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162 related items for PubMed ID: 22198519

  • 21. 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; 48(12):2371-85. PubMed ID: 19007114
    [Abstract] [Full Text] [Related]

  • 22. Receptor rigidity and ligand mobility in trypsin-ligand complexes.
    Guvench O, Price DJ, Brooks CL.
    Proteins; 2005 Feb 01; 58(2):407-17. PubMed ID: 15578663
    [Abstract] [Full Text] [Related]

  • 23. Evaluation of docking performance in a blinded virtual screening of fragment-like trypsin inhibitors.
    Surpateanu G, Iorga BI.
    J Comput Aided Mol Des; 2012 May 01; 26(5):595-601. PubMed ID: 22180049
    [Abstract] [Full Text] [Related]

  • 24. SAMPL6 host-guest binding affinities and binding poses from spherical-coordinates-biased simulations.
    Sun Z, He Q, Li X, Zhu Z.
    J Comput Aided Mol Des; 2020 May 01; 34(5):589-600. PubMed ID: 31974852
    [Abstract] [Full Text] [Related]

  • 25. Toward fully automated high performance computing drug discovery: a massively parallel virtual screening pipeline for docking and molecular mechanics/generalized Born surface area rescoring to improve enrichment.
    Zhang X, Wong SE, Lightstone FC.
    J Chem Inf Model; 2014 Jan 27; 54(1):324-37. PubMed ID: 24358939
    [Abstract] [Full Text] [Related]

  • 26. Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes.
    Friesner RA, Murphy RB, Repasky MP, Frye LL, Greenwood JR, Halgren TA, Sanschagrin PC, Mainz DT.
    J Med Chem; 2006 Oct 19; 49(21):6177-96. PubMed ID: 17034125
    [Abstract] [Full Text] [Related]

  • 27. Binding affinities in the SAMPL3 trypsin and host-guest blind tests estimated with the MM/PBSA and LIE methods.
    Mikulskis P, Genheden S, Rydberg P, Sandberg L, Olsen L, Ryde U.
    J Comput Aided Mol Des; 2012 May 19; 26(5):527-41. PubMed ID: 22198518
    [Abstract] [Full Text] [Related]

  • 28. Optimizing the affinity and specificity of ligand binding with the inclusion of solvation effect.
    Yan Z, Wang J.
    Proteins; 2015 Sep 19; 83(9):1632-42. PubMed ID: 26111900
    [Abstract] [Full Text] [Related]

  • 29. Comparative binding energy analysis for binding affinity and target selectivity prediction.
    Henrich S, Feierberg I, Wang T, Blomberg N, Wade RC.
    Proteins; 2010 Jan 19; 78(1):135-53. PubMed ID: 19768680
    [Abstract] [Full Text] [Related]

  • 30. 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 19; 26(6):725-35. PubMed ID: 22569592
    [Abstract] [Full Text] [Related]

  • 31. 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
    [Abstract] [Full Text] [Related]

  • 32. 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
    [Abstract] [Full Text] [Related]

  • 33. Improving performance of docking-based virtual screening by structural filtration.
    Novikov FN, Stroylov VS, Stroganov OV, Chilov GG.
    J Mol Model; 2010 Jul 22; 16(7):1223-30. PubMed ID: 20041273
    [Abstract] [Full Text] [Related]

  • 34. Docking ligands into flexible and solvated macromolecules. 5. Force-field-based prediction of binding affinities of ligands to proteins.
    Englebienne P, Moitessier N.
    J Chem Inf Model; 2009 Nov 22; 49(11):2564-71. PubMed ID: 19928836
    [Abstract] [Full Text] [Related]

  • 35. 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
    [Abstract] [Full Text] [Related]

  • 36. Calculation of protein-ligand binding free energy by using a polarizable potential.
    Jiao D, Golubkov PA, Darden TA, Ren P.
    Proc Natl Acad Sci U S A; 2008 Apr 29; 105(17):6290-5. PubMed ID: 18427113
    [Abstract] [Full Text] [Related]

  • 37. Using free energy of binding calculations to improve the accuracy of virtual screening predictions.
    Malmstrom RD, Watowich SJ.
    J Chem Inf Model; 2011 Jul 25; 51(7):1648-55. PubMed ID: 21696204
    [Abstract] [Full Text] [Related]

  • 38. The SAMPL5 host-guest challenge: computing binding free energies and enthalpies from explicit solvent simulations by the attach-pull-release (APR) method.
    Yin J, Henriksen NM, Slochower DR, Gilson MK.
    J Comput Aided Mol Des; 2017 Jan 25; 31(1):133-145. PubMed ID: 27638809
    [Abstract] [Full Text] [Related]

  • 39. Fast and accurate predictions of binding free energies using MM-PBSA and MM-GBSA.
    Rastelli G, Del Rio A, Degliesposti G, Sgobba M.
    J Comput Chem; 2010 Mar 25; 31(4):797-810. PubMed ID: 19569205
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  • 40. Discrete molecular dynamics distinguishes nativelike binding poses from decoys in difficult targets.
    Proctor EA, Yin S, Tropsha A, Dokholyan NV.
    Biophys J; 2012 Jan 04; 102(1):144-51. PubMed ID: 22225808
    [Abstract] [Full Text] [Related]

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