Prediction of partition coefficient based on atom-type electrotopological state indices

被引：51

作者：

Huuskonen, JJ

Villa, AEP

Tetko, IV

机构：

[1] Univ Lausanne, Inst Physiol, Lab Neuroheurist, CH-1005 Lausanne, Switzerland

[2] Univ Helsinki, Dept Pharm, Div Pharmaceut Chem, FIN-00014 Helsinki, Finland

[3] Inst Bioorgan & Petr Chem, Dept Biomed, UA-253660 Kiev, Ukraine

来源：

JOURNAL OF PHARMACEUTICAL SCIENCES | 1999年 / 88卷 / 02期

关键词：

D O I：

10.1021/js980266s

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

The aim of this study was to determine the efficacy of atom-type electrotopological state indices for estimation of the octanol-water partition coefficient (log P) values in a set of 345 drug compounds or related complex chemical structures. Multilinear regression analysis and artificial neural networks were used to construct models based on molecular weights and atom-type electrotopological state indices. Both multilinear regression and artificial neural networks provide reliable log P estimations. For the same set of parameters, application of neural networks provided better prediction ability for training and test sets. The present study indicates that atom-type electrotopological state indices offer valuable parameters for fast evaluation of octanol-water partition coefficients that can be applied to screen large databases of chemical compounds, such as combinatorial libraries.

引用

页码：229 / 233

页数：5

共 20 条

[1] Molecular size based approach to estimate partition properties for organic solutes [J].

Bodor, N ;

Buchwald, P .

JOURNAL OF PHYSICAL CHEMISTRY B, 1997, 101 (17) :3404-3412

[2] Assessment of n-octanol/water partition coefficient: When is the assessment reliable? [J].

Gombar, VK ;

Enslein, K .

JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 1996, 36 (06) :1127-1134

[3] Prediction of water-octanol partition coefficients using theoretical descriptors derived from the molecular surface area and the electrostatic potential [J].

Haeberlein, M ;

Brinck, T .

JOURNAL OF THE CHEMICAL SOCIETY-PERKIN TRANSACTIONS 2, 1997, (02) :289-294

[4] Boiling point and critical temperature of a heterogeneous data set: QSAR with atom type electrotopological state indices using artificial neural networks [J].

Hall, LH ;

Story, CT .

JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 1996, 36 (05) :1004-1014

[5] ELECTROTOPOLOGICAL STATE INDEXES FOR ATOM TYPES - A NOVEL COMBINATION OF ELECTRONIC, TOPOLOGICAL, AND VALENCE STATE INFORMATION [J].

HALL, LH ;

KIER, LB .

JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 1995, 35 (06) :1039-1045

[6]

Hansch C., 1979, Substituent constants for correlation analysis in chemistry and biology

[7]

Hansch C., 1995, Exploring QSAR - Hydrophobic, Electronic, and Steric Constants, V2

[8] Neural network modeling for estimation of the aqueous solubility of structurally related drugs [J].

Huuskonen, J ;

Salo, M ;

Taskinen, J .

JOURNAL OF PHARMACEUTICAL SCIENCES, 1997, 86 (04) :450-454

[9] Aqueous solubility prediction of drugs based on molecular topology and neural network modeling [J].

Huuskonen, J ;

Salo, M ;

Taskinen, J .

JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 1998, 38 (03) :450-456

[10] AN ELECTROTOPOLOGICAL-STATE INDEX FOR ATOMS IN MOLECULES [J].

KIER, LB ;

HALL, LH .

PHARMACEUTICAL RESEARCH, 1990, 7 (08) :801-807

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