Target Information
Target General Information | Top | |||||
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Target ID |
T87633
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Target Name |
HUMAN toll-like receptor 9 (TLR9)
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Synonyms |
UNQ5798/PRO19605; TLR-9; CD289
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Gene Name |
TLR9
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Disease | [+] 1 Target-related Diseases | + | ||||
1 | COVID-19 [ICD-11: 1D6Y] | |||||
Function |
Key component of innate and adaptive immunity. TLRs (Toll-like receptors) control host immune response against pathogens through recognition of molecular patterns specific to microorganisms. TLR9 is a nucleotide-sensing TLR which is activated by unmethylated cytidine-phosphate-guanosine (CpG) dinucleotides. Acts via MYD88 and TRAF6, leading to NF-kappa-B activation, cytokine secretion and the inflammatory response. Controls lymphocyte response to Helicobacter infection. Upon CpG stimulation, induces B-cell proliferation, activation, survival and antibody production.
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BioChemical Class |
Toll-like receptor
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UniProt ID | ||||||
Sequence |
MGFCRSALHPLSLLVQAIMLAMTLALGTLPAFLPCELQPHGLVNCNWLFLKSVPHFSMAA
PRGNVTSLSLSSNRIHHLHDSDFAHLPSLRHLNLKWNCPPVGLSPMHFPCHMTIEPSTFL AVPTLEELNLSYNNIMTVPALPKSLISLSLSHTNILMLDSASLAGLHALRFLFMDGNCYY KNPCRQALEVAPGALLGLGNLTHLSLKYNNLTVVPRNLPSSLEYLLLSYNRIVKLAPEDL ANLTALRVLDVGGNCRRCDHAPNPCMECPRHFPQLHPDTFSHLSRLEGLVLKDSSLSWLN ASWFRGLGNLRVLDLSENFLYKCITKTKAFQGLTQLRKLNLSFNYQKRVSFAHLSLAPSF GSLVALKELDMHGIFFRSLDETTLRPLARLPMLQTLRLQMNFINQAQLGIFRAFPGLRYV DLSDNRISGASELTATMGEADGGEKVWLQPGDLAPAPVDTPSSEDFRPNCSTLNFTLDLS RNNLVTVQPEMFAQLSHLQCLRLSHNCISQAVNGSQFLPLTGLQVLDLSHNKLDLYHEHS FTELPRLEALDLSYNSQPFGMQGVGHNFSFVAHLRTLRHLSLAHNNIHSQVSQQLCSTSL RALDFSGNALGHMWAEGDLYLHFFQGLSGLIWLDLSQNRLHTLLPQTLRNLPKSLQVLRL RDNYLAFFKWWSLHFLPKLEVLDLAGNQLKALTNGSLPAGTRLRRLDVSCNSISFVAPGF FSKAKELRELNLSANALKTVDHSWFGPLASALQILDVSANPLHCACGAAFMDFLLEVQAA VPGLPSRVKCGSPGQLQGLSIFAQDLRLCLDEALSWDCFALSLLAVALGLGVPMLHHLCG WDLWYCFHLCLAWLPWRGRQSGRDEDALPYDAFVVFDKTQSAVADWVYNELRGQLEECRG RWALRLCLEERDWLPGKTLFENLWASVYGSRKTLFVLAHTDRVSGLLRASFLLAQQRLLE DRKDVVVLVILSPDGRRSRYVRLRQRLCRQSVLLWPHQPSGQRSFWAQLGMALTRDNHHF YNRNFCQGPTAE Click to Show/Hide
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3D Structure | Click to Show 3D Structure of This Target | AlphaFold |
Drugs and Modes of Action | Top | |||||
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Drugs in Phase 2 Trial | [+] 1 | + | ||||
1 | PUL-042 | Drug Info | Phase 2 | Coronavirus Disease 2019 (COVID-19) | [2] | |
Mode of Action | [+] 1 Modes of Action | + | ||||
Agonist | [+] 1 Agonist drugs | + | ||||
1 | PUL-042 | Drug Info | [1], [3] |
Cell-based Target Expression Variations | Top | |||||
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Cell-based Target Expression Variations |
Different Human System Profiles of Target | Top |
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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 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 Pathway Affiliation
Biological Network Descriptors
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KEGG Pathway | Pathway ID | Affiliated Target | Pathway Map |
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Toll-like receptor signaling pathway | hsa04620 | Affiliated Target |
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Class: Organismal Systems => Immune system | Pathway Hierarchy |
Degree | 3 | Degree centrality | 3.22E-04 | Betweenness centrality | 1.94E-05 |
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Closeness centrality | 2.03E-01 | Radiality | 1.35E+01 | Clustering coefficient | 3.33E-01 |
Neighborhood connectivity | 2.40E+01 | Topological coefficient | 3.94E-01 | Eccentricity | 12 |
Download | Click to Download the Full PPI Network of This Target | ||||
Chemical Structure based Activity Landscape of Target | Top |
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Target Poor or Non Binders | Top | |||||
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Target Poor or Non Binders |
References | Top | |||||
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REF 1 | Pulmotects lead product, PUL-042, is a clinical stage inhaled therapeutic that in preclinical studies stimulates the innate immune system in minutes to provide immediate and effective protection against all major classes of pathogens that lasts for days. | |||||
REF 2 | ClinicalTrials.gov (NCT04312997) The Use of PUL-042 Inhalation Solution to Reduce the Severity of COVID-19 in Adults Positive for SARS-CoV-2 Infection. U.S. National Institutes of Health. | |||||
REF 3 | TLR 2/6/9 agonist PUL-042 |
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