Design and Characterization of The Peptide Surfactant of α- Hairpin and Double α-Hairpin Models for Enhance Oil Recovery - (NIM: 20514032), SUMARLIN
Crude petroleum oil available for economic utilization is only about 1/3 of its total amount, mainly explored by primary and secondary methods. The remaining is still trapped in rocks inside petroleum wells. This circumstance leads many experts in oil production to develop a recovery technology. Employing surfactant is one of the method to optimize oil recovery. Surfactant that has been used at present generally were synthesized from hardly decomposing crude oil residues that may become potential pollutant to the environment. Recent invention of biosurfactant produced by microorganisms opens the posibility to reduce or replace the application of synthetic surfactants. In addition to developing biosurfactants from microorganisms, another approached is by synthetizing surfactant from biomaterial, such as amino acid, carbohydrate or lipid. In the present work, peptide surfactant was created from particular amino acid sequence that form amphiphatics helix. Helix model surfactant was constructed from amphipathic α-helical segments, which originally parts of a crystal structure of TAQ Polymerase (1BGX). Three amphiphatic helical segments were selected by Wenxiang diagram approach, which those were helix A (residues A118 - K133), helix B (residues T756 - F772), dan helix C (residues A796 - E808). Those helical segments then were combined to form helix-turn-helix or α-hairpin (H) and double α-hairpin (DH) by an addition of a linker. Three pairs of H and DH models have been created in this study, which were model-1 consisted of helix A dan C, model-2 composed of helix A dan B, and model-3 created from helix B dan C. Their potential as surfactant were evaluated based on their capability to emulsify oil and to reduce interfacial tension (IFT) between water and oil. In the present study such potential was explored by performing molecular dynamics simulation to a three-component system comprised of randomly mixed of peptide model, octadecane, and water. The simulation was carried out by accelerated MD using coarse grained method implemented in GROMACS simulator program. The simulation to evaluate the emulsification and IFT calculation was carried out in different temperatures and different NaCl concentrations to mimics the oil well conditions that typically has high temperature and salinity. Results on MD simulation showed that variation of temperatures and NaCl concentrations were not significantly affected the three pairs of surfactant models in emulsifying and reducing IFT value. Among those three models, however, model-3 gave better performance compared to other models. Without the addition of NaCl, the optimum performance of model-3 in both H and DH designs was observed at 373 K with the corresponding IFT reduction was about 1,6 dyne/cm and 1,7 dyne/cm, respectively. While after the addition of 1,5 M NaCl, the decreasing of IFT value was 1,53 dyne/cm for H topology and 1.5 dyne/cm for DH topology. The other two models have optimum IFT reduction value at NaCl concentration lower than 1,5 M. Small differences in the simulation result was caused by the limited number of molecules involved in the simulation. Overall, we showed here that the model peptides have showed its potential as promising surfactant for Enhance Oil Recovery.