In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators

Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the pre...
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Autor*in:	Jiayi Yuan [verfasserIn] Chen Jiang [verfasserIn] Junmei Wang [verfasserIn] Chih-Jung Chen [verfasserIn] Yixuan Hao [verfasserIn] Guangyi Zhao [verfasserIn] Zhiwei Feng [verfasserIn] Xiang-Qun Xie [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	cannabinoid receptor 2 allosteric binding site positive allosteric modulators negative allosteric modulators

Übergeordnetes Werk:	In: Molecules - MDPI AG, 2003, 27(2022), 2, p 453
Übergeordnetes Werk:	volume:27 ; year:2022 ; number:2, p 453

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/molecules27020453

Katalog-ID:	DOAJ086036564

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allfields	10.3390/molecules27020453 doi (DE-627)DOAJ086036564 (DE-599)DOAJ7983175d743648388f73f2e0429acbad DE-627 ger DE-627 rakwb eng QD241-441 Jiayi Yuan verfasserin aut In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-β-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future. cannabinoid receptor 2 allosteric binding site positive allosteric modulators negative allosteric modulators Organic chemistry Chen Jiang verfasserin aut Junmei Wang verfasserin aut Chih-Jung Chen verfasserin aut Yixuan Hao verfasserin aut Guangyi Zhao verfasserin aut Zhiwei Feng verfasserin aut Xiang-Qun Xie verfasserin aut In Molecules MDPI AG, 2003 27(2022), 2, p 453 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:27 year:2022 number:2, p 453 https://doi.org/10.3390/molecules27020453 kostenfrei https://doaj.org/article/7983175d743648388f73f2e0429acbad kostenfrei https://www.mdpi.com/1420-3049/27/2/453 kostenfrei https://doaj.org/toc/1420-3049 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 27 2022 2, p 453
spelling	10.3390/molecules27020453 doi (DE-627)DOAJ086036564 (DE-599)DOAJ7983175d743648388f73f2e0429acbad DE-627 ger DE-627 rakwb eng QD241-441 Jiayi Yuan verfasserin aut In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-β-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future. cannabinoid receptor 2 allosteric binding site positive allosteric modulators negative allosteric modulators Organic chemistry Chen Jiang verfasserin aut Junmei Wang verfasserin aut Chih-Jung Chen verfasserin aut Yixuan Hao verfasserin aut Guangyi Zhao verfasserin aut Zhiwei Feng verfasserin aut Xiang-Qun Xie verfasserin aut In Molecules MDPI AG, 2003 27(2022), 2, p 453 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:27 year:2022 number:2, p 453 https://doi.org/10.3390/molecules27020453 kostenfrei https://doaj.org/article/7983175d743648388f73f2e0429acbad kostenfrei https://www.mdpi.com/1420-3049/27/2/453 kostenfrei https://doaj.org/toc/1420-3049 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 27 2022 2, p 453
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allfieldsGer	10.3390/molecules27020453 doi (DE-627)DOAJ086036564 (DE-599)DOAJ7983175d743648388f73f2e0429acbad DE-627 ger DE-627 rakwb eng QD241-441 Jiayi Yuan verfasserin aut In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-β-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future. cannabinoid receptor 2 allosteric binding site positive allosteric modulators negative allosteric modulators Organic chemistry Chen Jiang verfasserin aut Junmei Wang verfasserin aut Chih-Jung Chen verfasserin aut Yixuan Hao verfasserin aut Guangyi Zhao verfasserin aut Zhiwei Feng verfasserin aut Xiang-Qun Xie verfasserin aut In Molecules MDPI AG, 2003 27(2022), 2, p 453 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:27 year:2022 number:2, p 453 https://doi.org/10.3390/molecules27020453 kostenfrei https://doaj.org/article/7983175d743648388f73f2e0429acbad kostenfrei https://www.mdpi.com/1420-3049/27/2/453 kostenfrei https://doaj.org/toc/1420-3049 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 27 2022 2, p 453
allfieldsSound	10.3390/molecules27020453 doi (DE-627)DOAJ086036564 (DE-599)DOAJ7983175d743648388f73f2e0429acbad DE-627 ger DE-627 rakwb eng QD241-441 Jiayi Yuan verfasserin aut In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-β-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future. cannabinoid receptor 2 allosteric binding site positive allosteric modulators negative allosteric modulators Organic chemistry Chen Jiang verfasserin aut Junmei Wang verfasserin aut Chih-Jung Chen verfasserin aut Yixuan Hao verfasserin aut Guangyi Zhao verfasserin aut Zhiwei Feng verfasserin aut Xiang-Qun Xie verfasserin aut In Molecules MDPI AG, 2003 27(2022), 2, p 453 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:27 year:2022 number:2, p 453 https://doi.org/10.3390/molecules27020453 kostenfrei https://doaj.org/article/7983175d743648388f73f2e0429acbad kostenfrei https://www.mdpi.com/1420-3049/27/2/453 kostenfrei https://doaj.org/toc/1420-3049 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 27 2022 2, p 453
language	English
source	In Molecules 27(2022), 2, p 453 volume:27 year:2022 number:2, p 453
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topic_facet	cannabinoid receptor 2 allosteric binding site positive allosteric modulators negative allosteric modulators Organic chemistry
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authorswithroles_txt_mv	Jiayi Yuan @@aut@@ Chen Jiang @@aut@@ Junmei Wang @@aut@@ Chih-Jung Chen @@aut@@ Yixuan Hao @@aut@@ Guangyi Zhao @@aut@@ Zhiwei Feng @@aut@@ Xiang-Qun Xie @@aut@@
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callnumber-first	Q - Science
author	Jiayi Yuan
spellingShingle	Jiayi Yuan misc QD241-441 misc cannabinoid receptor 2 misc allosteric binding site misc positive allosteric modulators misc negative allosteric modulators misc Organic chemistry In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators
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topic_title	QD241-441 In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators cannabinoid receptor 2 allosteric binding site positive allosteric modulators negative allosteric modulators
topic	misc QD241-441 misc cannabinoid receptor 2 misc allosteric binding site misc positive allosteric modulators misc negative allosteric modulators misc Organic chemistry
topic_unstemmed	misc QD241-441 misc cannabinoid receptor 2 misc allosteric binding site misc positive allosteric modulators misc negative allosteric modulators misc Organic chemistry
topic_browse	misc QD241-441 misc cannabinoid receptor 2 misc allosteric binding site misc positive allosteric modulators misc negative allosteric modulators misc Organic chemistry
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title	In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators
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title_full	In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators
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title_sort	in silico prediction and validation of cb2 allosteric binding sites to aid the design of allosteric modulators
callnumber	QD241-441
title_auth	In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators
abstract	Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-β-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future.
abstractGer	Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-β-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future.
abstract_unstemmed	Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-β-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future.
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container_issue	2, p 453
title_short	In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators
url	https://doi.org/10.3390/molecules27020453 https://doaj.org/article/7983175d743648388f73f2e0429acbad https://www.mdpi.com/1420-3049/27/2/453 https://doaj.org/toc/1420-3049
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up_date	2024-07-03T18:20:34.387Z
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In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-β-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. 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In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators

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