Effect of Linear and Cyclic Lysine-Lysine-Tryptophan- Tryptophan -Lysine-Phenylalanine Antimicrobial Peptide on Sodium Dodecyl Sulfate Micelle as Cell Membrane Mimetic: Molecular Dynamics Simulation Study

Journal of Chemical Health Risks

دوره 13، شماره 4، اسفند 2023، صفحه 761-767   

نوع مقاله: Original Article

شناسه دیجیتال (DOI): 10.22034/jchr.2022.1955430.1533

نویسندگان

S. Hassan Mortazavi؛ Mohammad Reza Bozorgmehr^* ؛ Mohammad Momen Heravi

Department of Chemistry, Mashhad Branch, Islamic Azad University, Mashhad, Iran

چکیده

Drug resistance has limited the synthesis of new antibiotics. Therefore, the use of compounds that do not have drug resistance has been considered. Antimicrobial peptides are among the compounds for which drug resistance has not been reported. On the other hand, it has been found that the activity of these compounds is less than that of antibiotics. Therefore, the design of appropriate antimicrobial peptides is challenging. To address this challenge, efforts have been made to understand their mechanism of action. However, their mechanism of action is not well understood. In this work, the interaction of two cyclic and linear antimicrobial peptides with sodium dodecyl sulfate micelles as cell membrane mimetics method has been studied by molecular dynamics simulation. The micellar radius of gyration shows good agreement with the experimental results and the results of other simulations performed. Calculation of the conformational factor shows that cyclic antimicrobial peptide has a greater affinity for interaction with micelles. Charged and aromatic residues are involved in the interaction of cyclic antimicrobial peptides with micelles. Whereas, only charged residues are effective in the interaction of the linear antimicrobial peptides with micelle. 

کلیدواژه‌ها

Drug؛ Antibiotics؛ Antimicrobial peptide؛ Membrane

مراجع

1. Abebe E., Tegegne B., and Tibebu S., 2016. A review on molecular mechanisms of bacterial resistance to antibiotics. European Journal of Applied Sciences. 8(5), 301-310.
2. Bengtsson-Palme J., Larsson D.J., 2016. Concentrations of antibiotics predicted to select for resistant bacteria: proposed limits for environmental regulation. Environment International . 86, 140-149.
3. Wimley W.C., 2010. Describing the mechanism of antimicrobial peptide action with the interfacial activity model. ACS Chemical Biology. 5(10), 905-917.
4. Nizet V., 2006. Antimicrobial peptide resistance mechanisms of human bacterial pathogens. Current Issues in Molecular Biology. 8(1), 11-26.
5. Lee T.H., N Hall K., Aguilar M.I., 2016. Antimicrobial peptide structure and mechanism of action: a focus on the role of membrane structure. Current topics in Medicinal Chemistry. 16(1), 25-39.
6. Shahmiri M., Mechler A., 2020. The role of C-terminal amidation in the mechanism of action of the antimicrobial peptide aurein 1.2. The EuroBiotech Journal. 4(1), 25-31.
7. Li J., Liu S., Lakshminarayanan R., Bai Y., Pervushin K.,Verma C., Beuerman R.W., 2013. Molecular simulations suggest how a branched antimicrobial peptide perturbs a bacterial membrane and enhances permeability. Biochimica et Biophysica Acta (BBA)-Biomembranes. 1828(3), 1112-1121.
8. Kaminski H.M., Feix J.B., 2011. Effects of D-lysine substitutions on the activity and selectivity of antimicrobial peptide CM15. Polymers. 3(4), 2088-2106.
9. Hale J.D., Hancock R.E., 2007. Alternative mechanisms of action of cationic antimicrobial peptides on bacteria. Expert Review of Anti-infective Therapy. 5(6), 951-959.
10. Wessolowski A., Bienert M., Dathe M., 2004. Antimicrobial activity of arginine‐and tryptophan‐rich hexapeptides: the effects of aromatic clusters, d‐amino acid substitution and cyclization. The Journal of Peptide research. 64(4), 159-169.
11. Freudenthal O., Quilès F., Francius G., 2017. Discrepancies between cyclic and linear antimicrobial peptide actions on the spectrochemical and nanomechanical fingerprints of a young biofilm. ACS Omega. 2(9), 5861-5872.
12. Ahmadzade A., Bozorgmehr M.R., Parvaee E., 2020. The effect of sodium dodecyl sulfate concentration on the aggregation behavior of Aβ (1–42) peptide: Molecular dynamics simulation approach. Journal of Molecular Liquids. 303, 112651.
13. Del Alba Pacheco-Blas M., Vicente L., 2019. Molecular dynamics simulation of removal of heavy metals with sodium dodecyl sulfate micelle in water. Colloids and Surfaces A: Physicochemical and Engineering Aspects. 578, 123613.
14. Krüger D.M., Kamerlin S.C., 2017. Micelle Maker: An online tool for generating equilibrated micelles as direct input for molecular dynamics simulations. ACS Omega. 2(8), 4524-4530.
15. Shang B.Z.,Wang Z., Larson R.G., 2008. Molecular dynamics simulation of interactions between a sodium dodecyl sulfate micelle and a poly (ethylene oxide) polymer. The Journal of Physical Chemistry B. 112(10), 2888-2900.
16. Maginn E.J., Messerly R.A., Carlson D.J., Roe D.R., Elliot J.R., 2019. Best practices for computing transport properties 1. Self-diffusivity and viscosity from equilibrium molecular dynamics [article v1. 0]. Living Journal of Computational Molecular Science. 1(1), 6324-6324.
17. Schüttelkopf A.W., Van Aalten D.M., 2004. PRODRG: a tool for high-throughput crystallography of protein–ligand complexes. Acta Crystallographica Section D: Biological Crystallography. 60(8), 1355-1363.
18. Gordon M.S., Schmidt M.W., 2005. Advances in electronic structure theory: GAMESS a decade later, in Theory and applications of computational chemistry. Theory and Applications of Computational Chemistry. 1167-1189.
19. Appelt C.,Wessolowski A., Söderhäll J.A., Dathe M., Schmieder P., 2005. Structure of the antimicrobial, cationic hexapeptide cyclo (RRWWRF) and its analogues in solution and bound to detergent micelles. Chembiochem. 6(9), 1654-1662.
20. Van Der Spoel D., Lindahl E., Hess B., Groenhof G., Mark A.E., Berendsen H.J.C., 2005. GROMACS: fast, flexible, and free. Journal of Computational Chemistry. 26(16), 1701-1718.
21. Berendsen H.J., Postma J.P.M.,van Gunsteren W. F., DiNola A., Haak J.R., 1984. Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics. 81(8), 3684-3690.
22. Hess B., Bekker H.,Berendsen H.J.C.,Fraaije J.G.E.M., 1997. LINCS: a linear constraint solver for molecular simulations. Journal of Computational Chemistry. 18(12), 1463-1472.
23. Miyamoto S., Kollman P.A., 1992. Settle: An analytical version of the SHAKE and RATTLE algorithm for rigid water models. Journal of Computational Chemistry. 13(8), 952-962.
24. Bruce C.D., Berkowitz M.L., Perera L., Forbes M.D.E., 2002. Molecular dynamics simulation of sodium dodecyl sulfate micelle in water: micellar structural characteristics and counterion distribution. The Journal of Physical Chemistry B. 106(15), 3788-3793.
25. Santos S.F., Zanette D., Fischer H., Itri R., 2003. A systematic study of bovine serum albumin (BSA) and sodium dodecyl sulfate (SDS) interactions by surface tension and small angle X-ray scattering. Journal of Colloid and Interface Science. 262(2), 400-408.
26. Housaindokht M.R., Bozorgmehr M.R., Bahrololoom M., 2008. Analysis of ligand binding to proteins using molecular dynamics simulations. Journal of Theoretical Biology. 254(2), 294-300.