Secondary metabolite: beta-Sitosterol



beta-Sitosterol
Summary
Molecular formula: C29H50O
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-OAIXMFQVSA-N
Chemical classification
Kingdom: Organic compounds
Super class: Lipids and lipid-like molecules
Class: Steroids and steroid derivatives
Sub class: Stigmastanes and derivatives
Synonymous chemical names:
beta-sitosterol
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
Fraction of sp3 hybridized carbon atoms (Fsp3) RDKit 0.93
Shape complexity RDKit 0.93
Number of rotatable bonds SwissADME 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
Egan filter RDKit Bad
Pfizer’s 3/75 filter RDKit Bad
GSK 4/400 filter RDKit Bad
Number of Leadlikeness violations SwissADME 2
Weighted quantitative estimate of drug-likeness (QEDw) score RDKit 0.44



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
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 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.

Designed by R.P. Vivek-Ananth, M Karthikeyan and Ajaya Kumar Sahoo