- 作者: Shushen Liua+, Chunsheng Yinb, Shaoxi Caia and Zhiliang Lia
- 中文摘要:
aCollege of Biomedical Engineering, Chongqing University, Chongqing 400044, P.R. China
bDepartment of Applied Chemistry, University of Science and Technology of China,
Hefei, 230026, P.R. China
A novel molecular holographic distance vector (MHDV) is proposed to characterize the structures of the peptide molecules and employed to relate to the biological activities of the peptides by means of principal component regression (PCR) method. For two panels of dipeptides, the correlation coefficient (R) between the estimated and the observed activities are respectively 0.9370 and 0.9585 and the R obtained by cross-validation method are respectively 0.8676 and 0.9295, which is the best result to date for the two sets of dipeptides. The novel MHDV descriptor only depends on distance matrix and various atomic types of non-hydrogen atoms in a molecule and requires no 3D structural information, so, it is a very simple and easy to use descriptor. - 英文摘要: --
- 中文關鍵字: --
- 英文關鍵字: --