Next Article in Journal
Vehicular Ad Hoc Network (VANET) Connectivity Analysis of a Highway Toll Plaza
Previous Article in Journal
A Dataset for Comparing Mirrored and Non-Mirrored Male Bust Images for Facial Recognition
Open AccessData Descriptor

A Uniform In Vitro Efficacy Dataset to Guide Antimicrobial Peptide Design

Department of Biochemistry, Indian Institute of Science, Bangalore 560012, India
Department of Computer Science, University of Texas, Austin, TX 78751, USA
Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
Author to whom correspondence should be addressed.
Received: 16 December 2018 / Revised: 1 February 2019 / Accepted: 1 February 2019 / Published: 10 February 2019
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. View Full-Text
Keywords: antimicrobial peptides; bioinformatics; drug discovery antimicrobial peptides; bioinformatics; drug discovery
Show Figures

Figure 1

MDPI and ACS Style

Nagarajan, D.; Nagarajan, T.; Nanajkar, N.; Chandra, N. A Uniform In Vitro Efficacy Dataset to Guide Antimicrobial Peptide Design. Data 2019, 4, 27.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop