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Journal Abstract Search

191 related items for PubMed ID: 30563339

  • 1. All in One: Cavity Detection, Druggability Estimate, Cavity-Based Pharmacophore Perception, and Virtual Screening.
    Tran-Nguyen VK, Da Silva F, Bret G, Rognan D.
    J Chem Inf Model; 2019 Jan 28; 59(1):573-585. PubMed ID: 30563339
    [Abstract] [Full Text] [Related]

  • 2. Cosolvent-Based Protein Pharmacophore for Ligand Enrichment in Virtual Screening.
    Arcon JP, Defelipe LA, Lopez ED, Burastero O, Modenutti CP, Barril X, Marti MA, Turjanski AG.
    J Chem Inf Model; 2019 Aug 26; 59(8):3572-3583. PubMed ID: 31373819
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  • 3. Novel approach for efficient pharmacophore-based virtual screening: method and applications.
    Dror O, Schneidman-Duhovny D, Inbar Y, Nussinov R, Wolfson HJ.
    J Chem Inf Model; 2009 Oct 26; 49(10):2333-43. PubMed ID: 19803502
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  • 4. Comparison and druggability prediction of protein-ligand binding sites from pharmacophore-annotated cavity shapes.
    Desaphy J, Azdimousa K, Kellenberger E, Rognan D.
    J Chem Inf Model; 2012 Aug 27; 52(8):2287-99. PubMed ID: 22834646
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  • 5. Efficient virtual screening using multiple protein conformations described as negative images of the ligand-binding site.
    Virtanen SI, Pentikäinen OT.
    J Chem Inf Model; 2010 Jun 28; 50(6):1005-11. PubMed ID: 20504004
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  • 8. Beware of machine learning-based scoring functions-on the danger of developing black boxes.
    Gabel J, Desaphy J, Rognan D.
    J Chem Inf Model; 2014 Oct 27; 54(10):2807-15. PubMed ID: 25207678
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  • 11. LS-align: an atom-level, flexible ligand structural alignment algorithm for high-throughput virtual screening.
    Hu J, Liu Z, Yu DJ, Zhang Y.
    Bioinformatics; 2018 Jul 01; 34(13):2209-2218. PubMed ID: 29462237
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  • 14. Structure-Based Virtual Screening.
    Li Q, Shah S.
    Methods Mol Biol; 2017 Jul 01; 1558():111-124. PubMed ID: 28150235
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  • 15. Ligand efficiency based approach for efficient virtual screening of compound libraries.
    Ke YY, Coumar MS, Shiao HY, Wang WC, Chen CW, Song JS, Chen CH, Lin WH, Wu SH, Hsu JT, Chang CM, Hsieh HP.
    Eur J Med Chem; 2014 Aug 18; 83():226-35. PubMed ID: 24960626
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  • 16. High-throughput virtual screening of proteins using GRID molecular interaction fields.
    Sciabola S, Stanton RV, Mills JE, Flocco MM, Baroni M, Cruciani G, Perruccio F, Mason JS.
    J Chem Inf Model; 2010 Jan 18; 50(1):155-69. PubMed ID: 19919042
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  • 17. Lead finder: an approach to improve accuracy of protein-ligand docking, binding energy estimation, and virtual screening.
    Stroganov OV, Novikov FN, Stroylov VS, Kulkov V, Chilov GG.
    J Chem Inf Model; 2008 Dec 18; 48(12):2371-85. PubMed ID: 19007114
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  • 20. Molecular Dynamics as a Tool for Virtual Ligand Screening.
    Menchon G, Maveyraud L, Czaplicki G.
    Methods Mol Biol; 2018 Dec 18; 1762():145-178. PubMed ID: 29594772
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