Target Information

Target General Information

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Target ID

T78114 (Former ID: TTDI02050)

Target Name

Complement decay-accelerating factor (CD55)

Synonyms

DAF; Complement decayaccelerating factor; CR

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Gene Name

CD55

Target Type

Clinical trial target

[1]

Disease

[+] 6 Target-related Diseases

Brain cancer [ICD-11: 2A00]

Bladder cancer [ICD-11: 2C94]

Lung cancer [ICD-11: 2C25]

Melanoma [ICD-11: 2C30]

Prostate cancer [ICD-11: 2C82]

Stomach cancer [ICD-11: 2B72]

Function

Interaction of daf with cell-associated C4b and C3b polypeptides interferes with their ability to catalyze the conversion of C2 and factor B to enzymatically active C2a and Bb and thereby prevents the formation of C4b2a and C3bBb, the amplification convertases of the complement cascade. Inhibits complement activation by destabilizing and preventing the formation of C3 and C5 convertases, which prevents complement damage. This protein recognizes C4b and C3b fragments that condense with cell-surface hydroxyl or amino groups when nascent C4b and C3b are locally generated during C4 and c3 activation.

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UniProt ID

DAF_HUMAN

Sequence

MTVARPSVPAALPLLGELPRLLLLVLLCLPAVWGDCGLPPDVPNAQPALEGRTSFPEDTV
ITYKCEESFVKIPGEKDSVICLKGSQWSDIEEFCNRSCEVPTRLNSASLKQPYITQNYFP
VGTVVEYECRPGYRREPSLSPKLTCLQNLKWSTAVEFCKKKSCPNPGEIRNGQIDVPGGI
LFGATISFSCNTGYKLFGSTSSFCLISGSSVQWSDPLPECREIYCPAPPQIDNGIIQGER
DHYGYRQSVTYACNKGFTMIGEHSIYCTVNNDEGEWSGPPPECRGKSLTSKVPPTVQKPT
TVNVPTTEVSPTSQKTTTKTTTPNAQATRSTPVSRTTKHFHETTPNKGSGTTSGTTRLLS
GHTCFTLTGLLGTLVTMGLLT

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3D Structure

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PDB

HIT2.0 ID

T73AR5

Drugs and Modes of Action

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Clinical Trial Drug(s)

[+] 3 Clinical Trial Drugs

Coxsackievirus A21

Drug Info

Phase 2

Glioblastoma multiforme

[1]

Onyvax-105

Drug Info

Phase 1/2

Prostate cancer

[2]

PAT-SC1

Drug Info

Phase 1/2

Gastric adenocarcinoma

[3]

Mode of Action

[+] 1 Modes of Action

Inhibitor

[+] 1 Inhibitor drugs

Coxsackievirus A21

Drug Info

[1]

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
Haptoglobin (HP)	PF00089	26.866 (36/134)	2.06E-04


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
Complement and coagulation cascades	hsa04610	Affiliated Target
Class: Organismal Systems => Immune system	Pathway Hierarchy
Hematopoietic cell lineage	hsa04640	Affiliated Target
Class: Organismal Systems => Immune system	Pathway Hierarchy

Degree	3	Degree centrality	3.22E-04	Betweenness centrality	4.10E-05
Closeness centrality	1.60E-01	Radiality	1.23E+01	Clustering coefficient	0.00E+00
Neighborhood connectivity	9.33E+00	Topological coefficient	3.33E-01	Eccentricity	14
Download	Click to Download the Full PPI Network of This Target

Target Profiles in Patients

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Target Expression
Profile (TEP)

Target Expression Profile Info

Target Affiliated Biological Pathways

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KEGG Pathway

[+] 3 KEGG Pathways

Complement and coagulation cascades

Hematopoietic cell lineage

Viral myocarditis

NetPath Pathway

[+] 4 NetPath Pathways

IL5 Signaling Pathway

IL2 Signaling Pathway

FSH Signaling Pathway

TGF_beta_Receptor Signaling Pathway

Reactome

[+] 2 Reactome Pathways

Class B/2 (Secretin family receptors)

Regulation of Complement cascade

WikiPathways

[+] 5 WikiPathways

Complement and Coagulation Cascades

Complement Activation, Classical Pathway

Human Complement System

GPCR ligand binding

Complement cascade

References

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REF 1

Oncolytic Coxsackievirus A21 as a novel therapy for multiple myeloma. Br J Haematol. 2007 Apr;137(2):133-41.

REF 2

Onyvax-105 Cancer Vaccine Shows Encouraging Clinical Results in Osteosarcoma Patients After Intensive Chemotherapy. Onyvax vaccines therapies. April 19, 2005.

REF 3

Trusted, scientifically sound profiles of drug programs, clinical trials, safety reports, and company deals, written by scientists. Springer. 2015. Adis Insight (drug id 800013314)

REF 4

Technology evaluation: Onyvax-105, Onyvax. Curr Opin Mol Ther. 2003 Dec;5(6):668-72.

REF 5

Ten-year follow-up of a prospective trial for the targeted therapy of gastric cancer with the human monoclonal antibody PAT-SC1. Oncol Rep. 2014 Mar;31(3):1059-66.

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