Target Information
Target General Information | Top | |||||
---|---|---|---|---|---|---|
Target ID |
T93580
(Former ID: TTDI03512)
|
|||||
Target Name |
Regulator of G-protein signaling 4 (RGS4)
|
|||||
Synonyms |
RGP4
Click to Show/Hide
|
|||||
Gene Name |
RGS4
|
|||||
Target Type |
Literature-reported target
|
[1] | ||||
Function |
Activity on G(z)-alpha is inhibited by phosphorylation of the G-protein. Activity on G(z)-alpha and G(i)-alpha-1 is inhibited by palmitoylation of the G-protein. Inhibits signal transduction by increasing the GTPase activity of G protein alpha subunits thereby driving them into their inactive GDP-bound form.
Click to Show/Hide
|
|||||
UniProt ID | ||||||
Sequence |
MCKGLAGLPASCLRSAKDMKHRLGFLLQKSDSCEHNSSHNKKDKVVICQRVSQEEVKKWA
ESLENLISHECGLAAFKAFLKSEYSEENIDFWISCEEYKKIKSPSKLSPKAKKIYNEFIS VQATKEVNLDSCTREETSRNMLEPTITCFDEAQKKIFNLMEKDSYRRFLKSRFYLDLVNP SSCGAEKQKGAKSSADCASLVPQCA Click to Show/Hide
|
|||||
3D Structure | Click to Show 3D Structure of This Target | AlphaFold | ||||
HIT2.0 ID | T59X8J |
Cell-based Target Expression Variations | Top | |||||
---|---|---|---|---|---|---|
Cell-based Target Expression Variations |
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
|
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 | 3 | Degree centrality | 3.22E-04 | Betweenness centrality | 3.04E-06 |
---|---|---|---|---|---|
Closeness centrality | 1.97E-01 | Radiality | 1.34E+01 | Clustering coefficient | 3.33E-01 |
Neighborhood connectivity | 3.00E+01 | Topological coefficient | 3.90E-01 | Eccentricity | 12 |
Download | Click to Download the Full PPI Network of This Target | ||||
Chemical Structure based Activity Landscape of Target | Top |
---|---|
Drug Property Profile of Target | Top | |
---|---|---|
(1) Molecular Weight (mw) based Drug Clustering | (2) Octanol/Water Partition Coefficient (xlogp) based Drug Clustering | |
|
||
(3) Hydrogen Bond Donor Count (hbonddonor) based Drug Clustering | (4) Hydrogen Bond Acceptor Count (hbondacc) based Drug Clustering | |
|
||
(5) Rotatable Bond Count (rotbonds) based Drug Clustering | (6) Topological Polar Surface Area (polararea) based Drug Clustering | |
|
||
"RO5" indicates the cutoff set by lipinski's rule of five; "D123AB" colored in GREEN denotes the no violation of any cutoff in lipinski's rule of five; "D123AB" colored in PURPLE refers to the violation of only one cutoff in lipinski's rule of five; "D123AB" colored in BLACK represents the violation of more than one cutoffs in lipinski's rule of five |
Target Poor or Non Binders | Top | |||||
---|---|---|---|---|---|---|
Target Poor or Non Binders |
Target Regulators | Top | |||||
---|---|---|---|---|---|---|
Target-interacting Proteins |
References | Top | |||||
---|---|---|---|---|---|---|
REF 1 | 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. (Target id: 2811). |
If You Find Any Error in Data or Bug in Web Service, Please Kindly Report It to Dr. Zhou and Dr. Zhang.