Skip to content
2000
image of Potential Inhibitors of Mycobacterium abscessus VapC5 Protein: A Molecular Dynamics Simulation Study

Abstract

Introduction

(MAB) is severely resistant to available antibacterial agents. The current study aimed to find natural inhibitors against MAB to fight the resistant isolates.

Methodology

Ten lead compounds were selected against MAB VapC5 for Molecular Dynamics (MD) simulations for 200 ns. Root Mean Square Fluctuation (RMSF), Root Mean Square Deviation (RMSD), Radius of Gyration (Rg), and Dynamic Cross Correlation Matrix (DCCM) of apo and VapC5-ligand complexes were analyzed.

Results

Among the ten lead compounds, eight compounds (deoxy artemisinin, glaucocalyxin A, (1R,4E,9E,11S)-4,12,12-trimethyl-8-oxobicyclo[9.1.0]dodeca-4,9-dien-2-yl acetate, isorhamnetin, Kissoone C, piperlongumine, tectorigenin, and wogonin) showed a good potential against MAB VapC5. The apo-VapC5 exhibits a stable RMSD of 0.154 nm and RMSF of 0.088 nm ± 0.14. At the same time, ligands including Deoxy Artemisinin, Ftaxilide, Glaucocalyxin-A, and others range in RMSF from 0.097 nm to 0.147 nm, with standard deviations varying between 0.12 and 0.22. The highest RMSF was observed with Kissoone C (0.147 nm ± 0.15), and the lowest with Tectorigenin (0.097 nm ± 0.12). The Apo-VapC5 exhibited an Rg of 3.064 nm, whereas in complexes with ligands, the Rg values ranged from 0.097 nm to 0.147 nm. The DCCM analysis of VapC5-ligand complexes also reveals a more pronounced negative correlated motion.

Discussion

The simulation outcomes indicate that ligand binding enhanced the structural stability of VapC5 compared to the apo form. Among the tested compounds, deoxy artemisinin, glaucocalyxin A, and tectorigenin showed the most stable interactions, highlighting their potential as promising VapC5 inhibitors.

Conclusion

The selected compounds exhibit good binding affinity and residue interaction patterns. The ligand binding influenced VapC5 flexibility and conformational changes observed in complexes with MABVapC5, which could be useful inhibitors after experimental validation.

© 2026 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cad/10.2174/0115734099422413251124101238
2026-01-19
2026-01-27

  • From This Site

    /content/journals/cad/10.2174/0115734099422413251124101238
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Foote S.L. Lipner E.M. Prevots D.R. Ricotta E.E. Environmental predictors of pulmonary nontuberculous mycobacteria (NTM) sputum positivity among persons with cystic fibrosis in the state of Florida. PLoS One 2021 16 12 0259964 10.1371/journal.pone.0259964 34882686
    [Google Scholar]
  2. Whiley H. Adhikari S. Keerthirathne T.P. Tohme T.C. A review of nontuberculous mycobacteria presence in raw and pasteurized bovine milk. J. Environ. Health 2018 80 9 24 31
    [Google Scholar]
  3. Griffith D.E. Aksamit T. Brown-Elliott B.A. Catanzaro A. Daley C. Gordin F. Holland S.M. Horsburgh R. Huitt G. Iademarco M.F. Iseman M. Olivier K. Ruoss S. von Reyn C.F. Wallace R.J. Winthrop K. An official ATS/IDSA statement: Diagnosis, treatment, and prevention of nontuberculous mycobacterial diseases. Am. J. Respir. Crit. Care Med. 2007 175 4 367 416 10.1164/rccm.200604‑571ST 17277290
    [Google Scholar]
  4. To K. Cao R. Yegiazaryan A. Owens J. Venketaraman V. General overview of nontuberculous mycobacteria opportunistic pathogens: Mycobacterium avium and Mycobacterium abscessus. J. Clin. Med. 2020 9 8 2541 10.3390/jcm9082541 32781595
    [Google Scholar]
  5. Brown-Elliott B.A. Wallace R.J. Clinical and taxonomic status of pathogenic nonpigmented or late-pigmenting rapidly growing mycobacteria. Clin. Microbiol. Rev. 2002 15 4 716 746 10.1128/CMR.15.4.716‑746.2002 12364376
    [Google Scholar]
  6. Chauhan U. Barth V.C. Woychik N.A. tRNA fMet inactivating mycobacterium tuberculosis VapBC toxin-antitoxin systems as therapeutic targets. Antimicrob. Agents Chemother. 2022 66 5 e01896 e21 10.1128/aac.01896‑21 35404073
    [Google Scholar]
  7. Troian E.A. Maldonado H.M. Chauhan U. Barth V.C. Woychik N.A. Mycobacterium abscessus VapC5 toxin potentiates evasion of antibiotic killing by ribosome overproduction and activation of multiple resistance pathways. Nat. Commun. 2023 14 1 3705 10.1038/s41467‑023‑38844‑4 37349306
    [Google Scholar]
  8. Hollingsworth S.A. Dror R.O. Molecular dynamics simulation for all. Neuron 2018 99 6 1129 1143 10.1016/j.neuron.2018.08.011 30236283
    [Google Scholar]
  9. Kristanti A.N. Aminaha N.S. Siswanto I. Wardana A.P. Abdjan M.I. Khoirunisak A.R. Noviana E. Synthesis, pharmacokinetic, molecular docking, and molecular dynamics simulation of 2-Styrylchromone derivatives as potential inhibitor of human Kinesin Eg5. Eng. Sci. 2024 30 1168 10.30919/es1168
    [Google Scholar]
  10. Islamoğlu F. Molecular docking, bioactivity, adme, toxicity risks, and quantum mechanical parameters of some 1,2-dihydroquinoline derivatives were calculated theoretically for investigation of its use as a pharmaceutical active ingredient in the treatment of multiple sclerosis (MS). Prospects Pharm. Sci. 2024 22 4 168 187 10.56782/pps.261
    [Google Scholar]
  11. Jhoti H. Williams G. Rees D.C. Murray C.W. The ‘rule of three’ for fragment-based drug discovery: Where are we now? Nat. Rev. Drug Discov. 2013 12 8 644 645 10.1038/nrd3926‑c1 23845999
    [Google Scholar]
  12. Claros M.G. Heijne G. TopPred II: An improved software for membrane protein structure predictions. Bioinformatics 1994 10 6 685 686 10.1093/bioinformatics/10.6.685 7704669
    [Google Scholar]
  13. Rangisetty P.T. Kilaparthi A. Akula S. Bhardwaj M. Singh S. RSAD2: An exclusive target protein for Zika virus comparative modeling, characterization, energy minimization and stabilization. Int. J. Health Sci. 2023 17 1 12 17 36704497
    [Google Scholar]
  14. Dundas J. Ouyang Z. Tseng J. Binkowski A. Turpaz Y. Liang J. CASTp: Computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acids Res. 2006 34 Web Server W116 W118 10.1093/nar/gkl282 16844972
    [Google Scholar]
  15. Ma H. Dai X. Wang T. He Z. Du R. Pei H. Liu T. Sun R. Zhao K. Investigation of uridine in anti-aging-related diseases based on network pharmacology, molecular docking and cell experimental validation. Eng. Sci. 2025 35 10.30919/es1572
    [Google Scholar]
  16. Pettersen E.F. Goddard T.D. Huang C.C. Couch G.S. Greenblatt D.M. Meng E.C. Ferrin T.E. UCSF Chimera—A visualization system for exploratory research and analysis. J. Comput. Chem. 2004 25 13 1605 1612 10.1002/jcc.20084 15264254
    [Google Scholar]
  17. Butt S.S. Badshah Y. Shabbir M. Rafiq M. Molecular docking using chimera and autodock vina software for nonbioinformaticians. JMIR Bioinform. Biotechnol. 2020 1 1 14232 10.2196/14232 38943236
    [Google Scholar]
  18. Jokhakar P.H. Kalaria R. Patel H.K. In silico docking studies of antimalarial drug hydroxychloroquine to SARS-CoV proteins :An emerging pandemic worldwide. ChemRxiv 2020 10.26434/chemrxiv.12488804.v1
    [Google Scholar]
  19. Rudnev V.R. Nikolsky K.S. Petrovsky D.V. Kulikova L.I. Kargatov A.M. Malsagova K.A. Stepanov A.A. Kopylov A.T. Kaysheva A.L. Efimov A.V. 3β-corner stability by comparative molecular dynamics simulations. Int. J. Mol. Sci. 2022 23 19 11674 10.3390/ijms231911674 36232976
    [Google Scholar]
  20. Bugnon M. Goullieux M. Röhrig U.F. Perez M.A.S. Daina A. Michielin O. Zoete V. SwissParam 2023: A modern web-based tool for efficient small molecule parametrization. J. Chem. Inf. Model. 2023 63 21 6469 6475 10.1021/acs.jcim.3c01053 37853543
    [Google Scholar]
  21. Boonstra S. Onck P.R. van der Giessen E. CHARMM TIP3P water model suppresses peptide folding by solvating the unfolded state. J. Phys. Chem. B 2016 120 15 3692 3698 10.1021/acs.jpcb.6b01316 27031562
    [Google Scholar]
  22. Taldaev A. Rudnev V. Kulikova L. Nikolsky K. Efimov A. Malsagova K. Kaysheva A. Molecular dynamics study of citrullinated proteins associated with the development of rheumatoid arthritis. Proteomes 2022 10 1 10.3390/proteomes10010008 35225987
    [Google Scholar]
  23. Jaidhan B.J. Rao P.S. Apparao A. Energy minimization and conformation analysis of molecules using steepest descent method. Int. J. Comput. Sci. Inf. Technol. 5 3 3525 3528
    [Google Scholar]
  24. Takeuchi M. Teshima M. Okubo S. Aoki S. In silico and in vitro identification of compounds with dual pharmacological activity against Metionyl‐tRNA synthetase and Isoleucyl‐tRNA synthetase of Staphylococcus aureus. ChemistrySelect 2023 8 13 202300460 10.1002/slct.202300460
    [Google Scholar]
  25. López-Blanco J.R. Aliaga J.I. Quintana-Ortí E.S. Chacón P. iMODS: Internal coordinates normal mode analysis server. Nucleic Acids Res. 2014 42 W1 W271 W276 10.1093/nar/gku339 24771341
    [Google Scholar]
  26. Álvarez-Martínez F.J. Barrajón-Catalán E. Micol V. Tackling antibiotic resistance with compounds of natural origin: A comprehensive review. Biomedicines 2020 8 10 405 10.3390/biomedicines8100405 33050619
    [Google Scholar]
  27. Daina A. Michielin O. Zoete V. SwissADME: A free] web tool to evaluate pharmacokinetics, drug-likeness and] medicinal chemistry friendliness of small molecules. Sci. Rep. 2017 7 1 42717 10.1038/srep42717 28256516
    [Google Scholar]
  28. Ghose A.K. Viswanadhan V.N. Wendoloski J.J. A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. J. Comb. Chem. 1999 1 1 55 68 10.1021/cc9800071 10746014
    [Google Scholar]
  29. Veber D.F. Johnson S.R. Cheng H.Y. Smith B.R. Ward K.W. Kopple K.D. Molecular properties that influence the oral bioavailability of drug candidates. J. Med. Chem. 2002 45 12 2615 2623 10.1021/jm020017n 12036371
    [Google Scholar]
  30. Biswas S.S. Browne R.B. Borah V.V. Roy J.D. In silico approach for phytocompound-based drug designing to fight efflux pump-mediated multidrug-resistant mycobacterium tuberculosis. Appl. Biochem. Biotechnol. 2021 193 6 1757 1779 10.1007/s12010‑021‑03557‑1 33826064
    [Google Scholar]
  31. Liu K. Watanabe E. Kokubo H. xploring the stability of ligand binding modes to proteins by molecular dynamics simulations. J. Comput. Aided Mol. Des 2017 31 2 201 211 10.1007/s10822‑016‑0005‑2 28074360
    [Google Scholar]
  32. Agrawal K.S. Sarda A.V. Shrotriya R. Bachhav M. Puri V. Nataraj G. Acetic acid dressings: Finding the Holy Grail for infected wound management. Indian J. Plast. Surg. 2017 50 3 273 280 10.4103/ijps.IJPS_245_16 29618862
    [Google Scholar]
  33. Ecevit K. Barros A.A. Silva J.M. Reis R.L. Preventing microbial infections with natural phenolic compounds. Future Pharmacol. 2022 2 4 460 498 10.3390/futurepharmacol2040030
    [Google Scholar]
  34. Tyagi P. Singh M. Kumari H. Kumari A. Mukhopadhyay K. Bactericidal activity of curcumin I is associated with damaging of bacterial membrane. PLoS One 2015 10 3 0121313 10.1371/journal.pone.0121313 25811596
    [Google Scholar]
  35. Morão L.G. Polaquini C.R. Kopacz M. Torrezan G.S. Ayusso G.M. Dilarri G. Cavalca L.B. Zielińska A. Scheffers D.J. Regasini, L.O.; Ferreira, H. A simplified curcumin targets the membrane of Bacillus subtilis. MicrobiologyOpen 2019 8 4 00683 10.1002/mbo3.683 30051597
    [Google Scholar]
  36. Keighobadi M. Emami S. Lagzian M. Fakhar M. Rafiei,] A.; Valadan, R. Molecular modeling and structural stability of wild-type and mutant CYP51 from Leishmania major: In vitro and in silico analysis of a laboratory strain. Molecules 2018 23 3 696 10.3390/molecules23030696 29562710
    [Google Scholar]
  37. Singh I. Kumar S. Mishra H.P. Kumar A. Piperlongumine prospective COX-2 inhibitors were screened virtually using molecular docking, molecular dynamics simulations, and free energy calculations. Preprint 2023 10.21203/rs.3.rs‑2617486/v1
    [Google Scholar]
  38. Mickymaray S. Alfaiz F.A. Paramasivam A. Efficacy and mechanisms of flavonoids against the emerging opportunistic nontuberculous mycobacteria. Antibiotics 2020 9 8 450 10.3390/antibiotics9080450 32726972
    [Google Scholar]
  39. Smilgies D.M. Folta-Stogniew E. Molecular weight–gyration radius relation of globular proteins: A comparison of light scattering, small-angle X-ray scattering and structure-based data. J. Appl. Cryst. 2015 48 5 1604 1606 10.1107/S1600576715015551 26500468
    [Google Scholar]
  40. Arnold G.E. Ornstein R.L. Molecular dynamics study of time-correlated protein domain motions and molecular flexibility: Cytochrome P450BM-3. Biophys. J. 1997 73 3 1147 1159 10.1016/S0006‑3495(97)78147‑5 9284282
    [Google Scholar]
/content/journals/cad/10.2174/0115734099422413251124101238
Loading
Potential Inhibitors of Mycobacterium abscessus VapC5 Protein: A Molecular Dynamics Simulation Study
Bentham Science Publishers ; https://doi.org/10.2174/0115734099422413251124101238
/content/journals/cad/10.2174/0115734099422413251124101238
/content/journals/cad/10.2174/0115734099422413251124101238
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher’s website along with the published article.

file format download Download

  • Article Type:     Research Article
Keywords: MD simulation ; interactions ; docking ; Mycobacterium abscessus ; VapC5 ; Lead compounds

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test