LeadScope : Software for Exploring Large Sets of Screening Data

Journal of Chemical Information and Computer Sciences

Volumn 40, Issue 6, 2000, Pages 1302-1314

  Roberts, Gulsevin ^a   Myatt, Glenn J ^a   Johnson, Wayne P ^a   Cross, Kevin P ^a   Blower Jr , Paul E ^a  

^a Leadscope Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0001010920     PISSN: 00952338     EISSN: None     Source Type: Journal    
DOI: 10.1021/ci0000631     Document Type: Article

References (52)

1. Kubinyi, H. QSAR: Hansch Analysis and Related Approaches; VCH Publishers: New York, 1993.
2. Willett, P.; Barnard, J. M.; Downs, G. M. Chemical Similarity Searching. J. Chem. Inf. Comput. Sci. 1998, 38, 983-96.
3. Willett, P. Similarity and Clustering in Chemical Information Systems; Research Studies Press: Letchworth, 1987.
4. Brown, R. Descriptors for Diversity Analysis. Perspect. Drug Discovery Des. 1997, 7/8, 31-49.
5. Carhart, R. E.; Smith, D. H.; Venkataraghavan, R. Atom pairs as molecular features in structure-activity stidies: definitions and applications. J. Chem. Inf. Comput. Sci. 1985, 25, 64-73.
6. Kearsley, S. K.; Sallamack, S.; Fluder; E. M., Andose, J. D.; Mosley, R. T.; Sheridan, R. P. Chemical Similarity Using Physiochemical Property Descriptors. J. Chem. Inf. Comput. Sci. 1996, 36, 118-127.
7. Software for generating molecular fingerprint is available from Daylight Chemical Information Systems, 27401 Los Altos, Suite #370, Mission Viejo, CA 92691 and Tripos, Inc., 1699 South Hanley Road, St. Louis, MO 63144.
8. Brown, R. D.; Martin, Y. C. Use of Structure Activity Data to Compare Structure Based Clustering Methods and Descriptors for Use in Compound Selection. J. Chem. Inf. Comput. Sci. 1996, 36, 572-84.
9. Greene, J.; Kahn, S.; Savoj, H.; Sprague, P.; Teig, S. Chemical Function Queries for 3D Database Search. J. Chem. Inf. Comput. Sci. 1994, 34, 1297-1308.
10. Wang, T.; Zhou, J. 3DFS: A new 3D Flexible Searching System for Use in Drug Design. J. Chem. Inf. Comput. Sci. 1998, 38, 71-77.
11. Hansch, C.; Leo, A. Substituent Constants for Correlation Analysis in Chemistry and Biology; John Wiley & Sons: New York, 1979.
12. Cummins, D. J.; Andrews, C. W.; Bentley, J. A.; Cory, M. Molecular Diversity in Chemical Databases: Comparison of Medicinal Chemistry Knowledge Bases and Databases of Commercially Available Chemicals. J. Chem. Inf. Comput. Sci. 1996, 36, 750-63.
13. Matter, H. Selecting Optimally Diverse Compounds from a Structure Database: A Validation Study of Two-Dimensional and Three-Dimensional Molecular Descriptors. J. Med. Chem. 1997, 40, 1219-29.
14. Cosgrove, D. A.; Willett, P. SLASH: A program for analyzing the functional groups in molecules. J. Mol. Graphics Model. 1998, 16, 19-32.
15. Boyd, S. M.; Beverley, M.; Norskov, L.; Hubbard, R. E. Characterizing the geometric diversity of functional groups in chemical databases. J. Comput.-Aided Mol. Des. 1995, 9, 417-24.
16. Bemis, G. W. and Murcko, M. A. The Properties of Known Drugs, 1. Molecular Frameworks. J. Med. Chem. 1996, 39, 2887-2893
17. Comprehensive Medicinal Chemistry and the MACCS - II Drug Data Report are available from MDL Information Systems Inc., San Leandro, CA.
18. Lewell, Q. L.; Judd, D. B.; Watson; S. P.; Hann, M. M. RECAP -Retrosynthetic Combinatorial Analysis Procedure: A Powerful New Technique for Identifying Privileged Molecular Fragments with Useful Applications in Combinatorial Chemistry. J. Chem. Inf. Comput. Sci. 1998, 38, 511-22.
19. The World Drug Index is available from Derwent Information Ltd., Derwent House, 14 Great Queen Street, London WC2B 5DF, UK.
20. Shemetilskis; N. E.; Weininger; D.; Blankley, C. J.; Yang, J. J.; Humblet, C. Stigmata: An Algorithm to Determine Structural Commonalties in Diverse Datasets. J. Chem. Inf. Comput. Sci. 1996, 36, 862-71.
21. Sheridan, R. P.; Miller, M. D. A Method for Visualizing Recurrent Topological Substructures in Sets of Active Molecules. J. Chem. Inf. Comput. Sci. 1998, 38, 915-24.
22. Varmuza, K.; Scsibrany, H. Substructure Isomorphism Matrix. J. Chem. Inf. Comput. Sci. 1998, 40, 308-13. (b) The LeadScope structural feature Hierarchy described in this work is generated algorithmically from tables of parent and substituent substructures.
23. Chemical Abstracts Index Guide, Appendix IV; Chemical Substance Index Names, American Chemical Society: 1997.
24. Sawyer, T. K. In Structure-Based Drug Design; Veerapandian, P., Ed.; Marcel Dekker: 1997; pp 559-634.
25. Jens Loesel, private communication. See, also: Jens Loesel, IAFs - Empirical Descriptors for non-Covalent Interactions, UK QSAR & Chemoinformatics Group, Spring 1999 Meeting, April 27, Pfizer Ltd, Sandwich, UK, http://www.iainm.demon.co.uk/.
26. Jens Loesel, private communication. See, also: Jens Loesel, IAFs -Empirical Descriptors for non-Covalent Interactions, UK QSAR & Chemoinformatics Group, Spring 1999 Meeting, April 27, Pfizer Ltd, Sandwich, UK, http://www.iainm.demon.co.uk/.
27. IUPAC Nomenclature and Symbolism for Amino Acids and Peptides, section 3AA-18.1; http://www.chem.qmw.ac.uk/iupac/AminoAcid/, web version prepared by G. P. Moss.
28. Shneiderman, B. Designing the User Interface: Strategies for Effective Human-Computer Interaction, 3rd ed.; Addison-Wesley: 1998.
29. Ahlberg, C.; Shneiderman, B. Visual information seeking: Tight coupling of dynamic query filters with starfield displays. Proceedings of the CHI' 94 Conference on Human Factors in Computing Systems; ACM: New York, 1994; pp 313-317.
30. Chuah, M. C.; Kerpedjiev, S.; Kolojejchick, J.; Lucas, P.; Roth, S. F. Toward an Information Visualization Workspace: Combining Multiple Means of Expression. Human-Computer Interaction 1997, 12(1 & 2), pp 131-186.
31. Lipinski, C. A.; Lombardro, F.; Dominy, B. W.; Feeney, P. J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and developmental settings. Adv. Drug Del. Res. 1997, 23, 3-25.
32. Agresti, A. Categorical Data Analysis; John Wiley & Sons Inc.: New York, 1990; pp 286-287. (b) Dr. Mark Farmen, personal communication.
33. As indicated in the legend title, the activity data shown is for the SF-295 tumor cell line from the CNS panel.
34. Bonds that are colored in structure diagrams are generic and may match any bond or some combination of specific bonds such as "single or aromatic". The user can review the complete definition of the corresponding substructural query if desired.
35. Stobaugh, R. E. Chemical Structure Searching. J. Chem. Inf. Comput. Sci. 1985, 25, 271-275.
36. Myatt, G. J. Computer Aided Estimation of Synthetic Accessibility, Ph.D. Thesis, Leeds University, 1994.
37. ISIS Draw is a trademark of MDL Information Systems Inc., San Leandro, CA. ChemDraw is a trademark of CamhridgeSoft Corp., Cambridge, MA.
38. Nonconfidential screening results and chemical structural data from the NCI's Developmental Therapeutics Program are available online: (a) Human Tumor Cell Line Screen: http://dtp.nci.nih.gov/docs/cancer/ cancer_Jata.html. (b) AIDS Antiviral Screen: http://dtp.nci.nih.gov/ docs/aids/aids_data.html.
39. Nonconfidential screening results and chemical structural data from the NCI's Developmental Therapeutics Program are available online: (a) Human Tumor Cell Line Screen: http://dtp.nci.nih.gov/docs/cancer/ cancer_Jata.html. (b) AIDS Antiviral Screen: http://dtp.nci.nih.gov/ docs/aids/aids_data.html.
40. Weinstein, J. N.; Myers, T. G.; O'Connor, P. M.; Friend, S. H.; Fornace, A. J.; Kohn, K. W.; Fojo, T.; Bates, S. E.; Rubinstein, L. V.; Anderson, N. L.; Buolamwini J. K.; van Osdol, W. W.; Monks, A. P.; Scudiero, D'Monks, A. P.; Scudiero, D. A.; Johnson, G. S.; Paull, K. D.; Sausville, E. A. The NCI anti-cancer drug screen: a smart screen to identify effectors of novel targets. Anti-Cancer Drug Des. 1997, 12, 533-41.
41. Boyd, M. R.; Paull, K. D. Some Practical Consideration and Applications of the National Cancer Institute In Vitro Anticancer Drug Discovery Screen. Drug Dev. Des. 1995, 34, 91-109.
42. Weinstein, J. N.; Kohn, K. W.; Grever, M. R.; Viswanadham, V. N.; Rubinstein, L. V.; Monks, A. P.; Scudiero, D. A.; Welch, L.; Koutsoukos, A. D.; Chiausa, A. J.; Paull, K. D. Neural Computing in Cancer Drug Development: Predicting Mechanism of Action. Science 1992, 258, 447-51.
43. Paull, K. D.; Hamel, E.; Maispeis, L. Prediction of biochemical mechanism of action from the in vitro anticancer screen of the National Cancer Institute. In Cancer Chemotherapeutic Agents; Foye, W., Ed.; ACS professional Reference Books, ACS: Washington, DC, 1992; pp 9-45.
44. Gibson, S.; McGuire, R.; Rees, D. C. Principal Components Describing Biological Activities and Molecular Diversity of Heterocyclic Aromatic Ring Fragments. J. Med. Chem. 1996, 39, 4065-72.
45. Shi, L. M.; Fan, Y., Myers, T. G.; O'Connor, P. M.; Paull, K. D.; Friend, S. H.; Weinstein, J. N. Mining the NCI anticancer drug discovery databases: genetic function approximation for the QSAR study of anticancer ellipticine analogues. J. Chem. Inf. Comput. Sci. 1998, 38, 189-99.
46. Shi, L. M.; Myers, T. G.; Fan, Y.; O'Connor, P. M.; Paull, K. D.; Friend, S. H.; Weinstein, J. N. Mining the National Cancer Institute Anticancer Drug Discovery Database: cluster analysis of ellipticine analogues with p53-inverse and central nervous system-selective patterns of activity. Mol. Pharmacol. 1998, 53, 241-51.
47. Ohashi, M.; Oki, T. Ellipticine and related anticancer agents. Expert Opin. Ther. Pat. 1996, 6, 1285-1294.
48. Chen, X.; Rusinko, A., III; Young, S. S. Recursive Partitioning Analysis of a Large Structure-Activity Data Set Three-Dimensional Descriptors. J. Chem. Inf. Comput. Sci. 1998, 38, 1054-62.
49. Hawkins, D. M.; Young, S. S.; Rusinko, A., III. Analysis of a Large Structure-Activity Data Set Using Recursive Partitioning. Quant. Struct.-Act. Relat. 1997, 16, 1-7.
50. The Cerius2.CSAR (Classification SAR) program from Molecular Simulations, Inc., San Diego, is a commercial implementation of this technique.
51. Light gray shadows, particularly prominent in Figure 10a, show the original length of histogram bars before filters were applied.
52. 50 data, the user can determine how values are assigned to categories: the number of categories and the cutoff values between categories.