Vildagliptin je organsko jedinjenje, koje sadrži 17 atoma ugljenika i ima molekulsku masu od 303,399 Da.[5][6][7]

Vildagliptin
Klinički podaci
AHFS/Drugs.com Monografija
Identifikatori
CAS broj 274901-16-5
ATC kod A10BH02
PubChem[1][2] 6918537
DrugBank DB04876
ChemSpider[3] 5293734
ChEMBL[4] CHEMBL142703 DaY
Hemijski podaci
Formula C17H25N3O2 
Mol. masa 303,399
SMILES eMolekuli & PubHem
Farmakokinetički podaci
Poluvreme eliminacije 90 minuta
Farmakoinformacioni podaci
Trudnoća ?
Pravni status

Osobine uredi

Osobina Vrednost
Broj akceptora vodonika 4
Broj donora vodonika 2
Broj rotacionih veza 3
Particioni koeficijent[8] (ALogP) 0,2
Rastvorljivost[9] (logS, log(mol/L)) -2,5
Polarna površina[10] (PSA, Å2) 76,4

Reference uredi

  1. Li Q, Cheng T, Wang Y, Bryant SH (2010). „PubChem as a public resource for drug discovery.”. Drug Discov Today 15 (23-24): 1052-7. DOI:10.1016/j.drudis.2010.10.003. PMID 20970519.  edit
  2. Evan E. Bolton, Yanli Wang, Paul A. Thiessen, Stephen H. Bryant (2008). „Chapter 12 PubChem: Integrated Platform of Small Molecules and Biological Activities”. Annual Reports in Computational Chemistry 4: 217-241. DOI:10.1016/S1574-1400(08)00012-1. 
  3. Hettne KM, Williams AJ, van Mulligen EM, Kleinjans J, Tkachenko V, Kors JA. (2010). „Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining”. J Cheminform 2 (1): 3. DOI:10.1186/1758-2946-2-3. PMID 20331846.  edit
  4. Gaulton A, Bellis LJ, Bento AP, Chambers J, Davies M, Hersey A, Light Y, McGlinchey S, Michalovich D, Al-Lazikani B, Overington JP. (2012). „ChEMBL: a large-scale bioactivity database for drug discovery”. Nucleic Acids Res 40 (Database issue): D1100-7. DOI:10.1093/nar/gkr777. PMID 21948594.  edit
  5. Balas B, Baig MR, Watson C, Dunning BE, Ligueros-Saylan M, Wang Y, He YL, Darland C, Holst JJ, Deacon CF, Cusi K, Mari A, Foley JE, DeFronzo RA: The dipeptidyl peptidase IV inhibitor vildagliptin suppresses endogenous glucose production and enhances islet function after single-dose administration in type 2 diabetic patients. J Clin Endocrinol Metab. 2007 Apr;92(4):1249-55. Epub 2007 Jan 23. PMID 17244786
  6. Knox C, Law V, Jewison T, Liu P, Ly S, Frolkis A, Pon A, Banco K, Mak C, Neveu V, Djoumbou Y, Eisner R, Guo AC, Wishart DS (2011). „DrugBank 3.0: a comprehensive resource for omics research on drugs”. Nucleic Acids Res. 39 (Database issue): D1035-41. DOI:10.1093/nar/gkq1126. PMC 3013709. PMID 21059682.  edit
  7. David S. Wishart, Craig Knox, An Chi Guo, Dean Cheng, Savita Shrivastava, Dan Tzur, Bijaya Gautam, and Murtaza Hassanali (2008). „DrugBank: a knowledgebase for drugs, drug actions and drug targets”. Nucleic Acids Res 36 (Database issue): D901-6. DOI:10.1093/nar/gkm958. PMC 2238889. PMID 18048412.  edit
  8. Ghose, A.K., Viswanadhan V.N., and Wendoloski, J.J. (1998). „Prediction of Hydrophobic (Lipophilic) Properties of Small Organic Molecules Using Fragment Methods: An Analysis of AlogP and CLogP Methods”. J. Phys. Chem. A 102: 3762-3772. DOI:10.1021/jp980230o. 
  9. Tetko IV, Tanchuk VY, Kasheva TN, Villa AE. (2001). „Estimation of Aqueous Solubility of Chemical Compounds Using E-State Indices”. Chem Inf. Comput. Sci. 41: 1488-1493. DOI:10.1021/ci000392t. PMID 11749573.  edit
  10. Ertl P., Rohde B., Selzer P. (2000). „Fast calculation of molecular polar surface area as a sum of fragment based contributions and its application to the prediction of drug transport properties”. J. Med. Chem. 43: 3714-3717. DOI:10.1021/jm000942e. PMID 11020286.  edit

Literatura uredi

Spoljašnje veze uredi