These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

178 related items for PubMed ID: 17644015

  • 1.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 2. A virtual screening approach for thymidine monophosphate kinase inhibitors as antitubercular agents based on docking and pharmacophore models.
    Gopalakrishnan B, Aparna V, Jeevan J, Ravi M, Desiraju GR.
    J Chem Inf Model; 2005; 45(4):1101-8. PubMed ID: 16045305
    [Abstract] [Full Text] [Related]

  • 3.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 4. Virtual screening of cathepsin k inhibitors using docking and pharmacophore models.
    Ravikumar M, Pavan S, Bairy S, Pramod AB, Sumakanth M, Kishore M, Sumithra T.
    Chem Biol Drug Des; 2008 Jul; 72(1):79-90. PubMed ID: 18498326
    [Abstract] [Full Text] [Related]

  • 5. Identification of potential glycogen kinase-3 inhibitors by structure based virtual screening.
    Dessalew N, Bharatam PV.
    Biophys Chem; 2007 Jul; 128(2-3):165-75. PubMed ID: 17482749
    [Abstract] [Full Text] [Related]

  • 6. Multiple pharmacophore models combined with molecular docking: a reliable way for efficiently identifying novel PDE4 inhibitors with high structural diversity.
    Chen Z, Tian G, Wang Z, Jiang H, Shen J, Zhu W.
    J Chem Inf Model; 2010 Apr 26; 50(4):615-25. PubMed ID: 20353193
    [Abstract] [Full Text] [Related]

  • 7. Pharmacophore modeling and virtual screening studies to design some potential histone deacetylase inhibitors as new leads.
    Vadivelan S, Sinha BN, Rambabu G, Boppana K, Jagarlapudi SA.
    J Mol Graph Model; 2008 Feb 26; 26(6):935-46. PubMed ID: 17707666
    [Abstract] [Full Text] [Related]

  • 8. Pharmacophore identification, in silico screening, and virtual library design for inhibitors of the human factor Xa.
    Krovat EM, Frühwirth KH, Langer T.
    J Chem Inf Model; 2005 Feb 26; 45(1):146-59. PubMed ID: 15667140
    [Abstract] [Full Text] [Related]

  • 9. Pharmacophore-based virtual screening and docking studies on Hsp90 inhibitors.
    Saxena S, Chaudhaery SS, Varshney K, Saxena AK.
    SAR QSAR Environ Res; 2010 Jul 26; 21(5-6):445-62. PubMed ID: 20818581
    [Abstract] [Full Text] [Related]

  • 10. Ligand-based designing, in silico screening, and biological evaluation of new potent fructose-1,6-bisphosphatase (FBPase) inhibitors.
    Tayyem RF, Zalloum HM, Elmaghrabi MR, Yousef AM, Mubarak MS.
    Eur J Med Chem; 2012 Oct 26; 56():70-95. PubMed ID: 22960695
    [Abstract] [Full Text] [Related]

  • 11. Strategies for generating less toxic P-selectin inhibitors: pharmacophore modeling, virtual screening and counter pharmacophore screening to remove toxic hits.
    Ananthula RS, Ravikumar M, Pramod AB, Madala KK, Mahmood SK.
    J Mol Graph Model; 2008 Nov 26; 27(4):546-57. PubMed ID: 18993099
    [Abstract] [Full Text] [Related]

  • 12. Discovery of potential ZAP-70 kinase inhibitors: pharmacophore design, database screening and docking studies.
    Sanam R, Vadivelan S, Tajne S, Narasu L, Rambabu G, Jagarlapudi SA.
    Eur J Med Chem; 2009 Dec 26; 44(12):4793-800. PubMed ID: 19674816
    [Abstract] [Full Text] [Related]

  • 13. Structure-based virtual screening approach to identify novel classes of Cdc25B phosphatase inhibitors.
    Park H, Li M, Choi J, Cho H, Ham SW.
    Bioorg Med Chem Lett; 2009 Aug 01; 19(15):4372-5. PubMed ID: 19500977
    [Abstract] [Full Text] [Related]

  • 14. Discovery of novel cathepsin S inhibitors by pharmacophore-based virtual high-throughput screening.
    Markt P, McGoohan C, Walker B, Kirchmair J, Feldmann C, De Martino G, Spitzer G, Distinto S, Schuster D, Wolber G, Laggner C, Langer T.
    J Chem Inf Model; 2008 Aug 01; 48(8):1693-705. PubMed ID: 18637674
    [Abstract] [Full Text] [Related]

  • 15. Pharmacophore modeling, virtual screening, molecular docking studies and density functional theory approaches to identify novel ketohexokinase (KHK) inhibitors.
    Kavitha R, Karunagaran S, Chandrabose SS, Lee KW, Meganathan C.
    Biosystems; 2015 Dec 01; 138():39-52. PubMed ID: 26521124
    [Abstract] [Full Text] [Related]

  • 16. In silico screening of a novel scaffold for fructose-1,6-bisphosatase (FBPase) inhibitors.
    Huang Y, Chi B, Xu Y, Song R, Wei L, Rao L, Feng L, Ren Y, Wan J.
    J Mol Graph Model; 2019 Jan 01; 86():142-148. PubMed ID: 30366190
    [Abstract] [Full Text] [Related]

  • 17. Crystallographic study of inhibitors of tRNA-guanine transglycosylase suggests a new structure-based pharmacophore for virtual screening.
    Brenk R, Meyer EA, Reuter K, Stubbs MT, Garcia GA, Diederich F, Klebe G.
    J Mol Biol; 2004 Apr 16; 338(1):55-75. PubMed ID: 15050823
    [Abstract] [Full Text] [Related]

  • 18. Structure-guided design of AMP mimics that inhibit fructose-1,6-bisphosphatase with high affinity and specificity.
    Erion MD, Dang Q, Reddy MR, Kasibhatla SR, Huang J, Lipscomb WN, van Poelje PD.
    J Am Chem Soc; 2007 Dec 19; 129(50):15480-90. PubMed ID: 18041833
    [Abstract] [Full Text] [Related]

  • 19. Fuzzy pharmacophore models from molecular alignments for correlation-vector-based virtual screening.
    Renner S, Schneider G.
    J Med Chem; 2004 Sep 09; 47(19):4653-64. PubMed ID: 15341481
    [Abstract] [Full Text] [Related]

  • 20. The discovery of novel vascular endothelial growth factor receptor tyrosine kinases inhibitors: pharmacophore modeling, virtual screening and docking studies.
    Yu H, Wang Z, Zhang L, Zhang J, Huang Q.
    Chem Biol Drug Des; 2007 Mar 09; 69(3):204-11. PubMed ID: 17441906
    [Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 9.