IN SILICO POTENTIAL ANALYSIS OF X6D MODEL OF PEPTIDE SURFACTANT FOR ENHANCED OIL RECOVERY

Cut Nanda Sari, Usman Usman, Rukman Hertadi, Tegar Nurwahyu Wijaya, Leni Herlina, Ken Sawitri Suliandari, Syafrizal Syafrizal, Onie Kristiawan

Abstract


Peptides and their derivatives can be applied in enhanced oil recovery (EOR) due to their ability to form an emulsion with hydrophobic molecules. However, peptide research for EOR application, either theoretical or computational studies, is still limited. The purpose of this research is to analyse the potency of the X6D model of surfactant peptide for EOR by molecular dynamics simulations in oil-water interface. Molecular dynamics simulation using GROMACS Software with Martini force field can assess a peptide’s ability for self-assembly and emulsification on a microscopic scale. Molecular dynamics simulations combined with coarse grained models will give information about the dynamics of peptide molecules in oil-water interface and the calculation of interfacial tension value. Four designs of X6D model: F6D, L6D, V6D, and I6D are simulated on the oil-water interface. The value of interfacial tension from simulation show the trend of F6D L6D > I6D > V6D. The results indicate that V6D has the greatest reduction in interfacial tension and has the stability until 90°C with the salinity of at least 1M NaCl.

Keywords


peptide surfactant; potential analysis; X6D model; enhanced oil recovery

Full Text:

PDF

References


Dong, H., Paramonov, S. E. & Hartgerink, J. D. (2008). Self-assembly of alpha-helical coiled coil nanofibers. J. Am. Chem. Soc. 130, 13691–5.

Hamley, I. W. Peptide nanotubes. (2014).Angew. Chem. Int. Ed. Engl. 53, 6866–81.

Vauthey, S., Santoso, S., Gong, H., Watson, N. & Zhang, S. (2002). Molecular self-assembly of surfactant-like peptides to form nanotubes and nanovesicles. Proc. Natl. Acad. Sci. U. S. A. 99, 5355–60.

Dexter, A. F. & Middelberg,w A. P. J. (2008). Peptides As Functional Surfactants. Ind. Eng. Chem. Res. 47, 6391–6398.

Simpson, D. R., Natraj, N. R., McInerney, M. J. & Duncan, K. E. (2011). Biosurfactant-producing Bacillus are present in produced brines from Oklahoma oil reservoirs with a wide range of salinities. Appl. Microbiol. Biotechnol. 91, 1083–93.

Adjonu, R., Doran, G., Torley, P. & Agboola, S. (2014). Whey protein peptides as components of nanoemulsions: A review of emulsifying and biological functionalities. J. Food Eng. 122, 15–27.

Youssef, N., Simpson, D. R., McInerney, M. J. & Duncan, K. E. (2013). In-situ lipopeptide biosurfactant production by Bacillus strains correlates with improved oil recovery in two oil wells approaching their economic limit of production. Int. Biodeterior. Biodegradation 81, 127–132.

Pérez, L., Pinazo, A., Pons, R. & Infante, M. (2014). Gemini surfactants from natural amino acids. Adv. Colloid Interface Sci. 205, 134–55.

Xu, J. et al. (2013). Effect of surfactant headgroups on the oil/water interface: An interfacial tension measurement and simulation study. J. Mol. Struct. 1052, 50–56.

Herdes, C., Santiso, E. E., James, C., Eastoe, J. & Müller, E. A. (2015). Modelling the interfacial

behaviour of dilute light-switching surfactant solutions. J. Colloid Interface Sci. 445, 16–23.

Humphrey, W., Dalke, A. & Schulten, K. (1996). VMD: Visual molecular dynamics. J. Mol. Graph. 14, 33–38.

Kyte, J. & Doolittle, R. F. (1982). A simple method for displaying the hydropathic character of a protein. J. Mol. Biol. 157, 105–132.

Marrink, S. J., Risselada, H. J., Yefimov, S., Tieleman, D. P. & de Vries, A. H. (2007). The MARTINI Force Field: Coarse Grained Model for Biomolecular Simulations. J. Phys. Chem. B 111, 7812–7824.

Berendsen, H. J. C., van der Spoel, D. & van Drunen, R. (1995). GROMACS: A message-passing parallel molecular dynamics implementation. Comput. Phys. Commun. 91, 43–56.

Lindahl, E., Hess, B. & van der Spoel, D. (2001). GROMACS 3.0: a package for molecular simulation and trajectory analysis. J. Mol. Model. 7, 306–317.

Van Der Spoel, D. et al. (2005). GROMACS: fast, flexible, and free. J. Comput. Chem. 26, 1701–18.

Hess, B., Kutzner, C., van der Spoel, D. & Lindahl, E. (2008). GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. J. Chem. Theory Comput. 4, 435–447.




DOI: https://doi.org/10.29017/SCOG.39.2.107

DOI (PDF): https://doi.org/10.29017/SCOG.39.2.101-106

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.