Target Information
| Target General Information | Top | |||||
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| Target ID |
T07191
(Former ID: TTDI03384)
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| Target Name |
MEK kinase kinase 2 (MAP4K2)
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| Synonyms |
Rab8-interacting protein; RAB8IP; Mitogen-activated protein kinase kinase kinase kinase 2; MEKKK 2; MAPK/ERK kinase kinase kinase 2; Germinal center kinase; GCK; GC kinase; B lymphocyte serine/threonine-protein kinase
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| Gene Name |
MAP4K2
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| Target Type |
Patented-recorded target
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[1] | ||||
| Disease | [+] 1 Target-related Diseases | + | ||||
| 1 | Breast cancer [ICD-11: 2C60-2C6Y] | |||||
| Function |
Acts as a MAPK kinase kinase kinase (MAP4K) and is an upstream activator of the stress-activated protein kinase/c-Jun N-terminal kinase (SAP/JNK) signaling pathway and to a lesser extent of the p38 MAPKs signaling pathway. Required for the efficient activation of JNKs by TRAF6-dependent stimuli, including pathogen-associated molecular patterns (PAMPs) such as polyinosine-polycytidine (poly(IC)), lipopolysaccharides (LPS), lipid A, peptidoglycan (PGN), or bacterial flagellin. To a lesser degree, IL-1 and engagement of CD40 also stimulate MAP4K2-mediated JNKs activation. The requirement for MAP4K2/GCK is most pronounced for LPS signaling, and extends to LPS stimulation of c-Jun phosphorylation and induction of IL-8. Enhances MAP3K1 oligomerization, which may relieve N-terminal mediated MAP3K1 autoinhibition and lead to activation following autophosphorylation. Mediates also the SAP/JNK signaling pathway and the p38 MAPKs signaling pathway through activation of the MAP3Ks MAP3K10/MLK2 and MAP3K11/MLK3. May play a role in the regulation of vesicle targeting or fusion. regulation of vesicle targeting or fusion. Serine/threonine-protein kinase which acts as an essential component of the MAP kinase signal transduction pathway.
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| BioChemical Class |
Kinase
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| UniProt ID | ||||||
| EC Number |
EC 2.7.11.1
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| Sequence |
MALLRDVSLQDPRDRFELLQRVGAGTYGDVYKARDTVTSELAAVKIVKLDPGDDISSLQQ
EITILRECRHPNVVAYIGSYLRNDRLWICMEFCGGGSLQEIYHATGPLEERQIAYVCREA LKGLHHLHSQGKIHRDIKGANLLLTLQGDVKLADFGVSGELTASVAKRRSFIGTPYWMAP EVAAVERKGGYNELCDVWALGITAIELGELQPPLFHLHPMRALMLMSKSSFQPPKLRDKT RWTQNFHHFLKLALTKNPKKRPTAEKLLQHPFTTQQLPRALLTQLLDKASDPHLGTPSPE DCELETYDMFPDTIHSRGQHGPAERTPSEIQFHQVKFGAPRRKETDPLNEPWEEEWTLLG KEELSGSLLQSVQEALEERSLTIRSASEFQELDSPDDTMGTIKRAPFLGPLPTDPPAEEP LSSPPGTLPPPPSGPNSSPLLPTAWATMKQREDPERSSCHGLPPTPKVHMGACFSKVFNG CPLRIHAAVTWIHPVTRDQFLVVGAEEGIYTLNLHELHEDTLEKLISHRCSWLYCVNNVL LSLSGKSTHIWAHDLPGLFEQRRLQQQVPLSIPTNRLTQRIIPRRFALSTKIPDTKGCLQ CRVVRNPYTGATFLLAALPTSLLLLQWYEPLQKFLLLKNFSSPLPSPAGMLEPLVLDGKE LPQVCVGAEGPEGPGCRVLFHVLPLEAGLTPDILIPPEGIPGSAQQVIQVDRDTILVSFE RCVRIVNMQGEPTATLAPELTFDFPIETVVCLQDSVLAFWSHGMQGRSLDTNEVTQEITD ETRIFRVLGAHRDIILESIPTDNPEAHSNLYILTGHQSTY Click to Show/Hide
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| 3D Structure | Click to Show 3D Structure of This Target | AlphaFold | ||||
| Drugs and Modes of Action | Top | |||||
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| Clinical Trial Drug(s) | [+] 1 Clinical Trial Drugs | + | ||||
| 1 | Quinazoline derivative 9 | Drug Info | Phase 1 | Breast cancer | [2] | |
| Mode of Action | [+] 1 Modes of Action | + | ||||
| Inhibitor | [+] 2 Inhibitor drugs | + | ||||
| 1 | Quinazoline derivative 9 | Drug Info | [1] | |||
| 2 | NG-25 | Drug Info | [3] | |||
| 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 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 | ||
| Degree | 1 | Degree centrality | 1.07E-04 | Betweenness centrality | 0.00E+00 |
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| Closeness centrality | 1.90E-01 | Radiality | 1.32E+01 | Clustering coefficient | 0.00E+00 |
| Neighborhood connectivity | 1.80E+01 | Topological coefficient | 1.00E+00 | 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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| Target Poor or Non Binders | Top | |||||
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| Target Poor or Non Binders | ||||||
| Target Regulators | Top | |||||
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| Target-interacting Proteins | ||||||
| References | Top | |||||
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| REF 1 | Cyclin-dependent kinase inhibitors for cancer therapy: a patent review (2009 - 2014).Expert Opin Ther Pat. 2015;25(9):953-70. | |||||
| REF 2 | ClinicalTrials.gov (NCT03065010) Study of BCD-115 in Women With ER(+) HER2(-) Local Advanced and Metastatic Breast Cancer. U.S. National Institutes of Health. | |||||
| REF 3 | Discovery of type II inhibitors of TGFbeta-activated kinase 1 (TAK1) and mitogen-activated protein kinase kinase kinase kinase 2 (MAP4K2). J Med Chem. 2015 Jan 8;58(1):183-96. | |||||
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