Identifying the Interaction of Vancomycin With Novel pH-Responsive Lipids as Antibacterial Biomaterials Via Accelerated Molecular Dynamics and Binding Free Energy Calculations
Nano-drug delivery systems have proven to be an efficient formulation tool to overcome the challenges with current antibiotics therapy and resistance. A series of pH-responsive lipid molecules were designed and synthesized for future liposomal formulation as a nano-drug delivery system for vancomycin at the infection site. The structures of these lipids differ from each other in respect of hydrocarbon tails: Lipid1, 2, 3 and 4 have stearic, oleic, linoleic, and linolenic acid hydrocarbon chains, respectively. The impact of variation in the hydrocarbon chain in the lipid structure on drug encapsulation and release profile, as well as mode of drug interaction, was investigated using molecular modeling analyses. A wide range of computational tools, including accelerated molecular dynamics, normal molecular dynamics, binding free energy calculations and principle component analysis, were applied to provide comprehensive insight into the interaction landscape between vancomycin and the designed lipid molecules. Interestingly, both MM-GBSA and MM-PBSA binding affinity calculations using normal molecular dynamics and accelerated molecular dynamics trajectories showed a very consistent trend, where the order of binding affinity towards vancomycin was lipid4 > lipid1 > lipid2 > lipid3. From both normal molecular dynamics and accelerated molecular dynamics, the interaction of lipid3 with vancomycin is demonstrated to be the weakest (∆Gbinding = −2.17 and −11.57, for normal molecular dynamics and accelerated molecular dynamics, respectively) when compared to other complexes. We believe that the degree of unsaturation of the hydrocarbon chain in the lipid molecules may impact on the overall conformational behavior, interaction mode and encapsulation (wrapping) of the lipid molecules around the vancomycin molecule. This thorough computational analysis prior to the experimental investigation is a valuable approach to guide for predicting the encapsulation ability, drug release and further development of novel liposome-based pH-responsive nano-drug delivery system with refined structural and chemical features of potential lipid molecule for formulation development.
KeywordspH-responsive lipids Liposomes Nano-drug delivery systems (NDDS) Vancomycin Molecular dynamics Binding affinity calculations
The authors are thankful to National Research Foundation of South Africa, University of KwaZulu-Natal and UKZN Nano Platform for financial support and Carrin Martin for editing.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no competing interests.
- 1.Klevens, R. M., Edwards, J. R., Richards, C. L., Horan, T. C., Gaynes, R. P., Pollock, D. A., & Cardo, D. M. (2007). Estimating health care-associated infections and deaths in U.S. Hospitals, Public Health Reports 122(2):160–166.Google Scholar
- 9.Kalhapure, R. S., Suleman, N., Mocktar, C., Seedat, N., & Govender, T. (2014). Nanoengineered drug delivery systems for enhancing antibiotic therapy. Journal of Pharmaceutical Sciences. doi: 10.1002/jps.24298.
- 11.Radovic-Moreno, A. F., Lu, T. K., Puscasu, V. A., Yoon, C. J., Langer, R., & Farokhzad, O. C. (2012). Surface charge-switching polymeric nanoparticles for bacterial cell wall-targeted delivery of antibiotics. ACS Nano, 6(5), 4279–4287. doi: 10.1021/nn3008383.CrossRefPubMedPubMedCentralGoogle Scholar
- 12.Kalhapure, R. S., Mocktar, C., Sikwal, D. R., Sonawane, S. J., Kathiravan, M. K., Skelton, A., & Govender, T. (2014). Ion pairing with linoleic acid simultaneously enhances encapsulation efficiency and antibacterial activity of vancomycin in solid lipid nanoparticles. Colloids and Surfaces. B, Biointerfaces, 117, 303–11. doi: 10.1016/j.colsurfb.2014.02.045.CrossRefPubMedGoogle Scholar
- 13.Kashi, T. S. J., Eskandarion, S., Esfandyari-Manesh, M., Marashi, S. M. A., Samadi, N., & Fatemi, S. M., et al. (2012). Improved drug loading and antibacterial activity of minocycline-loaded PLGA nanoparticles prepared by solid/oil/water ion pairing method. International Journal of Nanomedicine, 7, 221–234. doi: 10.2147/IJN.S27709.PubMedPubMedCentralGoogle Scholar
- 14.UK Patent Application GB1614120.2. (n.d.).Google Scholar
- 16.Greenidge, P. a, Kramer, C., Mozziconacci, J.-C., & Sherman, W. (2014). Improving docking results via reranking of ensembles of ligand poses in multiple x-ray protein conformations with MM-GBSA. Journal of Chemical Information and Modeling. doi: 10.1021/ci5003735
- 18.Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera--a visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. doi: 10.1002/jcc.20084.CrossRefPubMedGoogle Scholar
- 19.Marvinsketch: https://www.chemaxon.com/products/marvin/marvinsketch/, accessed 23 Apr 2016.
- 20.Maestro: https://www.schrodinger.com/maestro/, accessed 13 Apr 2016.
- 21.Case, D. A., Berryman, J. T., Betz, R. M., Cerutti, D. S., Cheatham, T. E., Darden, T. A., & Kollman, P. A. (2015). AMBER 2015. San Francisco: University of California. University of California, San Francisco.Google Scholar
- 22.Götz, A. W., Williamson, M. J., Xu, D., Poole, D., Le Grand, S., & Walker, R. C. (2012). Routine microsecond molecular dynamics simulations with AMBER on GPUs. 1. Generalized born. Journal of Chemical Theory and Computation, 8(5), 1542–1555. doi: 10.1021/ct200909j.CrossRefPubMedPubMedCentralGoogle Scholar
- 23.Dupradeau, F.-Y., Pigache, A., Zaffran, T., Savineau, C., Lelong, R., Grivel, N., & Cieplak, P. (2010). The R.E.D. tools: Advances in RESP and ESP charge derivation and force field library building. Physical Chemistry Chemical Physics, 12(28), 7821–7839. doi: 10.1039/c0cp00111b.CrossRefPubMedPubMedCentralGoogle Scholar
- 30.Schrodinger LLC. (2015). The PyMOL Molecular Graphics System, Version 1.8.Google Scholar
- 31.Hou, T., Wang, J., Li, Y., & Wang, W. (2010). Assessing the performance of the MM/PBSA and MM/GBSA Methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations. Journal of Chemical Information and Modeling, 51, 69–82. doi: 10.1021/ci100275a.CrossRefPubMedPubMedCentralGoogle Scholar
- 32.Cocco, S., Monasson, R., & Weigt, M. (2013). From principal component to direct coupling analysis of coevolution in proteins: Low-eigenvalue modes are needed for structure prediction. PLoS Computational Biology, 9(8), e1003176. doi: 10.1371/journal.pcbi.1003176.CrossRefPubMedPubMedCentralGoogle Scholar
- 35.Pierce, L. C. T., Salomon-Ferrer, R., Augusto, C., de Oliveira, F., McCammon, Ja, & Walker, R. C. (2012). Routine access to millsecond timescale evenrs with accelerated molecular dynamics. Journal of Chemical Theory and Computation, 8, 2997–3002. doi: 10.1021/ct300284c.CrossRefPubMedPubMedCentralGoogle Scholar