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基于启发式方法和支持向量机对扩散速率受限药物的人体口服吸收进行预测。

The prediction of human oral absorption for diffusion rate-limited drugs based on heuristic method and support vector machine.

作者信息

Liu H X, Hu R J, Zhang R S, Yao X J, Liu M C, Hu Z D, Fan B T

机构信息

Department of Chemistry, Lanzhou University, Lanzhou 730000, P.R. China.

出版信息

J Comput Aided Mol Des. 2005 Jan;19(1):33-46. doi: 10.1007/s10822-005-0095-8.

DOI:10.1007/s10822-005-0095-8
PMID:16059665
Abstract

Support vector machine (SVM), as a novel machine learning technique, was used for the prediction of the human oral absorption for a large and diverse data set using the five descriptors calculated from the molecular structure alone. The molecular descriptors were selected by heuristic method (HM) implemented in CODESSA. At the same time, in order to show the influence of different molecular descriptors on absorption and to well understand the absorption mechanism, HM was used to build several multivariable linear models using different numbers of molecular descriptors. Both the linear and non-linear model can give satisfactory prediction results: the square of correlation coefficient R(2) was 0.78 and 0.86 for the training set, and 0.70 and 0.73 for the test set respectively. In addition, this paper provides a new and effective method for predicting the absorption of the drugs from their structures and gives some insight into structural features related to the absorption of the drugs.

摘要

支持向量机（SVM）作为一种新型机器学习技术，被用于依据仅从分子结构计算得出的五个描述符，对一个庞大且多样的数据集进行人体口服吸收预测。分子描述符通过CODESSA中实施的启发式方法（HM）进行选择。同时，为了展示不同分子描述符对吸收的影响并深入理解吸收机制，HM被用于构建使用不同数量分子描述符的多个多变量线性模型。线性和非线性模型均能给出令人满意的预测结果：训练集的相关系数R²分别为0.78和0.86，测试集的相关系数R²分别为0.70和0.73。此外，本文提供了一种从药物结构预测其吸收的新的有效方法，并对与药物吸收相关的结构特征给出了一些见解。

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本文引用的文献

1
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J Chem Inf Comput Sci. 2004 May-Jun;44(3):931-9. doi: 10.1021/ci034233w.
2
An accurate QSPR study of O-H bond dissociation energy in substituted phenols based on support vector machines.基于支持向量机的取代酚中O-H键解离能的精确QSPR研究。
J Chem Inf Comput Sci. 2004 Mar-Apr;44(2):669-77. doi: 10.1021/ci034248u.
3
Prediction of the isoelectric point of an amino acid based on GA-PLS and SVMs.
Int J Mol Sci. 2010 Sep 20;11(9):3413-33. doi: 10.3390/ijms11093413.
4
Predicting infinite dilution activity coefficients of organic compounds in water by quantum-connectivity descriptors.用量子连接性描述符预测有机化合物在水中的无限稀释活度系数。
J Comput Aided Mol Des. 2006 Sep;20(9):539-48. doi: 10.1007/s10822-006-9079-6. Epub 2006 Oct 19.
5
Recent progress in the computational prediction of aqueous solubility and absorption.水溶性和吸收的计算预测方面的最新进展。
AAPS J. 2006 Feb 3;8(1):E27-40. doi: 10.1208/aapsj080104.
基于遗传算法-偏最小二乘法和支持向量机预测氨基酸的等电点
J Chem Inf Comput Sci. 2004 Jan-Feb;44(1):161-7. doi: 10.1021/ci034173u.
4
A general treatment of solubility. 1. The QSPR correlation of solvation free energies of single solutes in series of solvents.
J Chem Inf Comput Sci. 2003 Nov-Dec;43(6):1794-805. doi: 10.1021/ci034120c.
5
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J Chem Inf Comput Sci. 2003 Jul-Aug;43(4):1288-96. doi: 10.1021/ci0340355.
6
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J Chem Inf Comput Sci. 2003 May-Jun;43(3):900-7. doi: 10.1021/ci0256438.
7
Prediction of the oral absorption of low-permeability drugs using small intestine-like 2/4/A1 cell monolayers.
Pharm Res. 2003 Mar;20(3):397-405. doi: 10.1023/a:1022699920043.
8
A QSPR study of O-H bond dissociation energy in phenols.酚类中O-H键解离能的定量结构-性质关系研究
J Chem Inf Comput Sci. 2003 Mar-Apr;43(2):637-42. doi: 10.1021/ci025632e.
9
Absorption classification of oral drugs based on molecular surface properties.基于分子表面性质的口服药物吸收分类
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