Estimating Factors Determining Emulsification Capability of Surfactant-Like Peptide with Coarse-Grained Molecular Dynamics Simulation

Abstract

The ability of surfactant-like peptides to emulsify oil has become the main focus of our current study. We predicted the ability of a series of surfactant-like peptides (G6D, A6D, M6D, F6D, L6D, V6D, and I6D) to emulsify decane molecules using coarse-grained molecular dynamics simulations. A 1-μs simulation of each peptide was carried out at 298 K and 1 atm using MARTINI force field. Simulation system was constructed to consist of 100 peptide molecules, 20 decane molecules, water, antifreeze particles and neutralizing ions in a random configuration. Out of seven tested peptides, M6D, F6D, L6D, V6D, and I6D were able to form emulsion while G6D and A6D self-assembled to order b-strands. A higher hydropathy index of amino acids constituting the hydrophobic tail renders the formation of an emulsion by peptides more likely. By calculating contact number between peptides and decanes, we found that emulsion stability and geometry depends on the structure of amino acids constituting the hydrophobic tail. Analysis of simulation trajectory revealed that emulsions are formed by small nucleation following by fusion to form a bigger emulsion. This study reveals the underlying principle at the molecular level of surfactant peptide ability to form an emulsion with hydrophobic molecules.

Keywords

• coarse-grained molecular dynamic simulation
• emulsion
• MARTINI
• peptide
• surfactant