Navigating high-dimensional activity landscapes: Design and application of the ligand-target differentiation map

Journal of Chemical Information and Modeling

Volumn 52, Issue 8, 2012, Pages 1962-1969

  Iyer, Preeti ^a   Dimova, Dilyana ^a   Vogt, Martin ^a   Bajorath, Jürgen ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL CHEMISTRY; LIGANDS;

ACTIVITY MEASUREMENTS; ACTIVITY SPACES; DESIGN AND APPLICATION; EXPERIMENTAL EVALUATION; HIGH-DIMENSIONAL; MEDICINAL CHEMISTRY; STRUCTURAL RELATIONSHIP; UNSOLVED PROBLEMS;

BIOACTIVITY;

LIGAND; PROTEIN KINASE; PROTEIN KINASE INHIBITOR;

ARTICLE; CHEMISTRY; COMPUTER GRAPHICS; DRUG DEVELOPMENT; ENZYME SPECIFICITY; METABOLISM; METHODOLOGY; MOLECULARLY TARGETED THERAPY; STRUCTURE ACTIVITY RELATION;

COMPUTER GRAPHICS; DRUG DISCOVERY; LIGANDS; MOLECULAR TARGETED THERAPY; PROTEIN KINASE INHIBITORS; PROTEIN KINASES; STRUCTURE-ACTIVITY RELATIONSHIP; SUBSTRATE SPECIFICITY;

EID: 84865527541     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci3002765     Document Type: Article

References (18)

1. Rix, U.; Superti-Furga, G. Target profiling of small molecules by chemical proteomics Nature Chem. Biol. 2009, 5, 616-624
2. Allen, J. A.; Roth, B. L. Strategies to discover unexpected targets for drugs active at G protein-coupled receptors Annu. Rev. Pharmacol. Toxicol. 2011, 51, 117-144
3. Goldstein, D. M.; Gray, N. S.; Zarrinkar, P. P. High-throughput kinase profiling as a platform for drug discovery Nature Rev. Drug. Discov 2008, 6, 391-397 (Pubitemid 351619111)
4. Bajorath, J. Computational analysis of ligand relationships within target families Curr. Opin. Chem. Biol. 2008, 12, 352-358
5. Bajorath, J.; Maggiora, G.; Lajiness, M., organizers. The Emerging Concepts of Activity Landscapes and Activity Cliffs and Their Role in Drug Research; 240th National Meeting of the American Chemical Society, Divisions of Chemical Information and Computers in Chemistry, Boston, MA, August 22-26, 2010.
6. Wassermann, A. M.; Wawer, M.; Bajorath, J. Activity landscape representations for structure-activity relationship analysis J. Med. Chem. 2010, 53, 8209-8223
7. Peltason, L.; Hu, Y.; Bajorath, J. From structure-activity to structure-selectivity relationships: Quantitative assessment, selectivity cliffs, and key compounds ChemMedChem 2009, 4, 1864-1873
8. Dimova, D.; Wawer, M.; Wassermann, A. M.; Bajorath, J. Design of multi-target activity landscapes that capture hierarchical activity cliff distributions J. Chem. Inf. Model. 2011, 51, 256-288
9. Stumpfe, D.; Bajorath, J. Exploring activity cliffs in medicinal chemistry J. Med. Chem. 2012, 55, 2932-2942
10. Medina-Franco, J. L.; Yongye, A. B.; Perez-Villanueva, J.; Houghten, R. A.; Martinez-Mayorga, K. Multi-target structure-activity relationships characterized by activity-difference maps and consensus similarity measures J. Chem. Inf. Model. 2011, 51, 2427-2439
11. Iyer, P.; Bajorath, J. Representation of multi-target activity landscapes through target pair-based compound encoding in self-organizing maps Chem. Biol. Drug Des. 2011, 78, 778-786
12. Metz, J. T.; Johnson, E. F.; Soni, N. B.; Merta, P. J.; Kifle, L.; Hajduk, P. J. Navigating the kinome Nature Chem. Biol. 2011, 7, 200-202
13. Weininger, D. SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules J. Chem. Inf. Comput. Sci. 1988, 28, 31-36 (Pubitemid 18574254)
14. Willett, P.; Barnard, J. M.; Downs, G. M. Chemical similarity searching J. Chem. Inf. Comput. Sci. 1998, 38, 983-996 (Pubitemid 128591261)
15. MACCS Structural Keys; Symyx Software: San Ramon, CA, USA.
16. Kenny, P. W.; Sadowski, J. Structure modification in chemical databases. In Chemoinformatics in Drug Discovery; Oprea, T. I., Ed.; Wiley-VCH: Weinheim, Germany, 2005; pp 271-285.
17. Wassermann, A. M.; Bajorath, J. Large-scale exploration of bioisosteric replacements on the basis of matched molecular pairs Future Med. Chem. 2011, 3, 425-436
18. R: A Language and Environment for Statistical Computing; R Development Core Team, R Foundation for Statistical Computing: Vienna, Austria, 2008.