PREDICTION OF HYDROPHOBIC PARTITION-COEFFICIENTS OF NUCLEOSIDES AND NUCLEOSIDE BASES BY ARTIFICIAL NEURAL-NETWORK

被引：0

作者：

ZHANG, XD ^{[1
]}

LIU, QT ^{[1
]}

ZHANG, SG ^{[1
]}

机构：

[1] BINZHOU TEACHER TRAINING COLL,DEPT CHEM,BINZHOU,PEOPLES R CHINA

来源：

CHEMICAL JOURNAL OF CHINESE UNIVERSITIES-CHINESE | 1995年 / 16卷 / 09期

关键词：

ANN; PARTITION COEFFICIENTS; NUCLEOSIDE; NUCLEOSIDE BASE;

D O I：

暂无

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

A back-propagation artificial neural network(ANN) was trained on the Gramer's parameters to predict the IgP(logarithm of ''1-octanol to water'' partition coefficients) of nucleosides and nucleoside bases. The prediction results show that the ANN method is better than other methods (BLgP, ClgP, AlgP) for this class of compounds. The effect of conformational flexibility or intramolecular hydrogen bonding on the IgP of nucleoside compounds is discussed.

引用

页码：1360 / 1363

页数：4

共 6 条

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