Novel antimicrobial peptide discovery using machine learning and biophysical selection of minimal bacteriocin domains-Reference-Cited by-同舟云学术

Novel antimicrobial peptide discovery using machine learning and biophysical selection of minimal bacteriocin domains

Published:2019-09-04 Issue:1 Volume:81 Page:43-51
ISSN:0272-4391
Container-title:Drug Development Research
language:en
Short-container-title:Drug Dev Res

Author:

Fields Francisco R.¹²³^ORCID,Freed Stefan D.¹²³,Carothers Katelyn E.¹²,Hamid Md Nafiz⁴⁵,Hammers Daniel E.¹²,Ross Jessica N.¹²,Kalwajtys Veronica R.¹,Gonzalez Alejandro J.¹,Hildreth Andrew D.¹,Friedberg Iddo⁴⁵^ORCID,Lee Shaun W.¹²³

Affiliation:

1. Department of Biological Sciences University of Notre Dame Notre Dame Indiana

2. Eck Institute for Global Health University of Notre Dame Notre Dame Indiana

3. Chemistry‐Biochemistry‐Biology Interface Program University of Notre Dame Notre Dame Indiana

4. Department of Veterinary Microbiology and Preventive Medicine Iowa State University Ames Iowa

5. Bioinformatics and Computational Biology Program Iowa State University Ames Iowa

Funder

Eck Institute for Global Health, University of Notre Dame

National Science Foundation

National Institutes of Health

Publisher

Wiley

Subject

Drug Discovery

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ddr.21601

Reference39 articles.

1. Bacteriocins of lactic acid bacteria: extending the family

2. Design, NMR characterization and activity of a 21-residue peptide fragment of bacteriocin AS-48 containing its putative membrane interacting region

3. Cationic antimicrobial peptides as potential new therapeutic agents in neonates and children

4. Interaction of W-Substituted Analogs of Cyclo-RRRWFW with Bacterial Lipopolysaccharides: the Role of the Aromatic Cluster in Antimicrobial Activity

5. The Biofilm-Specific Antibiotic Resistance Gene ndvB Is Important for Expression of Ethanol Oxidation Genes in Pseudomonas aeruginosa Biofilms

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