Target Information
| Target General Information | Top | |||||
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| Target ID |
T49989
(Former ID: TTDI02190)
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| Target Name |
TGF-beta receptor type II (TGFBR2)
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| Synonyms |
Transforminggrowth factor-beta receptor type II; Transforming growth factor-beta receptor type II; TbetaR-II; TGFR-2; TGF-beta type II receptor; TGF-beta receptor type-2
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| Gene Name |
TGFBR2
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| Target Type |
Clinical trial target
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[1] | ||||
| Disease | [+] 1 Target-related Diseases | + | ||||
| 1 | Solid tumour/cancer [ICD-11: 2A00-2F9Z] | |||||
| Function |
Transduces the TGFB1, TGFB2 and TGFB3 signal from the cell surface to the cytoplasm and is thus regulating a plethora of physiological and pathological processes including cell cycle arrest in epithelial and hematopoietic cells, control of mesenchymal cell proliferation and differentiation, wound healing, extracellular matrix production, immunosuppression and carcinogenesis. The formation of the receptor complex composed of 2 TGFBR1 and 2 TGFBR2 molecules symmetrically bound to the cytokine dimer results in the phosphorylation and the activation of TGFRB1 by the constitutively active TGFBR2. Activated TGFBR1 phosphorylates SMAD2 which dissociates from the receptor and interacts with SMAD4. The SMAD2-SMAD4 complex is subsequently translocated to the nucleus where it modulates the transcription of the TGF-beta-regulated genes. This constitutes the canonical SMAD-dependent TGF-beta signaling cascade. Also involved in non-canonical, SMAD-independent TGF-beta signaling pathways. Transmembrane serine/threonine kinase forming with the TGF-beta type I serine/threonine kinase receptor, TGFBR1, the non-promiscuous receptor for the TGF-beta cytokines TGFB1, TGFB2 and TGFB3.
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| BioChemical Class |
Kinase
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| UniProt ID | ||||||
| EC Number |
EC 2.7.11.30
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| Sequence |
MGRGLLRGLWPLHIVLWTRIASTIPPHVQKSVNNDMIVTDNNGAVKFPQLCKFCDVRFST
CDNQKSCMSNCSITSICEKPQEVCVAVWRKNDENITLETVCHDPKLPYHDFILEDAASPK CIMKEKKKPGETFFMCSCSSDECNDNIIFSEEYNTSNPDLLLVIFQVTGISLLPPLGVAI SVIIIFYCYRVNRQQKLSSTWETGKTRKLMEFSEHCAIILEDDRSDISSTCANNINHNTE LLPIELDTLVGKGRFAEVYKAKLKQNTSEQFETVAVKIFPYEEYASWKTEKDIFSDINLK HENILQFLTAEERKTELGKQYWLITAFHAKGNLQEYLTRHVISWEDLRKLGSSLARGIAH LHSDHTPCGRPKMPIVHRDLKSSNILVKNDLTCCLCDFGLSLRLDPTLSVDDLANSGQVG TARYMAPEVLESRMNLENVESFKQTDVYSMALVLWEMTSRCNAVGEVKDYEPPFGSKVRE HPCVESMKDNVLRDRGRPEIPSFWLNHQGIQMVCETLTECWDHDPEARLTAQCVAERFSE LEHLDRLSGRSCSEEKIPEDGSLNTTK Click to Show/Hide
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| 3D Structure | Click to Show 3D Structure of This Target | AlphaFold | ||||
| HIT2.0 ID | T50FHQ | |||||
| Drugs and Modes of Action | Top | |||||
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| Clinical Trial Drug(s) | [+] 1 Clinical Trial Drugs | + | ||||
| 1 | TGF-BR2 mab | Drug Info | Phase 1 | Solid tumour/cancer | [2] | |
| Mode of Action | [+] 1 Modes of Action | + | ||||
| Inhibitor | [+] 4 Inhibitor drugs | + | ||||
| 1 | LY2109761 | Drug Info | [3] | |||
| 2 | PMID16539403C15b | Drug Info | [4] | |||
| 3 | PMID23639540C13a | Drug Info | [5] | |||
| 4 | PMID23639540C13d | Drug Info | [5] | |||
| Cell-based Target Expression Variations | Top | |||||
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| Cell-based Target Expression Variations | ||||||
| Drug Binding Sites of Target | Top | |||||
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| Ligand Name: Staurosporine | Ligand Info | |||||
| Structure Description | TGF-BETA RECEPTOR TYPE 2 KINASE DOMAIN (E431A,R433A,E485A,K488A,R493A,R495A) IN COMPLEX WITH STAUROSPORINE | PDB:5E8Y | ||||
| Method | X-ray diffraction | Resolution | 2.05 Å | Mutation | Yes | [6] |
| PDB Sequence |
ELLPIELDTL
249 VGKGRFAEVY259 KAKLKQQFET273 VAVKIFPYEE283 YASWKTEKDI293 FSDINLKHEN 303 ILQFLTAEER313 KTELGKQYWL323 ITAFHAKGNL333 QEYLTRHVIS343 WEDLRKLGSS 353 LARGIAHLHS363 DHTPCGRPKM373 PIVHRDLKSS383 NILVKNDLTC393 CLCDFGLSLR 403 LDPTLSVDDL413 ANSGQVGTAR423 YMAPEVLASA433 MNLENVESFK443 QTDVYSMALV 453 LWEMTSRCNA463 VGEVKDYEPP473 FGSKVREHPC483 VASMADNVLA493 DAGRPEIPSF 503 WLNHQGIQMV513 CETLTECWDH523 DPEARLTAQC533 VAERFSEL
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VAL250
2.175
GLY251
2.945
LYS252
2.849
GLY253
3.725
ALA256
4.647
VAL258
2.887
ALA275
3.192
LYS277
2.469
GLU290
3.793
LEU305
2.863
THR325
3.006
ALA326
2.074
PHE327
3.030
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| Ligand Name: AMP-PNP | Ligand Info | |||||
| Structure Description | TGF-BETA RECEPTOR TYPE 2 KINASE DOMAIN (E431A,R433A,E485A,K488A,R493A,R495A) IN COMPLEX WITH AMPPNP | PDB:5E92 | ||||
| Method | X-ray diffraction | Resolution | 2.08 Å | Mutation | Yes | [6] |
| PDB Sequence |
ELLPIELDTL
249 VGKGRFAEVY259 KAKLKFETVA275 VKIFPYEEYA285 SWKTEKDIFS295 DINLKHENIL 305 QFLTAEERKT315 ELGKQYWLIT325 AFHAKGNLQE335 YLTRHVISWE345 DLRKLGSSLA 355 RGIAHLHSDH365 TPCGRPKMPI375 VHRDLKSSNI385 LVKNDLTCCL395 CDFGLSLRLD 405 PTLSVDDLAN415 SGQVGTARYM425 APEVLASAMN435 LENVESFKQT445 DVYSMALVLW 455 EMTSRCNAVG465 EVKDYEPPFG475 SKVREHPCVA485 SMADNVLADA495 GRPEIPSFWL 505 NHQGIQMVCE515 TLTECWDHDP525 EARLTAQCVA535 ERFSELEH
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VAL250
3.767
GLY251
2.998
LYS252
3.354
GLY253
3.044
ARG254
2.996
PHE255
3.131
ALA256
3.118
VAL258
3.460
ALA275
3.454
LYS277
2.791
PHE279
4.770
SER286
4.515
GLU290
3.621
LEU305
3.057
THR325
2.875
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| Click to View More Binding Site Information of This Target with Different Ligands | ||||||
| Different Human System Profiles of Target | Top |
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Human Similarity Proteins
of target is determined by comparing the sequence similarity of all human proteins with the target based on BLAST. The similarity proteins for a target are defined as the proteins with E-value < 0.005 and outside the protein families of the target.
A target that has fewer human similarity proteins outside its family is commonly regarded to possess a greater capacity to avoid undesired interactions and thus increase the possibility of finding successful drugs
(Brief Bioinform, 21: 649-662, 2020).
Human Tissue Distribution
of target is determined from a proteomics study that quantified more than 12,000 genes across 32 normal human tissues. Tissue Specificity (TS) score was used to define the enrichment of target across tissues.
The distribution of targets among different tissues or organs need to be taken into consideration when assessing the target druggability, as it is generally accepted that the wider the target distribution, the greater the concern over potential adverse effects
(Nat Rev Drug Discov, 20: 64-81, 2021).
Human Pathway Affiliation
of target is determined by the life-essential pathways provided on KEGG database. The target-affiliated pathways were defined based on the following two criteria (a) the pathways of the studied target should be life-essential for both healthy individuals and patients, and (b) the studied target should occupy an upstream position in the pathways and therefore had the ability to regulate biological function.
Targets involved in a fewer pathways have greater likelihood to be successfully developed, while those associated with more human pathways increase the chance of undesirable interferences with other human processes
(Pharmacol Rev, 58: 259-279, 2006).
Biological Network Descriptors
of target is determined based on a human protein-protein interactions (PPI) network consisting of 9,309 proteins and 52,713 PPIs, which were with a high confidence score of ≥ 0.95 collected from STRING database.
The network properties of targets based on protein-protein interactions (PPIs) have been widely adopted for the assessment of target’s druggability. Proteins with high node degree tend to have a high impact on network function through multiple interactions, while proteins with high betweenness centrality are regarded to be central for communication in interaction networks and regulate the flow of signaling information
(Front Pharmacol, 9, 1245, 2018;
Curr Opin Struct Biol. 44:134-142, 2017).
Human Similarity Proteins
Human Tissue Distribution
Human Pathway Affiliation
Biological Network Descriptors
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Note:
If a protein has TS (tissue specficity) scores at least in one tissue >= 2.5, this protein is called tissue-enriched (including tissue-enriched-but-not-specific and tissue-specific). In the plots, the vertical lines are at thresholds 2.5 and 4.
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| KEGG Pathway | Pathway ID | Affiliated Target | Pathway Map |
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| MAPK signaling pathway | hsa04010 | Affiliated Target |
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| Class: Environmental Information Processing => Signal transduction | Pathway Hierarchy | ||
| Cytokine-cytokine receptor interaction | hsa04060 | Affiliated Target |
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| Class: Environmental Information Processing => Signaling molecules and interaction | Pathway Hierarchy | ||
| FoxO signaling pathway | hsa04068 | Affiliated Target |
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| Class: Environmental Information Processing => Signal transduction | Pathway Hierarchy | ||
| Endocytosis | hsa04144 | Affiliated Target |
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| Class: Cellular Processes => Transport and catabolism | Pathway Hierarchy | ||
| Cellular senescence | hsa04218 | Affiliated Target |
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| Class: Cellular Processes => Cell growth and death | Pathway Hierarchy | ||
| TGF-beta signaling pathway | hsa04350 | Affiliated Target |
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| Class: Environmental Information Processing => Signal transduction | Pathway Hierarchy | ||
| Osteoclast differentiation | hsa04380 | Affiliated Target |
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| Class: Organismal Systems => Development and regeneration | Pathway Hierarchy | ||
| Hippo signaling pathway | hsa04390 | Affiliated Target |
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| Class: Environmental Information Processing => Signal transduction | Pathway Hierarchy | ||
| Adherens junction | hsa04520 | Affiliated Target |
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| Class: Cellular Processes => Cellular community - eukaryotes | Pathway Hierarchy | ||
| Th17 cell differentiation | hsa04659 | Affiliated Target |
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| Class: Organismal Systems => Immune system | Pathway Hierarchy | ||
| Relaxin signaling pathway | hsa04926 | Affiliated Target |
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| Class: Organismal Systems => Endocrine system | Pathway Hierarchy | ||
| Click to Show/Hide the Information of Affiliated Human Pathways | |||
| Degree | 24 | Degree centrality | 2.58E-03 | Betweenness centrality | 3.50E-04 |
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| Closeness centrality | 2.42E-01 | Radiality | 1.42E+01 | Clustering coefficient | 3.51E-01 |
| Neighborhood connectivity | 3.92E+01 | Topological coefficient | 7.78E-02 | Eccentricity | 12 |
| Download | Click to Download the Full PPI Network of This Target | ||||
| Chemical Structure based Activity Landscape of Target | Top |
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| Drug Property Profile of Target | Top | |
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| (1) Molecular Weight (mw) based Drug Clustering | (2) Octanol/Water Partition Coefficient (xlogp) based Drug Clustering | |
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| (3) Hydrogen Bond Donor Count (hbonddonor) based Drug Clustering | (4) Hydrogen Bond Acceptor Count (hbondacc) based Drug Clustering | |
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| (5) Rotatable Bond Count (rotbonds) based Drug Clustering | (6) Topological Polar Surface Area (polararea) based Drug Clustering | |
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| "RO5" indicates the cutoff set by lipinski's rule of five; "D123AB" colored in GREEN denotes the no violation of any cutoff in lipinski's rule of five; "D123AB" colored in PURPLE refers to the violation of only one cutoff in lipinski's rule of five; "D123AB" colored in BLACK represents the violation of more than one cutoffs in lipinski's rule of five | ||
| Target Regulators | Top | |||||
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| Target-regulating microRNAs | ||||||
| Target-interacting Proteins | ||||||
| References | Top | |||||
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| REF 1 | URL: http://www.guidetopharmacology.org Nucleic Acids Res. 2015 Oct 12. pii: gkv1037. The IUPHAR/BPS Guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands. (Target id: 1795). | |||||
| REF 2 | Targeting the TGFbeta signalling pathway in disease. Nat Rev Drug Discov. 2012 Oct;11(10):790-811. | |||||
| REF 3 | LY2109761, a novel transforming growth factor beta receptor type I and type II dual inhibitor, as a therapeutic approach to suppressing pancreatic cancer metastasis. Mol Cancer Ther. 2008 Apr;7(4):829-40. | |||||
| REF 4 | Dihydropyrrolopyrazole transforming growth factor-beta type I receptor kinase domain inhibitors: a novel benzimidazole series with selectivity vers... J Med Chem. 2006 Mar 23;49(6):2138-42. | |||||
| REF 5 | Synthesis and structure-activity relationships of a novel and selective bone morphogenetic protein receptor (BMP) inhibitor derived from the pyrazolo[1.5-a]pyrimidine scaffold of dorsomorphin: the discovery of ML347 as an ALK2 versus ALK3 selective MLPCN probe. Bioorg Med Chem Lett. 2013 Jun 1;23(11):3248-52. | |||||
| REF 6 | Crystal structures of apo and inhibitor-bound TGFbetaR2 kinase domain: insights into TGFbetaR isoform selectivity. Acta Crystallogr D Struct Biol. 2016 May;72(Pt 5):658-74. | |||||
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