title: Predicting the activity of antimicrobial peptides with amino acid topological information.
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.
authors: School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, PR China.
authors: Mao
authors: M
authors: Shu
authors: Rui
authors: R
authors: Yu
authors: Yunru
authors: Y
authors: Zhang
authors: Juan
authors: J
authors: Wang
authors: Li
authors: L
authors: Yang
authors: Li
authors: L
authors: Wang
authors: Zhihua
authors: Z
authors: Lin
mesh_terms: D000596:Amino Acids / Q000737:chemistry*; D000818:Animals; D000890:Anti-Infective Agents / Q000737:chemistry* / Q000494:pharmacology*; D002417:Cattle; D060326:Chemistry Techniques, Synthetic; D008826:Microbial Sensitivity Tests; D009154:Mutation; D010455:Peptides / Q000737:chemistry* / Q000235:genetics / Q000494:pharmacology*; D025341:Principal Component Analysis; D021281:Quantitative Structure-Activity Relationship; D013211:Staphylococcus aureus / Q000187:drug effects*
chemical_list: D000596:Amino Acids; D000890:Anti-Infective Agents; D010455:Peptides