Target Information
Target General Information | Top | |||||
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Target ID |
T21334
(Former ID: TTDC00224)
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Target Name |
Osteoclast differentiation factor (ODF)
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Synonyms |
Tumor necrosis factor ligand superfamily member 11; TRANCE; TNF-related activation-induced cytokine; Receptor activatorof nuclear factor kappa B ligand; Receptor activator of nuclear factor kappa-B ligand; RANKL; Osteoprotegerin ligand; OPGL; CD254
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Gene Name |
TNFSF11
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Target Type |
Successful target
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[1] | ||||
Disease | [+] 1 Target-related Diseases | + | ||||
1 | Low bone mass disorder [ICD-11: FB83] | |||||
Function |
Osteoclast differentiation and activation factor. Augments the ability of dendritic cells to stimulate naive T-cell proliferation. May be an important regulator of interactions between T-cells and dendritic cells and may play a role in the regulation of the T-cell-dependent immune response. May also play an important role in enhanced bone-resorption in humoral hypercalcemia of malignancy. Induces osteoclastogenesis by activating multiple signaling pathways in osteoclast precursor cells, chief among which is induction of long lasting oscillations in the intracellular concentration of Ca (2+) resulting in the activation of NFATC1, which translocates to the nucleus and induces osteoclast-specific gene transcription to allow differentiation of osteoclasts. During osteoclast differentiation, in a TMEM64 and ATP2A2-dependent manner induces activation of CREB1 and mitochondrial ROS generation necessary for proper osteoclast generation. Cytokine that binds to TNFRSF11B/OPG and to TNFRSF11A/RANK.
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BioChemical Class |
Cytokine: tumor necrosis factor
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UniProt ID | ||||||
Sequence |
MRRASRDYTKYLRGSEEMGGGPGAPHEGPLHAPPPPAPHQPPAASRSMFVALLGLGLGQV
VCSVALFFYFRAQMDPNRISEDGTHCIYRILRLHENADFQDTTLESQDTKLIPDSCRRIK QAFQGAVQKELQHIVGSQHIRAEKAMVDGSWLDLAKRSKLEAQPFAHLTINATDIPSGSH KVSLSSWYHDRGWAKISNMTFSNGKLIVNQDGFYYLYANICFRHHETSGDLATEYLQLMV YVTKTSIKIPSSHTLMKGGSTKYWSGNSEFHFYSINVGGFFKLRSGEEISIEVSNPSLLD PDQDATYFGAFKVRDID Click to Show/Hide
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3D Structure | Click to Show 3D Structure of This Target | AlphaFold | ||||
HIT2.0 ID | T03G09 |
Drugs and Modes of Action | Top | |||||
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Approved Drug(s) | [+] 1 Approved Drugs | + | ||||
1 | Denosumab | Drug Info | Approved | Postmenopausal osteoporosis | [1], [2] | |
Clinical Trial Drug(s) | [+] 2 Clinical Trial Drugs | + | ||||
1 | ALX-0141 | Drug Info | Phase 1 | Osteoporosis | [3] | |
2 | CEP-37251 | Drug Info | Phase 1 | Bone metastases | [4] | |
Mode of Action | [+] 1 Modes of Action | + | ||||
Inhibitor | [+] 2 Inhibitor drugs | + | ||||
1 | ALX-0141 | Drug Info | [5] | |||
2 | CEP-37251 | Drug Info | [6] |
Cell-based Target Expression Variations | Top | |||||
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Cell-based Target Expression Variations |
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 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 Pathway Affiliation
Biological Network Descriptors
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Protein Name | Pfam ID | Percentage of Identity (%) | E value |
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#N/A | 60.000 (36/60) | 3.35E-16 |
KEGG Pathway | Pathway ID | Affiliated Target | Pathway Map |
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Cytokine-cytokine receptor interaction | hsa04060 | Affiliated Target |
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Class: Environmental Information Processing => Signaling molecules and interaction | Pathway Hierarchy | ||
NF-kappa B signaling pathway | hsa04064 | 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 | ||
Prolactin signaling pathway | hsa04917 | Affiliated Target |
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Class: Organismal Systems => Endocrine system | Pathway Hierarchy | ||
Parathyroid hormone synthesis, secretion and action | hsa04928 | Affiliated Target |
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Class: Organismal Systems => Endocrine system | Pathway Hierarchy |
Degree | 6 | Degree centrality | 6.45E-04 | Betweenness centrality | 3.97E-04 |
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Closeness centrality | 2.22E-01 | Radiality | 1.39E+01 | Clustering coefficient | 6.67E-02 |
Neighborhood connectivity | 2.77E+01 | Topological coefficient | 1.74E-01 | Eccentricity | 12 |
Download | Click to Download the Full PPI Network of This Target | ||||
Target Regulators | Top | |||||
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Target-regulating microRNAs |
Target Profiles in Patients | Top | |||||
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Target Expression Profile (TEP) |
Target Affiliated Biological Pathways | Top | |||||
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KEGG Pathway | [+] 5 KEGG Pathways | + | ||||
1 | Cytokine-cytokine receptor interaction | |||||
2 | NF-kappa B signaling pathway | |||||
3 | Osteoclast differentiation | |||||
4 | Prolactin signaling pathway | |||||
5 | Rheumatoid arthritis | |||||
NetPath Pathway | [+] 2 NetPath Pathways | + | ||||
1 | Leptin Signaling Pathway | |||||
2 | TWEAK Signaling Pathway | |||||
PID Pathway | [+] 1 PID Pathways | + | ||||
1 | IL6-mediated signaling events | |||||
Reactome | [+] 3 Reactome Pathways | + | ||||
1 | TNFR2 non-canonical NF-kB pathway | |||||
2 | TNFs bind their physiological receptors | |||||
3 | TNF receptor superfamily (TNFSF) members mediating non-canonical NF-kB pathway | |||||
WikiPathways | [+] 5 WikiPathways | + | ||||
1 | Osteoblast Signaling | |||||
2 | Vitamin D Receptor Pathway | |||||
3 | Differentiation Pathway | |||||
4 | RANKL/RANK Signaling Pathway | |||||
5 | Osteoclast Signaling |
Target-Related Models and Studies | Top | |||||
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Target Validation |
References | Top | |||||
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REF 1 | Mullard A: 2010 FDA drug approvals. Nat Rev Drug Discov. 2011 Feb;10(2):82-5. | |||||
REF 2 | 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. (Ligand id: 6886). | |||||
REF 3 | Trusted, scientifically sound profiles of drug programs, clinical trials, safety reports, and company deals, written by scientists. Springer. 2015. Adis Insight (drug id 800031383) | |||||
REF 4 | ClinicalTrials.gov (NCT01159873) Single Ascending-Dose Study to Characterize the Safety, Pharmacokinetics, and Pharmacodynamics of CEP-37251 in Healthy Postmenopausal Women. U.S. National Institutes of Health. | |||||
REF 5 | Clinical pipeline report, company report or official report of Ablynx. | |||||
REF 6 | This week in therapeutics Cancer. SciBX 3(40); doi:10.1038/scibx.2010.1202. Oct. 14, 2010 |
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