Computational investigation of stoichiometric effects, binding site heterogeneities, and selectivities of molecularly imprinted polymers

摘要: A series of quantum mechanical (QM) computational optimizations molecularly imprinted polymer (MIP) systems were used to determine optimal monomer-to-target ratios. Imidazole- and xanthine-derived target molecules studied. The investigation included both small-scale models (3–7 molecules) larger-scale (15–35 molecules). ratios differed between the small larger scales. For containing multiple targets, binding-site surface area analysis was quantify heterogeneity these sites. more fully surrounded sites had greater binding energies. No discretization modes seen, furthering arguments for continuous affinity distribution models. Molecular (MM) docking then measure selectivities QM-optimized Selectivity also shown improve as become encased by monomers. internal sites, consistently showed selectivity favoring that been via QM geometry optimizations. computationally exhibit size-, shape-, polarity-based selectivity. Here we present a novel approach investigate applying rapid orientation screening MM highly accurate geometries. Modeling schemes designed such no computing clusters or other specialized modeling equipment would be required. Improving in silico MIP system properties will ultimately allow production sensitive selective polymers.