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Metilprednisolon

Izvor: Wikipedija
Metilprednisolon
Klinički podaci
Robne marke Artisone-Wyeth, Besonia, Dopomedrol, Esametone
AHFS/Drugs.com Monografija
Identifikatori
CAS broj 83-43-2
ATC kod D07AA01 , H02AB04
PubChem[1][2] 6741
DrugBank DB00959
ChemSpider[3] 6485
ChEBI CHEBI:6888 DaY
ChEMBL[4] CHEMBL650 DaY
Hemijski podaci
Formula C22H30O5 
Mol. masa 374,471
SMILES eMolekuli & PubHem
Fizički podaci
Tačka topljenja 232.5 °C (451 °F)
Farmakokinetički podaci
Poluvreme eliminacije 1-3 h
Farmakoinformacioni podaci
Trudnoća ?
Pravni status
Način primene Intramaskularno, intravenozno, oralno

Metilprednisolon je organsko jedinjenje, koje sadrži 22 atoma ugljenika i ima molekulsku masu od 374,471 Da.[5][6][7]

Osobine

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Osobina Vrednost
Broj akceptora vodonika 5
Broj donora vodonika 3
Broj rotacionih veza 2
Particioni koeficijent[8] (ALogP) 1,5
Rastvorljivost[9] (logS, log(mol/L)) -3,6
Polarna površina[10] (PSA, Å2) 94,8

Reference

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  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. Sloka JS, Stefanelli M: The mechanism of action of methylprednisolone in the treatment of multiple sclerosis. Mult Scler. 2005 Aug;11(4):425-32. PMID 16042225
  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. 
  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. 
  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. 
  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. 

Literatura

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Spoljašnje veze

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