Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 26Antimicrobial Peptides and ActivitiesAntimicrobial agents and applicationsChemical Synthesis and Analysis

The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.

Novel Antimicrobial Peptides Designed Using a Recurrent Neural Network Reduce Mortality in Experimental Sepsis

Open access
Bolatchiev, Albert, Baturin, Vladimir, Shchetinin, Evgeny, Bolatchieva, Elizaveta·2022·Antibiotics
DOI 10.3390/antibiotics11030411PMC PMC8944797

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

The search and development of new antibiotics is relevant due to widespread antibiotic resistance. One of the promising strategies is the de novo design of novel antimicrobial peptides. The amino acid sequences of 198 novel peptides were obtained using a generative long short-term memory recurrent neural network (LSTM RNN). To assess their antimicrobial effect, we synthesized five out of 198 generated peptides. The PEP-38 and PEP-137 peptides were active in vitro against carbapenem-resistant isolates of Klebsiella aerogenes and K. pneumoniae. PEP-137 was also active against Pseudomonas aeruginosa. The remaining three peptides (PEP-36, PEP-136 and PEP-174) showed no antibacterial effect. Then the effect of PEP-38 and PEP-137 (a single intraperitoneal administration of a 100 μg dose 30 min after infection) on animal survival in an experimental murine model of K. pneumoniae-induced sepsis was investigated. As a control, two groups of mice were used: one received sterile saline, and the other received inactive in vitro PEP-36 (a single 100 μg dose). The PEP-36 peptide was shown to provide the highest survival rate (66.7%). PEP-137 showed a survival rate of 50%. PEP-38 was found to be ineffective. The data obtained can be used to develop new antibacterial peptide drugs to combat antibiotic resistance.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/antibiotics11030411

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Comparison of peptide characteristics between the training data (Training, orange), the generated sequences (Sampled, blue), the pseudo-random sequences with the same amino acid distribution as in the training set (Ran, purple), and the manually created hypothetical amphipathic helices (Hel, green). The horizontal dashed lines represent the mean (violin plots) and median (box plots) values; the whiskers extend to the outermost non-outlier data points. Graphs from left to right: Eisenberg hydrophobicity, Eisenberg hydrophobic moment, and sequence length. The figure was generated using the modlAMP’s GlobalAnalysis.plot_summary method in Python [16].
Figure 1 Comparison of peptide characteristics between the training data (Training, orange), the generated sequences (Sampled, blue), the pseudo-random sequences with the same amino acid distribution as in the training set (Ran, purple), and the manually created hypothetical amphipathic helices (Hel, green). The horizontal dashed lines represent the mean (violin plots) and median (box plots) values; the whiskers extend to the outermost non-outlier data points. Graphs from left to right: Eisenberg hydrophobicity, Eisenberg hydrophobic moment, and sequence length. The figure was generated using the modlAMP’s GlobalAnalysis.plot_summary method in Python [16].CC BY · PubMed Central
Figure 2 Comparison of probability of survival (%) in each group: control (sterile saline), PEP-36, PEP-38 and PEP-137. The peptides were injected once in a dose of 100 μg 30 min after infection of mice with 6.75 × 108 CFU suspension of a carbapenem-resistant isolate of K. pneumoniae. *—significant differences from the control group using the Kaplan-Meier method and Log-rank (Mantel-Cox) test.
Figure 2 Comparison of probability of survival (%) in each group: control (sterile saline), PEP-36, PEP-38 and PEP-137. The peptides were injected once in a dose of 100 μg 30 min after infection of mice with 6.75 × 108 CFU suspension of a carbapenem-resistant isolate of K. pneumoniae. *—significant differences from the control group using the Kaplan-Meier method and Log-rank (Mantel-Cox) test.CC BY · PubMed Central
Figure 3 Visual comparison of the structures of LL-37 (yellow; PDB ID: 2K6O) and synthesized peptides: PEP-137—blue, PEP-38—red, PEP-36—green (by AlphaFold).
Figure 3 Visual comparison of the structures of LL-37 (yellow; PDB ID: 2K6O) and synthesized peptides: PEP-137—blue, PEP-38—red, PEP-36—green (by AlphaFold).CC BY · PubMed Central
Figure 4 Initial and final snapshot of peptide-membrane system before and after 225 ns of MD simulation. The membrane is shown in lines (cyan) and the peptides are shown in helical structure (colored according to the type of amino acids). Phosphate atoms of the membrane are shown in gray color.
Figure 4 Initial and final snapshot of peptide-membrane system before and after 225 ns of MD simulation. The membrane is shown in lines (cyan) and the peptides are shown in helical structure (colored according to the type of amino acids). Phosphate atoms of the membrane are shown in gray color.CC BY · PubMed Central
Figure 5 Top view of the peptide-membrane system (left) at 225 ns of MD simulation showing the unravelling of the helical structure. Phosphate atoms of the membrane are shown in gray color. Side view (right) showing the penetration of peptide at 225 ns.
Figure 5 Top view of the peptide-membrane system (left) at 225 ns of MD simulation showing the unravelling of the helical structure. Phosphate atoms of the membrane are shown in gray color. Side view (right) showing the penetration of peptide at 225 ns.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 42 references

Research works printed but not linked: 1

  1. Baturin, 2017, The Prognosis and Investigation of α-Defensin-1 (HNP-1) Influence on Morphological Changes of Staphylococcus Aureus Cells by the Atomic-Force Microscopy Data, Med. News North Cauc., 12, 290

Cited by

Metadata

Authors
Bolatchiev, A., Baturin, V., Shchetinin, E., & Bolatchieva, E.
Affiliations
  • Stavropol State Medical University (RU)
  • Department of Clinical Pharmacology, Stavropol State Medical University, 355000 Stavropol, Russia
Corresponding author
Bolatchiev, Albert
ORCID
Venue
Antibiotics
Publisher
MDPI AG
Published
2022-03-18
Volume
11
Issue
3
Pages
411
ISSN
2079-6382 (ISSN-L)
DOI
10.3390/antibiotics11030411
PMC
PMC8944797
OpenAlex
W4220710498
Cited by
26
References
42
Citations by year
2026: 5 · 2025: 5 · 2024: 6 · 2023: 7 · 2022: 3
FWCI
3.28
Type
journal article
Language
en
Open access
Licence
Locations
  • Antibiotics (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
Russian Science Foundation (20-75-00004)
Topics
  • Life Sciences › Immunology and Microbiology › Microbiology › Antimicrobial Peptides and Activities
  • Life Sciences › Immunology and Microbiology › Applied Microbiology and Biotechnology › Antimicrobial agents and applications
  • Physical Sciences › Chemistry › Organic Chemistry › Chemical Synthesis and Analysis
Keywords
antimicrobial peptides, de novo peptide design, recurrent neural networks, long short-term memory, antibiotic resistance, carbapenem resistance, Klebsiella pneumoniae, Enterobacter aerogenes, Pseudomonas aeruginosa, sepsis, murine sepsis model, survival rate, antibacterial activity

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.