BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

114 related articles for article (PubMed ID: 17381179)

  • 1. eHiTS-to-VMD interface application. The search for tyrosine-tRNA ligase inhibitors.
    Eitner K; Gaweda T; Hoffmann M; Jura M; Rychlewski L; Barciszewski J
    J Chem Inf Model; 2007; 47(2):695-702. PubMed ID: 17381179
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Computational approaches for predicting CYP-related metabolism properties in the screening of new drugs.
    Crivori P; Poggesi I
    Eur J Med Chem; 2006 Jul; 41(7):795-808. PubMed ID: 16644065
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Analysis of a high-throughput screening data set using potency-scaled molecular similarity algorithms.
    Vogt I; Bajorath J
    J Chem Inf Model; 2007; 47(2):367-75. PubMed ID: 17300172
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Evaluation of virtual screening as a tool for chemical genetic applications.
    Campagna-Slater V; Schapira M
    J Chem Inf Model; 2009 Sep; 49(9):2082-91. PubMed ID: 19702241
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Structure-based virtual screening approach to identify novel classes of PTP1B inhibitors.
    Park H; Bhattarai BR; Ham SW; Cho H
    Eur J Med Chem; 2009 Aug; 44(8):3280-4. PubMed ID: 19269068
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Fast and efficient in silico 3D screening: toward maximum computational efficiency of pharmacophore-based and shape-based approaches.
    Kirchmair J; Ristic S; Eder K; Markt P; Wolber G; Laggner C; Langer T
    J Chem Inf Model; 2007; 47(6):2182-96. PubMed ID: 17929799
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Discovery of potent thermolysin inhibitors using structure based virtual screening and binding assays.
    Khan MT; Fuskevåg OM; Sylte I
    J Med Chem; 2009 Jan; 52(1):48-61. PubMed ID: 19072688
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Design of new plasmepsin inhibitors: a virtual high throughput screening approach on the EGEE grid.
    Kasam V; Zimmermann M; Maass A; Schwichtenberg H; Wolf A; Jacq N; Breton V; Hofmann-Apitius M
    J Chem Inf Model; 2007; 47(5):1818-28. PubMed ID: 17727268
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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; 48(8):1693-705. PubMed ID: 18637674
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Pursuing aldose reductase inhibitors through in situ cross-docking and similarity-based virtual screening.
    Cosconati S; Marinelli L; La Motta C; Sartini S; Da Settimo F; Olson AJ; Novellino E
    J Med Chem; 2009 Sep; 52(18):5578-81. PubMed ID: 19719141
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Pharmacophore-based virtual screening: the discovery of novel methionyl-tRNA synthetase inhibitors.
    Kim SY; Lee YS; Kang T; Kim S; Lee J
    Bioorg Med Chem Lett; 2006 Sep; 16(18):4898-907. PubMed ID: 16824759
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Virtual screening to enrich hit lists from high-throughput screening: a case study on small-molecule inhibitors of angiogenin.
    Jenkins JL; Kao RY; Shapiro R
    Proteins; 2003 Jan; 50(1):81-93. PubMed ID: 12471601
    [TBL] [Abstract][Full Text] [Related]  

  • 13. In silico chemical library screening and experimental validation of a novel 9-aminoacridine based lead-inhibitor of human S-adenosylmethionine decarboxylase.
    Brooks WH; McCloskey DE; Daniel KG; Ealick SE; Secrist JA; Waud WR; Pegg AE; Guida WC
    J Chem Inf Model; 2007; 47(5):1897-905. PubMed ID: 17676832
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Virtual high-throughput screening of molecular databases.
    Seifert MH; Kraus J; Kramer B
    Curr Opin Drug Discov Devel; 2007 May; 10(3):298-307. PubMed ID: 17554856
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Structure-based approach to pharmacophore identification, in silico screening, and three-dimensional quantitative structure-activity relationship studies for inhibitors of Trypanosoma cruzi dihydrofolate reductase function.
    Schormann N; Senkovich O; Walker K; Wright DL; Anderson AC; Rosowsky A; Ananthan S; Shinkre B; Velu S; Chattopadhyay D
    Proteins; 2008 Dec; 73(4):889-901. PubMed ID: 18536013
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Identification of novel inhibitors of methionyl-tRNA synthetase (MetRS) by virtual screening.
    Finn J; Stidham M; Hilgers M; G C K
    Bioorg Med Chem Lett; 2008 Jul; 18(14):3932-7. PubMed ID: 18590962
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Calculating the probability of detection for inhibitors in enzymatic or binding reactions in high-throughput screening.
    Buxser S; Vroegop S
    Anal Biochem; 2005 May; 340(1):1-13. PubMed ID: 15802124
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Scoring ligand similarity in structure-based virtual screening.
    Zavodszky MI; Rohatgi A; Van Voorst JR; Yan H; Kuhn LA
    J Mol Recognit; 2009; 22(4):280-92. PubMed ID: 19235177
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Inhibitors of bacterial tyrosyl tRNA synthetase: synthesis of carbocyclic analogues of the natural product SB-219383.
    Jarvest RL; Berge JM; Houge-Frydrych CS; Mensah LM; O'Hanlon PJ; Pope AJ
    Bioorg Med Chem Lett; 2001 Sep; 11(18):2499-502. PubMed ID: 11549455
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Identification of ellagic acid as potent inhibitor of protein kinase CK2: a successful example of a virtual screening application.
    Cozza G; Bonvini P; Zorzi E; Poletto G; Pagano MA; Sarno S; Donella-Deana A; Zagotto G; Rosolen A; Pinna LA; Meggio F; Moro S
    J Med Chem; 2006 Apr; 49(8):2363-6. PubMed ID: 16610779
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.