Use of artificial intelligence in the design of small peptide antibiotics effective against a broad spectrum of highly antibiotic-resistant superbugs.
By Artem Cherkasov, K. Hilpert, H. Jenssen, Christopher D. Fjell, Matthew Waldbrook, Sarah C. Mullaly, R. Volkmer, Robert E. W. Hancock. ACS Chemical Biology, 2009
349 citations recorded by the source corpus.
Subfields: Immunology, Microbiology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/3f3c6cd3d7699257634fd99fad70a8b4e416b30e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Immunology
In Microbiology
In Molecular Biology
- Christopher D. Fjell
- Robert E. W. Hancock
- Jan A. Hiss
- S. Gellatly
- Amy T. Y. Yeung
- Gisbert Schneider
- Roderick E. Hubbard
- Abhinav Vishnu
Citations in the corpus
- Designing antimicrobial peptides: form follows function (2011, methodology): “By replacing MIC values with such surrogate measures 148 , and combining these with highthroughput analysis and relatively inexpensive peptide array synthesis on cellulose sheets, a set of peptides with more than 1,400 distinct sequences was assayed for activity 149,150 .”
- Multifunctional cationic host defence peptides and their clinical applications (2011, background): “Regarding cost of goods increasingly practical recombinant DNA expression strategies are starting to impact on cost of goods [7, 55]; furthermore, the use of peptide array and advanced computational strategies [ 13 ] and addition of fatty acyl chains have led to much smaller broad-spectrum peptides.”
- Antimicrobial Peptides (2013, neutral): “against antibiotic-resistant superbugs [190].”