Abstract
Molecular imprinting is an interesting technique for preparation of molecular recognition materials with discriminating similar molecules from complex systems. In particular, imprinting more than one molecule has immense application in remediation of industrial waste. Major difficulty in molecular imprinting is the selection of suitable polymer precursors. In this article, authors have proposed a new computational approach for combinatorial screening of polymer precursor library to select appropriate polymer precursors to prepare imprinted polymer capable of selectively binding carcinogenic polycyclic aromatic hydrocarbons (PAHs). Molecular Dynamics (MD) and Quantum Mechanics (QM) models were used to compute interaction energy scores between polymer precursors and PAHs in a simulated solvent box. A self-designed virtual library of functional monomers has been prepared, and then used for MD simulations to screen the best functional monomers. Initially, molecules used in the study were geometrically optimized and then interaction energies were computed using density functional theory (DFT) in Becke 3-Parameter Exchange Correlation Function (B3LYP) level with 6-31G*basis set on Gaussian 4.1 Ver. software. Complimentary to theoretical predictions, selected polymers were prepared in laboratory and compared theoretically computed binding score with the binding capacity of the polymer on spectrofluorimetry. The computer simulations used in this research paper are rapid and reliable for the combinatorial screening of polymer precursors in experimental-free way to design of multi-template imprinted polymers.
Keywords: Computational chemistry, density functional theory, molecular imprinting, molecular mechanics, molecular simulation.
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