Targeting the Cannabinoid CB2 Receptor: Mutations, Modeling and Development of CB2 Selective Ligands

Raitio, Katri H.; Salo, Outi M. H.; Nevalainen, Tapio; Poso, Antti; Järvinen, Tomi

doi:10.2174/0929867053764617

Cited by 64 publications

(76 citation statements)

References 60 publications

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“…This is critical to the binding affinity of CB2 ligands including CP55940 and Win55212-2 as summarized in a recent review article. 27 Therefore, this site was speculated to be the CB2 agonist binding pocket. The defined CB2 agonist binding pocket shows certain differences with the model reported by Salo et al 15 The correspondent structure-based database search results for novel CB2 agonist leads will be reported elsewhere, whereas the current study is mainly focused on developing a virtual screening protocol for a CB2 antagonist search.…”

Section: Resultsmentioning

confidence: 99%

“…40 First, a CB2 receptor description file (RDF file) was generated to contain the information about the protein, its amino acids, the active site, non-amino acid residues, and specific torsion angles for the FlexX-Pharm calculations. In this file, the CB2 binding pocket for its antagonist was defined as a set of residues within a radius of 8 Å around the ligand in the SR144528- 24 32, and 33 27,53 were reported to be bioactive CB2 antagonists. bound CB2 receptor model, whereas no torsion angle was defined for the specific residues' interaction with the ligand.…”

Section: Methodsmentioning

confidence: 99%

“…[20][21][22][23][24][25] The advances made in the medicinal chemistry of arylpyrazoles as cannabinergic ligands have been highlighted in recent review articles. 26,27 Structure-activity relationship (SAR) studies were also conducted to gain further insight into quantitative 28,29 and qualitative 30,31 SAR models for the arylpyrazoles affinities on cannabinoid receptors. Furthermore, positive results in the clinical trials of SR141716A have successfully enabled it to become a new drug, named Rimonabant (Acomplia, Sanofi-Synthelabo), for the management of obesity, smoking cessation, and cardimetabolic risk factor 32 in Britain.…”

mentioning

confidence: 99%

“…In addition, another three compounds, including JTE907, tricyclicpyrazole compound-32, and sulfonamide compound-33, were also identified as CB2 antagonists. 27,53 Therefore, these 15 compounds were considered as bioactive CB2 antagonists in the training database for the generation of the CB2 structure-based virtual screening search protocol. All of the randomly selected compounds from the NCI2000 compound database and the other cannabinoids were considered inactive ligands in the training database.…”

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confidence: 99%

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GPCR Structure‐Based Virtual Screening Approach for CB2 Antagonist Search.

Chen¹,

Wang²,

Xie³

2007

ChemInform

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The potential for therapeutic specificity in regulating diseases has made cannabinoid (CB) receptors one of the most important G-protein-coupled receptor (GPCR) targets in search for new drugs. Considering the lack of related 3D experimental structures, we have established a structure-based virtual screening protocol to search for CB2 bioactive antagonists based on the 3D CB2 homology structure model. However, the existing homology-predicted 3D models often deviate from the native structure and therefore may incorrectly bias the in silico design. To overcome this problem, we have developed a 3D testing database query algorithm to examine the constructed 3D CB2 receptor structure model as well as the predicted binding pocket. In the present study, an antagonist-bound CB2 receptor complex model was initially generated using flexible docking simulation and then further optimized by molecular dynamic and mechanical (MD/MM) calculations. The refined 3D structural model of the CB2-ligand complex was then inspected by exploring the interactions between the receptor and ligands in order to predict the potential CB2 binding pocket for its antagonist. The ligand-receptor complex model and the predicted antagonist binding pockets were further processed and validated by FlexX-Pharm docking against a testing compound database that contains known antagonists. Furthermore, a consensus scoring (CScore) function algorithm was established to rank the binding interaction modes of a ligand on the CB2 receptor. Our results indicated that the known antagonists seeded in the testing database can be distinguished from a significant amount of randomly chosen molecules. Our studies demonstrated that the established GPCR structure-based virtual screening approach provided a new strategy with a high potential for in silico identifying novel CB2 antagonist leads based on the homology-generated 3D CB2 structure model.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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GPCR Structure‐Based Virtual Screening Approach for CB2 Antagonist Search.

Chen¹,

Wang²,

Xie³

2007

ChemInform

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“…of immune origin, as well as immunological disorders such as multiple sclerosis [2]. However, structure-function studies and structure-based ligand design have been impeded by the absence of an experimental three-dimensional (3D) structure of the CB2 receptor.…”

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confidence: 99%

Biosynthesis, purification, and characterization of a cannabinoid receptor 2 fragment (CB2271–326)

Zhang

Xie

2008

Protein Expression and Purification

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Obtaining sufficient amount of purified G-protein coupled receptors (GPCRs) is almost always one of the major challenges for their structural studies. CB2 , a human cannabinoid receptor 2 (CB2) fragment comprising part of the third extracellular loop (EL3), the seventh transmembrane domain (TM7) and C-terminal juxtamembrane region of the receptor, was over-expressed as a fusion protein into inclusion body (IB) of Escherichia coli. The fusion protein was purified by histidineselected nickel affinity chromatography under denaturing conditions. Then, the fusion protein IBs were solubilized in detergent (Brij58) and the expression fusion leader sequence (TrpLE) was specifically cleaved with tobacco etch virus (TEV) protease. The target fragment, CB2 , was subsequently purified by reverse-phase HPLC and confirmed by SDS-PAGE and mass spectrometry. This hydrophobic fragment can refold in mild detergents digitonin and Brij58. Circular dichroism (CD) spectroscopy of CB2 in digitonin and Brij58 micelles showed that the fragment adopts a more than 75% α-helical structure, with the remainder having β-strand structure. Fluorescence spectroscopy and quenching studies suggested that the C-terminal region lies near the surface of the digitonin micelles and the TM7 region is folded relatively close to the center of the micelles. This study may provide an alternative strategy for the production and structure/functional studies of GPCRs such as CB2 receptor protein produced in the form of IBs. KeywordsCannabinoid receptor 2; transmembrane domain; inclusion body; affinity chromatography; HPLC; circular dichroism; fluorescence Since the discovery of the CB2 receptor in 1993 [1], there has been a growing interest to clarify the importance of this GPCR membrane protein in human physiology, and to investigate it as a possible target for current and future drug development. The CB2 receptor seems to have a significant role in mediating the immunological functions of cannabinoid receptor ligands. Thus, the CB2 receptor is a promising target for drug development that aims at management of neurological pain, inflammation, osteoporosis, and growth of malignant gliomas and tumors * Corresponding author. Fax: +1 412 383 5276. E-mail address: xix15@pitt.edu (X-Q. Xie). Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. [3][4][5][6][7]. In general, the Escherichia coli expression system is the most attractive strategy due to its advantages of simplicity of use, low cost, easy scale-up, and homogeneous protein production. Though few attempts were promising to express full length CB2 receptor in ...

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Expression of G‐Protein‐Coupled Receptors

Yeliseev¹,

Vukoti²

2011

Production of Membrane Proteins

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Targeting the Cannabinoid CB2 Receptor: Mutations, Modeling and Development of CB2 Selective Ligands

Cited by 64 publications

References 60 publications

GPCR Structure‐Based Virtual Screening Approach for CB2 Antagonist Search.

GPCR Structure‐Based Virtual Screening Approach for CB2 Antagonist Search.

Biosynthesis, purification, and characterization of a cannabinoid receptor 2 fragment (CB2271–326)

Expression of G‐Protein‐Coupled Receptors

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