Oxybutynin-imprinted polymer: A theoretical investigation

Levobunolol-imprinted polymer: a theoretical study

CONTEXT

Levobunolol is a β-blocker drug prescribed for the control and prevention of cardiovascular events, such as individuals with cardiac arrhythmia or a history of myocardial infarction. Creating a levobunolol-specific molecularly imprinted polymer (MIP) allows for enhanced selectivity, efficient sample preparation, controlled drug delivery, and improved sensing and detection capabilities. In this sense, the aim of this study was to obtain through DFT calculations the synthesis protocol of a MIP for levobunolol testing different functional monomers (FMs), solvents, and cross-linker agents (CLAs). The analysis of structural and energetic data led to the identification of the optimal MIP synthesis parameters, which involves the use of (trifluoromethyl)-arylic acid (TFMAA) as the functional monomer, toluene and chloroform as the solvents, and pentaerythritol triacrylate (PETRA) as the cross-linking agent. This rational design offers valuable insights for experimentalists seeking to efficiently synthesize a MIP for this important β-blocker drug.

METHODS

DFT calculations were conducted using the B97D functional along with the Pople's split valence 6-31G(d,p) basis set, which includes polarization functions on all atoms (B97D/6-31G(d,p)).

Rational In Silico Design of Molecularly Imprinted Polymers: Current Challenges and Future Potential

The rational design of molecularly imprinted polymers has evolved along with state-of-the-art experimental imprinting strategies taking advantage of sophisticated computational tools. In silico methods enable the screening and simulation of innovative polymerization components and conditions superseding conventional formulations. The combined use of quantum mechanics, molecular mechanics, and molecular dynamics strategies allows for macromolecular modelling to study the systematic translation from the pre- to the post-polymerization stage. However, predictive design and high-performance computing to advance MIP development are neither fully explored nor practiced comprehensively on a routine basis to date. In this review, we focus on different steps along the molecular imprinting process and discuss appropriate computational methods that may assist in optimizing the associated experimental strategies. We discuss the potential, challenges, and limitations of computational approaches including ML/AI and present perspectives that may guide next-generation rational MIP design for accelerating the discovery of innovative molecularly templated materials.