Title:Predicting the Activity of Antimicrobial Peptides with Amino Acid Topological Information
VOLUME: 9 ISSUE: 1
Author(s):Mao Shu, Rui Yu, Yunru Zhang, Juan Wang, Li Yang, Li Wang and Zhihua Lin
Affiliation:School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, PR China
Keywords:Antimicrobial peptides (AMPs), VSTPV, Genetic algorithm (GA), Partial least square (PLS), Quantitative structure-
activity relationship (QSAR)
Abstract:In this paper, VSTPV, was recruited as a novel set of structural and topological descriptors derived from principal
component analysis (PCA) on 85 structural and topological variables of 166 coded and non-coded amino acids. By
using partial least squares (PLS), we applied VSTPV for the study of quantitative structure-activity models (QSARs) studies
on two peptide panels as 101 synthetic cationic Antimicrobial polypeptides (CAMELs), and 28 bovine lactoferricin-
(17–31)-pentadecapeptides (LFB). The results of QSARs models were superior to that of the earlier studies, with squared
correlative coefficient R2 and cross-validated Q2 of 0.783, 0.656; and 0.864, 0.793, respectively. So, VSTPV descriptors
were confirmed to be competent to extract information on 85 structural variables and to relate with biological activities.
