IMPPAT Phytochemical information: 
Cynaroside

Cynaroside
Summary

SMILES: OC[C@H]1O[C@@H](Oc2cc(O)c3c(c2)oc(cc3=O)c2ccc(c(c2)O)O)[C@@H]([C@H]([C@@H]1O)O)O
InChI: InChI=1S/C21H20O11/c22-7-16-18(27)19(28)20(29)21(32-16)30-9-4-12(25)17-13(26)6-14(31-15(17)5-9)8-1-2-10(23)11(24)3-8/h1-6,16,18-25,27-29H,7H2/t16-,18-,19+,20-,21-/m1/s1
InChIKey: PEFNSGRTCBGNAN-QNDFHXLGSA-N
DeepSMILES: OC[C@H]O[C@@H]OcccO)ccc6)occc6=O)))cccccc6)O))O)))))))))))))[C@@H][C@H][C@@H]6O))O))O
Scaffold Graph/Node/Bond level: O=c1cc(-c2ccccc2)oc2cc(OC3CCCCO3)ccc12
Scaffold Graph/Node level: OC1CC(C2CCCCC2)OC2CC(OC3CCCCO3)CCC12
Scaffold Graph level: CC1CC(C2CCCCC2)CC2CC(CC3CCCCC3)CCC12
Functional groups: CO; cO[C@@H](C)OC; cO; coc; c=O
Chemical classification
ClassyFire Kingdom: Organic compounds
ClassyFire Superclass: Phenylpropanoids and polyketides
ClassyFire Class: Flavonoids
ClassyFire Subclass: Flavonoid glycosides
NP Classifier Biosynthetic pathway: Shikimates and Phenylpropanoids
NP Classifier Superclass: Flavonoids
NP Classifier Class: Flavones
Synonymous chemical names:
Luteolin-7-glucoside, luteolin-7-glucoside, luteolin and its 7 glucoside, Glucoluteolin, luteolin-7-o-glucopyranoside, luteolin-7-β-glucoside, luteolin-7-glucosides, cynaroside, Gluco Luteolin, Luteolin-7-O-glucoside, cinaroside, galuteolin, luteolin-7-mono-beta-d-glucopyranoside, luteolin-7-β-d-glucoside, Cynaroside, luteolin-7-o-glucoside, luteoloside, luteolin 7-o-glucoside, luteolin-7-glucosylglucuronide, luteolin-7-o-beta-glucoside, glucoluteolin, 7-glucoside of luteolin, luteolin 7-glucoside, luteolin -7- glucoside
External chemical identifiers:
CID:CID_5280637; ChEMBL:CHEMBL233929; ChEBI:CHEBI:27994; ZINC:ZINC000004096258; FDASRS:98J6XDS46I; SureChEMBL:SCHEMBL149118; MolPort-001-740-780
Chemical structure download


Cynaroside
Physicochemical properties
Property name Tool Property value
Molecular weight (g/mol) RDKit 448.38
Log P RDKit -0.24
Topological polar surface area (Å2) RDKit 190.28
Number of hydrogen bond acceptors RDKit 11
Number of hydrogen bond donors RDKit 7
Number of carbon atoms RDKit 21
Number of heavy atoms RDKit 32
Number of heteroatoms RDKit 11
Number of nitrogen atoms RDKit 0
Number of sulfur atoms RDKit 0
Number of chiral carbon atoms RDKit 5
Stereochemical complexity RDKit 0.24
Number of sp hybridized carbon atoms RDKit 0
Number of sp2 hybridized carbon atoms RDKit 15
Number of sp3 hybridized carbon atoms RDKit 6
Shape complexity RDKit 0.29
Number of rotatable bonds RDKit 4
Number of aliphatic carbocycles RDKit 0
Number of aliphatic heterocycles RDKit 1
Number of aliphatic rings RDKit 1
Number of aromatic carbocycles RDKit 2
Number of aromatic heterocycles RDKit 1
Number of aromatic rings RDKit 3
Total number of rings RDKit 4
Number of saturated carbocycles RDKit 0
Number of saturated heterocycles RDKit 1
Number of saturated rings RDKit 1
Number of Smallest Set of Smallest Rings (SSSR) RDKit 4


Cynaroside
Drug-likeness properties
Property nameToolProperty value
Number of Lipinski’s rule of 5 violations RDKit 2
Lipinski’s rule of 5 RDKit Failed
Number of Ghose rule violations RDKit 0
Ghose rule RDKit Passed
Veber rule RDKit Bad
Egan rule RDKit Bad
GSK 4/400 rule RDKit Bad
Pfizer 3/75 rule RDKit Good
Weighted quantitative estimate of drug-likeness (QEDw) score RDKit 0.26


Cynaroside
ADME properties
Property nameToolProperty value
Bioavailability score SwissADME 0.17
Solubility class [ESOL] SwissADME Soluble
Solubility class [Silicos-IT] SwissADME Soluble
Blood Brain Barrier permeation SwissADME No
Gastrointestinal absorption SwissADME Low
Log Kp (Skin permeation, cm/s) SwissADME -8.00
Number of PAINS structural alerts SwissADME 1
Number of Brenk structural alerts SwissADME 1
CYP1A2 inhibitor SwissADME No
CYP2C19 inhibitor SwissADME No
CYP2C9 inhibitor SwissADME No
CYP2D6 inhibitor SwissADME No
CYP3A4 inhibitor SwissADME No
P-glycoprotein substrate SwissADME Yes


Cynaroside
Human target proteins
Protein identifierHGNC symbolCombined score from STITCH database
ENSP00000297494NOS3920
ENSP00000327251NOS2784
ENSP00000216117HMOX1800
The human target proteins were predicted using STITCH, a database of Chemical-Protein interaction networks.