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Novel Biomolecules and Antimicrobial Peptides as a New Generation Antibiofilm...
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Novel Biomolecules and Antimicrobial Peptides as a New Generation Antibiofilm Agents

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Applied Chemistry".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 7027

Special Issue Editors

Dr. Mohd Adnan

E-Mail Website
Guest Editor
Department of Biology, College of Science University of Ha'il, Ha'il, Saudi Arabia
Interests: drug discovery; microbial biofilms; natural products; secondary metabolites; biosurfactants; novel antimicrobials
Special Issues, Collections and Topics in MDPI journals
Dr. Md. Imtaiyaz Hassan

E-Mail Website
Guest Editor
Center for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, India
Interests: drug discovery; antimicrobial therapy functional genomics; pathogenesis; drug resistance

Special Issue Information

Dear Colleagues,

Biofilms are one of the primary causes of antibiotic resistance in bacteria. Despite them being a significant health concern, there are no approved drugs that specifically target bacterial biofilms. In recent years, the development of antimicrobial peptides (AMPs) and novel molecules from natural sources has gained considerable attention from the scientific community due to their broad-spectrum antimicrobial activity and their lower chance of inducing antibiotic resistance. The mechanisms of action of AMPs and their structure–activity relationships are not fully understood. AMPs are new-generation alternatives for inhibiting biofilm formation that can be implicated in drug development. This Special Issue highlights the need to identify novel biomolecules and AMPs as antimicrobial and antibiofilm agents to address drug-resistant pathogens globally.

AMP design can drastically reduce the production costs and time required to evaluate the activity and toxicity of compounds targeting critical signaling pathways in biofilm development. In silico approaches for the modeling of novel AMPs will accelerate the process of drug discovery and design and be an invaluable asset for attaining a thorough understanding of the activity of AMPs, leading to the discovery of new AMPs with diverse potential. Simulations and current structural bioinformatic approaches will eventually guide the recognition of AMPs' potential. In recent years, several lines of research have addressed new strategies for developing novel and active biomolecules either alone or in synergy with conventional antimicrobial agents to inhibit bacterial adhesion, dispersion and biofilm growth effectively. To fully develop the potential of AMPs for biofilm therapies, advanced research on the design of AMPs that can target biofilms and free bacteria is needed. Bioinformatic tools may help in analyzing large databases, predicting novel sequences and identifying possible mechanisms of action on the biofilm matrix. Due to the nature of the subject, further exploration by the scientific community using in silico, in vitro and in vivo studies is required, ultimately fulfilling the scope and goals of this Special Issue. This could provide the basis for a new generation of antibiofilm antimicrobial agents.

Dr. Mohd Adnan
Dr. Md. Imtaiyaz Hassan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Molecules is an international peer-reviewed open access semimonthly 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 2700 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

  • biofilm
  • antimicrobial peptides
  • antibiotic resistance
  • anti-quorum sensing
  • drug discovery
  • bioactive molecules
  • molecular pathogenesis
  • in silico modeling

Published Papers (2 papers)

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12 pages, 2726 KiB  
Article
Biofilm-i: A Platform for Predicting Biofilm Inhibitors Using Quantitative Structure—Relationship (QSAR) Based Regression Models to Curb Antibiotic Resistance
by Akanksha Rajput, Kailash T. Bhamare, Anamika Thakur and Manoj Kumar
Molecules 2022, 27(15), 4861; https://doi.org/10.3390/molecules27154861 - 29 Jul 2022
Cited by 4 | Viewed by 1694
Abstract
Antibiotic drug resistance has emerged as a major public health threat globally. One of the leading causes of drug resistance is the colonization of microorganisms in biofilm mode. Hence, there is an urgent need to design novel and highly effective biofilm inhibitors that [...] Read more.
Antibiotic drug resistance has emerged as a major public health threat globally. One of the leading causes of drug resistance is the colonization of microorganisms in biofilm mode. Hence, there is an urgent need to design novel and highly effective biofilm inhibitors that can work either synergistically with antibiotics or individually. Therefore, we have developed a recursive regression-based platform “Biofilm-i” employing a quantitative structure–activity relationship approach for making generalized predictions, along with group and species-specific predictions of biofilm inhibition efficiency of chemical(s). The platform encompasses eight predictors, three analysis tools, and data visualization modules. The experimentally validated biofilm inhibitors for model development were retrieved from the “aBiofilm” resource and processed using a 10-fold cross-validation approach using the support vector machine and andom forest machine learning techniques. The data was further sub-divided into training/testing and independent validation sets. From training/testing data sets the Pearson’s correlation coefficient of overall chemicals, Gram-positive bacteria, Gram-negative bacteria, fungus, Pseudomonas aeruginosa, Staphylococcus aureus, Candida albicans, and Escherichia coli was 0.60, 0.77, 0.62, 0.77, 0.73, 0.83, 0.70, and 0.71 respectively via Support Vector Machine. Further, all the QSAR models performed equally well on independent validation data sets. Additionally, we also checked the performance of the random forest machine learning technique for the above datasets. The integrated analysis tools can convert the chemical structure into different formats, search for a similar chemical in the aBiofilm database and design the analogs. Moreover, the data visualization modules check the distribution of experimentally validated biofilm inhibitors according to their common scaffolds. The Biofilm-i platform would be of immense help to researchers engaged in designing highly efficacious biofilm inhibitors for tackling the menace of antibiotic drug resistance. Full article
(This article belongs to the Special Issue Novel Biomolecules and Antimicrobial Peptides as a New Generation Antibiofilm Agents)
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Review

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25 pages, 1145 KiB  
Review
The Role of Antimicrobial Peptides as Antimicrobial and Antibiofilm Agents in Tackling the Silent Pandemic of Antimicrobial Resistance
by Bruno S. Lopes, Alfizah Hanafiah, Ramesh Nachimuthu, Saravanan Muthupandian, Zarith Nameyrra Md Nesran and Sandip Patil
Molecules 2022, 27(9), 2995; https://doi.org/10.3390/molecules27092995 - 06 May 2022
Cited by 15 | Viewed by 4618
Abstract
Just over a million people died globally in 2019 due to antibiotic resistance caused by ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species). The World Health Organization (WHO) also lists [...] Read more.
Just over a million people died globally in 2019 due to antibiotic resistance caused by ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species). The World Health Organization (WHO) also lists antibiotic-resistant Campylobacter and Helicobacter as bacteria that pose the greatest threat to human health. As it is becoming increasingly difficult to discover new antibiotics, new alternatives are needed to solve the crisis of antimicrobial resistance (AMR). Bacteria commonly found in complex communities enclosed within self-produced matrices called biofilms are difficult to eradicate and develop increased stress and antimicrobial tolerance. This review summarises the role of antimicrobial peptides (AMPs) in combating the silent pandemic of AMR and their application in clinical medicine, focusing on both the advantages and disadvantages of AMPs as antibiofilm agents. It is known that many AMPs display broad-spectrum antimicrobial activities, but in a variety of organisms AMPs are not stable (short half-life) or have some toxic side effects. Hence, it is also important to develop new AMP analogues for their potential use as drug candidates. The use of one health approach along with developing novel therapies using phages and breakthroughs in novel antimicrobial peptide synthesis can help us in tackling the problem of AMR. Full article
(This article belongs to the Special Issue Novel Biomolecules and Antimicrobial Peptides as a New Generation Antibiofilm Agents)
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