Recent research highlights the effectiveness of combining quantum mechanics (QM) and molecular dynamics (MD) methods to enhance the design of molecularly imprinted polymers (MIPs), improving their affinity and selectivity.

This study specifically focuses on the design and optimization of MIPs targeting epinephrine (EPI), utilizing advanced computational techniques such as density functional theory (DFT) and MD simulations.

The research identifies acrylic acid (AA) as the most suitable functional monomer for EPI-MIP formulation, based on evaluations using six DFT functionals.

An optimal molar ratio of 1:4 EPI:AA, combined with ethylene glycol dimethacrylate (EGDMA) and acetonitrile as solvent, was established for efficient MIP development.

QM calculations were conducted using Gaussian 09 software, while MD simulations were performed with Gromacs2018.8 software, allowing for a thorough investigation of non-covalent interactions during imprinting.

The study suggests that the molar ratio of the template (2,4-D) to functional monomer significantly impacts the formation of template-functional monomer complexes.

The study employs a combined method of QM and MD simulations to screen imprinting systems for 2,4-dichlorophenoxyacetic acid (2,4-D), showcasing the potential of MIPs in various applications.

Molecularly imprinted polymers (MIPs) are gaining importance in polymer chemistry due to their stability and versatility across a range of applications.

MIPs act as synthetic antibodies, providing high selectivity and sensitivity for target molecule recognition, making them particularly valuable in cancer diagnostics.

With global cancer incidence exceeding 11 million annually, there is an urgent need for improved diagnostic techniques, where MIPs could play a crucial role.

Biomarkers are essential for the screening, diagnosis, prevention, and monitoring of malignant tumors, and MIPs show promise in enhancing detection methods.

The review discusses the limitations and prospects of MIPs in cancer diagnostics, emphasizing their potential to improve accuracy in screening and diagnosis.