EMULSIFICATION AND SELF-ASSEMBLY ABILITY OF SURFACTANT-LIKE PEPTIDES PREDICTED BY COARSE GRAINED MOLECULAR DYNAMIC SIMULATIONS

• Main Author: Nurwahyu Wijaya, Tegar
• Format: Theses
• Language: Indonesia
• Subjects: Kimia
• Online Access: https://digilib.itb.ac.id/gdl/view/32765
• Institution: Institut Teknologi Bandung

Peptides are biomolecules that consist of two or more amino acids linked by amide group. Peptides and their derivatives are reported having ability to selfassembly to form nanotubes, micelles, or vesicles. The nanostructures are controllable using environment’s conditions such as pH and the present of Ca2+ ions. Peptides and their derivatives are able to form emulsion with hydrophobic molecules such in enhanced oil recovery (EOR) application. Peptides have potential to be used as drug delivery molecules or bioactive additive compounds due to their non toxic and biodegradable properties. Although having huge potentials, theoretical and computational studies on these peptides and derivatives are still limited. Molecular dynamics simulation offers an ability to study and predict at molecular level the ability of peptides to self-assemble and to form emulsions. Thus, the research reported here focused on the prediction of surfactant-like peptides ability to self assemble and to form emulsion and the determining factors of these properties. Emulsification ability of two peptides sets, X6D and X6D2 (X represents glycin, alanine, valine, leucine, and isoleucine) was determined by molecular dynamics simulations. Each type of residue was characterized by its hydropathicity index which describes the hydrophobic/hydrophilic properties of each residue. Simulations were carried out using GROMACS software with MARTINI forcefield. Simulation boxes were constructed to consist of 100 peptide molecules, 20 decane molecules, nuetralizing ions, antifreeze molecules and water. Simulations were carried out at 298 K and 1 atm with 1 ?s simulation time. The results were analyzed visually and quantitatively by counting the contact number formed during simulation. The method was validated by comparing the simulation result of peptide A6K with the data aqcuired from FTIR and SSNMR spectroscopy that have been reported. Simulation of A6K reproduced the secondary strucutre ?-sheet that has been reported before using FTIR and SSNMR spectroscopy, thus validated the method used here. Simulation results showed that only peptides containing residue with hydropathicity index ? 3,8 (valine, leusine, and isoleusine) were able to form emulsion with decane molecules. Contact number analysis between decane molecule and the peptides showed that peptides containing leusine and isoleusine were able to form emulsion faster and better (contact number ? 45) than peptides containing valine (contact number ? 30). This result showed that the longer side chain residues the better they made contact with decane molecules. Visual analysis showed that formation of the emulsions started from small micelles that united to form bigger structure later on. The number of aspartic acid residue did not have significant effect on the ability to form emulsions, instead it had determining effect on the shape of emulsion. Peptides containing one aspartic acid had micelle shape emulsions while peptides containing two aspartic acids had tubular shape emulsions (except valine containing peptides which had micelle shape emulsions). Although did not form emulsions, peptides containing alanine and glisine were able to form ?-sheet secondary structure. The secondary structure formed by peptides containing glysine were more ordered than that formed by peptides containing alanine. Addition of aspartic acid residue decreased the order of the ?-sheet structure. This research showed that emulsification ability of peptides is greatly affected by hydropathicity of residues constituting the “tail” part of surfactant-like peptides. The “head” part had determining effect on the shape of the emulsion or self-assembled structure. The results of this research could be used to help designing peptides for EOR or drug delivery applications.