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Microorganisms
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Antimicrobial Research: In Silico Strategies for Drug Discovery Against Microbial...
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Antimicrobial Research: In Silico Strategies for Drug Discovery Against Microbial Infections

A special issue of Microorganisms (ISSN 2076-2607). This special issue belongs to the section "Antimicrobial Agents and Resistance".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 726

Special Issue Editor

Prof. Dr. Alejandro Speck-Planche

E-Mail Website
Guest Editor
LAQV@REQUIMTE/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, Porto, Portugal
Interests: multi-target drug discovery; chemoinformatics; QSAR-based approaches; virtual screening; multi-scale de novo drug design; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Microbial infections represent a global threat to public health. With the rise of antimicrobial resistance, there is a pressing need to develop more effective and safer antimicrobial agents to tackle microbial infections. Computational approaches can accelerate the discovery of novel and efficacious antimicrobial agents.

This special issue focuses on the key role of in silico approaches in the fight against microbial infections. We welcome high-impact contributions that explore computational methods such as AI/machine learning, QSAR, complex network analysis, classical ligand- and structure-based drug discovery, de novo design, etc. Submissions may cover a wide range of targets (from proteins to bacterial, fungal, viral, and parasitic strains) and include both novel and well-established computational techniques.

This Special Issue welcomes review articles, original research contributions, and perspectives where in silico strategies play a central role in antimicrobial drug discovery, including (but not limited to) lead identification, prediction of antimicrobial activity/efficacy, integration of multi-omics data, and many other topics.

Prof. Dr. Alejandro Speck-Planche
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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. Microorganisms 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 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

  • antibacterial
  • antifungal
  • antiparasitic
  • antiviral
  • AI/machine learning
  • QSAR
  • complex network analysis
  • ligand-based drug discovery
  • structure-based drug discovery
  • de novo design
  • molecular modeling
  • chemoinformatics

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Published Papers (2 papers)

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20 pages, 3986 KB  
Article
Investigation of the Mechanisms of Transition of Gram-Negative Bacterial Cells into Induced Anabiosis Using Computational Methods of Classical Molecular Dynamics
by Ksenia Tereshkina, Eduard Tereshkin, Licheng Zhang, Petr Zaytsev, Vladislav Kovalenko, Yuriy Litti, Olga S. Sokolova, Yurii Krupyanskii and Nataliya Loiko
Microorganisms 2026, 14(2), 472; https://doi.org/10.3390/microorganisms14020472 - 14 Feb 2026
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Abstract
Studying the mechanisms by which Gram-negative heterotrophic bacteria transition from active metabolism to dormancy is an important task, as it is directly related to the problem of bacterial antibiotic resistance and the spread of nosocomial infections. Using electron microscopy, microbiology, and molecular modeling, [...] Read more.
Studying the mechanisms by which Gram-negative heterotrophic bacteria transition from active metabolism to dormancy is an important task, as it is directly related to the problem of bacterial antibiotic resistance and the spread of nosocomial infections. Using electron microscopy, microbiology, and molecular modeling, we investigated the dose-dependent mechanisms of action of 4-hexylresorcinol (4HR), a chemical analog of the anabiosis autoinducer, on the cell membranes of Gram-negative bacteria (using Escherichia coli as an example), leading to the formation of stressed, dormant, and mummified cells. It was shown that 4HR penetrates membranes equally easily both as single molecules and as micelles, distributing itself across the membrane so that the hydrocarbon radicals are aligned parallel to the lipid tails. When micelles penetrate the membrane, uneven distribution of 4HR within and between leaflets occurs, as well as lipid redistribution within the membrane, leading to the appearance of a third peak on the phospholipid electron density profile and a third black band in the membrane region in TEM images of such cells. At 4HR concentrations in solution of 200 µM, its micelles cover the cell membranes in a thick layer, penetrate into the membrane, and completely saturate it. Even higher concentrations create agglomerates or actually micellar arrays within the cell membranes, leading to cell death through mummification. Full article
(This article belongs to the Special Issue Antimicrobial Research: In Silico Strategies for Drug Discovery Against Microbial Infections)
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23 pages, 7352 KB  
Article
In Silico Targeting of Trypanothione Reductase and Glycerol-3-Phosphate Dehydrogenase in Leishmania
by Ali Alisaac
Microorganisms 2026, 14(2), 407; https://doi.org/10.3390/microorganisms14020407 - 9 Feb 2026
Viewed by 249
Abstract
Leishmaniasis remains a neglected tropical disease with treatment limitations driven by toxicity, cost, and emerging resistance. Trypanothione reductase (TryR) and glycerol-3-phosphate dehydrogenase (GPDH) are essential Leishmania enzymes supporting redox homeostasis and energy/redox-linked metabolism, providing a biologically grounded rationale for dual-target inhibition. We applied [...] Read more.
Leishmaniasis remains a neglected tropical disease with treatment limitations driven by toxicity, cost, and emerging resistance. Trypanothione reductase (TryR) and glycerol-3-phosphate dehydrogenase (GPDH) are essential Leishmania enzymes supporting redox homeostasis and energy/redox-linked metabolism, providing a biologically grounded rationale for dual-target inhibition. We applied an integrated in silico workflow to prioritize candidate inhibitors using ADMET prediction (SwissADME/pkCSM), molecular docking (AutoDock Vina), and 100 ns molecular dynamics (MD) simulations; human GPDH was included as a negative control to probe potential off-target liability. ADMET screening identified 41 drug-like candidates, with most predicted to have high GI absorption and low toxicity flags across assessed endpoints (computational predictions interpreted cautiously). Docking highlighted two leading compounds. CID 6529858 showed the most favorable predicted binding to Leishmania GPDH (−8.9 kcal/mol) with a modest parasite-favored score difference versus human GPDH (−7.2 kcal/mol; Δ = −1.7 kcal/mol), while eupatorin (CID: 97214) displayed dual-target potential (TryR −7.5 kcal/mol; Leishmania GPDH −8.2 kcal/mol; human GPDH −7.2 kcal/mol; Δ = −1.0 kcal/mol). In MD, key complexes remained stable: CID 6529858 exhibited low GPDH backbone deviation (~0.25–0.40 nm), and eupatorin showed the most stable TryR trajectory (average RMSD ~0.45 nm), supported by generally low residue fluctuations across complexes. PCA further suggested ligand-associated restriction of large-scale motions (e.g., GPDH PC1 = 27.38%; TryR PC1 = 18.1%). Overall, these results nominate eupatorin as a promising dual-target lead and CID 6529858 as a strong GPDH-focused scaffold, warranting experimental enzyme inhibition, antiparasitic efficacy, and host–cell cytotoxicity testing to confirm potency and selectivity. Full article
(This article belongs to the Special Issue Antimicrobial Research: In Silico Strategies for Drug Discovery Against Microbial Infections)
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