title: QSAR modeling and design of cationic antimicrobial peptides based on structural properties of amino acids.
abstract: Drug resistance to existing antibiotics poses alarming threats to global public health, which inspires heightened interests in searching for new antibiotics, including antimicrobial peptides (AMPs). Accurate prediction of antibacterial activities of AMPs may expedite novel AMP design and reduce the costs and efforts involved in laboratory screening. In the present study, a novel quantitative prediction method of AMP was established by quantitative structure-activity relationship (QSAR) modeling based on the physicochemical properties of amino acids. The indices of these physicochemical properties were used to define AMP. The structural variables were optimized by stepwise regression (STR). Three series of AMPs from the QSAR model were constructed by multiple linear regressions (MLR). These QSAR models showed good performance in reliability and predictability. The normalized regression coefficients of the QSAR model and the contribution of amino acids at each position of AMP may determine the suitableness of a particular residue at any given position. QSAR models constructed by STR-MLR should prove to be useful tools in peptide design with respect to the calculation, explanation, good and reliable performance, and definition of physiochemical properties.
authors.affiliation: Institute of Sericulture and Systems Biology, Southwest University, Chongqing 400716, P.R. China.
authors.forename: Yuanqiang
authors.initials: Y
authors.lastname: Wang
authors.forename: Yuan
authors.initials: Y
authors.lastname: Ding
authors.forename: Haixia
authors.initials: H
authors.lastname: Wen
authors.forename: Yong
authors.initials: Y
authors.lastname: Lin
authors.forename: Yong
authors.initials: Y
authors.lastname: Hu
authors.forename: Ya
authors.initials: Y
authors.lastname: Zhang
authors.forename: Qingyou
authors.initials: Q
authors.lastname: Xia
authors.forename: Zhihua
authors.initials: Z
authors.lastname: Lin
mesh_terms: D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry* / Q000494:pharmacology; D000818:Animals; D000900:Anti-Bacterial Agents / Q000737:chemistry* / Q000494:pharmacology; D023181:Antimicrobial Cationic Peptides / Q000737:chemistry* / Q000494:pharmacology; D001419:Bacteria / Q000187:drug effects; D001424:Bacterial Infections / Q000188:drug therapy; D015195:Drug Design; D006801:Humans; D008954:Models, Biological; D008969:Molecular Sequence Data; D021281:Quantitative Structure-Activity Relationship
chemical_list: D000596:Amino Acids; D000900:Anti-Bacterial Agents; D023181:Antimicrobial Cationic Peptides