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题名: Prediction of standard Gibbs energies of the transfer of peptide anions from aqueous solution to nitrobenzene based on support vector machine and the heuristic method
作者: Feng, L; Zhang, XY; Zhang, HX(张海霞); Zhang, RS(张瑞生); Liu, MC; Hu, ZD(胡之德); Fan, BT
收录类别: SCIE ; PubMed ; MEDLINE ; BIOSIS
出版日期: 2006-01
刊名: JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
卷号: 20, 期号:1, 页码:1-11
出版者: SPRINGER
出版地: DORDRECHT
英文摘要: Quantitative structure-property relationship (QSPR) method was performed for the prediction of the standard Gibbs energies (Delta G(theta)) of the transfer of peptide anions from aqueous solution to nitrobenzene. Descriptors calculated from the molecular structures alone were used to represent the characteristics of the peptides. The four molecular descriptors selected by the heuristic method (HM) in COmprehensive DEscriptors for Structural and Statistical Analysis (CODESSA) were used as inputs for support vector machine (SVM) and radial basis function neural networks (RNFNN). The results obtained by the novel machine learning technique, SVM, were compared with those obtained by HM and RBFNN. The root mean squared errors (RMS) of the training, predicted and overall data sets are 2.192, 2.541 and 2.267 unit (kJ/mol) for HM, 1.604, 2.478 and 1.817 unit (kJ/mol) for RBFNN and 1.5621, 2.364 and 1.756 unit (kJ/mol) for SVM, respectively. The prediction results were in agreement with the experimental values. This paper provided a potential method for predicting the physiochemical property (Delta G(theta)) of various small peptides.
关键词: HM ; QSPR ; peptide ; SVM ; Delta G(theta)
作者部门: Lanzhou Univ, Dept Comp Sci, Lanzhou 730000, Peoples R China ; Lanzhou Univ, Dept Chem, Lanzhou 730000, Peoples R China ; Univ Paris 7 Denis Diderot, ITODYS 1, F-75005 Paris, France
通讯作者: Zhang, RS (reprint author), Lanzhou Univ, Dept Comp Sci, Lanzhou 730000, Peoples R China.
学科分类: Biochemistry & Molecular Biology; Biophysics; Computer Science
文章类型: Article
语种: 英语
DOI: 10.1007/s10822-005-9031-1
ISSN号: 0920-654X
WOS记录号: WOS:000238317300001
PM记录号: 16622797
BIOSIS记录号: BIOSIS:PREV200600471799
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内容类型: 期刊论文
URI标识: http://ir.lzu.edu.cn/handle/262010/116088
Appears in Collections:信息科学与工程学院_期刊论文

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Recommended Citation:
Feng, L,Zhang, XY,Zhang, HX,et al. Prediction of standard Gibbs energies of the transfer of peptide anions from aqueous solution to nitrobenzene based on support vector machine and the heuristic method[J]. JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN,2006,20(1):1-11.
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