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Journal Abstract Search

105 related items for PubMed ID: 11297451

  • 1.
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  • 2. Binding affinities for sulfonamide inhibitors with human thrombin using Monte Carlo simulations with a linear response method.
    Jones-Hertzog DK, Jorgensen WL.
    J Med Chem; 1997 May 09; 40(10):1539-49. PubMed ID: 9154975
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  • 5. Prediction of binding affinities for TIBO inhibitors of HIV-1 reverse transcriptase using Monte Carlo simulations in a linear response method.
    Smith RH, Jorgensen WL, Tirado-Rives J, Lamb ML, Janssen PA, Michejda CJ, Kroeger Smith MB.
    J Med Chem; 1998 Dec 17; 41(26):5272-86. PubMed ID: 9857095
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  • 6. Prediction of activity for nonnucleoside inhibitors with HIV-1 reverse transcriptase based on Monte Carlo simulations.
    Rizzo RC, Udier-Blagović M, Wang DP, Watkins EK, Kroeger Smith MB, Smith RH, Tirado-Rives J, Jorgensen WL.
    J Med Chem; 2002 Jul 04; 45(14):2970-87. PubMed ID: 12086483
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  • 7. A novel serine protease inhibition motif involving a multi-centered short hydrogen bonding network at the active site.
    Katz BA, Elrod K, Luong C, Rice MJ, Mackman RL, Sprengeler PA, Spencer J, Hataye J, Janc J, Link J, Litvak J, Rai R, Rice K, Sideris S, Verner E, Young W.
    J Mol Biol; 2001 Apr 13; 307(5):1451-86. PubMed ID: 11292354
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  • 8. Estimation of the binding affinities of FKBP12 inhibitors using a linear response method.
    Lamb ML, Tirado-Rives J, Jorgensen WL.
    Bioorg Med Chem; 1999 May 13; 7(5):851-60. PubMed ID: 10400338
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  • 9. Molecular modeling calculations of HIV-1 reverse transcriptase nonnucleoside inhibitors: correlation of binding energy with biological activity for novel 2-aryl-substituted benzimidazole analogues.
    Kroeger Smith MB, Hose BM, Hawkins A, Lipchock J, Farnsworth DW, Rizzo RC, Tirado-Rives J, Arnold E, Zhang W, Hughes SH, Jorgensen WL, Michejda CJ, Smith RH.
    J Med Chem; 2003 May 08; 46(10):1940-7. PubMed ID: 12723956
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  • 10. General model for estimation of the inhibition of protein kinases using Monte Carlo simulations.
    Tominaga Y, Jorgensen WL.
    J Med Chem; 2004 May 06; 47(10):2534-49. PubMed ID: 15115396
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  • 12. Profiling the structural determinants for the selectivity of representative factor-Xa and thrombin inhibitors using combined ligand-based and structure-based approaches.
    Bhunia SS, Roy KK, Saxena AK.
    J Chem Inf Model; 2011 Aug 22; 51(8):1966-85. PubMed ID: 21761917
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  • 13. Investigations of neurotrophic inhibitors of FK506 binding protein via Monte Carlo simulations.
    Lamb ML, Jorgensen WL.
    J Med Chem; 1998 Oct 08; 41(21):3928-39. PubMed ID: 9767630
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  • 14. Think twice: understanding the high potency of bis(phenyl)methane inhibitors of thrombin.
    Baum B, Muley L, Heine A, Smolinski M, Hangauer D, Klebe G.
    J Mol Biol; 2009 Aug 21; 391(3):552-64. PubMed ID: 19520086
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  • 15. The crystal structures of human alpha-thrombin complexed with active site-directed diamino benzo[b]thiophene derivatives: a binding mode for a structurally novel class of inhibitors.
    Chirgadze NY, Sall DJ, Briggs SL, Clawson DK, Zhang M, Smith GF, Schevitz RW.
    Protein Sci; 2000 Jan 21; 9(1):29-36. PubMed ID: 10739244
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  • 19. A thermodynamic characterization of the binding of thrombin inhibitors to human thrombin, combining biosensor technology, stopped-flow spectrophotometry, and microcalorimetry.
    Deinum J, Gustavsson L, Gyzander E, Kullman-Magnusson M, Edström A, Karlsson R.
    Anal Biochem; 2002 Jan 15; 300(2):152-62. PubMed ID: 11779106
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  • 20. E-novo: an automated workflow for efficient structure-based lead optimization.
    Pearce BC, Langley DR, Kang J, Huang H, Kulkarni A.
    J Chem Inf Model; 2009 Jul 15; 49(7):1797-809. PubMed ID: 19552372
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