Target Information

Target General Information

Target ID

T01441 (Former ID: TTDI00111)

Target Name

Synovial apoptosis inhibitor 1 (SYVN1)

Synonyms

RING-type E3 ubiquitin transferase synoviolin; KIAA1810; HRD1; E3 ubiquitinprotein ligase synoviolin; E3 ubiquitin-protein ligase synoviolin

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Gene Name

SYVN1

Target Type

Literature-reported target

[1]

Function

Component of the endoplasmic reticulum quality control (ERQC) system also called ER-associated degradation (ERAD) involved in ubiquitin-dependent degradation of misfolded endoplasmic reticulum proteins. Also promotes the degradation of normal but naturally short-lived proteins such as SGK. Protects cells from ER stress-induced apoptosis. Protects neurons from apoptosis induced by polyglutamine-expanded huntingtin (HTT) or unfolded GPR37 by promoting their degradation. Sequesters p53/TP53 in the cytoplasm and promotes its degradation, thereby negatively regulating its biological function in transcription, cell cycle regulation and apoptosis. Mediates the ubiquitination and subsequent degradation of cytoplasmic NFE2L1. Acts as an E3 ubiquitin-protein ligase which accepts ubiquitin specifically from endoplasmic reticulum-associated UBC7 E2 ligase and transfers it to substrates, promoting their degradation.

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BioChemical Class

Acyltransferase

UniProt ID

SYVN1_HUMAN

EC Number

EC 2.3.2.27

Sequence

MFRTAVMMAASLALTGAVVAHAYYLKHQFYPTVVYLTKSSPSMAVLYIQAFVLVFLLGKV
MGKVFFGQLRAAEMEHLLERSWYAVTETCLAFTVFRDDFSPRFVALFTLLLFLKCFHWLA
EDRVDFMERSPNISWLFHCRIVSLMFLLGILDFLFVSHAYHSILTRGASVQLVFGFEYAI
LMTMVLTIFIKYVLHSVDLQSENPWDNKAVYMLYTELFTGFIKVLLYMAFMTIMIKVHTF
PLFAIRPMYLAMRQFKKAVTDAIMSRRAIRNMNTLYPDATPEELQAMDNVCIICREEMVT
GAKRLPCNHIFHTSCLRSWFQRQQTCPTCRMDVLRASLPAQSPPPPEPADQGPPPAPHPP
PLLPQPPNFPQGLLPPFPPGMFPLWPPMGPFPPVPPPPSSGEAVAPPSTSAAALSRPSGA
ATTTAAGTSATAASATASGPGSGSAPEAGPAPGFPFPPPWMGMPLPPPFAFPPMPVPPAG
FAGLTPEELRALEGHERQHLEARLQSLRNIHTLLDAAMLQINQYLTVLASLGPPRPATSV
NSTEETATTVVAAASSTSIPSSEATTPTPGASPPAPEMERPPAPESVGTEEMPEDGEPDA
AELRRRRLQKLESPVAH

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3D Structure

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AlphaFold

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). 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

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).

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

Protein Name	Pfam ID	Percentage of Identity (%)	E value
E3 ubiquitin ligase RNF121 (RNF121)		36.842 (21/57)	6.84E-07
RING finger protein 175 (RNF175)		35.088 (20/57)	1.22E-06
RING finger protein 151 (RNF151)	PF13923	44.898 (22/49)	3.98E-06
E3 ubiquitin-protein ligase RNFT1 (RNFT1)	PF13920	38.462 (20/52)	6.92E-06
RING finger and transmembrane domain-containing protein 2 (RNFT2)	PF13923	35.385 (23/65)	4.39E-05
E3 ubiquitin-protein ligase RNF8 (RNF8)	PF00498 ; PF13920	39.286 (22/56)	9.72E-05
E3 ubiquitin-protein ligase CHFR (CHFR)	PF00498 ; PF13923 ; PF10283 ; PF17979 More >>	32.394 (23/71)	1.32E-04
E3 ubiquitin-protein ligase MGRN1 (MGRN1)	PF13920	27.119 (32/118)	3.69E-04
RING-box protein 2 (RNF7)	PF12678	27.586 (16/58)	5.50E-04
Nuclear receptor subfamily 6 group A member 1 (NR6A1)	PF00104 ; PF00105	23.741 (33/139)	8.69E-04
Signal transduction protein CBL (CBL)	PF02262 ; PF02761 ; PF02762 ; PF14447 ; PF00627 More >>	38.462 (20/52)	1.00E-03
E3 ubiquitin-protein ligase SH3RF3 (SH3RF3)	PF00018 ; PF14604 ; PF00097 More >>	42.222 (19/45)	2.00E-03
Anaphase-promoting complex subunit 11 (ANAPC11)	PF12861	44.828 (13/29)	5.00E-03
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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.

KEGG Pathway	Pathway ID	Affiliated Target
Ubiquitin mediated proteolysis	hsa04120	Affiliated Target
Class: Genetic Information Processing => Folding, sorting and degradation	Pathway Hierarchy
Protein processing in endoplasmic reticulum	hsa04141	Affiliated Target
Class: Genetic Information Processing => Folding, sorting and degradation	Pathway Hierarchy

Degree	14	Degree centrality	1.50E-03	Betweenness centrality	1.20E-04
Closeness centrality	2.03E-01	Radiality	1.35E+01	Clustering coefficient	2.64E-01
Neighborhood connectivity	1.11E+01	Topological coefficient	1.17E-01	Eccentricity	12
Download	Click to Download the Full PPI Network of This Target

Target Regulators

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Target-interacting Proteins

Target-interacting Proteins Info

References

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REF 1

Upregulation of microRNA-125b-5p is involved in the pathogenesis of osteoarthritis by downregulating SYVN1. Oncol Rep. 2017 Apr;37(4):2490-2496.

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