Computational Design for The Development of Monomer Selectivity to α-Mangostin in Molecularly Imprinted Polymer

Abstract

α-mangostin is the largest content in Garcinia mangostana rind, which has a wide range of biological activities and pharmacological properties. The extraction process to separate α-mangostin from complex matrices requires selectivity. A novel method of molecularly imprinted polymer (MIP) has characterization high selectivity, high stability, and low cost. MIP uses as a selective sorbent with adsorption method that α-mangostin has the higher binding capacity and specific recognition with MIP. The computational approach was developed to study monomer selectivity towards α-mangostin as a template for rational MIP design. The purpose of this research is to study molecular interaction between template and monomer and monomer template ratio optimization in computational design to find the best pre-polymerization complex for MIP preparations. The structure of α-mangostin and nine functional monomers was drawn using Marvin Sketch and then optimized by Hyperchem 8.0.10 software. Monomer positions are placed on the template structure in various complex ratios. Each conformation was calculated using a semi-empirical PM3 simulation method to obtain the lowest bond free energy. The results showed that the α-mangostin-methacrylic acid complex with 1:6 molar ratio had the most stable structure, the most hydrogen bonds, and the highest ∆G was -27.5114588 kcal/mol. This study presented a method of selecting numerous functional monomers and determining appropriate monomer ratios with a template to obtain MIP for α-mangostin.