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Journal Abstract Search

327 related items for PubMed ID: 21707397

  • 41. QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.
    Votano JR, Parham M, Hall LM, Hall LH, Kier LB, Oloff S, Tropsha A.
    J Med Chem; 2006 Nov 30; 49(24):7169-81. PubMed ID: 17125269
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  • 42. Structure-based approach for the study of estrogen receptor binding affinity and subtype selectivity.
    Salum LB, Polikarpov I, Andricopulo AD.
    J Chem Inf Model; 2008 Nov 30; 48(11):2243-53. PubMed ID: 18937440
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  • 43. 3D-QSAR and molecular docking studies of selective agonists for the thyroid hormone receptor beta.
    Du J, Qin J, Liu H, Yao X.
    J Mol Graph Model; 2008 Sep 30; 27(2):95-104. PubMed ID: 18436460
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  • 44. Modeling the molecular basis for α4β1 integrin antagonism.
    Hutt OE, Saubern S, Winkler DA.
    Bioorg Med Chem; 2011 Oct 01; 19(19):5903-11. PubMed ID: 21889349
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  • 45. Structural basis for ligand recognition at the benzodiazepine binding site of GABAA alpha 3 receptor, and pharmacophore-based virtual screening approach.
    Vijayan RS, Ghoshal N.
    J Mol Graph Model; 2008 Oct 01; 27(3):286-98. PubMed ID: 18565775
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  • 46. Combined 3D-QSAR modeling and molecular docking study on quinoline derivatives as inhibitors of P-selectin.
    Zeng H, Cao R, Zhang H.
    Chem Biol Drug Des; 2009 Dec 01; 74(6):596-610. PubMed ID: 19843078
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  • 49. A 3D-QSAR-driven approach to binding mode and affinity prediction.
    Tosco P, Balle T.
    J Chem Inf Model; 2012 Feb 27; 52(2):302-7. PubMed ID: 22087561
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  • 50. Combined 3D QSAR and molecular docking studies to reveal novel cannabinoid ligands with optimum binding activity.
    Durdagi S, Papadopoulos MG, Papahatjis DP, Mavromoustakos T.
    Bioorg Med Chem Lett; 2007 Dec 15; 17(24):6754-63. PubMed ID: 17980589
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  • 52. Binding interaction analysis of the active site and its inhibitors for neuraminidase (N1 subtype) of human influenza virus by the integration of molecular docking, FMO calculation and 3D-QSAR CoMFA modeling.
    Zhang Q, Yang J, Liang K, Feng L, Li S, Wan J, Xu X, Yang G, Liu D, Yang S.
    J Chem Inf Model; 2008 Sep 15; 48(9):1802-12. PubMed ID: 18707092
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  • 54. Insight into the structural requirements of urokinase-type plasminogen activator inhibitors based on 3D QSAR CoMFA/CoMSIA models.
    Bhongade BA, Gadad AK.
    J Med Chem; 2006 Jan 26; 49(2):475-89. PubMed ID: 16420035
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  • 55. Predicting the Binding Affinity of ERβ Ligands Based on a Novel Variable Selection Method.
    Liu HY, Zhang F, Qin LT, Yi ZS, Wang XL, Mo LY.
    Interdiscip Sci; 2016 Dec 26; 8(4):412-418. PubMed ID: 26525889
    [Abstract] [Full Text] [Related]

  • 56. X-ray crystallographic structures as a source of ligand alignment in 3D-QSAR.
    Urniaż RD, Jóźwiak K.
    J Chem Inf Model; 2013 Jun 24; 53(6):1406-14. PubMed ID: 23705769
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  • 58. Target specific virtual screening: optimization of an estrogen receptor screening platform.
    Knox AJ, Meegan MJ, Sobolev V, Frost D, Zisterer DM, Williams DC, Lloyd DG.
    J Med Chem; 2007 Nov 01; 50(22):5301-10. PubMed ID: 17918820
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