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Journal Abstract Search

334 related items for PubMed ID: 18069986

  • 1. Atomic property fields: generalized 3D pharmacophoric potential for automated ligand superposition, pharmacophore elucidation and 3D QSAR.
    Totrov M.
    Chem Biol Drug Des; 2008 Jan; 71(1):15-27. PubMed ID: 18069986
    [Abstract] [Full Text] [Related]

  • 2. Flexible 3D pharmacophores as descriptors of dynamic biological space.
    Nettles JH, Jenkins JL, Williams C, Clark AM, Bender A, Deng Z, Davies JW, Glick M.
    J Mol Graph Model; 2007 Oct; 26(3):622-33. PubMed ID: 17395510
    [Abstract] [Full Text] [Related]

  • 3. Multiple field three dimensional quantitative structure-activity relationship (MF-3D-QSAR).
    Du QS, Huang RB, Wei YT, Du LQ, Chou KC.
    J Comput Chem; 2008 Jan 30; 29(2):211-9. PubMed ID: 17559075
    [Abstract] [Full Text] [Related]

  • 4. FLEXS: a method for fast flexible ligand superposition.
    Lemmen C, Lengauer T, Klebe G.
    J Med Chem; 1998 Nov 05; 41(23):4502-20. PubMed ID: 9804690
    [Abstract] [Full Text] [Related]

  • 5. Comparison of ligand-based and structure-based 3D-QSAR approaches: a case study on (aryl-)bridged 2-aminobenzonitriles inhibiting HIV-1 reverse transcriptase.
    Sciabola S, Carosati E, Baroni M, Mannhold R.
    J Med Chem; 2005 Jun 02; 48(11):3756-67. PubMed ID: 15916427
    [Abstract] [Full Text] [Related]

  • 6. Application of 3D-QSAR in the rational design of receptor ligands and enzyme inhibitors.
    Mor M, Rivara S, Lodola A, Lorenzi S, Bordi F, Plazzi PV, Spadoni G, Bedini A, Duranti A, Tontini A, Tarzia G.
    Chem Biodivers; 2005 Nov 02; 2(11):1438-51. PubMed ID: 17191945
    [Abstract] [Full Text] [Related]

  • 7. 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 02; 73(4):889-901. PubMed ID: 18536013
    [Abstract] [Full Text] [Related]

  • 8. Insights into ligand-elicited activation of human constitutive androstane receptor based on novel agonists and three-dimensional quantitative structure-activity relationship.
    Jyrkkärinne J, Windshügel B, Rönkkö T, Tervo AJ, Küblbeck J, Lahtela-Kakkonen M, Sippl W, Poso A, Honkakoski P.
    J Med Chem; 2008 Nov 27; 51(22):7181-92. PubMed ID: 18983136
    [Abstract] [Full Text] [Related]

  • 9. Pharmacophore-based 3D-QSAR of HIF-1 inhibitors.
    Chung JY, Pasha FA, Cho SJ, Won M, Lee JJ, Lee K.
    Arch Pharm Res; 2009 Mar 27; 32(3):317-23. PubMed ID: 19387572
    [Abstract] [Full Text] [Related]

  • 10. 3D-QSAR with the aid of pharmacophore search and docking-based alignments for farnesyltransferase inhibitors.
    Vaidya M, Weigt M, Wiese M.
    Eur J Med Chem; 2009 Oct 27; 44(10):4070-82. PubMed ID: 19515462
    [Abstract] [Full Text] [Related]

  • 11. Improving the quality of 3D-QSAR by using flexible-ligand receptor models.
    Pei J, Chen H, Liu Z, Han X, Wang Q, Shen B, Zhou J, Lai L.
    J Chem Inf Model; 2005 Oct 27; 45(6):1920-33. PubMed ID: 16309299
    [Abstract] [Full Text] [Related]

  • 12. Pharao: pharmacophore alignment and optimization.
    Taminau J, Thijs G, De Winter H.
    J Mol Graph Model; 2008 Sep 27; 27(2):161-9. PubMed ID: 18485770
    [Abstract] [Full Text] [Related]

  • 13. Novel DOCK clique driven 3D similarity database search tools for molecule shape matching and beyond: adding flexibility to the search for ligand kin.
    Good AC.
    J Mol Graph Model; 2007 Oct 27; 26(3):656-66. PubMed ID: 17482856
    [Abstract] [Full Text] [Related]

  • 14. Development and validation of AMANDA, a new algorithm for selecting highly relevant regions in Molecular Interaction Fields.
    Durán A, Martínez GC, Pastor M.
    J Chem Inf Model; 2008 Sep 27; 48(9):1813-23. PubMed ID: 18693718
    [Abstract] [Full Text] [Related]

  • 15. 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
    [Abstract] [Full Text] [Related]

  • 16. Structural analysis of carboline derivatives as inhibitors of MAPKAP K2 using 3D QSAR and docking studies.
    Nayana RS, Bommisetty SK, Singh K, Bairy SK, Nunna S, Pramod A, Muttineni R.
    J Chem Inf Model; 2009 Jan 15; 49(1):53-67. PubMed ID: 19119997
    [Abstract] [Full Text] [Related]

  • 17. Structure-based quantitative structure--activity relationship modeling of estrogen receptor β-ligands.
    Dong X, Hilliard SG, Zheng W.
    Future Med Chem; 2011 Jun 15; 3(8):933-45. PubMed ID: 21707397
    [Abstract] [Full Text] [Related]

  • 18. 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
    [Abstract] [Full Text] [Related]

  • 19. 3D-QSAR based on quantum-chemical molecular fields: toward an improved description of halogen interactions.
    Güssregen S, Matter H, Hessler G, Müller M, Schmidt F, Clark T.
    J Chem Inf Model; 2012 Sep 24; 52(9):2441-53. PubMed ID: 22917472
    [Abstract] [Full Text] [Related]

  • 20. Grid-based Continual Analysis of Molecular Interior for Drug Discovery, QSAR and QSPR.
    Potemkin AV, Grishina MA, Potemkin VA.
    Curr Drug Discov Technol; 2017 Sep 24; 14(3):181-205. PubMed ID: 28176631
    [Abstract] [Full Text] [Related]

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