Target Information

Target General Information

Target ID

T88322 (Former ID: TTDI02183)

Target Name

Facilitates chromatin transcription complex (FACT)

Synonyms

hSSRP1; T160; Structure-specific recognition protein 1; Recombination signal sequence recognition protein 1; Facilitates chromatin transcription complex subunit SSRP1; Facilitates chromatin transcription complex 80 kDa subunit; FACTp80; FACT80; FACT complex subunit SSRP1; FACT 80 kDa subunit; Chromatin-specific transcription elongation factor 80 kDa subunit

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Gene Name

SSRP1

Target Type

Clinical trial target

[1]

Disease

[+] 2 Target-related Diseases

Liver cancer [ICD-11: 2C12]

Solid tumour/cancer [ICD-11: 2A00-2F9Z]

Function

The FACT complex is involved in multiple processes that require DNA as a template such as mRNA elongation, DNA replication and DNA repair. During transcription elongation the FACT complex acts as a histone chaperone that both destabilizes and restores nucleosomal structure. It facilitates the passage of RNA polymerase II and transcription by promoting the dissociation of one histone H2A-H2B dimer from the nucleosome, then subsequently promotes the reestablishment of the nucleosome following the passage of RNA polymerase II. The FACT complex is probably also involved in phosphorylation of 'Ser-392' of p53/TP53 via its association with CK2 (casein kinase II). Binds specifically to double-stranded DNA and at low levels to DNA modified by the antitumor agent cisplatin. May potentiate cisplatin-induced cell death by blocking replication and repair of modified DNA. Also acts as a transcriptional coactivator for p63/TP63. Component of the FACT complex, a general chromatin factor that acts to reorganize nucleosomes.

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UniProt ID

SSRP1_HUMAN

Sequence

MAETLEFNDVYQEVKGSMNDGRLRLSRQGIIFKNSKTGKVDNIQAGELTEGIWRRVALGH
GLKLLTKNGHVYKYDGFRESEFEKLSDFFKTHYRLELMEKDLCVKGWNWGTVKFGGQLLS
FDIGDQPVFEIPLSNVSQCTTGKNEVTLEFHQNDDAEVSLMEVRFYVPPTQEDGVDPVEA
FAQNVLSKADVIQATGDAICIFRELQCLTPRGRYDIRIYPTFLHLHGKTFDYKIPYTTVL
RLFLLPHKDQRQMFFVISLDPPIKQGQTRYHFLILLFSKDEDISLTLNMNEEEVEKRFEG
RLTKNMSGSLYEMVSRVMKALVNRKITVPGNFQGHSGAQCITCSYKASSGLLYPLERGFI
YVHKPPVHIRFDEISFVNFARGTTTTRSFDFEIETKQGTQYTFSSIEREEYGKLFDFVNA
KKLNIKNRGLKEGMNPSYDEYADSDEDQHDAYLERMKEEGKIREENANDSSDDSGEETDE
SFNPGEEEEDVAEEFDSNASASSSSNEGDSDRDEKKRKQLKKAKMAKDRKSRKKPVEVKK
GKDPNAPKRPMSAYMLWLNASREKIKSDHPGISITDLSKKAGEIWKGMSKEKKEEWDRKA
EDARRDYEKAMKEYEGGRGESSKRDKSKKKKKVKVKMEKKSTPSRGSSSKSSSRQLSESF
KSKEFVSSDESSSGENKSKKKRRRSEDSEEEELASTPPSSEDSASGSDE

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3D Structure

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PDB

Drugs and Modes of Action

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Clinical Trial Drug(s)

[+] 2 Clinical Trial Drugs

CBL0102

Drug Info

Phase 1/2

Hepatocellular carcinoma

[2]

CBL0137

Drug Info

Phase 1

Advanced solid tumour

[3]

Mode of Action

[+] 1 Modes of Action

Modulator

[+] 2 Modulator drugs

CBL0102

Drug Info

[1]

CBL0137

Drug Info

[4]

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	19	Degree centrality	2.04E-03	Betweenness centrality	1.90E-04
Closeness centrality	2.11E-01	Radiality	1.37E+01	Clustering coefficient	2.81E-01
Neighborhood connectivity	2.57E+01	Topological coefficient	1.20E-01	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

Target-interacting Proteins

Target-interacting Proteins Info

Target Affiliated Biological Pathways

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WikiPathways

[+] 2 WikiPathways

HIV Life Cycle

RNA Polymerase II Transcription

References

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REF 1

Company report (Incuron)

REF 2

Trusted, scientifically sound profiles of drug programs, clinical trials, safety reports, and company deals, written by scientists. Springer. 2015. Adis Insight (drug id 800025385)

REF 3

ClinicalTrials.gov (NCT01905228) A Phase 1 Trial of CBL0137 in Patients With Metastatic or Unresectable Advanced Solid Neoplasm or Refractory Lymphomas. U.S. National Institutes of Health.

REF 4

Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues. Genomics 2005 Aug;86(2):127-41.

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