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Computational-Assisted Development of Molecularly Imprinted Polymers for Synthetic Cannabinoid Recognition.
Leonardo Martins Carneiro1, Karen Rafaela Gonçalves Araújo2, Diego Ulysses Melo3
1Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, São Paulo 09210-580, Brazil.
ACS Omega
|August 11, 2025
Summary
Computational methods were used to design molecularly imprinted polymers (MIPs) for selective synthetic cannabinoid (SC) detection. This approach aids in developing tools to combat the global SC epidemic.
Area of Science:
- Computational chemistry
- Materials science
- Forensic toxicology
Background:
- Synthetic cannabinoids (SCs) present significant public health risks due to toxicity and global prevalence.
- Developing selective detection methods for SCs is crucial for forensic analysis and public safety.
Purpose of the Study:
- To computationally design molecularly imprinted polymers (MIPs) for the selective recognition and potential extraction of seven synthetic cannabinoids.
- To identify optimal monomer-solvent combinations for MIP synthesis using computational modeling.
Main Methods:
- Density functional theory (DFT) and GFN2-xTB calculations were utilized to optimize molecular geometries.
- Solvation energies of six solvents were assessed to determine suitable polymerization media.
- Hydrogen bonding interactions were mapped to guide the selection of functional monomers, including acrylic acid (AA), 4-vinylbenzoic acid (BA), 2-(trifluoromethyl)-acrylic acid (TFAA), and methacrylic acid.
Main Results:
- Computational analysis identified 2-(trifluoromethyl)-acrylic acid (TFAA) and 4-vinylbenzoic acid (BA) as promising functional monomers.
- These monomers demonstrated stable complexation with synthetic cannabinoids, driven by acidity and aromatic interactions.
- The study predicted suitable monomer-solvent combinations for effective MIP synthesis.
Conclusions:
- Computational predictions provide a foundation for efficient experimental validation of MIPs for SC detection.
- Developed MIPs can serve as valuable tools for extracting synthetic cannabinoids from complex matrices.
- This research contributes to combating the global synthetic cannabinoid epidemic through advanced analytical methods.
