Abstract

Molecular modelling and computational screening were used to identify functional monomers capable of interacting with several different photosynthesis-inhibiting herbicides. The process involved the design of a virtual library of molecular models of functional monomers containing polymerizable residues and residues able to interact with the template through electrostatic, hydrophobic, Van der Waals forces and dipole–dipole interactions. Each of the entries in the virtual library was probed for its possible interactions with molecular models of the template molecules. It was anticipated that the monomers giving the highest binding score would represent good candidates for the preparation of affinity polymers. Strong interactions were computationally determined between acidic functional monomers like methacrylic acid (MAA) or itaconic acid (IA) with triazines, and between vinylimidazole with bentazone and bromoxynil. Nevertheless, weaker interactions were seen with phenylureas. The corresponding blank polymers were prepared using the selected monomers and tested in the solid phase extraction (SPE) of herbicides from chloroform solutions. A good correlation was found between the binding score of the monomers and the affinities of the corresponding polymers. The use of computationally designed blanks can potentially eliminate the need for molecular imprinting, (adding a template to the monomer mixture to create specific binding sites). Data also showed that some monomers have a natural selectivity for some herbicides, which can be further enhanced by imprinting. Thus, in regard to retention on the blank polymer, we can estimate if the resulting imprinted polymer will be effective or not.

Keywords: Molecular modelling; Imprinted polymer; Solid phase extraction; Herbicide

Article Outline

1. Introduction

2. Materials and methods

2.1. Reagents

2.2. Molecular modelling and computational design

2.3. Preparation of blank polymers

2.4. Preparation of molecularly imprinted polymers (MIPs)

2.5. Solid phase extraction

3. Results and discussion

4. A perspective: MIPs in help of bad polymers?

5. Conclusion

Acknowledgements

References