Computational approximations of molecularly imprinted polymers with sulphur based monomers for biological purposes

Abstract Molecularly imprinted polymers (MIPs) are uniquely suited materials for specific recognition of molecules of interest. Adding the desired molecule to the pre – polymerization mixture, is possible to achieve a polymer with cavities able to specifically adsorb this certain molecule. Nevertheless, the multicomponent conformation of MIPs makes their design optimization a tedious search for the best combinations of template, functional monomer, crosslinker and porogen, but the significant work load implied in experimental screening of these components in the laboratory can be greatly reduced by implementing new computational techniques which can narrow the search space to just a few optimum combinations which can then be more manageably screened and confirmed empirically in a classical laboratory setting. In this sense, computational techniques play a key role in the development of artificial receptors with novel components, hitherto undocumented in the literature, by allowing for in silico analysis of target – receptor docking scenarios. In this work, new sulphur based monomers with probed antitumor and antioxidant capacity were developed for biological applications through the employment of computational approximations, confirmed by traditional experimental procedures. The obtained MIP was seen to display a selective adsorption of catechin, which had been used as the template molecule due to the antioxidant capacity of polyphenol molecules.