Target Information
| Target General Information | Top | |||||
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| Target ID |
T93903
(Former ID: TTDR01006)
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| Target Name |
Caspase-9 (CASP9)
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| Synonyms |
MCH6; ICE-like apoptotic protease 6; ICE-LAP6; CASP-9; Apoptotic protease-activating factor 3; Apoptotic protease activating factor 3; Apoptotic protease Mch-6; APAF-3
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| Gene Name |
CASP9
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| Target Type |
Clinical trial target
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[1] | ||||
| Disease | [+] 1 Target-related Diseases | + | ||||
| 1 | Cystic fibrosis [ICD-11: CA25] | |||||
| Function |
Binding of caspase-9 to Apaf-1 leads to activation of the protease which then cleaves and activates caspase-3. Promotes DNA damage-induced apoptosis in a ABL1/c-Abl-dependent manner. Proteolytically cleaves poly(ADP-ribose) polymerase (PARP). Involved in the activation cascade of caspases responsible for apoptosis execution.
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| BioChemical Class |
Peptidase
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| UniProt ID | ||||||
| EC Number |
EC 3.4.22.62
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| Sequence |
MDEADRRLLRRCRLRLVEELQVDQLWDALLSRELFRPHMIEDIQRAGSGSRRDQARQLII
DLETRGSQALPLFISCLEDTGQDMLASFLRTNRQAAKLSKPTLENLTPVVLRPEIRKPEV LRPETPRPVDIGSGGFGDVGALESLRGNADLAYILSMEPCGHCLIINNVNFCRESGLRTR TGSNIDCEKLRRRFSSLHFMVEVKGDLTAKKMVLALLELAQQDHGALDCCVVVILSHGCQ ASHLQFPGAVYGTDGCPVSVEKIVNIFNGTSCPSLGGKPKLFFIQACGGEQKDHGFEVAS TSPEDESPGSNPEPDATPFQEGLRTFDQLDAISSLPTPSDIFVSYSTFPGFVSWRDPKSG SWYVETLDDIFEQWAHSEDLQSLLLRVANAVSVKGIYKQMPGCFNFLRKKLFFKTS Click to Show/Hide
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| 3D Structure | Click to Show 3D Structure of This Target | AlphaFold | ||||
| ADReCS ID | BADD_A05675 ; BADD_A08298 | |||||
| HIT2.0 ID | T23P74 | |||||
| Drugs and Modes of Action | Top | |||||
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| Clinical Trial Drug(s) | [+] 1 Clinical Trial Drugs | + | ||||
| 1 | isatin sulfonamide 34 | Drug Info | Clinical trial | Cystic fibrosis | [1], [2] | |
| Mode of Action | [+] 2 Modes of Action | + | ||||
| Inhibitor | [+] 2 Inhibitor drugs | + | ||||
| 1 | isatin sulfonamide 34 | Drug Info | [1] | |||
| 2 | Z-LEHD-fmk | Drug Info | [5] | |||
| Modulator | [+] 2 Modulator drugs | + | ||||
| 1 | Glionitrin A | Drug Info | [3] | |||
| 2 | NVX-207 | Drug Info | [4] | |||
| Cell-based Target Expression Variations | Top | |||||
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| Cell-based Target Expression Variations | ||||||
| Drug Binding Sites of Target | Top | |||||
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| Ligand Name: D-malate | Ligand Info | |||||
| Structure Description | Crystal structure of a dimeric caspase-9 | PDB:2AR9 | ||||
| Method | X-ray diffraction | Resolution | 2.80 Å | Mutation | Yes | [6] |
| PDB Sequence |
GALESLRGNA
149 DLAYILSMEP159 CGHCLIINNV169 NFCRESGLRT179 RTGSNIDCEK189 LRRRFSSLHF 199 MVEVKGDLTA209 KKMVLALLEL219 ARQDHGALDC229 CVVVILSHGC239 QASHLQFPGA 249 VYGTDGCPVS259 VEKIVNIFNG269 TSCPSLGGKP279 KLFFIQASLP336 TPSDIFVSYS 346 TFPGFVSWRD356 PKSGSWYVET366 LDDIFEQWAH376 SEDLQSLLLR386 VANAVSVKGI 396 YKQMPCIVSM406 LRKKLFFKTS416
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| Click to View More Binding Site Information of This Target with Different Ligands | ||||||
| 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 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
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There is no similarity protein (E value < 0.005) for this target
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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.
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| KEGG Pathway | Pathway ID | Affiliated Target | Pathway Map |
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| p53 signaling pathway | hsa04115 | Affiliated Target |
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| Class: Cellular Processes => Cell growth and death | Pathway Hierarchy | ||
| PI3K-Akt signaling pathway | hsa04151 | Affiliated Target |
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| Class: Environmental Information Processing => Signal transduction | Pathway Hierarchy | ||
| Apoptosis | hsa04210 | Affiliated Target |
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| Class: Cellular Processes => Cell growth and death | Pathway Hierarchy | ||
| Apoptosis - multiple species | hsa04215 | Affiliated Target |
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| Class: Cellular Processes => Cell growth and death | Pathway Hierarchy | ||
| VEGF signaling pathway | hsa04370 | Affiliated Target |
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| Class: Environmental Information Processing => Signal transduction | Pathway Hierarchy | ||
| Thyroid hormone signaling pathway | hsa04919 | Affiliated Target |
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| Class: Organismal Systems => Endocrine system | Pathway Hierarchy | ||
| Click to Show/Hide the Information of Affiliated Human Pathways | |||
| Degree | 14 | Degree centrality | 1.50E-03 | Betweenness centrality | 3.47E-04 |
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| Closeness centrality | 2.39E-01 | Radiality | 1.42E+01 | Clustering coefficient | 3.19E-01 |
| Neighborhood connectivity | 4.54E+01 | Topological coefficient | 1.17E-01 | Eccentricity | 11 |
| Download | Click to Download the Full PPI Network of This Target | ||||
| Chemical Structure based Activity Landscape of Target | Top |
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| Drug Property Profile of Target | Top | |
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| (1) Molecular Weight (mw) based Drug Clustering | (2) Octanol/Water Partition Coefficient (xlogp) based Drug Clustering | |
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| (3) Hydrogen Bond Donor Count (hbonddonor) based Drug Clustering | (4) Hydrogen Bond Acceptor Count (hbondacc) based Drug Clustering | |
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| (5) Rotatable Bond Count (rotbonds) based Drug Clustering | (6) Topological Polar Surface Area (polararea) based Drug Clustering | |
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| "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 | ||
| Co-Targets | Top | |||||
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| Co-Targets | ||||||
| Target Poor or Non Binders | Top | |||||
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| Target Poor or Non Binders | ||||||
| Target Regulators | Top | |||||
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| Target-regulating microRNAs | ||||||
| Target-interacting Proteins | ||||||
| References | Top | |||||
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| REF 1 | Potent and selective nonpeptide inhibitors of caspases 3 and 7. J Med Chem. 2001 Jun 7;44(12):2015-26. | |||||
| REF 2 | 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. (Ligand id: 6515). | |||||
| REF 3 | Glionitrin A, a new diketopiperazine disulfide, activates ATM-ATR-Chk1/2 via 53BP1 phosphorylation in DU145 cells and shows antitumor effect in xenograft model. Biol Pharm Bull. 2014;37(3):378-86. | |||||
| REF 4 | 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: 1625). | |||||
| REF 5 | The expression of Smac and XIAP in rat hippocampus following limbic seizure induced by kainic acid injection into amygdaloid nucleus. Sheng Li Xue Bao. 2004 Apr 25;56(2):172-7. | |||||
| REF 6 | Engineering a dimeric caspase-9: a re-evaluation of the induced proximity model for caspase activation. PLoS Biol. 2005 Jun;3(6):e183. | |||||
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