Antimicrobial Peptides - Discovery, Structure, Function, and Application

A special issue of Antibiotics (ISSN 2079-6382). This special issue belongs to the section "Antimicrobial Peptides".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 13363

Special Issue Editors


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Guest Editor
Institute of Science and Environment, University of Saint Joseph, Rua de Londres 106, Macau
Interests: computer-aided drug design; docking; molecular dynamics; cheminformatics; machine learning; therapeutic peptides; GPCR; ion channels

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Guest Editor
Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa, ON K1N 6N5, Canada
Interests: molecular and cellular microbiology; host-pathogen interactions; anti-infective drugs and alternative therapeutic strategies

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Guest Editor
Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand
Interests: bioinformatics; immunoinformatics; machine learning; drug discovery and development

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Guest Editor
Structural Bioinformatics & Molecular Modeling Lab, Faculty of Pharmacy, Universiti Teknologi MARA (UiTM), 42300, Bandar Puncak Alam, Selangor, Malaysia
Interests: computer-aided drug design; docking; molecular dynamics; membrane proteins; nuclear receptors; COVID-19 inhibitors; flaviviridae virus

Special Issue Information

Dear Colleagues,

The emergence of multidrug-resistant bacteria (MDR) has become a global health crisis, affecting our ability to treat infectious diseases and leading to increasing morbidity and mortality. New treatment options are therefore urgently needed to eradicate MDR bacteria. Among them, antimicrobial peptides (AMPs) are emerging as promising antibiotic agents due to their remarkable broad-spectrum antibacterial properties and lower probability of bacterial resistance development. To date, more than 3000 AMPs have been discovered from nature, and many more chemically modified synthetic peptides with improved biological activities have been developed. Nevertheless, the successful translational applications of AMPs are very limited. On the one hand, our incomplete understanding of how these peptides work hinders their development into therapeutics. On the other hand, the relatively high production costs, short half-life, low bioavailability, and potential toxic side effects of AMPs compared to conventional small molecule drugs make them less attractive to study through the established drug discovery pipeline. Addressing these challenges requires a deeper understanding of AMPs and innovative techniques to discover and design potent AMPs that are relevant to clinical applications.

In this Special Issue, we aim to collect and disseminate the latest experimental and computational works on the discovery and characterization of AMPs, in terms of their structures, functions and potential applications. Manuscripts from original research and review articles are invited. Submitted manuscripts will be peer-reviewed to ensure high quality of contributions in this issue.

Prof. Dr. Shirley W. I. Siu
Prof. Dr. François-Xavier Campbell-Valois
Prof. Dr. Watshara Shoombuatong
Dr. Siti Azma Jusoh
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Antibiotics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • antimicrobial peptides
  • antibacterial peptides
  • antibiotics
  • bioinformatics
  • host defense peptides
  • multidrug-resistance bacteria
  • peptide sequence
  • peptide structure
  • peptide design
  • peptide drug discovery
  • peptide therapeutics
  • secretions
  • toxins

Published Papers (3 papers)

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Research

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15 pages, 6052 KiB  
Article
Virtual Screening for SARS-CoV-2 Main Protease Inhibitory Peptides from the Putative Hydrolyzed Peptidome of Rice Bran
by Nathaphat Harnkit, Thanakamol Khongsonthi, Noprada Masuwan, Pornpinit Prasartkul, Tipanart Noikaew and Pramote Chumnanpuen
Antibiotics 2022, 11(10), 1318; https://doi.org/10.3390/antibiotics11101318 - 27 Sep 2022
Cited by 8 | Viewed by 1874
Abstract
The Coronavirus Disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the loss of life and has affected the life quality, economy, and lifestyle. The SARS-CoV-2 main protease (Mpro), which hydrolyzes the polyprotein, is an interesting [...] Read more.
The Coronavirus Disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the loss of life and has affected the life quality, economy, and lifestyle. The SARS-CoV-2 main protease (Mpro), which hydrolyzes the polyprotein, is an interesting antiviral target to inhibit the spreading mechanism of COVID-19. Through predictive digestion, the peptidomes of the four major proteins in rice bran, albumin, glutelin, globulin, and prolamin, with three protease enzymes (pepsin, trypsin, and chymotrypsin), the putative hydrolyzed peptidome was established and used as the input dataset. Then, the prediction of the antiviral peptides (AVPs) was performed by online bioinformatics tools, i.e., AVPpred, Meta-iAVP, AMPfun, and ENNAVIA programs. The amino acid composition and cytotoxicity of candidate AVPs were analyzed by COPid and ToxinPred, respectively. The ten top-ranked antiviral peptides were selected and docked to the SARS-CoV-2 main protease using GalaxyPepDock. Only the top docking scored candidate (AVP4) was further analyzed by molecular dynamics simulation for one nanosecond. According to the bioinformatic analysis results, the candidate SARS-CoV-2 main protease inhibitory peptides were 7–33 amino acid residues and formed hydrogen bonds at Thr22–24, Glu154, and Thr178 in domain 2 with short bonding distances. In addition, these top-ten candidate bioactive peptides contain hydrophilic amino acid residues and have a positive net charge. We hope that this study will provide a potential starting point for peptide-based therapeutic agents against COVID-19. Full article
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Review

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30 pages, 1306 KiB  
Review
Recent Progress in the Discovery and Design of Antimicrobial Peptides Using Traditional Machine Learning and Deep Learning
by Jielu Yan, Jianxiu Cai, Bob Zhang, Yapeng Wang, Derek F. Wong and Shirley W. I. Siu
Antibiotics 2022, 11(10), 1451; https://doi.org/10.3390/antibiotics11101451 - 21 Oct 2022
Cited by 22 | Viewed by 5404
Abstract
Antimicrobial resistance has become a critical global health problem due to the abuse of conventional antibiotics and the rise of multi-drug-resistant microbes. Antimicrobial peptides (AMPs) are a group of natural peptides that show promise as next-generation antibiotics due to their low toxicity to [...] Read more.
Antimicrobial resistance has become a critical global health problem due to the abuse of conventional antibiotics and the rise of multi-drug-resistant microbes. Antimicrobial peptides (AMPs) are a group of natural peptides that show promise as next-generation antibiotics due to their low toxicity to the host, broad spectrum of biological activity, including antibacterial, antifungal, antiviral, and anti-parasitic activities, and great therapeutic potential, such as anticancer, anti-inflammatory, etc. Most importantly, AMPs kill bacteria by damaging cell membranes using multiple mechanisms of action rather than targeting a single molecule or pathway, making it difficult for bacterial drug resistance to develop. However, experimental approaches used to discover and design new AMPs are very expensive and time-consuming. In recent years, there has been considerable interest in using in silico methods, including traditional machine learning (ML) and deep learning (DL) approaches, to drug discovery. While there are a few papers summarizing computational AMP prediction methods, none of them focused on DL methods. In this review, we aim to survey the latest AMP prediction methods achieved by DL approaches. First, the biology background of AMP is introduced, then various feature encoding methods used to represent the features of peptide sequences are presented. We explain the most popular DL techniques and highlight the recent works based on them to classify AMPs and design novel peptide sequences. Finally, we discuss the limitations and challenges of AMP prediction. Full article
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16 pages, 1669 KiB  
Review
Overcoming Methicillin-Resistance Staphylococcus aureus (MRSA) Using Antimicrobial Peptides-Silver Nanoparticles
by Mohammad Asyraf Adhwa Masimen, Noor Aniza Harun, M. Maulidiani and Wan Iryani Wan Ismail
Antibiotics 2022, 11(7), 951; https://doi.org/10.3390/antibiotics11070951 - 15 Jul 2022
Cited by 25 | Viewed by 4661
Abstract
Antibiotics are regarded as a miracle in the medical field as it prevents disease caused by pathogenic bacteria. Since the discovery of penicillin, antibiotics have become the foundation for modern medical discoveries. However, bacteria soon became resistant to antibiotics, which puts a burden [...] Read more.
Antibiotics are regarded as a miracle in the medical field as it prevents disease caused by pathogenic bacteria. Since the discovery of penicillin, antibiotics have become the foundation for modern medical discoveries. However, bacteria soon became resistant to antibiotics, which puts a burden on the healthcare system. Methicillin-resistant Staphylococcus aureus (MRSA) has become one of the most prominent antibiotic-resistant bacteria in the world since 1961. MRSA primarily developed resistance to beta-lactamases antibiotics and can be easily spread in the healthcare system. Thus, alternatives to combat MRSA are urgently required. Antimicrobial peptides (AMPs), an innate host immune agent and silver nanoparticles (AgNPs), are gaining interest as alternative treatments against MRSA. Both agents have broad-spectrum properties which are suitable candidates for controlling MRSA. Although both agents can exhibit antimicrobial effects independently, the combination of both can be synergistic and complementary to each other to exhibit stronger antimicrobial activity. The combination of AMPs and AgNPs also reduces their own weaknesses as their own, which can be developed as a potential agent to combat antibiotic resistance especially towards MRSA. Thus, this review aims to discuss the potential of antimicrobial peptides and silver nanoparticles towards controlling MRSA pathogen growth. Full article
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