1.0 2016-09-30 22:49:25 UTC 2020-06-04 20:33:27 UTC BMDB0001976 BMDB01976 Docosapentaenoic acid Docosapentaenoic acid, also known as 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 is a very hydrophobic molecule, practically insoluble (in water), and relatively neutral. In cattle, docosapentaenoic acid is involved in the metabolic pathway called the Alpha linolenic Acid and linoleic Acid metabolism pathway. Docosapentaenoate C22H34O2 330.512 330.255880335 (2E,4E,6E,8E,10E)-docosa-2,4,6,8,10-pentaenoic acid docosapentaenoic acid [H]\C(CCCCCCCCCCC)=C(\[H])/C(/[H])=C(\[H])/C(/[H])=C(\[H])/C(/[H])=C(\[H])/C(/[H])=C(\[H])C(O)=O 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/h12-21H,2-11H2,1H3,(H,23,24)/b13-12+,15-14+,17-16+,19-18+,21-20+ YEKFYCQGYMVFKR-MBFZXKRTSA-N 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. Organic compounds Lipids and lipid-like molecules Fatty Acyls Fatty acids and conjugates Very long-chain fatty acids Carbonyl compounds Carboxylic acids Hydrocarbon derivatives Monocarboxylic acids and derivatives Organic oxides Straight chain fatty acids Unsaturated fatty acids Aliphatic acyclic compound Carbonyl group Carboxylic acid Carboxylic acid derivative Hydrocarbon derivative Monocarboxylic acid or derivatives Organic oxide Organic oxygen compound Organooxygen compound Straight chain fatty acid Unsaturated fatty acid Very long-chain fatty acid Aliphatic acyclic compounds Docosanoids Solid logp 7.80 ALOGPS logs -6.90 ALOGPS logp 7.47 ChemAxon pka_strongest_acidic 4.88 ChemAxon iupac (2E,4E,6E,8E,10E)-docosa-2,4,6,8,10-pentaenoic acid ChemAxon average_mass 330.512 ChemAxon mono_mass 330.255880335 ChemAxon smiles [H]\C(CCCCCCCCCCC)=C(\[H])/C(/[H])=C(\[H])/C(/[H])=C(\[H])/C(/[H])=C(\[H])/C(/[H])=C(\[H])C(O)=O ChemAxon formula C22H34O2 ChemAxon inchi 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/h12-21H,2-11H2,1H3,(H,23,24)/b13-12+,15-14+,17-16+,19-18+,21-20+ ChemAxon inchikey YEKFYCQGYMVFKR-MBFZXKRTSA-N ChemAxon polar_surface_area 37.3 ChemAxon refractivity 110.25 ChemAxon polarizability 43.77 ChemAxon rotatable_bond_count 15 ChemAxon acceptor_count 2 ChemAxon donor_count 1 ChemAxon physiological_charge -1 ChemAxon formal_charge 0 ChemAxon number_of_rings 0 ChemAxon bioavailability 0 ChemAxon rule_of_five Yes ChemAxon ghose_filter Yes ChemAxon veber_rule Yes ChemAxon mddr_like_rule Yes ChemAxon Specdb::MsMs 1261402 Specdb::MsMs 1261403 Specdb::MsMs 1261404 Specdb::MsMs 1376518 Specdb::MsMs 1376519 Specdb::MsMs 1376520 Adipose Tissue Cull beef cows fed barley silage diet for 12 weeks He ML, McAllister TA, Kastelic JP, Mir PS, Aalhus JL, Dugan ME, Aldai N, McKinnon JJ: Feeding flaxseed in grass hay and barley silage diets to beef cows increases alpha-linolenic acid and its biohydrogenation intermediates in subcutaneous fat. J Anim Sci. 2012 Feb;90(2):592-604. doi: 10.2527/jas.2011-4281. 22274861 Adipose Tissue Cull beef cows fed barley silage diet with flaxseed for 12 weeks He ML, McAllister TA, Kastelic JP, Mir PS, Aalhus JL, Dugan ME, Aldai N, McKinnon JJ: Feeding flaxseed in grass hay and barley silage diets to beef cows increases alpha-linolenic acid and its biohydrogenation intermediates in subcutaneous fat. J Anim Sci. 2012 Feb;90(2):592-604. doi: 10.2527/jas.2011-4281. 22274861 Adipose Tissue Cull beef cows fed hay for 12 weeks He ML, McAllister TA, Kastelic JP, Mir PS, Aalhus JL, Dugan ME, Aldai N, McKinnon JJ: Feeding flaxseed in grass hay and barley silage diets to beef cows increases alpha-linolenic acid and its biohydrogenation intermediates in subcutaneous fat. J Anim Sci. 2012 Feb;90(2):592-604. doi: 10.2527/jas.2011-4281. 22274861 Adipose Tissue Cull beef cows fed hay with flaxseed for 12 weeks He ML, McAllister TA, Kastelic JP, Mir PS, Aalhus JL, Dugan ME, Aldai N, McKinnon JJ: Feeding flaxseed in grass hay and barley silage diets to beef cows increases alpha-linolenic acid and its biohydrogenation intermediates in subcutaneous fat. J Anim Sci. 2012 Feb;90(2):592-604. doi: 10.2527/jas.2011-4281. 22274861 Fibroblasts Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089. 29140435 Liver Metabolomics analysis was performed using GC-MS/LC-MS in multiparous Holstein dairy cows Shahzad K, Lopreiato V, Liang Y, Trevisi E, Osorio JS, Xu C, Loor JJ: Hepatic metabolomics and transcriptomics to study susceptibility to ketosis in response to prepartal nutritional management. J Anim Sci Biotechnol. 2019 Dec 18;10:96. doi: 10.1186/s40104-019-0404-z. eCollection 2019. 31867104 Milk Commercial, conventional whole milk Kurt J. Boudonck, Matthew W. Mitchell, Jacob Wulff, John A. Ryals. Characterization of the biochemical variability of bovine milk using metabolomics. Metabolomics (2009) 5:375-386 doi: 10.1007/s11306-009-0160-8 Milk 2390.289 +/- 574.880 uM The samples were collected from crossbred Holstein × Normande dairy cows, Montbéliarde cattles and Prim'Holstein. The fat content was estimated by MIR spectrometry. This the calibration set of samples 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 Milk 2269.261 +/- 484.109 uM The samples were collected from crossbred Holstein × Normande dairy cows, Montbéliarde cattles and Prim'Holstein. The fat content was estimated by MIR spectrometry. This the validation set of samples 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 Muscle Samples have been collected from Heifer cows. Osorio MT, Downey G, Moloney AP, Rohrle FT, Luciano G, Schmidt O, Monahan FJ: Beef authentication using dietary markers: chemometric selection and modelling of significant beef biomarkers using concatenated data from multiple analytical methods. Food Chem. 2013 Dec 1;141(3):2795-801. doi: 10.1016/j.foodchem.2013.05.118. Epub 2013 Jun 5. 23871026 Oocyte Detected by CP9010 autosampler onto a capillary column within a CP9001 gas chromatograph in slaughtered cow ovaries. McEvoy TG, Coull GD, Broadbent PJ, Hutchinson JS, Speake BK: Fatty acid composition of lipids in immature cattle, pig and sheep oocytes with intact zona pellucida. J Reprod Fertil. 2000 Jan;118(1):163-70. 10793638 Platelet Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vazquez-Fresno R, Sajed T, Johnson D, Li C, Karu N, Sayeeda Z, Lo E, Assempour N, Berjanskii M, Singhal S, Arndt D, Liang Y, Badran H, Grant J, Serra-Cayuela A, Liu Y, Mandal R, Neveu V, Pon A, Knox C, Wilson M, Manach C, Scalbert A: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 2018 Jan 4;46(D1):D608-D617. doi: 10.1093/nar/gkx1089. 29140435 6438348 Docosapentaenoic acid Glasser F, Ferlay A, Chilliard Y: Oilseed lipid supplements and fatty acid composition of cow milk: a meta-analysis. J Dairy Sci. 2008 Dec;91(12):4687-703. doi: 10.3168/jds.2008-0987. 19038946 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 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