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Cited by 1Computational Drug Discovery MethodsAntimicrobial Peptides and Activitiesvaccines and immunoinformatics approaches

The DOI matches its Crossref record; 96 of the 96 references it cites were found in a registry or an index.

Virtual Screening of Bacteriocins From Lactic Acid Bacteria Against Monkeypox DNA Polymerase: Sakacin P and Mundticin KS Emerge as Promising Candidates

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Karaman, Melisa Z., Goel, Karan, Zanchi, Fernando Berton, Ozdarendeli, Aykut, Mujwar, Somdutt, Yetiman, Ahmet E., Fidan, Ozkan·2026·Food Science & Nutrition
DOI 10.1002/fsn3.72219PMC PMC13447968

Published version of a preprint

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Abstract

The monkeypox virus (MPXV) has recently risen to be a significant global health threat and currently there are no approved antiviral agents, which makes it necessary to develop new antiviral strategies. In this study, we employed in silico techniques to investigate whether bacteriocins could be potent inhibitors of the MPXV DNA polymerase (MPDP). At first, the MPXV DNA polymerase enzyme chain was extracted from the Cryo‐EM structure of MPXV DNA replication complex and was then assessed using SWISS‐MODEL/QMEAN for structural quality. The structures of selected bacteriocins were either retrieved from the Protein Data Bank or predicted using AlphaFold. The quality of these predicted models was measured by LGscore. Moreover, the physicochemical properties of the selected bacteriocins, such as Sakacin P and Mundticin KS, were analyzed to assess their molecular stability and compatibility with the molecular docking process. The results of protein‐peptide docking simulations on the HADDOCK platform showed that among all the bacteriocins tested, Sakacin P and Mundticin KS had the highest binding affinities toward MPXV DNA polymerase. The analysis of the docking experiments also revealed vital stabilizing interactions, such as the formation of hydrogen bonds, ionic linkages, and π–π stacking, which were crucial in the strength of the protein–ligand complexes. Subsequently, the molecular dynamics (MD) simulations further confirmed the stability of the protein–bacteriocin complexes. Our results indicate that bacteriocins, especially Sakacin P and Mundticin KS, can be considered potential antiviral agents against MPXV by interfering with its DNA replication mechanism. The present work shall serve as a reference for future laboratory testing and for the promising innovation of bacteriocin‐based drugs targeting MPXV.

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Crossref · 10.1002/fsn3.72219

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Figures

FIGURE 1 Structure confirmation of the MPXV DNA polymerase. (A) Confirmation of the 3D structure predicted via the Ramachandran plot. (B) Cartoon illustration of the 3D structure of MPXV DNA polymerase. (C) The secondary structure of the MPXV DNA polymerase comprises α‐helices, β‐sheets, and random‐coiled polypeptide configurations. (D) The peptide sequence and Ramachandran fields are depicted.
FIGURE 1 Structure confirmation of the MPXV DNA polymerase. (A) Confirmation of the 3D structure predicted via the Ramachandran plot. (B) Cartoon illustration of the 3D structure of MPXV DNA polymerase. (C) The secondary structure of the MPXV DNA polymerase comprises α‐helices, β‐sheets, and random‐coiled polypeptide configurations. (D) The peptide sequence and Ramachandran fields are depicted.CC BY · PubMed Central
FIGURE 2 (A) Surface representation of MPDP showing the DNA‐binding groove (green) with Sakacin P (red cartoon) docked within the predicted binding pocket. (B) Hydrogen‐bond interactions between Sakacin P and MPDP. Residues of MPDP involved in hydrogen bonding are highlighted in blue, whereas interacting residues of Sakacin P are shown in green. (C) Non‐covalent interactions identified using the RING 4.0 server, including an ionic interaction between LYS‐525 (Chain A) and GLU‐11 (Chain B), a π–cation interaction between LYS‐973 (Chain A) and TRP‐59 (Chain B), and π–π stacking interactions involving PHE‐930 (Chain A), TYR‐932 (Chain A), and TRP‐36 (Chain B). MPDP residues are shown in blue, whereas interacting residues of Sakacin P are shown in green. (D) Van der Waals contacts between residues of the MPDP DNA‐binding groove (blue) and interacting residues of Sakacin P (green). The interacting residue labels belonging to Sakacin P were displayed as red, whereas the interacting residue labels from MPDP were shown as black.
FIGURE 2 (A) Surface representation of MPDP showing the DNA‐binding groove (green) with Sakacin P (red cartoon) docked within the predicted binding pocket. (B) Hydrogen‐bond interactions between Sakacin P and MPDP. Residues of MPDP involved in hydrogen bonding are highlighted in blue, whereas interacting residues of Sakacin P are shown in green. (C) Non‐covalent interactions identified using the RING 4.0 server, including an ionic interaction between LYS‐525 (Chain A) and GLU‐11 (Chain B), a π–cation interaction between LYS‐973 (Chain A) and TRP‐59 (Chain B), and π–π stacking interactions involving PHE‐930 (Chain A), TYR‐932 (Chain A), and TRP‐36 (Chain B). MPDP residues are shown in blue, whereas interacting residues of Sakacin P are shown in green. (D) Van der Waals contacts between residues of the MPDP DNA‐binding groove (blue) and interacting residues of Sakacin P (green). The interacting residue labels belonging to Sakacin P were displayed as red, whereas the interacting residue labels from MPDP were shown as black.CC BY · PubMed Central
FIGURE 3 (A) Surface representation of MPDP showing the DNA‐binding groove (green) with Mundticin KS (red cartoon) docked within the predicted binding pocket. (B) Hydrogen‐bond interactions between Mundticin KS and MPDP. Residues of MPDP involved in hydrogen bonding are highlighted in blue, whereas interacting residues of Mundticin KS are shown in green. (C) Ionic interactions between the DNA‐binding groove of MPDP (Chain A) and Mundticin KS (Chain B), as identified using the RING 4.0 server. MPDP residues participating in ionic contacts are shown in blue, while interacting Mundticin KS residues are shown in dark green. (D) Van der Waals contacts between residues of the MPDP DNA‐binding groove (blue) and interacting residues of Mundticin KS (green). The interacting residue labels for Mundticin KS were displayed in red, whereas those from MPDP were shown in black.
FIGURE 3 (A) Surface representation of MPDP showing the DNA‐binding groove (green) with Mundticin KS (red cartoon) docked within the predicted binding pocket. (B) Hydrogen‐bond interactions between Mundticin KS and MPDP. Residues of MPDP involved in hydrogen bonding are highlighted in blue, whereas interacting residues of Mundticin KS are shown in green. (C) Ionic interactions between the DNA‐binding groove of MPDP (Chain A) and Mundticin KS (Chain B), as identified using the RING 4.0 server. MPDP residues participating in ionic contacts are shown in blue, while interacting Mundticin KS residues are shown in dark green. (D) Van der Waals contacts between residues of the MPDP DNA‐binding groove (blue) and interacting residues of Mundticin KS (green). The interacting residue labels for Mundticin KS were displayed in red, whereas those from MPDP were shown in black.CC BY · PubMed Central
FIGURE 4 Root mean square deviation (RMSD) profiles of MPDP in its unbound (free) form and in complex with Sakacin P and Mundticin KS during the molecular dynamics simulation. RMSD values were calculated over the simulation time to evaluate structural stability and conformational changes upon peptide binding.
FIGURE 4 Root mean square deviation (RMSD) profiles of MPDP in its unbound (free) form and in complex with Sakacin P and Mundticin KS during the molecular dynamics simulation. RMSD values were calculated over the simulation time to evaluate structural stability and conformational changes upon peptide binding.CC BY · PubMed Central
FIGURE 5 Root mean square fluctuation (RMSF) profiles of MPDP residues in the unbound (free) state and in complex with Sakacin P and Mundticin KS during the molecular dynamics simulation. RMSF values were calculated to evaluate residue‐level flexibility and to identify regions affected by peptide binding.
FIGURE 5 Root mean square fluctuation (RMSF) profiles of MPDP residues in the unbound (free) state and in complex with Sakacin P and Mundticin KS during the molecular dynamics simulation. RMSF values were calculated to evaluate residue‐level flexibility and to identify regions affected by peptide binding.CC BY · PubMed Central
FIGURE 6 Solvent‐accessible surface area (SASA) of MPDP in its unbound (free) state and in complex with Sakacin P and Mundticin KS during the molecular dynamics simulation. The analysis reflects changes in the exposure of the protein surface and provides insight into conformational rearrangements induced by peptide binding.
FIGURE 6 Solvent‐accessible surface area (SASA) of MPDP in its unbound (free) state and in complex with Sakacin P and Mundticin KS during the molecular dynamics simulation. The analysis reflects changes in the exposure of the protein surface and provides insight into conformational rearrangements induced by peptide binding.CC BY · PubMed Central
FIGURE 7 Radius of gyration (Rg) profiles of MPDP in its unbound (free) state and in complex with Sakacin P and Mundticin KS during the molecular dynamics simulation. Rg values were calculated over the simulation time to assess the overall compactness and structural stability of the protein upon peptide binding.
FIGURE 7 Radius of gyration (Rg) profiles of MPDP in its unbound (free) state and in complex with Sakacin P and Mundticin KS during the molecular dynamics simulation. Rg values were calculated over the simulation time to assess the overall compactness and structural stability of the protein upon peptide binding.CC BY · PubMed Central
FIGURE 8 Analysis of intermolecular interactions between MPDP and bacteriocins (Sakacin P and Mundticin KS) during molecular dynamics simulations: (A) number of hydrogen bonds and (B) van der Waals interaction energy. These parameters were monitored over the simulation time to evaluate the stability and strength of protein–peptide interactions.
FIGURE 8 Analysis of intermolecular interactions between MPDP and bacteriocins (Sakacin P and Mundticin KS) during molecular dynamics simulations: (A) number of hydrogen bonds and (B) van der Waals interaction energy. These parameters were monitored over the simulation time to evaluate the stability and strength of protein–peptide interactions.CC BY · PubMed Central

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Citations

Cites

Research works printed but not linked: 2

  1. Qureshi H., 2006, Coliphage Hsa as a Model for Antiviral Studies/Spectrum by Some Indigenous Bacteriocin Like Inhibitory Substances (BLIS), Pakistan Journal of Pharmaceutical Sciences, 19, 182
  2. Yang S. C., 2014, Antibacterial Activities of Bacteriocins: Application in Foods and Pharmaceuticals, Frontiers in Microbiology, 5

Metadata

Authors
Karaman, M. Z., Goel, K., Zanchi, F. B., Ozdarendeli, A., Mujwar, S., Yetiman, A. E., & Fidan, O.
Affiliations
  • Abdullah Gül University (TR)
  • Chitkara University (IN)
  • Fiocruz Rondônia (BR)
  • Department of Microbiology, Faculty of Medicine Erciyes University Kayseri Kayseri Türkiye
  • Erciyes University (TR)
  • Department of Bioengineering, Faculty of Life and Natural Sciences Abdullah Gul University Kayseri Türkiye
Corresponding author
Yetiman, Ahmet E.
ORCID
Venue
Food Science & Nutrition
Publisher
Wiley
Published
2026-08
Volume
14
Issue
8
Pages
e72219-e72219
ISSN
2048-7177 (ISSN-L)
DOI
10.1002/fsn3.72219
PMC
PMC13447968
OpenAlex
W7197002866
Cited by
1
References
96
Citations by year
2026: 1
FWCI
3.63
Type
journal article
Language
en
Open access
Licence
Locations
  • Food Science & Nutrition (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • Erciyes University - AVESIS (submittedVersion, cc-by-nc-sa)
Funders
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (2210A)
Topics
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
  • Life Sciences › Immunology and Microbiology › Microbiology › Antimicrobial Peptides and Activities
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
Keywords
monkeypox virus, bacteriocins, sakacin P, lactic acid bacteria, antiviral agents, DNA replication inhibition, protein-peptide docking, protein-ligand binding affinity, molecular dynamics simulation, virtual screening

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