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Pubmed for Handhelds

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Journal Abstract Search

204 related items for PubMed ID: 28678484

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  • 2. 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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  • 4. Structural protein-ligand interaction fingerprints (SPLIF) for structure-based virtual screening: method and benchmark study.
    Da C, Kireev D.
    J Chem Inf Model; 2014 Sep 22; 54(9):2555-61. PubMed ID: 25116840
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  • 5. Molecular Dynamics as a Tool for Virtual Ligand Screening.
    Menchon G, Maveyraud L, Czaplicki G.
    Methods Mol Biol; 2018 Sep 22; 1762():145-178. PubMed ID: 29594772
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  • 6. FINDSITE(comb): a threading/structure-based, proteomic-scale virtual ligand screening approach.
    Zhou H, Skolnick J.
    J Chem Inf Model; 2013 Jan 28; 53(1):230-40. PubMed ID: 23240691
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  • 8. Empirical Scoring Functions for Affinity Prediction of Protein-ligand Complexes.
    Pason LP, Sotriffer CA.
    Mol Inform; 2016 Dec 28; 35(11-12):541-548. PubMed ID: 27870243
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  • 11. 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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  • 12. Task-Specific Scoring Functions for Predicting Ligand Binding Poses and Affinity and for Screening Enrichment.
    Ashtawy HM, Mahapatra NR.
    J Chem Inf Model; 2018 Jan 22; 58(1):119-133. PubMed ID: 29190087
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  • 18. FitScore: a fast machine learning-based score for 3D virtual screening enrichment.
    Gehlhaar DK, Mermelstein DJ.
    J Comput Aided Mol Des; 2024 Aug 16; 38(1):29. PubMed ID: 39150579
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