BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

114 related articles for article (PubMed ID: 24796936)

  • 1. Improvement of virtual screening results by docking data feature analysis.
    Arciniega M; Lange OF
    J Chem Inf Model; 2014 May; 54(5):1401-11. PubMed ID: 24796936
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comparison of several molecular docking programs: pose prediction and virtual screening accuracy.
    Cross JB; Thompson DC; Rai BK; Baber JC; Fan KY; Hu Y; Humblet C
    J Chem Inf Model; 2009 Jun; 49(6):1455-74. PubMed ID: 19476350
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Boosting Docking-Based Virtual Screening with Deep Learning.
    Pereira JC; Caffarena ER; Dos Santos CN
    J Chem Inf Model; 2016 Dec; 56(12):2495-2506. PubMed ID: 28024405
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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; 54(1):324-37. PubMed ID: 24358939
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Boosting virtual screening enrichments with data fusion: coalescing hits from two-dimensional fingerprints, shape, and docking.
    Sastry GM; Inakollu VS; Sherman W
    J Chem Inf Model; 2013 Jul; 53(7):1531-42. PubMed ID: 23782297
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comprehensive comparison of ligand-based virtual screening tools against the DUD data set reveals limitations of current 3D methods.
    Venkatraman V; Pérez-Nueno VI; Mavridis L; Ritchie DW
    J Chem Inf Model; 2010 Dec; 50(12):2079-93. PubMed ID: 21090728
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Extensive consensus docking evaluation for ligand pose prediction and virtual screening studies.
    Tuccinardi T; Poli G; Romboli V; Giordano A; Martinelli A
    J Chem Inf Model; 2014 Oct; 54(10):2980-6. PubMed ID: 25211541
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Molecular docking to flexible targets.
    Sørensen J; Demir Ö; Swift RV; Feher VA; Amaro RE
    Methods Mol Biol; 2015; 1215():445-69. PubMed ID: 25330975
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands.
    Pérez GM; Salomón LA; Montero-Cabrera LA; de la Vega JM; Mascini M
    Mol Divers; 2016 May; 20(2):421-38. PubMed ID: 26553204
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Reliability analysis and optimization of the consensus docking approach for the development of virtual screening studies.
    Poli G; Martinelli A; Tuccinardi T
    J Enzyme Inhib Med Chem; 2016; 31(sup2):167-173. PubMed ID: 27311630
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Optimization of compound ranking for structure-based virtual ligand screening using an established FRED-Surflex consensus approach.
    Du J; Bleylevens IW; Bitorina AV; Wichapong K; Nicolaes GA
    Chem Biol Drug Des; 2014 Jan; 83(1):37-51. PubMed ID: 23941463
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Using consensus-shape clustering to identify promiscuous ligands and protein targets and to choose the right query for shape-based virtual screening.
    Pérez-Nueno VI; Ritchie DW
    J Chem Inf Model; 2011 Jun; 51(6):1233-48. PubMed ID: 21604699
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy.
    Therrien E; Weill N; Tomberg A; Corbeil CR; Lee D; Moitessier N
    J Chem Inf Model; 2014 Nov; 54(11):3198-210. PubMed ID: 25280064
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Structure-based virtual screening approach for discovery of covalently bound ligands.
    Toledo Warshaviak D; Golan G; Borrelli KW; Zhu K; Kalid O
    J Chem Inf Model; 2014 Jul; 54(7):1941-50. PubMed ID: 24932913
    [TBL] [Abstract][Full Text] [Related]  

  • 15. How to benchmark methods for structure-based virtual screening of large compound libraries.
    Christofferson AJ; Huang N
    Methods Mol Biol; 2012; 819():187-95. PubMed ID: 22183538
    [TBL] [Abstract][Full Text] [Related]  

  • 16. CRDOCK: an ultrafast multipurpose protein-ligand docking tool.
    Cortés Cabrera Á; Klett J; Dos Santos HG; Perona A; Gil-Redondo R; Francis SM; Priego EM; Gago F; Morreale A
    J Chem Inf Model; 2012 Aug; 52(8):2300-9. PubMed ID: 22764680
    [TBL] [Abstract][Full Text] [Related]  

  • 17. FlexAID: Revisiting Docking on Non-Native-Complex Structures.
    Gaudreault F; Najmanovich RJ
    J Chem Inf Model; 2015 Jul; 55(7):1323-36. PubMed ID: 26076070
    [TBL] [Abstract][Full Text] [Related]  

  • 18. LigMatch: a multiple structure-based ligand matching method for 3D virtual screening.
    Kinnings SL; Jackson RM
    J Chem Inf Model; 2009 Sep; 49(9):2056-66. PubMed ID: 19685924
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Exploring polypharmacology using a ROCS-based target fishing approach.
    AbdulHameed MD; Chaudhury S; Singh N; Sun H; Wallqvist A; Tawa GJ
    J Chem Inf Model; 2012 Feb; 52(2):492-505. PubMed ID: 22196353
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Highly specific and sensitive pharmacophore model for identifying CXCR4 antagonists. Comparison with docking and shape-matching virtual screening performance.
    Karaboga AS; Planesas JM; Petronin F; Teixidó J; Souchet M; Pérez-Nueno VI
    J Chem Inf Model; 2013 May; 53(5):1043-56. PubMed ID: 23577723
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.