Target Information

Target General Information

Target ID

T20017 (Former ID: TTDNC00392)

Target Name

CREB-regulated transcription coactivator 1 (TORC1)

Synonyms

WAMTP1; Transducer of regulated cAMP response elementbinding protein 1; Transducer of regulated cAMP response element-binding protein 1; Transducer of CREB protein 1; TORC1; TORC-1; Mucoepidermoid carcinoma translocated protein 1; MECT1; KIAA0616; CREBregulated transcription coactivator 1

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Gene Name

CRTC1

Target Type

Clinical trial target

[1]

Disease

[+] 1 Target-related Diseases

Respiratory infection [ICD-11: CA07-CA4Z]

Function

Acts as a coactivator, in the SIK/TORC signaling pathway, being active when dephosphorylated and acts independently of CREB1 'Ser-133' phosphorylation. Enhances the interaction of CREB1 with TAF4. Regulates the expression of specific CREB-activated genes such as the steroidogenic gene, StAR. Potent coactivator of PGC1alpha and inducer of mitochondrial biogenesis in muscle cells. In the hippocampus, involved in late-phase long-term potentiation (L-LTP) maintenance at the Schaffer collateral-CA1 synapses. May be required for dendritic growth of developing cortical neurons. In concert with SIK1, regulates the light-induced entrainment of the circadian clock. In response to light stimulus, coactivates the CREB-mediated transcription of PER1 which plays an important role in the photic entrainment of the circadian clock. Transcriptional coactivator for CREB1 which activates transcription through both consensus and variant cAMP response element (CRE) sites.

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UniProt ID

CRTC1_HUMAN

Sequence

MATSNNPRKFSEKIALHNQKQAEETAAFEEVMKDLSLTRAARLQLQKSQYLQLGPSRGQY
YGGSLPNVNQIGSGTMDLPFQTPFQSSGLDTSRTTRHHGLVDRVYRERGRLGSPHRRPLS
VDKHGRQADSCPYGTMYLSPPADTSWRRTNSDSALHQSTMTPTQPESFSSGSQDVHQKRV
LLLTVPGMEETTSEADKNLSKQAWDTKKTGSRPKSCEVPGINIFPSADQENTTALIPATH
NTGGSLPDLTNIHFPSPLPTPLDPEEPTFPALSSSSSTGNLAANLTHLGIGGAGQGMSTP
GSSPQHRPAGVSPLSLSTEARRQQASPTLSPLSPITQAVAMDALSLEQQLPYAFFTQAGS
QQPPPQPQPPPPPPPASQQPPPPPPPQAPVRLPPGGPLLPSASLTRGPQPPPLAVTVPSS
LPQSPPENPGQPSMGIDIASAPALQQYRTSAGSPANQSPTSPVSNQGFSPGSSPQHTSTL
GSVFGDAYYEQQMAARQANALSHQLEQFNMMENAISSSSLYSPGSTLNYSQAAMMGLTGS
HGSLPDSQQLGYASHSGIPNIILTVTGESPPSLSKELTSSLAGVGDVSFDSDSQFPLDEL
KIDPLTLDGLHMLNDPDMVLADPATEDTFRMDRL

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3D Structure

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AlphaFold

HIT2.0 ID

T68OIU

Drugs and Modes of Action

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Clinical Trial Drug(s)

[+] 1 Clinical Trial Drugs

RTB101

Drug Info

Phase 3

Respiratory tract infection

[2]

Mode of Action

[+] 1 Modes of Action

Inhibitor

[+] 1 Inhibitor drugs

RTB101

Drug Info

[3]

Cell-based Target Expression Variations

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Cell-based Target Expression Variations

Cell-based Target Expression Variations Info

Different Human System Profiles of Target	Top
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). 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 Biological Network Descriptors

Different Human System Profiles of Target

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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).

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

Biological Network Descriptors

There is no similarity protein (E value < 0.005) for this target


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.

Degree	1	Degree centrality	1.07E-04	Betweenness centrality	0.00E+00
Closeness centrality	2.07E-01	Radiality	1.36E+01	Clustering coefficient	0.00E+00
Neighborhood connectivity	5.00E+01	Topological coefficient	1.00E+00	Eccentricity	12
Download	Click to Download the Full PPI Network of This Target

Target Regulators

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Target-regulating microRNAs

Target-regulating microRNAs Info

References

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REF 1

Palomid 529, a novel small-molecule drug, is a TORC1/TORC2 inhibitor that reduces tumor growth, tumor angiogenesis, and vascular permeability. Cancer Res. 2008 Nov 15;68(22):9551-7.

REF 2

ClinicalTrials.gov (NCT04139915) Effect of RTB101 on Illness Associated With Respiratory Tract Infections in the Elderly. U.S. National Institutes of Health.

REF 3

Anti-ageing pipeline starts to mature.Nat Rev Drug Discov. 2018 Sep;17(9):609-612.

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