IMPPAT Phytochemical information: 
Phorbol 12-myristate 13-acetate
Phorbol 12-myristate 13-acetate
Summary

SMILES: CCCCCCCCCCCCCC(=O)O[C@@H]1[C@@H](C)[C@@]2(O)[C@H]([C@H]3[C@]1(OC(=O)C)C3(C)C)C=C(C[C@]1([C@H]2C=C(C1=O)C)O)CO
InChI: InChI=1S/C36H56O8/c1-7-8-9-10-11-12-13-14-15-16-17-18-29(39)43-32-24(3)35(42)27(30-33(5,6)36(30,32)44-25(4)38)20-26(22-37)21-34(41)28(35)19-23(2)31(34)40/h19-20,24,27-28,30,32,37,41-42H,7-18,21-22H2,1-6H3/t24-,27+,28-,30-,32-,34-,35-,36-/m1/s1
InChIKey: PHEDXBVPIONUQT-RGYGYFBISA-N
DeepSMILES: CCCCCCCCCCCCCC=O)O[C@@H][C@@H]C)[C@@]O)[C@H][C@H][C@]6OC=O)C)))C3C)C))))C=CC[C@][C@H]7C=CC5=O))C))))O)))CO
Scaffold Graph/Node/Bond level: O=C1C=CC2C1CC=CC1C3CC3CCC21
Scaffold Graph/Node level: OC1CCC2C1CCCC1C3CC3CCC21
Scaffold Graph level: CC1CCC2C1CCCC1C3CC3CCC21
Functional groups: CC(=O)OC; CC(C)=CC; CC1=CCCC1=O; CO
Chemical classification
ClassyFire Kingdom: Organic compounds
ClassyFire Superclass: Lipids and lipid-like molecules
ClassyFire Class: Prenol lipids
ClassyFire Subclass: Diterpenoids
NP Classifier Biosynthetic pathway: Terpenoids
NP Classifier Superclass: Diterpenoids
NP Classifier Class: Tetracyclic diterpenoids|Tigliane diterpenoids
Synonymous chemical names:
12-o-tetradecanoylphorbol-13-acetate, phorbol 12-myristate 13-acetate, phorbol ester
External chemical identifiers:
CID:27924; ChEMBL:CHEMBL279115; ChEBI:37537; ZINC:ZINC000008214783; FDASRS:NI40JAQ945; SureChEMBL:SCHEMBL115567; MolPort-003-665-586
Chemical structure download
2D:2D MOL2D MOL22D SDF
3D:3D MOL3D MOL23D SDF3D PDB3D PDBQT
Phorbol 12-myristate 13-acetate
Physicochemical properties
Property name Tool Property value
Molecular weight (g/mol) RDKit 616.84
Log P RDKit 5.75
Topological polar surface area (Å2) RDKit 130.36
Number of hydrogen bond acceptors RDKit 8
Number of hydrogen bond donors RDKit 3
Number of carbon atoms RDKit 36
Number of heavy atoms RDKit 44
Number of heteroatoms RDKit 8
Number of nitrogen atoms RDKit 0
Number of sulfur atoms RDKit 0
Number of chiral carbon atoms RDKit 8
Stereochemical complexity RDKit 0.22
Number of sp hybridized carbon atoms RDKit 0
Number of sp2 hybridized carbon atoms RDKit 7
Number of sp3 hybridized carbon atoms RDKit 29
Shape complexity RDKit 0.81
Number of rotatable bonds RDKit 17
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 2
Number of saturated heterocycles RDKit 0
Number of saturated rings RDKit 2
Number of Smallest Set of Smallest Rings (SSSR) RDKit 4
Phorbol 12-myristate 13-acetate
Drug-likeness properties
Property nameToolProperty value
Number of Lipinski’s rule of 5 violations RDKit 2
Lipinski’s rule of 5 filter RDKit Failed
Number of Ghose filter violations RDKit 4
Ghose filter RDKit Failed
Veber filter RDKit Bad
Pfizer 3/75 filter RDKit Bad
GSK 4/400 filter RDKit Bad
Weighted quantitative estimate of drug-likeness (QEDw) score RDKit 0.1204
Phorbol 12-myristate 13-acetate
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 -5.41
Number of PAINS structural alerts SwissADME 0.0
Number of Brenk structural alerts SwissADME 2.0
CYP1A2 inhibitor SwissADME No
CYP2C19 inhibitor SwissADME No
CYP2C9 inhibitor SwissADME No
CYP2D6 inhibitor SwissADME No
CYP3A4 inhibitor SwissADME Yes
P-glycoprotein substrate SwissADME Yes
Phorbol 12-myristate 13-acetate
Predicted human target proteins
Protein identifierHGNC symbolCombined score from STITCH database
ENSP00000234111ODC1958
ENSP00000263431PRKCG913
ENSP00000293371DCD800
ENSP00000305355PRKCB974
ENSP00000306124PRKCE866
ENSP00000331602PRKCD778
ENSP00000356438PTGS2879
ENSP00000368727XDH800
ENSP00000408695PRKCA990
The human target proteins were predicted using STITCH, a database of Chemical-Protein interaction networks.