Using general regression and probabilistic neural networks to predict human intestinal absorption with topological descriptors derived from two-dimensional chemical structures

Journal of Chemical Information and Computer Sciences

Volumn 43, Issue 1, 2003, Pages 113-119

  Niwa, Tomoko ^a  

^a NIPPON SHINYAKU CO LTD   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

DRUG-LIKE MOLECULES; HUMAN INTESTINAL ABSORPTION; PROBABILISTIC NEURAL NETWORKS; REGRESSION NEURAL NETWORK;

ABSORPTION; DRUG INTERACTIONS; MATHEMATICAL MODELS; PROBABILITY; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS; TWO DIMENSIONAL;

MOLECULAR STRUCTURE;

DRUG;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; CHEMICAL STRUCTURE; CHEMISTRY; HUMAN; INTESTINE ABSORPTION; PHARMACOKINETICS; REGRESSION ANALYSIS; STATISTICAL MODEL;

HUMANS; INTESTINAL ABSORPTION; MODELS, BIOLOGICAL; MODELS, STATISTICAL; MOLECULAR STRUCTURE; NEURAL NETWORKS (COMPUTER); PHARMACEUTICAL PREPARATIONS; PHARMACOKINETICS; REGRESSION ANALYSIS;

EID: 0037208305     PISSN: 00952338     EISSN: None     Source Type: Journal    
DOI: 10.1021/ci020013r     Document Type: Article

References (16)

1. Van de Waterbeend, H.; Camenisch, G.; Folkers, G.; Raevsky, O. A. Estimation of Caco-2 Cell Permeability Using Calculated Molecular Descriptors. Quant. Struct.-Act. Relat. 1996, 15, 480-490.
2. Palm, K.; Stenberg, P.; Luthman, K.; Artursson, P. Polar Molecular Surface Properties Predict the Intestinal Absorption of Drugs in Humans. Pharm. Res. 1997, 14, 568-571.
3. Clark, D. E. Rapid Calculation of Polar Molecular Surface Area and its Application to the Prediction of Transport Phenomena. 1. Prediction of Intestinal Absorption. J. Pharm. Sci. 1999, 88, 807-814.
4. Wessel, M. D.; Jurs, P. C.; Tolan, J. W.; Muskal, S. M. Prediction of Human Intestinal Absorption of Drug Compounds from Molecular Structure. J. Chem. Inf. Comput. Sci. 1998, 38, 726-735.
5. Specht, D. F. A General Regression Neural Network, IEEE Transactions on Neural Networks 1991, 2, 568-576.
6. Specht, D. F. Probabilistic Neural Networks. Neural Networks 1990, 3, 109-118.
7. Shaffer, R. E.; Rose-Pehrsson, S. L. Improved Probabilistic Neural Network Algorithm for Chemical Sensor Array Pattern Recognition. Anal. Chem. 1999, 71, 4263-4271.
8. Bishop, C. M. In Neural Networks for Pattern Recognition; Oxford University Press: New York, 1995; pp 164-193.
9. Parzen, E. On Estimation of a Probability Density Function and Mode. Ann. Math. Stat. 1962, 33, 1065-1076.
10. Clark, D. E. Rapid Calculation of Polar Molecular Surface Area and its Application to the Prediction of Transport Phenomena. 2. Prediction of Blood-Brain Barrier Penetration. J. Pharm. Sci. 1999, 88, 815-821.
11. ClogP version 4.51. Daylight Chemical Information Inc., 27401 Loa Altos, Suite #370, Mission Viejo, CA 92691.
12. StatView 5.0. SAS Institute Inc., 100 SAS Campus Drive Cary, NC 27513-2414.
13. NeuroShell 2. Ward Systems Group, Inc., Executive Park West 5 Hillcrest Drive Frederick, MD 21703.
14. Ertl, P.; Rohde, B.; Selzer, P. Fast Calculation of Molecular Polar Surface Area as a Sum of Fragment-Based Contributions and its Application to the Prediction of Drug Transport Properties. J. Med. Chem. 2000, 43, 3714-3717.
15. Sadowski, J.; Gasteiger, J.; Klebe, G. Comparison of Automatic Three-Dimensional Model Builders Using 639 X-Ray Structures. J. Chem. Inf. Comput. Sci. 1994, 34, 1000-1008.
16. Veber, D. F.; Johnson, S. R.; Cheng, H.-Y.; Smith, B. R.; Ward, K. W.; Kopple, K. D. Molecular Properties That Influence the Oral Bioavailability of Drug Candidates. J. Med. Chem. 2002, 45, 2615-2623.