Glibenklamid

Izvor: Wikipedija
(Preusmjereno sa stranice Gliburid)
Prijeđi na navigaciju Prijeđi na pretragu
Glibenklamid
Klinički podaci
Robne marke Abbenclamide, Adiab, Azuglucon, Bastiverit
AHFS/Drugs.com Monografija
Identifikatori
CAS broj 10238-21-8
ATC kod A10BB01
PubChem[1][2] 3488
DrugBank DB01016
ChemSpider[3] 3368
KEGG[4] C07022 DaY
ChEBI CHEBI:5441 DaY
ChEMBL[5] CHEMBL472 DaY
Hemijski podaci
Formula C23H28ClN3O5S 
Mol. masa 494,004
SMILES eMolekuli & PubHem
Fizički podaci
Tačka topljenja 169 °C (336 °F)
Farmakokinetički podaci
Poluvreme eliminacije 1,4-1,8 h
Izlučivanje Bilijarno, renalno
Farmakoinformacioni podaci
Trudnoća ?
Pravni status
Način primene Oralno

Glibenklamid je organsko jedinjenje, koje sadrži 23 atoma ugljenika i ima molekulsku masu od 494,004 Da.[6][7][8]

Osobine[uredi | uredi kod]

Osobina Vrednost
Broj akceptora vodonika 5
Broj donora vodonika 3
Broj rotacionih veza 8
Particioni koeficijent[9] (ALogP) 4,1
Rastvorljivost[10] (logS, log(mol/L)) -7,1
Polarna površina[11] (PSA, Å2) 122,0

Reference[uredi | uredi kod]

  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. Joanne Wixon, Douglas Kell (2000). „Website Review: The Kyoto Encyclopedia of Genes and Genomes — KEGG”. Yeast 17 (1): 48–55. DOI:10.1002/(SICI)1097-0061(200004)17:1<48::AID-YEA2>3.0.CO;2-H. 
  5. 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
  6. Monami M, Luzzi C, Lamanna C, Chiasserini V, Addante F, Desideri CM, Masotti G, Marchionni N, Mannucci E: Three-year mortality in diabetic patients treated with different combinations of insulin secretagogues and metformin. Diabetes Metab Res Rev. 2006 Nov-Dec;22(6):477-82. PMID 16634115
  7. 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
  8. 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
  9. 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. 
  10. 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
  11. 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 | uredi kod]

Spoljašnje veze[uredi | uredi kod]