A bi-functional polymeric coating for the co-immobilization of proteins and peptides on microarray substrates

Autor: Marina Cretich, Alessandro Mussida, Dario Brambilla, Roberto Consonni, Francesco Damin, Alessandro Gori, Marcella Chiari, Laura Sola
Rok vydání: 2021
Předmět:
Zdroj: ChemRxiv
Analytica chimica acta
1187 (2021). doi:10.1016/j.aca.2021.339138
info:cnr-pdr/source/autori:Sola L.; Brambilla D.; Mussida A.; Consonni R.; Damin F.; Cretich M.; Gori A.; Chiari M./titolo:A bi-functional polymeric coating for the co-immobilization of proteins and peptides on microarray substrates/doi:10.1016%2Fj.aca.2021.339138/rivista:Analytica chimica acta (Print)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume:1187
ISSN: 1873-4324
Popis: The analytical performance of the microarray technique in screening the affinity and reactivity of several probes towards a specific target, is highly affected by the coupling chemistry adopted to bind probes to the surface. However, the surface functionality limits the biomolecules that can be attached to the surface to a single type of molecule (DNA, protein, or peptide), thus forcing the execution of separate analyses to compare the performance of different species in recognizing their targets. Here we introduce a new N, N-dimethylacrylamide-based polymeric coating, bearing simultaneously different functionalities (N-acryloyloxysuccinimide and azide groups) to allow an easy and straightforward method to co-immobilize proteins and oriented peptides on the same substrate. The bi-functional copolymer has been obtained by partial post polymerization modification of the functional groups (NAS) of a common precursor. A deep characterization of the copolymer was carried out by means of NMR to quantify the percentage of NAS that has been transformed into azido groups. The polymer was then used to coat surfaces onto which both native antibodies and alkyne modified peptides were immobilized, to perform the phenotype characterization of extracellular vesicles (EVs). Ultimately, this strategy represents a convenient method to reduce the number of analysis, thus possible systematic or random errors, besides offering a drastic shortage in time, reagents and costs.
Databáze: OpenAIRE