A new SVRDF 3D-descriptor of amino acids and its application to peptide quantitative structure activity relationship.
- Author:
Jian-Bo TONG
1
;
Sheng-Wan ZHANG
;
Su-Li CHENG
;
Gai-Xian LI
Author Information
1. College of Chemistry and Chemical Engineering, Shanxi University, Taiyuan 030006, China.
- Publication Type:Journal Article
- MeSH:
Amino Acid Sequence;
Amino Acids;
chemistry;
Dipeptides;
chemistry;
pharmacology;
Least-Squares Analysis;
Models, Chemical;
Oxytocin;
analogs & derivatives;
chemistry;
pharmacology;
Peptides;
chemistry;
pharmacology;
Principal Component Analysis;
methods;
Quantitative Structure-Activity Relationship;
Thromboplastin;
antagonists & inhibitors;
chemistry;
pharmacology
- From:
Acta Pharmaceutica Sinica
2007;42(1):40-46
- CountryChina
- Language:Chinese
-
Abstract:
To establish a new amino acid structure descriptor that can be applied to polypeptide quantitative structure activity relationship (QSAR) studies, a new descriptor, SVRDF, was derived from a principal components analysis of a matrix of 150 radial distribution function index of amino acids. The scale was then applied in three panels of peptide QSAR that were molded by partial least squares regression. The obtained models with the correlation coefficients (R2(cum)), cross-validation correlation coefficients (Q2(cum)) were 0.766 and 0.724 for 48 bitter tasting dipeptides; 0.941 and 0.811 for 21 oxytocin analogues; 0.996 and 0.919 for 20 thromboplastin inhibitors. Satisfactory results showed that information related to biological activity can be systemically expressed by SVRDF scales, which may be an useful structural expression methodology for the study of peptides QSAR.
