IMPPAT Phytochemical information: 
beta-Sitosterol

beta-Sitosterol
Summary

SMILES: CC[C@@H](C(C)C)CC[C@H]([C@H]1CC[C@@H]2[C@]1(C)CC[C@H]1[C@H]2CC=C2[C@]1(C)CC[C@@H](C2)O)C
InChI: InChI=1S/C29H50O/c1-7-21(19(2)3)9-8-20(4)25-12-13-26-24-11-10-22-18-23(30)14-16-28(22,5)27(24)15-17-29(25,26)6/h10,19-21,23-27,30H,7-9,11-18H2,1-6H3/t20-,21-,23+,24+,25-,26+,27+,28+,29-/m1/s1
InChIKey: KZJWDPNRJALLNS-VJSFXXLFSA-N
DeepSMILES: CC[C@@H]CC)C))CC[C@H][C@H]CC[C@@H][C@]5C)CC[C@H][C@H]6CC=C[C@]6C)CC[C@@H]C6)O)))))))))))))))))C
Scaffold Graph/Node/Bond level: C1=C2CCCCC2C2CCC3CCCC3C2C1
Scaffold Graph/Node level: C1CCC2C(C1)CCC1C3CCCC3CCC21
Scaffold Graph level: C1CCC2C(C1)CCC1C3CCCC3CCC21
Functional groups: CC=C(C)C; CO
Chemical classification
ClassyFire Kingdom: Organic compounds
ClassyFire Superclass: Lipids and lipid-like molecules
ClassyFire Class: Steroids and steroid derivatives
ClassyFire Subclass: Stigmastanes and derivatives
NP Classifier Biosynthetic pathway: Terpenoids
NP Classifier Superclass: Steroids
NP Classifier Class: Stigmastane steroids
Synonymous chemical names:
beta -sitosterol, beta sitosterol, beta- sitosterol, beta-sitosteol, beta-sitosterol, phytopherols (β-sitosterol), sitosterol, sitosterol ,beta, sitosterol ,beta-, sitosterol beta-, sitosterol, beta, sitosterol, beta-, sitosterol,beta, sitosterol,beta-, ß-sitosterol, β -sitosterol, β-sitos-terol, β-sitosterol
External chemical identifiers:
CID:222284; ChEMBL:CHEMBL221542; ChEBI:27693; ZINC:ZINC000004095717; FDASRS:S347WMO6M4; SureChEMBL:SCHEMBL16105; MolPort-001-742-476
Chemical structure download


beta-Sitosterol
Physicochemical properties
Property name Tool Property value
Molecular weight (g/mol) RDKit 414.72
Log P RDKit 8.02
Topological polar surface area (Å2) RDKit 20.23
Number of hydrogen bond acceptors RDKit 1
Number of hydrogen bond donors RDKit 1
Number of carbon atoms RDKit 29
Number of heavy atoms RDKit 30
Number of heteroatoms RDKit 1
Number of nitrogen atoms RDKit 0
Number of sulfur atoms RDKit 0
Number of chiral carbon atoms RDKit 9
Stereochemical complexity RDKit 0.31
Number of sp hybridized carbon atoms RDKit 0
Number of sp2 hybridized carbon atoms RDKit 2
Number of sp3 hybridized carbon atoms RDKit 27
Shape complexity RDKit 0.93
Number of rotatable bonds RDKit 6
Number of aliphatic carbocycles RDKit 4
Number of aliphatic heterocycles RDKit 0
Number of aliphatic rings RDKit 4
Number of aromatic carbocycles RDKit 0
Number of aromatic heterocycles RDKit 0
Number of aromatic rings RDKit 0
Total number of rings RDKit 4
Number of saturated carbocycles RDKit 3
Number of saturated heterocycles RDKit 0
Number of saturated rings RDKit 3
Number of Smallest Set of Smallest Rings (SSSR) RDKit 4


beta-Sitosterol
Drug-likeness properties
Property nameToolProperty value
Number of Lipinski’s rule of 5 violations RDKit 1
Lipinski’s rule of 5 filter RDKit Passed
Number of Ghose filter violations RDKit 2
Ghose filter RDKit Failed
Veber filter RDKit Good
Pfizer 3/75 filter RDKit Bad
GSK 4/400 filter RDKit Bad
Weighted quantitative estimate of drug-likeness (QEDw) score RDKit 0.4361


beta-Sitosterol
ADMET properties
Property nameToolProperty value
Bioavailability score SwissADME 0.55
Solubility class [ESOL] SwissADME Poorly soluble
Solubility class [Silicos-IT] SwissADME Poorly soluble
Blood Brain Barrier permeation SwissADME No
Gastrointestinal absorption SwissADME Low
Log Kp (Skin permeation, cm/s) SwissADME -2.2
Number of PAINS structural alerts SwissADME 0.0
Number of Brenk structural alerts SwissADME 1.0
CYP1A2 inhibitor SwissADME No
CYP2C19 inhibitor SwissADME No
CYP2C9 inhibitor SwissADME No
CYP2D6 inhibitor SwissADME No
CYP3A4 inhibitor SwissADME No
P-glycoprotein substrate SwissADME No


beta-Sitosterol
Predicted human target proteins
Protein identifierHGNC symbolCombined score from STITCH database
ENSP00000252486APOE872
ENSP00000260645ABCG5879
ENSP00000263817ABCB11815
ENSP00000264832ICAM1800
ENSP00000272286ABCG8920
ENSP00000301645CYP7A1771
ENSP00000311032CASP3818
ENSP00000348069SREBF1816
ENSP00000354476SREBF2926
ENSP00000360316DHCR24841
The human target proteins were predicted using STITCH, a database of Chemical-Protein interaction networks.