Biomimetic recognition utilizing molecularly imprinted polymers (MIPs) has proven its potential by providing synthetic receptors for numerous analytical applications including liquid chromatography, solid phase extraction, biomimetic assays, and sensor systems. The inherent advantages of synthetic receptors and functionalized membranes in contrast to biochemical/biological recognition and immobilization schemes include their robustness, synthetic versatility, and potentially lower costs. In principle, molecularly imprinted/templated materials are an ideal molecular capturing matrix tailorable for selective recognition or immobilization of a wide range of molecules. However, tailoring synthetic recognition elements to a target analyte requires thorough analysis and fundamental understanding of the governing molecular processes during the imprinting procedure, with the ultimate goal of rationally designing and predicting optimized synthesis pathways leading to molecular capture, recognition, and immobilization matrices with superior control on their physical geometry and molecular selectivity.
Of particular interest is the development of biomimetic recognition schemes for selectively binding proteins and large biomolecules, e.g., at the surface of biomedical devices for promoting or preventing adhesion of selected biomolecules, as well as for controlled molecular release. While materials with recognition capabilities even for larger biomolecules have achieved substantial advancements, the synthesis of molecularly imprinted materials with virus recognition properties remain challenging to date.
Here, an innovative synthetic strategy for biomimetic virus capture material is presented. An optimized sol-gel imprinting method finally yielded excellent binding selectivity, which could be achieved by a novel and generic strategy for suppressing non-specific binding via coating with deliberately selected blocking agents – a strategy termed ‘enhanced selectivity by passivation’. Next to competitive studies with non-template viruses, applications in real-world biotechnological scenarios corroborate the practical potential of this approach.
In addition, a breakthrough approach will be shown to potentially answer this pertinent question once and forever. Teaming up with one of the leading groups on large-scale molecular dynamics (MD) simulations of complex systems, we have developed a simulation concept that for the first time provides an MD strategy for generating ’virtually imprinted polymers’ (VIPs), testing such VIPs within a second set of MD simulations enabling ’virtual chromatography experiments’, and – last but not least - applying local density of states (LDOS) calculations for the first time in classifying and selecting suitable functional monomers.
In conclusion, the fundamental concepts discussed in this presentation provide a solid step towards truly predictive modeling of molecular imprinting strategies that could be expanded in future to almost any level of complexity.
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