Record Information
Version1.0
Creation Date2016-09-30 23:23:02 UTC
Update Date2020-06-04 21:15:45 UTC
MCDB ID BMDB0006528
Secondary Accession Numbers
  • BMDB06528
Metabolite Identification
Common NameClupanodonic acid
DescriptionDocosapentaenoic acid (22N-3), also known as DPA or docosapentaenoate, belongs to the class of organic compounds known as very long-chain fatty acids. These are fatty acids with an aliphatic tail that contains at least 22 carbon atoms. Docosapentaenoic acid (22N-3) is a very hydrophobic molecule, practically insoluble (in water), and relatively neutral. Docosapentaenoic acid (22N-3) participates in a number of enzymatic reactions, within cattle. In particular, Docosapentaenoic acid (22N-3) can be biosynthesized from eicosapentaenoic acid through its interaction with the enzyme elongation OF very long chain fatty acids protein 5. In addition, Docosapentaenoic acid (22N-3) can be converted into tetracosapentaenoic acid (24:5N-3); which is catalyzed by the enzyme elongation OF very long chain fatty acids protein 4. In cattle, docosapentaenoic acid (22N-3) is involved in the metabolic pathway called the Alpha linolenic Acid and linoleic Acid metabolism pathway. Docosapentaenoic acid (22N-3) has been found to be associated with the diseases known as colorectal cancer; also docosapentaenoic acid (22n-3) has been linked to the inborn metabolic disorders including isovaleric acidemia.
Structure
Thumb
Synonyms
ValueSource
(7Z,10Z,13Z,16Z,19Z)-Docosa-7,10,13,16,19-pentaenoic acidChEBI
(all Z)-7,10,13,16,19-Docosapentaenoic acidChEBI
all-cis-7,10,13,16,19-Docosapentaenoic acidChEBI
cis-7,10,13,16,19-Docosapentaenoic acidChEBI
Clupanodonic acidChEBI
Docosa-7Z,10Z,13Z,16Z,19Z-pentaenoic acidChEBI
Docosapentaenoic acidChEBI
DPAChEBI
DPAn-3ChEBI
7Z,10Z,13Z,16Z,19Z-Docosapentaenoic acidKegg
(7Z,10Z,13Z,16Z,19Z)-Docosa-7,10,13,16,19-pentaenoateGenerator
(all Z)-7,10,13,16,19-DocosapentaenoateGenerator
all-cis-7,10,13,16,19-DocosapentaenoateGenerator
cis-7,10,13,16,19-DocosapentaenoateGenerator
ClupanodonateGenerator
Docosa-7Z,10Z,13Z,16Z,19Z-pentaenoateGenerator
DocosapentaenoateGenerator
7Z,10Z,13Z,16Z,19Z-DocosapentaenoateGenerator
Docosapentaenoate (22N-3)Generator
7,10,13,16,19-Docosapentaenoic acid, (all-Z)-isomerMeSH
Docosapentaenoic acid (C22:5 N3)MeSH
Osbond acidMeSH
(all-Z)-7, 10, 13, 16, 19-Docosapentaenoic acidMeSH
7,10,13,16,19-Docosapentaenoic acidMeSH
Docosapentaenoic acid, (all Z)-isomerMeSH
(7Z,10Z,13Z,16Z,19Z)-Docosa 7,10,13,16,19-pentaenoateHMDB
(7Z,10Z,13Z,16Z,19Z)-Docosa 7,10,13,16,19-pentaenoic acidHMDB
7,10,13,16,19-DocosapentaenoateHMDB
FA(22:5(7Z,10Z,13Z,16Z,19Z))HMDB
(7Z,10Z,13Z,16Z,19Z)-7,10,13,16,19-Docosapentaenoic acidHMDB
(all-Z)-7,10,13,16,19-Docosapentaenoic acidHMDB
FA(22:5n3)HMDB
delta7,10,13,16,19-Docosapentaenoic acidHMDB
omega3-Docosapentaenoic acidHMDB
Δ7,10,13,16,19-Docosapentaenoic acidHMDB
ω3-Docosapentaenoic acidHMDB
Chemical FormulaC22H34O2
Average Molecular Weight330.5042
Monoisotopic Molecular Weight330.255880332
IUPAC Name(7Z,10Z,13Z,16Z,19Z)-docosa-7,10,13,16,19-pentaenoic acid
Traditional Nameclupanodonic acid
CAS Registry Number24880-45-3
SMILES
CC\C=C/C\C=C/C\C=C/C\C=C/C\C=C/CCCCCC(O)=O
InChI Identifier
InChI=1S/C22H34O2/c1-2-3-4-5-6-7-8-9-10-11-12-13-14-15-16-17-18-19-20-21-22(23)24/h3-4,6-7,9-10,12-13,15-16H,2,5,8,11,14,17-21H2,1H3,(H,23,24)/b4-3-,7-6-,10-9-,13-12-,16-15-
InChI KeyYUFFSWGQGVEMMI-JLNKQSITSA-N
Chemical Taxonomy
Description belongs to the class of organic compounds known as very long-chain fatty acids. These are fatty acids with an aliphatic tail that contains at least 22 carbon atoms.
KingdomOrganic compounds
Super ClassLipids and lipid-like molecules
ClassFatty Acyls
Sub ClassFatty acids and conjugates
Direct ParentVery long-chain fatty acids
Alternative Parents
Substituents
  • Very long-chain fatty acid
  • Unsaturated fatty acid
  • Straight chain fatty acid
  • Monocarboxylic acid or derivatives
  • Carboxylic acid
  • Carboxylic acid derivative
  • Organic oxygen compound
  • Organic oxide
  • Hydrocarbon derivative
  • Organooxygen compound
  • Carbonyl group
  • Aliphatic acyclic compound
Molecular FrameworkAliphatic acyclic compounds
External Descriptors
Physical Properties
StateSolid
Experimental Properties
PropertyValueReference
Melting PointNot AvailableNot Available
Boiling PointNot AvailableNot Available
Water SolubilityNot AvailableNot Available
LogPNot AvailableNot Available
Predicted Properties
PropertyValueSource
logP7.08ALOGPS
logP7.11ChemAxon
logS-6.4ALOGPS
pKa (Strongest Acidic)4.96ChemAxon
Physiological Charge-1ChemAxon
Hydrogen Acceptor Count2ChemAxon
Hydrogen Donor Count1ChemAxon
Polar Surface Area37.3 ŲChemAxon
Rotatable Bond Count15ChemAxon
Refractivity110.27 m³·mol⁻¹ChemAxon
Polarizability40.1 ųChemAxon
Number of Rings0ChemAxon
Bioavailability0ChemAxon
Rule of FiveNoChemAxon
Ghose FilterNoChemAxon
Veber's RuleNoChemAxon
MDDR-like RuleNoChemAxon
Spectra
Spectrum TypeDescriptionSplash KeyDeposition DateView
Predicted GC-MSPredicted GC-MS Spectrum - GC-MS (Non-derivatized) - 70eV, Positivesplash10-004l-5491000000-56de363323dabc6f26e32017-09-01View Spectrum
Predicted GC-MSPredicted GC-MS Spectrum - GC-MS (1 TMS) - 70eV, Positivesplash10-009i-9583000000-943203f8659c9ab3cac42017-10-06View Spectrum
Predicted GC-MSPredicted GC-MS Spectrum - GC-MS (Non-derivatized) - 70eV, PositiveNot Available2021-10-12View Spectrum
LC-MS/MSLC-MS/MS Spectrum - LC-ESI-IT , negativesplash10-000i-0090000000-260dcf8cd2e9cacf0e812017-09-14View Spectrum
LC-MS/MSLC-MS/MS Spectrum - Linear Ion Trap , negativesplash10-000i-0090000000-b359128b4a9edc7dc9ca2017-09-14View Spectrum
LC-MS/MSLC-MS/MS Spectrum - Linear Ion Trap , positivesplash10-01x3-0492000000-89d3794a87bea421691b2017-09-14View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 10V, Positivesplash10-03di-0039000000-405cbfa338b34ddb74412017-09-01View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 20V, Positivesplash10-000i-5793000000-59855762e7bce0a8ec9d2017-09-01View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 40V, Positivesplash10-0avv-8970000000-49596865551dfe04eaa12017-09-01View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 10V, Negativesplash10-004i-0019000000-4d8832b1fd953fd8ec082017-09-01View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 20V, Negativesplash10-01ti-1039000000-f6df0e4a8ec7c01d99552017-09-01View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 40V, Negativesplash10-0a4l-9130000000-a69f7e9f82c75012f7282017-09-01View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 10V, Negativesplash10-004i-0009000000-f4bd181f9378195136602021-09-22View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 20V, Negativesplash10-01t9-1009000000-fd8104aee9b78a72f4db2021-09-22View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 40V, Negativesplash10-0006-9221000000-a71d2d6e07928441d5ef2021-09-22View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 10V, Positivesplash10-01q9-2329000000-918ad0c35d9079c18ee12021-09-23View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 20V, Positivesplash10-001i-4911000000-cca43fd70d0980b4845e2021-09-23View Spectrum
Predicted LC-MS/MSPredicted LC-MS/MS Spectrum - 40V, Positivesplash10-001i-9700000000-ca068d510d72f2bb000e2021-09-23View Spectrum
1D NMR13C NMR Spectrum (1D, 100 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR1H NMR Spectrum (1D, 100 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR13C NMR Spectrum (1D, 1000 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR1H NMR Spectrum (1D, 1000 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR13C NMR Spectrum (1D, 200 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR1H NMR Spectrum (1D, 200 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR13C NMR Spectrum (1D, 300 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR1H NMR Spectrum (1D, 300 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR13C NMR Spectrum (1D, 400 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR1H NMR Spectrum (1D, 400 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR13C NMR Spectrum (1D, 500 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR1H NMR Spectrum (1D, 500 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR13C NMR Spectrum (1D, 600 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR1H NMR Spectrum (1D, 600 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR13C NMR Spectrum (1D, 700 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR1H NMR Spectrum (1D, 700 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR13C NMR Spectrum (1D, 800 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR1H NMR Spectrum (1D, 800 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR13C NMR Spectrum (1D, 900 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
1D NMR1H NMR Spectrum (1D, 900 MHz, H2O, predicted)Not Available2022-08-20View Spectrum
Concentrations
StatusValueReferenceDetails
Detected and Quantified1028 +/- 424 uMTotal fatty acid
  • M. Ferrand et al....
details
Detected and Quantified878 +/- 303 uMTotal fatty acid
  • M. Ferrand et al....
details
HMDB IDHMDB0006528
DrugBank IDNot Available
Phenol Explorer Compound IDNot Available
FoodDB IDFDB021831
KNApSAcK IDC00052249
Chemspider ID4593750
KEGG Compound IDC16513
BioCyc IDCPD-13792
BiGG ID2218032
Wikipedia LinkDocosapentaenoic acid
METLIN ID194
PubChem Compound5497182
PDB IDNot Available
ChEBI ID53488
References
Synthesis ReferenceNot Available
Material Safety Data Sheet (MSDS)Not Available
General References
  1. Kurt J. Boudonck, Matthew W. Mitchell, Jacob Wulff and John A. Ryals (2009). Kurt J. Boudonck, Matthew W. Mitchell, Jacob Wulff and John A. Ryals. Characterization of the biochemical variability of bovine milk using metabolomics. Metabolomics (2009) 5:375?386. Metabolomics.
  2. M. Ferrand, B. Huquet. S. Barbey, F. Barillet, F. Faucon, H. Larroque, O. Leray, J.M. Trommenschlager, M. Brochard (2011). M. Ferrand et al. Determination of fatty acid profile in cow's milk using mid-infrared spectrometry: Interest of applying a variable selection by genetic algorithms before a PLS regression. Chemometrics and Intelligent Laboratory Systems 106 (2011) 183?189. Chemometrics and Intelligent Laboratory Systems.