1016/j.ejphar.2020.173183

Cited by 7 publications

(8 citation statements)

References 23 publications

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“…8A). 61,65,66,74,75,81,82,85,86,103,111,120,124,132,135 Compared to allosteric modulators, dualsteric modulators do not require natural ligands in biased activation. In fact, the orthosteric pharmacophore might realize a higher fold of activation.…”

Section: Development Of Function-biased Modulatorsmentioning

confidence: 99%

“…After a manual filtering, 133 research articles focusing on identifications of novel dualsteric modulators were found. Modulators targeting GPCR 50,53,56–137 or kinase 138–157 account for more than three quarters (Fig. 5).…”

Section: Targets For Dualsteric Modulatorsmentioning

confidence: 99%

“…GPCR itself has accommodated 62.4% targets of reports. 50,53,56–137 GPCR is a class of 7-transmembrane (7TM) proteins decorated on the cell membrane for transduction amplification of exterior signals into cells. 189 They are vital in many physiological processes and are therefore popular drug targets for a series of diseases like cancers and neurological disorders.…”

Section: Targets For Dualsteric Modulatorsmentioning

confidence: 99%

“…Dualsteric modulators, which bind to both orthosteric and allosteric sites, have been showing a good balance of potency and selectivity. 50,56,61–66,68,70,72,75,77–85,88,89,96–100,102,103,106,108,114,117,121–124,126,127,131,136,138,140,142–145,149,150,153,156,159–162,164–166,171–174,176,179–182,184–188,195–199 It could be found that the combined molecule would have a better selectivity than the orthosteric synthon while a better potency than the allosteric synthon. For example, Antony et al 136 designed a dualsteric modulator targeting muscarinic M 2 receptor (M 2 R).…”

Section: Aims Of Dualsteric Modulatorsmentioning

confidence: 99%

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Designing drugs and chemical probes with the dualsteric approach

Zha,

He,

et al. 2023

Chem. Soc. Rev.

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Section: Development Of Function-biased Modulatorsmentioning

confidence: 99%

Section: Targets For Dualsteric Modulatorsmentioning

confidence: 99%

Section: Targets For Dualsteric Modulatorsmentioning

confidence: 99%

Section: Aims Of Dualsteric Modulatorsmentioning

confidence: 99%

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Designing drugs and chemical probes with the dualsteric approach

Zha,

He,

et al. 2023

Chem. Soc. Rev.

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“…As mentioned in the Introduction, all performed docking simulations involved two resolved human hM 2 structures: the inactive state bound to an antagonist (PDB Id: 3UON) [14] and the active state bound to the agonist iperoxo and the allosteric modulator LY2119620 (PDB Id: 4MQT) [15]. The downloaded structures were prepared as recently described [25]. Briefly, the structures were completed by adding hydrogens and the missed side-chains: to remain compatible to physiological pH, the residues Asp, Glu, Lys and Arg were considered ionized while Cys and His as neutral by default.…”

Section: Preliminary Virtual Screening Simulationsmentioning

confidence: 99%

Repositioning Dequalinium as Potent Muscarinic Allosteric Ligand by Combining Virtual Screening Campaigns and Experimental Binding Assays

Mazzolari

Gervasoni

Pedretti

et al. 2020

IJMS

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Structure-based virtual screening is a truly productive repurposing approach provided that reliable target structures are available. Recent progresses in the structural resolution of the G-Protein Coupled Receptors (GPCRs) render these targets amenable for structure-based repurposing studies. Hence, the present study describes structure-based virtual screening campaigns with a view to repurposing known drugs as potential allosteric (and/or orthosteric) ligands for the hM2 muscarinic subtype which was indeed resolved in complex with an allosteric modulator thus allowing a precise identification of this binding cavity. First, a docking protocol was developed and optimized based on binding space concept and enrichment factor optimization algorithm (EFO) consensus approach by using a purposely collected database including known allosteric modulators. The so-developed consensus models were then utilized to virtually screen the DrugBank database. Based on the computational results, six promising molecules were selected and experimentally tested and four of them revealed interesting affinity data; in particular, dequalinium showed a very impressive allosteric modulation for hM2. Based on these results, a second campaign was focused on bis-cationic derivatives and allowed the identification of other two relevant hM2 ligands. Overall, the study enhances the understanding of the factors governing the hM2 allosteric modulation emphasizing the key role of ligand flexibility as well as of arrangement and delocalization of the positively charged moieties.

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