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City, D. J. & Roth, B. L. DREADDs (designer receptors solely activated by designer medication): chemogenetic instruments with therapeutic utility. Annu. Rev. Pharmacol. Toxicol. 55, 399–417 (2015).
Roth, B. L. DREADDs for neuroscientists. Neuron 89, 683–694 (2016).
Roth, B. L. How construction informs and transforms chemogenetics. Curr. Opin. Struct. Biol. 57, 9–16 (2019).
Wang, L. et al. Use of DREADD expertise to establish novel targets for antidiabetic medication. Annu. Rev. Pharmacol. Toxicol. 61, 421–440 (2021).
Armbruster, B. N., Li, X., Pausch, M. H., Herlitze, S. & Roth, B. L. Evolving the lock to suit the important thing to create a household of G protein-coupled receptors potently activated by an inert ligand. Proc. Natl Acad. Sci. USA 104, 5163–5168 (2007).
Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G. & Deisseroth, Okay. Millisecond-timescale, genetically focused optical management of neural exercise. Nat. Neurosci. 8, 1263–1268 (2005).
Isberg, V. et al. Generic GPCR residue numbers—aligning topology maps whereas minding the gaps. Tendencies Pharmacol. Sci. 36, 22–31 (2015).
Hu, J. et al. A G protein-biased designer G protein-coupled receptor helpful for finding out the physiological relevance of Gq/11-dependent signaling pathways. J. Biol. Chem. 291, 7809–7820 (2016).
Nakajima, Okay. & Wess, J. Design and purposeful characterization of a novel, arrestin-biased designer G protein-coupled receptor. Mol. Pharmacol. 82, 575–582 (2012).
Guettier, J. M. et al. A chemical-genetic method to check G protein regulation of β cell perform in vivo. Proc. Natl Acad. Sci. USA 106, 19197–19202 (2009).
Inoue, A. et al. Illuminating G-protein-coupling selectivity of GPCRs. Cell 177, 1933–1947.e25 (2019).
Bender, D., Holschbach, M. & Stöcklin, G. Synthesis of n.c.a. carbon-11 labelled clozapine and its main metabolite clozapine-N-oxide and comparability of their biodistribution in mice. Nucl. Med. Biol. 21, 921–925 (1994).
Gomez, J. L. et al. Chemogenetics revealed: DREADD occupancy and activation by way of transformed clozapine. Science 357, 503–507 (2017).
Jann, M. W., Lam, Y. W. & Chang, W. H. Speedy formation of clozapine in guinea-pigs and man following clozapine-N-oxide administration. Arch. Int. Pharmacodyn. Ther. 328, 243–250 (1994).
Roth, B. L., Sheffler, D. J. & Kroeze, W. Okay. Magic shotguns versus magic bullets: selectively non-selective medication for temper issues and schizophrenia. Nat. Rev. Drug Discov. 3, 353–359 (2004).
Weston, M. et al. Olanzapine: a potent agonist on the hM4D(Gi) DREADD amenable to medical translation of chemogenetics. Sci. Adv. 5, eaaw1567 (2019).
Nagai, Y. et al. Deschloroclozapine, a potent and selective chemogenetic actuator allows speedy neuronal and behavioral modulations in mice and monkeys. Nat. Neurosci. 23, 1157–1167 (2020).
Thompson, Okay. J. et al. DREADD agonist 21 is an efficient agonist for muscarinic-based DREADDs in vitro and in vivo. ACS Pharmacol. Transl. Sci. 1, 61–72 (2018).
Chen, X. et al. The primary construction–exercise relationship research for designer receptors solely activated by designer medication. ACS Chem. Neurosci. 6, 476–484 (2015).
Bonaventura, J. et al. Excessive-potency ligands for DREADD imaging and activation in rodents and monkeys. Nat. Commun. 10, 4627 (2019).
Nehme, R. et al. Mini-G proteins: novel instruments for finding out GPCRs of their lively conformation. PLoS ONE 12, e0175642 (2017).
Kim, Okay. et al. Construction of a hallucinogen-activated Gq-coupled 5-HT2A serotonin receptor. Cell 182, 1574–1588.e19 (2020).
Garcia-Nafria, J., Nehme, R., Edwards, P. C. & Tate, C. G. Cryo-EM construction of the serotonin 5-HT1B receptor coupled to heterotrimeric Go. Nature 558, 620–623 (2018).
Zhang, S. et al. Inactive and lively state constructions template selective instruments for the human 5-HT5A receptor. Nat. Struct. Mol. Biol. 29, 677–687 (2022).
Duan, J. et al. Cryo-EM construction of an activated VIP1 receptor–G protein advanced revealed by a NanoBiT tethering technique. Nat. Commun. 11, 4121 (2020).
Maeda, S., Qu, Q., Robertson, M. J., Skiniotis, G. & Kobilka, B. Okay. Buildings of the M1 and M2 muscarinic acetylcholine receptor/G-protein complexes. Science 364, 552–557 (2019).
Wang, J. et al. The unconventional activation of the muscarinic acetylcholine receptor M4R by various ligands. Nat. Commun. 13, 2855 (2022).
Liu, H. et al. Construction-guided improvement of selective M3 muscarinic acetylcholine receptor antagonists. Proc. Natl Acad. Sci. USA 115, 12046–12050 (2018).
Thorsen, T. S., Matt, R., Weis, W. I. & Kobilka, B. Okay. Modified T4 lysozyme fusion proteins facilitate G protein-coupled receptor crystallogenesis. Construction 22, 1657–1664 (2014).
Kruse, A. C. et al. Construction and dynamics of the M3 muscarinic acetylcholine receptor. Nature 482, 552–556 (2012).
Kenakin, T., Watson, C., Muniz-Medina, V., Christopoulos, A. & Novick, S. A easy technique for quantifying purposeful selectivity and agonist bias. ACS Chem. Neurosci. 3, 193–203 (2012).
Wess, J., Maggio, R., Palmer, J. R. & Vogel, Z. Position of conserved threonine and tyrosine residues in acetylcholine binding and muscarinic receptor activation. A examine with M3 muscarinic receptor level mutants. J. Biol. Chem. 267, 19313–19319 (1992).
Heitz, F. et al. Web site-directed mutagenesis of the putative human muscarinic M2 receptor binding web site. Eur. J. Pharmacol. 380, 183–195 (1999).
Nawaratne, V. et al. New insights into the perform of M4 muscarinic acetylcholine receptors gained utilizing a novel allosteric modulator and a DREADD (designer receptor solely activated by a designer drug). Mol. Pharmacol. 74, 1119–1131 (2008).
Abdul-Ridha, A., Lane, J. R., Sexton, P. M., Canals, M. & Christopoulos, A. Allosteric modulation of a chemogenetically modified G protein-coupled receptor. Mol. Pharmacol. 83, 521–530 (2013).
Haga, Okay. et al. Construction of the human M2 muscarinic acetylcholine receptor certain to an antagonist. Nature 482, 547–551 (2012).
Jumper, J. et al. Extremely correct protein construction prediction with AlphaFold. Nature 596, 583–589 (2021).
McCorvy, J. D. et al. Structural determinants of 5-HT2B receptor activation and biased agonism. Nat. Struct. Mol. Biol. 25, 787–796 (2018).
Wacker, D., Stevens, R. C. & Roth, B. L. How ligands illuminate GPCR molecular pharmacology. Cell 170, 414–427 (2017).
Suno, R. et al. Structural insights into the subtype-selective antagonist binding to the M2 muscarinic receptor. Nat. Chem. Biol. 14, 1150–1158 (2018).
Flock, T. et al. Common allosteric mechanism for Gα activation by GPCRs. Nature 524, 173–179 (2015).
Xia, R. et al. Cryo-EM construction of the human histamine H1 receptor/Gq advanced. Nat. Commun. 12, 2086 (2021).
Cao, C. et al. Construction, perform and pharmacology of human itch GPCRs. Nature 600, 170–175 (2021).
Mobbs, J. I. et al. Buildings of the human cholecystokinin 1 (CCK1) receptor certain to Gs and Gq mimetic proteins present perception into mechanisms of G protein selectivity. PLoS Biol. 19, e3001295 (2021).
Yin, Y. L. et al. Molecular foundation for kinin selectivity and activation of the human bradykinin receptors. Nat. Struct. Mol. Biol. 28, 755–761 (2021).
Blin, N., Yun, J. & Wess, J. Mapping of single amino acid residues required for selective activation of Gq/11 by the m3 muscarinic acetylcholine receptor. J. Biol. Chem. 270, 17741–17748 (1995).
Xu, P. et al. Structural insights into the lipid and ligand regulation of serotonin receptors. Nature 592, 469–473 (2021).
Kooistra, A. J. et al. GPCRdb in 2021: integrating GPCR sequence, construction and performance. Nucleic Acids Res. 49, D335–D343 (2021).
Wang, Y. et al. Molecular recognition of an acyl-peptide hormone and activation of ghrelin receptor. Nat. Commun. 12, 5064 (2021).
Zhang, X. et al. Buildings of the human cholecystokinin receptors certain to agonists and antagonists. Nat. Chem. Biol. 17, 1230–1237 (2021).
Peck, J. V., Fay, J. F. & Strauss, J. D. Excessive-speed high-resolution knowledge assortment on a 200 keV cryo-TEM. IUCrJ 9, 243–252 (2022).
Mastronarde, D. N. Automated electron microscope tomography utilizing sturdy prediction of specimen actions. J. Struct. Biol. 152, 36–51 (2005).
Bepler, T., Kelley, Okay., Noble, A. J. & Berger, B. Topaz-Denoise: common deep denoising fashions for cryoEM and cryoET. Nat. Commun. 11, 5208 (2020).
Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for speedy unsupervised cryo-EM construction willpower. Nat. Strategies 14, 290–296 (2017).
Punjani, A., Zhang, H. & Fleet, D. J. Non-uniform refinement: adaptive regularization improves single-particle cryo-EM reconstruction. Nat. Strategies 17, 1214–1221 (2020).
Rosenthal, P. B. & Henderson, R. Optimum willpower of particle orientation, absolute hand, and distinction loss in single-particle electron cryomicroscopy. J. Mol. Biol. 333, 721–745 (2003).
Heymann, J. B. & Belnap, D. M. Bsoft: picture processing and molecular modeling for electron microscopy. J. Struct. Biol. 157, 3–18 (2007).
Sanchez-Garcia, R. et al. DeepEMhancer: a deep studying answer for cryo-EM quantity post-processing. Commun. Biol. 4, 874 (2021).
Pettersen, E. F. et al. UCSF Chimera—a visualization system for exploratory analysis and evaluation. J. Comput. Chem. 25, 1605–1612 (2004).
Emsley, P. & Cowtan, Okay. Coot: model-building instruments for molecular graphics. Acta Crystallogr. D 60, 2126–2132 (2004).
Adams, P. D. et al. PHENIX: a complete Python-based system for macromolecular construction answer. Acta Crystallogr. D 66, 213–221 (2010).
Chen, V. B. et al. MolProbity: all-atom construction validation for macromolecular crystallography. Acta Crystallogr. D 66, 12–21 (2010).
Olsen, R. H. J. et al. TRUPATH, an open-source biosensor platform for interrogating the GPCR transducerome. Nat. Chem. Biol. 16, 841–849 (2020).
Lomize, M. A., Pogozheva, I. D., Joo, H., Mosberg, H. I. & Lomize, A. L. OPM database and PPM net server: assets for positioning of proteins in membranes. Nucleic Acids Res. 40, D370–D376 (2012).
Brooks, B. R. et al. CHARMM: the biomolecular simulation program. J. Comput. Chem. 30, 1545–1614 (2009).
Jo, S., Kim, T., Iyer, V. G. & Im, W. CHARMM-GUI: a web-based graphical consumer interface for CHARMM. J. Comput. Chem. 29, 1859–1865 (2008).
Lee, J. et al. CHARMM-GUI enter generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations utilizing the CHARMM36 additive drive discipline. J. Chem. Idea Comput. 12, 405–413 (2016).
Wu, E. L. et al. CHARMM-GUI membrane builder towards real looking organic membrane simulations. J. Comput. Chem. 35, 1997–2004 (2014).
Huang, J. et al. CHARMM36m: an improved drive discipline for folded and intrinsically disordered proteins. Nat. Strategies 14, 71–73 (2017).
Klauda, J. B. et al. Replace of the CHARMM all-atom additive drive discipline for lipids: validation on six lipid varieties. J. Phys. Chem. B 114, 7830–7843 (2010).
Case, D. A. et al. AMBER v.2020 (Univ. of California, San Francisco, 2020).
Roe, D. R. & Cheatham, T. E. PTRAJ and CPPTRAJ: software program for processing and evaluation of molecular dynamics trajectory knowledge. J. Chem. Idea Comput. 9, 3084–3095 (2013).
Humphrey, W., Dalke, A. & Schulten, Okay. VMD: visible molecular dynamics. J. Mol. Graphics 14, 33–38 (1996).
Pettersen, E. F. et al. UCSF ChimeraX: construction visualization for researchers, educators, and builders. Protein Sci. 30, 70–82 (2021).
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