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Selective recognition of veterinary drugs residues by artificial antibodies designed using a computational approach

Paper ID Volume ID Publish Year Pages File Format Full-Text
8531 596 2009 7 PDF Available
Title
Selective recognition of veterinary drugs residues by artificial antibodies designed using a computational approach
Abstract

In this work we introduce a simple and inexpensive veterinary drugs residues detection method. Molecular dynamics simulations and computational screening were used to identify functional monomers capable of interacting with sulfadimidine (SM2). A library of 15 kinds of common functional monomers for preparing molecular imprinted polymer (MIP) was built and their interactions with SM2 in acetonitrile were calculated using the molecular dynamics software (GROMACS 3.3). According to the theoretical calculation results, the surface molecularly imprinted silica (MIP-silica) with SM2 as template was prepared by surface-imprinting technique using methacrylic acid (MAA) as functional monomer and divinylbenzene as cross-linker in acetonitrile. The surface composition of the MIP-silica was determined by Fourier transform infrared spectrometer (FT-IR) and energy dispersive X-ray spectrometer (EDS). Scanning electron microscopy (SEM) was used to characterize the morphological properties of the MIP-silica. The synthesized MIP-silica was then tested by equilibrium-adsorption method, and the MIP-silica demonstrated high binding specificity to the SM2. The molecular recognition of SM2 was analyzed in detail by using molecular modeling software (Gaussian 03).

Keywords
Surface molecular imprinting; Molecular dynamics simulations; Sulfadimidine; Recognition
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Selective recognition of veterinary drugs residues by artificial antibodies designed using a computational approach
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biomaterials - Volume 30, Issue 18, June 2009, Pages 3205–3211
Authors
, , , , , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us