Target Information

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Target General Information
Different Human System Profiles of Target
References
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
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.
 Download Picture         KEGG Link      
 Download Picture         KEGG Link      
 Download Picture         KEGG Link      
 Download Picture         KEGG Link      
 Download Picture         KEGG Link      
KEGG Pathway Pathway ID Affiliated Target Pathway Map
PI3K-Akt signaling pathway hsa04151 Affiliated Target
  Class: Environmental Information Processing => Signal transduction Pathway Hierarchy
Focal adhesion hsa04510 Affiliated Target
  Class: Cellular Processes => Cellular community - eukaryotes Pathway Hierarchy
ECM-receptor interaction hsa04512 Affiliated Target
  Class: Environmental Information Processing => Signaling molecules and interaction Pathway Hierarchy
Cell adhesion molecules hsa04514 Affiliated Target
  Class: Environmental Information Processing => Signaling molecules and interaction Pathway Hierarchy
Regulation of actin cytoskeleton hsa04810 Affiliated Target
  Class: Cellular Processes => Cell motility Pathway Hierarchy
Degree 10 Degree centrality 1.07E-03 Betweenness centrality 1.81E-05
Closeness centrality 2.11E-01 Radiality 1.37E+01 Clustering coefficient 2.44E-01
Neighborhood connectivity 2.88E+01 Topological coefficient 2.00E-01 Eccentricity 12
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