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Pubmed for Handhelds

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Journal Abstract Search

236 related items for PubMed ID: 22371207

  • 1. Pose prediction and virtual screening performance of GOLD scoring functions in a standardized test.
    Liebeschuetz JW, Cole JC, Korb O.
    J Comput Aided Mol Des; 2012 Jun; 26(6):737-48. PubMed ID: 22371207
    [Abstract] [Full Text] [Related]

  • 2. Surflex-Dock: Docking benchmarks and real-world application.
    Spitzer R, Jain AN.
    J Comput Aided Mol Des; 2012 Jun; 26(6):687-99. PubMed ID: 22569590
    [Abstract] [Full Text] [Related]

  • 3. Improving docking results via reranking of ensembles of ligand poses in multiple X-ray protein conformations with MM-GBSA.
    Greenidge PA, Kramer C, Mozziconacci JC, Sherman W.
    J Chem Inf Model; 2014 Oct 27; 54(10):2697-717. PubMed ID: 25266271
    [Abstract] [Full Text] [Related]

  • 4. Are predefined decoy sets of ligand poses able to quantify scoring function accuracy?
    Korb O, Ten Brink T, Victor Paul Raj FR, Keil M, Exner TE.
    J Comput Aided Mol Des; 2012 Feb 27; 26(2):185-97. PubMed ID: 22231069
    [Abstract] [Full Text] [Related]

  • 5. Evaluation of docking performance: comparative data on docking algorithms.
    Kontoyianni M, McClellan LM, Sokol GS.
    J Med Chem; 2004 Jan 29; 47(3):558-65. PubMed ID: 14736237
    [Abstract] [Full Text] [Related]

  • 6. A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance.
    Perola E, Walters WP, Charifson PS.
    Proteins; 2004 Aug 01; 56(2):235-49. PubMed ID: 15211508
    [Abstract] [Full Text] [Related]

  • 7. Comparative assessment of scoring functions on an updated benchmark: 2. Evaluation methods and general results.
    Li Y, Han L, Liu Z, Wang R.
    J Chem Inf Model; 2014 Jun 23; 54(6):1717-36. PubMed ID: 24708446
    [Abstract] [Full Text] [Related]

  • 8. Scoring functions and enrichment: a case study on Hsp90.
    Konstantinou-Kirtay C, Mitchell JB, Lumley JA.
    BMC Bioinformatics; 2007 Jan 26; 8():27. PubMed ID: 17257425
    [Abstract] [Full Text] [Related]

  • 9. A critical assessment of docking programs and scoring functions.
    Warren GL, Andrews CW, Capelli AM, Clarke B, LaLonde J, Lambert MH, Lindvall M, Nevins N, Semus SF, Senger S, Tedesco G, Wall ID, Woolven JM, Peishoff CE, Head MS.
    J Med Chem; 2006 Oct 05; 49(20):5912-31. PubMed ID: 17004707
    [Abstract] [Full Text] [Related]

  • 10. How sophisticated should a scoring function be to ensure successful docking, scoring and virtual screening?
    Tarasov D, Tovbin D.
    J Mol Model; 2009 Mar 05; 15(3):329-41. PubMed ID: 19066998
    [Abstract] [Full Text] [Related]

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  • 12. Docking and scoring with ICM: the benchmarking results and strategies for improvement.
    Neves MA, Totrov M, Abagyan R.
    J Comput Aided Mol Des; 2012 Jun 05; 26(6):675-86. PubMed ID: 22569591
    [Abstract] [Full Text] [Related]

  • 13. Variability in docking success rates due to dataset preparation.
    Corbeil CR, Williams CI, Labute P.
    J Comput Aided Mol Des; 2012 Jun 05; 26(6):775-86. PubMed ID: 22566074
    [Abstract] [Full Text] [Related]

  • 14. A Hybrid Docking and Machine Learning Approach to Enhance the Performance of Virtual Screening Carried out on Protein-Protein Interfaces.
    Singh N, Villoutreix BO.
    Int J Mol Sci; 2022 Nov 18; 23(22):. PubMed ID: 36430841
    [Abstract] [Full Text] [Related]

  • 15. SCORCH: Improving structure-based virtual screening with machine learning classifiers, data augmentation, and uncertainty estimation.
    McGibbon M, Money-Kyrle S, Blay V, Houston DR.
    J Adv Res; 2023 Apr 18; 46():135-147. PubMed ID: 35901959
    [Abstract] [Full Text] [Related]

  • 16. Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening.
    Hsieh JH, Yin S, Wang XS, Liu S, Dokholyan NV, Tropsha A.
    J Chem Inf Model; 2012 Jan 23; 52(1):16-28. PubMed ID: 22017385
    [Abstract] [Full Text] [Related]

  • 17. Scoring confidence index: statistical evaluation of ligand binding mode predictions.
    Zavodszky MI, Stumpff-Kane AW, Lee DJ, Feig M.
    J Comput Aided Mol Des; 2009 May 23; 23(5):289-99. PubMed ID: 19153808
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  • 19. eHiTS: a new fast, exhaustive flexible ligand docking system.
    Zsoldos Z, Reid D, Simon A, Sadjad SB, Johnson AP.
    J Mol Graph Model; 2007 Jul 23; 26(1):198-212. PubMed ID: 16860582
    [Abstract] [Full Text] [Related]

  • 20. Lead Finder docking and virtual screening evaluation with Astex and DUD test sets.
    Novikov FN, Stroylov VS, Zeifman AA, Stroganov OV, Kulkov V, Chilov GG.
    J Comput Aided Mol Des; 2012 Jun 23; 26(6):725-35. PubMed ID: 22569592
    [Abstract] [Full Text] [Related]

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