346 related articles for article (PubMed ID: 16882313)
21. High-throughput characterization and quality control of small-molecule combinatorial libraries.
Kenseth JR; Coldiron SJ
Curr Opin Chem Biol; 2004 Aug; 8(4):418-23. PubMed ID: 15288253
[TBL] [Abstract][Full Text] [Related]
22. Optimization of high throughput virtual screening by combining shape-matching and docking methods.
Lee HS; Choi J; Kufareva I; Abagyan R; Filikov A; Yang Y; Yoon S
J Chem Inf Model; 2008 Mar; 48(3):489-97. PubMed ID: 18302357
[TBL] [Abstract][Full Text] [Related]
23. Practical approaches to efficient screening: information-rich screening protocol.
Karnachi PS; Brown FK
J Biomol Screen; 2004 Dec; 9(8):678-86. PubMed ID: 15634794
[TBL] [Abstract][Full Text] [Related]
24. Discovering novel ligands for macromolecules using X-ray crystallographic screening.
Nienaber VL; Richardson PL; Klighofer V; Bouska JJ; Giranda VL; Greer J
Nat Biotechnol; 2000 Oct; 18(10):1105-8. PubMed ID: 11017052
[TBL] [Abstract][Full Text] [Related]
25. Kinase inhibitor data modeling and de novo inhibitor design with fragment approaches.
Vieth M; Erickson J; Wang J; Webster Y; Mader M; Higgs R; Watson I
J Med Chem; 2009 Oct; 52(20):6456-66. PubMed ID: 19791746
[TBL] [Abstract][Full Text] [Related]
26. Strategy for discovering chemical inhibitors of human cyclophilin a: focused library design, virtual screening, chemical synthesis and bioassay.
Li J; Zhang J; Chen J; Luo X; Zhu W; Shen J; Liu H; Shen X; Jiang H
J Comb Chem; 2006; 8(3):326-37. PubMed ID: 16677001
[TBL] [Abstract][Full Text] [Related]
27. Slow-binding human serine racemase inhibitors from high-throughput screening of combinatorial libraries.
Dixon SM; Li P; Liu R; Wolosker H; Lam KS; Kurth MJ; Toney MD
J Med Chem; 2006 Apr; 49(8):2388-97. PubMed ID: 16610782
[TBL] [Abstract][Full Text] [Related]
28. Receptor-based virtual ligand screening for the identification of novel CDC25 phosphatase inhibitors.
Montes M; Braud E; Miteva MA; Goddard ML; Mondésert O; Kolb S; Brun MP; Ducommun B; Garbay C; Villoutreix BO
J Chem Inf Model; 2008 Jan; 48(1):157-65. PubMed ID: 18154280
[TBL] [Abstract][Full Text] [Related]
29. Novel 2D fingerprints for ligand-based virtual screening.
Ewing T; Baber JC; Feher M
J Chem Inf Model; 2006; 46(6):2423-31. PubMed ID: 17125184
[TBL] [Abstract][Full Text] [Related]
30. Application of QSAR and shape pharmacophore modeling approaches for targeted chemical library design.
Ebalunode JO; Zheng W; Tropsha A
Methods Mol Biol; 2011; 685():111-33. PubMed ID: 20981521
[TBL] [Abstract][Full Text] [Related]
31. Structure-based development of target-specific compound libraries.
Orry AJ; Abagyan RA; Cavasotto CN
Drug Discov Today; 2006 Mar; 11(5-6):261-6. PubMed ID: 16580603
[TBL] [Abstract][Full Text] [Related]
32. Analysis of structure-based virtual screening studies and characterization of identified active compounds.
Ripphausen P; Stumpfe D; Bajorath J
Future Med Chem; 2012 Apr; 4(5):603-13. PubMed ID: 22458680
[TBL] [Abstract][Full Text] [Related]
33. Design and combinatorial synthesis of a novel kinase-focused library using click chemistry-based fragment assembly.
Irie T; Fujii I; Sawa M
Bioorg Med Chem Lett; 2012 Jan; 22(1):591-6. PubMed ID: 22104147
[TBL] [Abstract][Full Text] [Related]
34. Discovery of novel cathepsin S inhibitors by pharmacophore-based virtual high-throughput screening.
Markt P; McGoohan C; Walker B; Kirchmair J; Feldmann C; De Martino G; Spitzer G; Distinto S; Schuster D; Wolber G; Laggner C; Langer T
J Chem Inf Model; 2008 Aug; 48(8):1693-705. PubMed ID: 18637674
[TBL] [Abstract][Full Text] [Related]
35. Learning from the data: mining of large high-throughput screening databases.
Yan SF; King FJ; He Y; Caldwell JS; Zhou Y
J Chem Inf Model; 2006; 46(6):2381-95. PubMed ID: 17125181
[TBL] [Abstract][Full Text] [Related]
36. High-throughput determination of mode of inhibition in lead identification and optimization.
Wei M; Wynn R; Hollis G; Liao B; Margulis A; Reid BG; Klabe R; Liu PC; Becker-Pasha M; Rupar M; Burn TC; McCall DE; Li Y
J Biomol Screen; 2007 Mar; 12(2):220-8. PubMed ID: 17351185
[TBL] [Abstract][Full Text] [Related]
37. A similarity-based data-fusion approach to the visual characterization and comparison of compound databases.
Medina-Franco JL; Maggiora GM; Giulianotti MA; Pinilla C; Houghten RA
Chem Biol Drug Des; 2007 Nov; 70(5):393-412. PubMed ID: 17927720
[TBL] [Abstract][Full Text] [Related]
38. Protein structure similarity clustering and natural product structure as guiding principles in drug discovery.
Koch MA; Waldmann H
Drug Discov Today; 2005 Apr; 10(7):471-83. PubMed ID: 15809193
[TBL] [Abstract][Full Text] [Related]
39. Novel lead structures for p38 MAP kinase via FieldScreen virtual screening.
Cheeseright TJ; Holm M; Lehmann F; Luik S; Göttert M; Melville JL; Laufer S
J Med Chem; 2009 Jul; 52(14):4200-9. PubMed ID: 19489590
[TBL] [Abstract][Full Text] [Related]
40. Protein structure similarity clustering (PSSC) and natural product structure as inspiration sources for drug development and chemical genomics.
Dekker FJ; Koch MA; Waldmann H
Curr Opin Chem Biol; 2005 Jun; 9(3):232-9. PubMed ID: 15939324
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
