Design of antimicrobial peptides containing non-proteinogenic amino acids using multi-objective Bayesian optimisation-Reference-Cited by-同舟云学术

Design of antimicrobial peptides containing non-proteinogenic amino acids using multi-objective Bayesian optimisation

Published:2023 Issue:5 Volume:2 Page:1347-1353
ISSN:2635-098X
Container-title:Digital Discovery
language:en
Short-container-title:Digital Discovery

Author:

Murakami Yuki¹^ORCID,Ishida Shoichi¹^ORCID,Demizu Yosuke¹²^ORCID,Terayama Kei¹³⁴^ORCID

Affiliation:

1. Graduate School of Medical Life Science, Yokohama City University, 1-7-29, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan

2. Division of Organic Chemistry, National Institute of Health Sciences, 3-25-26, Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa 210-9501, Japan

3. RIKEN Center for Advanced Intelligence Project, 1-4-1, Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan

4. MDX Research Center for Element Strategy, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, Kanagawa, 226-8501, Japan

Abstract

MODAN is a multi-objective Bayesian framework for automated design of antimicrobial peptides containing various non-proteinogenic amino acids and side-chain stapling.

Funder

Ministry of Education, Culture, Sports, Science and Technology

Japan Society for the Promotion of Science

Japan Agency for Medical Research and Development

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2023/DD/D3DD00090G

Reference57 articles.

1. Molecular engineering of antimicrobial peptides: microbial targets, peptide motifs and translation opportunities

2. Evaluation of short synthetic antimicrobial peptides for treatment of drug-resistant and intracellular Staphylococcus aureus

3. Role and modulation of the secondary structure of antimicrobial peptides to improve selectivity

4. An amphipathic peptide with antibiotic activity against multidrug-resistant Gram-negative bacteria

5. Foldamers: A Manifesto

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