文章基本信息

标题：Novel 3D Structure Based Model for Activity Prediction and Design of Antimicrobial Peptides
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作者：Shicai Liu ; Jingxiao Bao ; Xingzhen Lao 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2018
卷号：8
期号：1
页码：11189
DOI：10.1038/s41598-018-29566-5
语种：English
出版社：Springer Nature
摘要：The emergence and worldwide spread of multi-drug resistant bacteria makes an urgent challenge for the development of novel antibacterial agents. A perspective weapon to fight against severe infections caused by drug-resistant microorganisms is antimicrobial peptides (AMPs). AMPs are a diverse class of naturally occurring molecules that are produced as a first line of defense by all multi-cellular organisms. Limited by the number of experimental determinate 3D structure, most of the prediction or classification methods of AMPs were based on 2D descriptors, including sequence, amino acid composition, peptide net charge, hydrophobicity, amphiphilic, etc. Due to the rapid development of structural simulation methods, predicted models of proteins (or peptides) have been successfully applied in structure based drug design, for example as targets of virtual ligand screening. Here, we establish the activity prediction model based on the predicted 3D structure of AMPs molecule. To our knowledge, it is the first report of prediction method based on 3D descriptors of AMPs. Novel AMPs were designed by using the model, and their antibacterial effect was measured by in vitro experiments.