文章基本信息

标题：A Uniform In Vitro Efficacy Dataset to Guide Antimicrobial Peptide Design
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作者：Deepesh Nagarajan , Tushar Nagarajan , Neha Nanajkar ; Nagasuma Chandra
期刊名称：Data
印刷版ISSN：2306-5729
出版年度：2019
卷号：4
期号：1
页码：27-39
DOI：10.3390/data4010027
出版社：MDPI Publishing
摘要：Antimicrobial peptides are ubiquitous molecules that form the innate immune system of organisms across all kingdoms of life. Despite their prevalence and early origins, they continue to remain potent natural antimicrobial agents. Antimicrobial peptides are therefore promising drug candidates in the face of overwhelming multi-drug resistance to conventional antibiotics. Over the past few decades, thousands of antimicrobial peptides have been characterized in vitro, and their efficacy data are now available in a multitude of public databases. Computational antimicrobial peptide design attempts typically use such data. However, utilizing heterogenous data aggregated from different sources presents significant drawbacks. In this report, we present a uniform dataset containing 20 antimicrobial peptides assayed against 30 organisms of Gram-negative, Gram-positive, mycobacterial, and fungal origin. We also present circular dichroism spectra for all antimicrobial peptides. We draw simple inferences from this data, and we discuss what characteristics are essential for antimicrobial peptide efficacy. We expect our uniform dataset to be useful for future projects involving computational antimicrobial peptide design.
关键词：antimicrobial peptides; bioinformatics; drug discovery antimicrobial peptides ; bioinformatics ; drug discovery