Neural Network Modeling for Estimation of Partition Coefficient Based on Atom-Type Electrotopological State Indices

Journal of Chemical Information and Computer Sciences

Volumn 40, Issue 4, 2000, Pages 947-955

  Huuskonen, Jarmo J ^a   Livingstone, David J ^b,c   Tetko, Igor V ^d,e  

^a UNIVERSITY OF HELSINKI   (Finland)

^b ChemQuest   (United Kingdom)

^c UNIVERSITY OF PORTSMOUTH   (United Kingdom)

^d UNIVERSITY OF LAUSANNE   (Switzerland)

^e INSTITUTE OF BIOORGANIC CHEMISTRY AND PETROCHEMISTRY   (Ukraine)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0000691934     PISSN: 00952338     EISSN: None     Source Type: Journal    
DOI: 10.1021/ci9904261     Document Type: Article

References (37)

1. Gillet, V. J.; Willett, P.; Bradshaw, J. Identification of Biological Active Profiles Using Substructural Analysis and Genetic Algorithm. J. Chem. Inf. Comput. Sci. 1998, 38, 165-179.
2. Ferguson, A. M.; Patterson, D. E.; Garr, C. D.; Underinger, T. L. Designing Chemical Libraries for Lead Discovery. J. Biomol. Screen. 1996, 1, 65-73.
3. Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J. Experimental and Computational Approaches to Estimate Solubility and Permeability in Drug Discovery and Development Settings. Adv. Drug Delivery Rev. 1997, 23, 3-25.
4. Ghose, A. K.; Viswanadhan, V. N.; Wendoloski, J. J. A KnowledgeBased Approach in Designing Combinatorial or Medicinal Chemistry Libraries for Drug Discovery. 1. A Qualitative and Quantitative Characterization of Known Drug Databases. J. Comb. Chem. 1999, 1, 55-68.
5. Hansch, L.; Leo, A. Substituent Constants for Correlation Analysis in Chemistry and Biology, Wiley: New York, 1979.
6. oct from Structures. Chem. Rev. 1993, 93, 1281-1306.
7. Rekker, R. E. Hydrophobic Fragment Constant; Elsevier: New York, 1977.
8. Klopman, G.; Li, J.-Y.; Wang, S.; Dimayuga, M. Computer Automated log P Calculations Based on an Extended Group Contribution Approach. J. Chem. Inf. Comput. Sci. 1994, 34, 752-781.
9. Meylan, W. M.; Howard, P. H. Atom/Fragment Contribution Method for Estimating Octanol-Water Partition Coefficients. J. Pharm. Sci. 1995, 84, 83-92.
10. Wang, R.; Fu, Y.; Lai, L. A New Atom-Additive Method for Calculating Partition Coefficients. J. Chem. Inf. Comput. Sci. 1997, 37, 615-621.
11. Klopman, G.; Iroff, L. Calculation of Partition Coefficients by the Charge Density Methodol. J. Comput. Chem. 1981, 2, 157.
12. Bodor, N.; Huang, M.-J. An Extended Version of a Novel Method for Estimation of Partition Coefficients. J. Pharm. Sci. 1992, 81, 272-281.
13. Haeberlin, M.; Brinck, T. Prediction of Water-Octanol Partition Coefficients Using Theoretical Descriptors Derived from the Molecular Surface Area and the Electrostatic Potential. J. Chem. Soc., Perkin Trans. 2 1997, 289-294.
14. Bodor, N.; Buchwald, P. Molecular Size Based Approach to Estimate Partition Properties for Organic Solutes. J. Phys. Chem. 1997, 101, 3404-3412.
15. Breindl, A.; Beck, N.; Clark, T., Glen, R. C. Prediction of the n-Octanol/Water Partition Coefficient, logP, Using a Combination of Semiempirical MO-Calculations and a Neural Network. J. Mol. Model. 1997, 3, 142-155.
16. Buchwald, P.; Bodor, N. Octanol-Water Partitioning: Searching for Predictive Models. Curr. Med. Chem. 1998, 5, 353-380.
17. Kier, L. B.; Hall, L. H An Electrotopological State Index for Atoms in Molecules. Pharm. Res. 1990, 7, 801-807.
18. Hall, L. H.; Kier, L. B. Electrotopological State Indices for Atom Types: A Novel Combination of Electronic, Topological, and Valence State Information. J. Chem. Inf. Comput. Sci. 1995, 35, 1039-1045.
19. Hall, L. H.; Story, C. T. Boiling Point and Critical Temperature of a Heterogeneous Data Set: QSAR with Atom Type Electrotopological State Indices Using Artificial Neural Networks. J. Chem. Inf. Comput. Sci. 1996, 36, 1004-1014.
20. Huuskonen, J.; Salo, M.; Taskinen, J. Aqueous Solubility Prediction of Drugs Based on Molecular Topology and Neural Network Modeling. J. Chem. Inf. Comput. Sci. 1998, 38, 450-456.
21. Huuskonen, J. J.; Villa, A. E. P.; Tetko, I. V. Prediction of Partition Coefficient Based on Atom-Type Electrotopological State Indices. J. Pharm. Sci. 1999, 88, 229-233.
22. Viswanadhan, V. N.; Reddy, M. R.; Bacquet, R. J.; Erion, M. D. Assessment of Methods Used for Predicting Lipophilicity: Application to Nucleosides and Nucleoside Bases. J. Comput. Chem. 1993, 14, 1019-1025.
23. Moriguchi, I.; Hirono, S.; Nakagome, I.; Hirano, H. Comparison of Reliability of logP Values for Drugs Calculated by Several Methods. Chem. Pharm. Bull. 1994, 42 (2), 976-978.
24. Schaper, K.-J.; Samitier, M. L. R. Calculation of Octanol/Water Partition Coefficients (logP) using Artificial Neural Networks and Connection Matrixes. Quant. Struct.-Act. Relat. 1997, 16, 224-230.
25. Devillers, J.; Domine, D.; Guillon, C. Autocorrelation Modeling of Lipophilicity with a Back-Propagation Neural Network. Eur. J. Med. Chem. 1998, 33, 659-664.
26. Tetko, I. V.; Livingstone, D. J.; Luik, A. I. Neural Network Studies. 1. Comparison of Overfitting and Overtraining. J. Chem. Inf. Comput. Sci. 1995, 35, 826-833.
27. Tetko, I. V.; Villa, A. E. P.; Livingstone, D. J. Neural Network Studies. 2. Variable Selection. J. Chem. Inf. Comput. Sci. 1996, 36, 794-803.
28. Tetko, I. V.; Villa, A. E. P. Efficient Partition of Learning Data Sets for Neural Network Training. Neural Networks 1997, 10, 1361-1374.
29. Huuskonen, J.; Salo, M.; Taskinen, J. Neural Network Modeling for Estimation of the Aqueous Solubility of Structurally Related Drugs. J. Pharm. Sci. 1997, 86, 450-454.
30. Huuskonen, J. Estimation of Aqueous Solubility for a Diverse Set of Organic Compounds Based on Molecular Topology. J. Chem. Inf. Comput. Sci., in press.
31. Tetko, I. V.; Aksenova, T. I.; Volkovich, V. V.; Kasheva, T. N.; Filipov, D. V.; Villa, A. E. P.; Welsh, W. J.; Livingstone, D. J. Polynomial Neural Network for Linear and Nonlinear Model Selection in Quantitative-Structure Activity Relationship Studies on WWW. SAR QSAR Environ. Res., in press.
32. Abou-Shaaban, R. R.; al-Khamees, H. A.; Abou-Auda, H. S.; Simonelli, A. P. Atom Level Electrotopological State Indices in QSAR: Designing and Testing Antithyroid Agents. Pharm. Res. 1996, 13, 129-136.
33. Buolamwini, J. K.; Raghavan, K.; Fesen, M. R.; Pommier, Y.; Kohn, K. W.; Weinstein, J. N. Application of the Electrotopological State Index to QSAR Analysis of Flavone Derivatives as HlV-1 Integrase Inhibitors. Pharm. Res. 1996, 13, 1892-1895.
34. de Gregorio, C.; Kier, L. B.; Hall, L. H. QSAR Modeling with the Electrotopological State Indices: Corticosteroids. J. Comput.-Aided Mol. Des. 1998, 12, 557-561.
35. Liang, H. R.; Vuorela, H.; Vuorela, P.; Riekkola, M. L.; Hiltunen, R. Prediction of migration behavior of flavonoids in capillary zone electrophoresis by means of topological indices. J. Chromatogr. 1998, 798, 233-242.
36. Gough, J. D.; Hall, L. H. Modeling Antileukemic Activity of Carboquinones with Electrotopological State and Chi Indices. J. Chem. Inf. Comput. Sci. 1999, 39, 356-361
37. Livingstone, D. J. The Characterization of Chemical Structures Using Molecular Properties. A Survey. J. Chem. Inf. Comput. Sci. 2000, 40, 195-209.