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Volume 20, Issue 1
  • ISSN: 2772-4344
  • E-ISSN: 2772-4352

Abstract

Background

The emergence of resistance to multiple drugs has posed a multitude of difficulties that demand immediate attention and solutions. Multiple drug resistance arises from the accumulation of numerous genes within a single cell, each conferring resistance to a specific drug, and from the heightened expression of genes responsible for multidrug efflux pumps. These pumps effectively expel a diverse array of drugs from the cell.

Objective

The multi-drug-resistant organisms, including methicillin-resistant are the hub of numerous diseases, from minute ailments to fatal diseases, like catheter infections. Nowadays, a combination of many antibiotics is given together as a multimodality therapy to cure MRSA infections. However, researchers are exploring novel approaches to find better solutions.

Methods

designing of the peptide sequences has been done through an tool. The peptides were further screened using different computational methods. Following this, the selection was conducted utilizing physicochemical properties as criteria. Molecular docking of the selected peptide sequence was carried out. Based on the highest docking score, the model complex was chosen for validation purposes by conducting studies through molecular dynamics simulations.

Results

A total of fifty-two novel antimicrobial peptides were designed and evaluated based on various parameters, targeting MRSA-specific proteins PBP2a and PVL toxin. Among these designed peptides, the peptide sequence VILRMFYHWAVKTNGP emerged as the optimal candidate, satisfying all the necessary parameters to be an effective antimicrobial peptide.

Conclusion

Molecular docking and MD simulation results showed that the designed peptide sequence could be the possible solution for MRSA treatment.

© 2025 Bentham Science Publishers
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2024-05-03
2025-06-26

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References

  1. TanwarJ. DasS. FatimaZ. HameedS. Multidrug resistance: an emerging crisis.Interdiscip. Perspect. Infect. Dis.201420141710.1155/2014/541340 25140175
     [Google Scholar]
  2. NikaidoH. Multidrug resistance in bacteria.Annu. Rev. Biochem.200978111914610.1146/annurev.biochem.78.082907.145923 19231985
     [Google Scholar]
  3. SantajitS. IndrawattanaN. Mechanisms of antimicrobial resistance in ESKAPE pathogens.BioMed Res. Int.201620161810.1155/2016/2475067 27274985
     [Google Scholar]
  4. LakhundiS. ZhangK. Methicillin-resistant staphylococcus aureus: molecular characterization, evolution, and epidemiology.Clin. Microbiol. Rev.2018314e00020e1810.1128/CMR.00020‑18 30209034
     [Google Scholar]
  5. TurnerN.A. Sharma-KuinkelB.K. MaskarinecS.A. Methicillin-resistant Staphylococcus aureus: an overview of basic and clinical research.Nat. Rev. Microbiol.201917420321810.1038/s41579‑018‑0147‑4 30737488
     [Google Scholar]
  6. BalA.M. DavidM.Z. GarauJ. Future trends in the treatment of methicillin-resistant Staphylococcus aureus (MRSA) infection: An in-depth review of newer antibiotics active against an enduring pathogen.J. Glob. Antimicrob. Resist.20171029530310.1016/j.jgar.2017.05.019 28732783
     [Google Scholar]
  7. VestergaardM FreesD IngmerH Antibiotic resistance and the MRSA problem. Microbiol Spectr2019727.2.1810.1128/microbiolspec.GPP3‑0057‑201830900543
    [Google Scholar]
  8. KurosuM. SiricillaS. MitachiK. Advances in MRSA drug discovery: Where are we and where do we need to be?Expert Opin. Drug Discov.2013891095111610.1517/17460441.2013.807246 23829425
     [Google Scholar]
  9. VrancianuC.O. GheorgheI. DobreE.G. Emerging strategies to combat β-lactamase producing ESKAPE pathogens.Int. J. Mol. Sci.20202122852710.3390/ijms21228527 33198306
     [Google Scholar]
  10. MulaniM.S. KambleE.E. KumkarS.N. TawreM.S. PardesiK.R. Emerging strategies to combat eskape pathogens in the era of antimicrobial resistance: A review.Front. Microbiol.20191053953910.3389/fmicb.2019.00539 30988669
     [Google Scholar]
  11. WangC. HongT. CuiP. WangJ. XiaJ. Antimicrobial peptides towards clinical application: Delivery and formulation.Adv. Drug Deliv. Rev.202117511381810.1016/j.addr.2021.05.028 34090965
     [Google Scholar]
  12. FosgerauK. HoffmannT. Peptide therapeutics: current status and future directions.Drug Discov. Today201520112212810.1016/j.drudis.2014.10.003 25450771
     [Google Scholar]
  13. LuoY. SongY. Mechanism of antimicrobial peptides: antimicrobial, Anti-inflammatory and antibiofilm activities.Int. J. Mol. Sci.202122211140110.3390/ijms222111401 34768832
     [Google Scholar]
  14. ZhouJia-Le JianJ. TanXinyi. HaojiX.U. HuangXueqin. XiaoW. Design of a novel antimicrobial peptide 1018M targeted PpGpp to inhibit MRSA biofilm formation.AMB Express20211114910.1186/s13568‑021‑01208‑6
     [Google Scholar]
  15. WangL. WangN. ZhangW. Therapeutic peptides: Current applications and future directions.Signal Transduct. Target. Ther.2022714810.1038/s41392‑022‑00904‑4 35165272
     [Google Scholar]
  16. FarhadiT. HashemianS.M. Computer-aided design of amino acid-based therapeutics: A review.Drug Des. Devel. Ther.2018121239125410.2147/DDDT.S159767 29795978
     [Google Scholar]
  17. MoradiM. GolmohammadiR. NajafiA. MoghaddamM. Fasihi-RamandiM. MirnejadR. A contemporary review on the important role of in silico approaches for managing different aspects of COVID-19 crisis.Informatics in Medicine. Unlocked20222810086210.1016/j.imu.2022.100862 35079621
     [Google Scholar]
  18. UsmaniS.S. KumarR. BhallaS. KumarV. RaghavaG.P.S. In Silico tools and databases for designing peptide-based vaccine and drugs.Adv. Protein Chem. Struct. Biol.201811222126310.1016/bs.apcsb.2018.01.006 29680238
     [Google Scholar]
  19. SalmasoV. MoroS. Bridging molecular docking to molecular dynamics in exploring ligand-protein recognition process: An overview.Front. Pharmacol.2018992310.3389/fphar.2018.00923 30186166
     [Google Scholar]
  20. FerreiraL. dos SantosR. OlivaG. AndricopuloA. Molecular docking and structure-based drug design strategies.Molecules2015207133841342110.3390/molecules200713384 26205061
     [Google Scholar]
  21. FilipeH.A.L. LouraL.M.S. Molecular dynamics simulations: Advances and applications.Molecules2022277210510.3390/molecules27072105 35408504
     [Google Scholar]
  22. BohnuudT. JonesG. Schueler-FurmanO. KozakovD. Detection of peptide-binding sites on protein surfaces using the peptimap server.Methods Mol. Biol.20171561112010.1007/978‑1‑4939‑6798‑8_2 28236230
     [Google Scholar]
  23. KumarN. SoodD. TomarR. ChandraR. Antimicrobial peptide designing and optimization employing large-scale flexibility analysis of protein-peptide fragments.ACS Omega2019425213702138010.1021/acsomega.9b03035 31867532
     [Google Scholar]
  24. MólA.R. CastroM.S. FontesW. NetWheels: A web application to create high quality peptide helical wheel and net projections.Res Gat201810.1101/416347
     [Google Scholar]
  25. YangJ. ZhangY. I-TASSER server: new development for protein structure and function predictions.Nucleic Acids Res.201543W1W174-8110.1093/nar/gkv342 25883148
     [Google Scholar]
  26. SkolnickJ. GaoM. ZhouH. SinghS. Alphafold 2: why it works and its implications for understanding the relationships of protein sequence, structure, and function.J. Chem. Inf. Model.202161104827483110.1021/acs.jcim.1c01114 34586808
     [Google Scholar]
  27. GuptaS. KapoorP. ChaudharyK. GautamA. KumarR. RaghavaG.P.S. Open source drug discovery consortium. In silico approach for predicting toxicity of peptides and proteins.PLoS One201389e7395710.1371/journal.pone.0073957 24058508
     [Google Scholar]
  28. ChaudharyK. KumarR. SinghS. A web server and mobile app for computing hemolytic potency of peptides.Sci. Rep.2016612284310.1038/srep22843 26953092
     [Google Scholar]
  29. MooneyC. HaslamN.J. PollastriG. ShieldsD.C. Towards the improved discovery and design of functional peptides: common features of diverse classes permit generalized prediction of bioactivity.PLoS One2012710e4501210.1371/journal.pone.0045012 23056189
     [Google Scholar]
  30. DimitrovI. NanevaL. DoytchinovaI. BangovI. AllergenF.P. AllergenFP: allergenicity prediction by descriptor fingerprints.Bioinformatics201430684685110.1093/bioinformatics/btt619 24167156
     [Google Scholar]
  31. YanY. ZhangD. ZhouP. LiB. HuangS.Y. HDOCK: a web server for protein–protein and protein–DNA/RNA docking based on a hybrid strategy.Nucleic Acids Res.201745W1W365-7310.1093/nar/gkx407 28521030
     [Google Scholar]
  32. ShalabyM.A.W. DoklaE.M.E. SeryaR.A.T. AbouzidK.A.M. Penicillin binding protein 2a: An overview and a medicinal chemistry perspective.Eur. J. Med. Chem.202019911231210.1016/j.ejmech.2020.112312 32442851
     [Google Scholar]
  33. AcebrónI. ChangM. MobasheryS. HermosoJ. The allosteric site for the nascent cell wall in penicillin-binding protein 2a: an achilles’ heel of methicillin-resistant Staphylococcus aureus.Curr. Med. Chem.201522141678168610.2174/0929867322666150311150215 25760091
     [Google Scholar]
  34. LiuJ. KozhayaL. TorresV.J. UnutmazD. LuM. Structure-based discovery of a small-molecule inhibitor of methicillin-resistant Staphylococcus aureus virulence.J. Biol. Chem.2020295185944595910.1074/jbc.RA120.012697 32179646
     [Google Scholar]
  35. AldmanM. SkovbyA. I Påhlman L, Penicillin-Susceptible Staphylococcus Aureus L. Penicillin-susceptible Staphylococcus aureus: susceptibility testing, resistance rates and outcome of infection.Infect Dis201749645446010.1080/23744235.2017.1280617 28135900
     [Google Scholar]
  36. Aires-de-SousaM. Methicillin-resistant Staphylococcus aureus among animals: Current overview.Clin. Microbiol. Infect.201723637338010.1016/j.cmi.2016.11.002 27851997
     [Google Scholar]
  37. McGuinnessW.A. MalachowaN. DeLeoF.R. Vancomycin resistance in Staphylococcus aureus.Yale J. Biol. Med.2017902269281 28656013
     [Google Scholar]
  38. LeiJ. SunL. HuangS. The antimicrobial peptides and their potential clinical applications.Am. J. Transl. Res.201911739193931 31396309
     [Google Scholar]
  39. LimD. StrynadkaN.C.J. Structural basis for the β lactam resistance of PBP2a from methicillin-resistant Staphylococcus aureus.Nat. Struct. Biol.200291187087610.1038/nsb858 12389036
     [Google Scholar]
  40. SpaanA.N. van StrijpJ.A.G. TorresV.J. Leukocidins: Staphylococcal bi-component pore-forming toxins find their receptors.Nat. Rev. Microbiol.201715743544710.1038/nrmicro.2017.27 28420883
     [Google Scholar]
  41. BrunieraF.R. FerreiraF.M. SaviolliL.R.M. The use of vancomycin with its therapeutic and adverse effects: A review.Eur. Rev. Med. Pharmacol. Sci.2015194694700 25753888
     [Google Scholar]
  42. GurusamyK.S. KotiR. ToonC.D. WilsonP. DavidsonB.R. Antibiotic therapy for the treatment of methicillin-resistant Staphylococcus aureus (MRSA) infections in surgical wounds.Cochrane Libr.20138CD00972610.1002/14651858.CD009726.pub2 23963687
     [Google Scholar]
  43. GattiM. ViaggiB. RossoliniG.M. PeaF. VialeP. Targeted therapy of severe infections caused by staphylococcus aureus in critically ill adult patients: A multidisciplinary proposal of therapeutic algorithms based on real-world evidence.Microorganisms202311239410.3390/microorganisms11020394 36838359
     [Google Scholar]
  44. SinghS. NumanA. SomailyH.H. Nano-enabled strategies to combat methicillin-resistant Staphylococcus aureus.Mater. Sci. Eng. C202112911238410.1016/j.msec.2021.112384 34579903
     [Google Scholar]
  45. GaoY. ChenY. CaoY. MoA. PengQ. Potentials of nanotechnology in treatment of methicillin-resistant Staphylococcus aureus.Eur. J. Med. Chem.202121311305610.1016/j.ejmech.2020.113056 33280899
     [Google Scholar]
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De novo Designing of the Antimicrobial Peptide as a Curative Agent for Methicillin-Resistant Staphylococcus aureus through a Computational Approach
Recent Adv Antiinfect Drug Discov 20, 37 (2025); https://doi.org/10.2174/0127724344297458240415113008
/content/journals/raaidd/10.2174/0127724344297458240415113008
/content/journals/raaidd/10.2174/0127724344297458240415113008
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  • Article Type:     Research Article
Keyword(s): antimicrobial peptides; methicillin-resistant Staphylococcus aureus; molecular docking; molecular dynamics simulation; Multiple drug resistance; peptide designing

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