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Journal Abstract Search

241 related items for PubMed ID: 12213058

  • 1. DrugScore meets CoMFA: adaptation of fields for molecular comparison (AFMoC) or how to tailor knowledge-based pair-potentials to a particular protein.
    Gohlke H, Klebe G.
    J Med Chem; 2002 Sep 12; 45(19):4153-70. PubMed ID: 12213058
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  • 2. New approach to pharmacophore mapping and QSAR analysis using inductive logic programming. Application to thermolysin inhibitors and glycogen phosphorylase B inhibitors.
    Marchand-Geneste N, Watson KA, Alsberg BK, King RD.
    J Med Chem; 2002 Jan 17; 45(2):399-409. PubMed ID: 11784144
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  • 3. AFMoC enhances predictivity of 3D QSAR: a case study with DOXP-reductoisomerase.
    Silber K, Heidler P, Kurz T, Klebe G.
    J Med Chem; 2005 May 19; 48(10):3547-63. PubMed ID: 15887963
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  • 4. Improving binding mode predictions by docking into protein-specifically adapted potential fields.
    Radestock S, Böhm M, Gohlke H.
    J Med Chem; 2005 Aug 25; 48(17):5466-79. PubMed ID: 16107145
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  • 5. DrugScore(CSD)-knowledge-based scoring function derived from small molecule crystal data with superior recognition rate of near-native ligand poses and better affinity prediction.
    Velec HF, Gohlke H, Klebe G.
    J Med Chem; 2005 Oct 06; 48(20):6296-303. PubMed ID: 16190756
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  • 6. Three-dimensional quantitative structure-activity relationship of angiotesin-converting enzyme and thermolysin inhibitors. II. A comparison of CoMFA models incorporating molecular orbital fields and desolvation free energies based on active-analog and complementary-receptor-field alignment rules.
    Waller CL, Marshall GR.
    J Med Chem; 1993 Aug 06; 36(16):2390-403. PubMed ID: 8360884
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  • 12. Consensus adaptation of fields for molecular comparison (AFMoC) models incorporate ligand and receptor conformational variability into tailor-made scoring functions.
    Breu B, Silber K, Gohlke H.
    J Chem Inf Model; 2007 Aug 06; 47(6):2383-400. PubMed ID: 17958410
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  • 13. Effects of variable docking conditions and scoring functions on corresponding protein-aligned comparative molecular field analysis models constructed from diverse human protein tyrosine phosphatase 1B inhibitors.
    Taha MO, AlDamen MA.
    J Med Chem; 2005 Dec 15; 48(25):8016-34. PubMed ID: 16335926
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  • 17. Receptor-based 3D QSAR analysis of estrogen receptor ligands--merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods.
    Sippl W.
    J Comput Aided Mol Des; 2000 Aug 15; 14(6):559-72. PubMed ID: 10921772
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  • 18. Evaluation of designed ligands by a multiple screening method: application to glycogen phosphorylase inhibitors constructed with a variety of approaches.
    So SS, Karplus M.
    J Comput Aided Mol Des; 2001 Jul 15; 15(7):613-47. PubMed ID: 11688944
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  • 20. 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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