QSAR Modeling and Design of Cationic Antimicrobial Peptides Based on Structural Properties of Amino Acids

Author(s): Yuanqiang Wang, Yuan Ding, Haixia Wen, Yong Lin, Yong Hu, Ya Zhang, Qingyou Xia, Zhihua Lin

Journal Name: Combinatorial Chemistry & High Throughput Screening
Accelerated Technologies for Biotechnology, Bioassays, Medicinal Chemistry and Natural Products Research

Volume 15 , Issue 4 , 2012

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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.

Keywords: Antimicrobial peptides (AMPs), descriptor, normalized regression coefficients (NRCs), peptide design, quantitative structural activity relationship (QSAR), structural characterization, drug resistance, antibacterial activities, amino acids, multiple linear regressions, peptides, cysteine residues, lipopolysaccharides, QSAR, normalized regression coefficients, novispirin

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Article Details

Year: 2012
Page: [347 - 353]
Pages: 7
DOI: 10.2174/138620712799361807
Price: $65

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