(189cb) Molecular Dynamics Analysis of Membrane Proteins As Biosurfactants into Triglycerides – Water Mixtures

Cardona Jaramillo, J. E. C.¹; Alvarez O.A.¹, Achenie, L.E.K. ²; Gonzalez Barrios, A.F.¹

1. Grupo de Diseño de Productos y Procesos (GDPP), Departamento de Ingeniería Química, Universidad de los Andes, Bogotá, Colombia {je. Cardona10, oalvarez, andgonza} @uniandes.edu.co
2. Department of Chemical Engineering. Virginia Polytechnic Institute and State University. achenie@vt.edu

Cosmetics are mass consumption products that play an important role in our daily lives. Therefore, the cosmetic industry is a rapidly growing economic sector, whose main research interest is staying ahead in a highly competitive market through product improvements [1]. As many finished products are made from colloidal mixtures, identifying surfactants that modify the interfacial tension between immiscible liquids to form emulsions is a very attractive research topic. The surfactant benefit and societal impact are increased if the surfactant is derived from a renewable source. Biosurfactants are a structurally quite diverse group of compounds synthesized by microorganisms, that are characterized by large structures which confer special properties such as surface activity [2]. Among these natural compounds, the membrane protein A from Escherichia coli (OmpA) has been recognized as a potential biosurfactant because it has a high homology with the emulsifier protein of the commercial biosurfactant Alasan (i.e. AlnA) [3], [4]. Considering that membrane proteins have an amphiphilic nature that allows them to interact both with the middle of the periplasm as well as the hydrophobic membrane, OmpA, OmpN and other membrane proteins may be potential biosurfactants [3], [4]. However, there are a poorly knowledge about the interaction patterns between biosurfactants and hydrophobic molecules.

A mixture of water and oil forms a model system that can lead to a better understanding of the biosurfactant behavior in a cosmetic product. Vegetable oils are commonly included as the main ingredients in cosmetic products, and they are composed mainly of triglycerides that are esters formed by glycerol and three fatty acids [5]. Those type of oils are complex mixtures of triglycerides with different unsaturation levels and chain lengths. The use of the oils requires a real understanding of the composition of the model system because it directly affects skin sensation during use. Also, depending on its composition, vegetable oils could be susceptible to degradation because the level of unsaturation in the fatty acid chain promotes oxidation reactions [5].

A computational strategy, specifically an all atom molecular dynamics (MD) for establishing the effect of two selected biosurfactants (i.e. OmpA and OmpN) within the interface. To model the vegetable oil, a set of different triglycerides was analyzed. In greater detail, a cross-factorial array experimental design was used to analyze the effect of three different factors, namely the type of biosurfactant molecule, the presence of double bonds in the triglyceride molecule, and the triglyceride molar concentration. As explained above, OmpA and OmpN served as biosurfactants, while T54:3, T54:0, T48:3 and T48:0 were the triglycerides (where the number after “T” denotes the number of carbon atoms within the triglyceride molecule, and the second number represents the number of double bonds). Simulation boxes included one biosurfactant molecule, 6 or 12 triglyceride molecules and 3231 water molecules. MD were performed using LAMMPS (Nov. 17, 2016 version)[6]. Each system was energy minimized, and then equilibrated in a microcanonical ensemble. The production step was carried out with an a NVT ensemble for 1ns. All trajectories were analyzed using the Ovito [7] and VMD [8] packages through the estimation of the system’s surface accessible to solvent area (SASA), second virial coefficient (β) and radial distribution function g(r).

Our results suggest differences in the biosurfactant behavior once they were placed in a media with unsaturated triglycerides as compared to those mixtures containing saturated triglycerides. Triglyceride agglomeration patterns, as well as triglyceride–protein interactions, appear to be dependent on the presence of double bonds within the fatty acid chains. While SASA values of OmpA and OmpN were similar, significant differences were observed in the SASA and β values when the system contains unsaturated triglycerides comparing with saturated ones. This result may be associated with the biosurfactant interaction with non-polar molecules. In conclusion, using an all atom MD, the authors accomplished a mechanistic understanding of protein interaction with molecules of different polarity. This approach could be the first step in a rational multiscale design of emulsions with particular emphasis on the cosmetic industry.

References

[1] M. Secchi, V. Castellani, E. Collina, N. Mirabella, and S. Sala, “Assessing eco-innovations in green chemistry: Life Cycle Assessment (LCA) of a cosmetic product with a bio-based ingredient,” J. Clean. Prod., vol. 129, pp. 269–281, 2016.

[2] N. Ranasalva, R. Sunil, and G. Poovarasan, “Importance of Biosurfactant in Food Industry,” IOSR J. Agric. Vet. Sci., vol. 7, no. 5, pp. 6–9, 2014.

[3] S. M. Aguilera-Segura, A. P. Macias, D. Carrero-Pinto, W. Lawrence, M.J. Vives-Florez, H.E. Castro-Barrera, O. Alvarez-Solano, A. F. Gonzalez-Barrios. “Escherichia coli’s OmpA as Biosurfactant for Cosmetic Industry: Stability Analysis and Experimental Validation Based on Molecular Simulations,” in Advances in Computational Biology SE - 38, vol. 232, L. F. Castillo, M. Cristancho, G. Isaza, A. Pinzón, and J. M. C. Rodríguez, Eds. Springer International Publishing, 2014, pp. 265–271.

[4] S. M. Aguilera-Segura, V. Nuñez-Vélez, L. Achenie, O. Alvarez-Solano, R. Torres, and A. F. González Barrios, “Peptides design based on transmembrane Escherichia coli’s OmpA protein through molecular dynamics simulations in water–dodecane interfaces,” J. Mol. Graph. Model., 2016.

[5] H. Iwata and K. Shimada, Formulas, Ingredients and Production of Cosmetics. Saitama, Japan: Springer, 2013.

[6] S. Plimpton, “Fast Parallel Algorithms for Short–Range Molecular Dynamics,” J. Comput. Phys., vol. 117, no. 1, pp. 1–19, 1995.

[7] A. Stukowski, “Visualization and analysis of atomistic simulation data with OVITO–the Open Visualization Tool,” Model. Simul. Mater. Sci. Eng, vol. 18, pp. 15012–7, 2010.

[8] W. Humphrey, A. Dalke, and K. Schulten, “VMD: Visual Molecular Dynamics.”