A Uniform In Vitro Efficacy Dataset to Guide Antimicrobial Peptide Design

Deepesh Nagarajan, Tushar Nagarajan, Neha Nanajkar and Nagasuma Chandra
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Deepesh Nagarajan: Department of Biochemistry, Indian Institute of Science, Bangalore 560012, India
Tushar Nagarajan: Department of Computer Science, University of Texas, Austin, TX 78751, USA
Neha Nanajkar: Department of Biochemistry, Indian Institute of Science, Bangalore 560012, India
Nagasuma Chandra: Department of Biochemistry, Indian Institute of Science, Bangalore 560012, India

Data, 2019, vol. 4, issue 1, 1-13

Abstract: 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.

Keywords: antimicrobial peptides; bioinformatics; drug discovery (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2019
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