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Article

Computational Evolution of Beta-2-Microglobulin Binding Peptides for Nanopatterned Surface Sensors

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Department of Medical and Biological Sciences, University of Udine, 33100 Udine, Italy
2
Department of Physics, PhD School of Nanotechnology, University of Trieste, 34127 Trieste, Italy
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Regional Referral Centre for Rare Diseases, Azienda Sanitaria Universitaria Integrata di Udine, 33100 Udine, Italy
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School of Food Science and Nutrition, University of Leeds, Leeds LS2 9JT, UK
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Italian Institute of Technology (IIT), Via Melen 83, B Block, 16152 Genova, Italy
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Nanoinnovation Lab, Elettra-Sincrotone S.C.p.A., ss 14 km 163,5 in AREA Science Park, 34149 Trieste, Italy
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Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via L. Giorgieri 1, 34127 Trieste, Italy
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Department of Pharmacy, University of Naples “Federico II”, Via Montesano, 80134 Naples, Italy
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2021, 22(2), 812; https://doi.org/10.3390/ijms22020812
Received: 27 November 2020 / Revised: 24 December 2020 / Accepted: 4 January 2021 / Published: 15 January 2021
The bottom-up design of smart nanodevices largely depends on the accuracy by which each of the inherent nanometric components can be functionally designed with predictive methods. Here, we present a rationally designed, self-assembled nanochip capable of capturing a target protein by means of pre-selected binding sites. The sensing elements comprise computationally evolved peptides, designed to target an arbitrarily selected binding site on the surface of beta-2-Microglobulin (β2m), a globular protein that lacks well-defined pockets. The nanopatterned surface was generated by an atomic force microscopy (AFM)-based, tip force-driven nanolithography technique termed nanografting to construct laterally confined self-assembled nanopatches of single stranded (ss)DNA. These were subsequently associated with an ssDNA–peptide conjugate by means of DNA-directed immobilization, therefore allowing control of the peptide’s spatial orientation. We characterized the sensitivity of such peptide-containing systems against β2m in solution by means of AFM-based differential topographic imaging and surface plasmon resonance (SPR) spectroscopy. Our results show that the confined peptides are capable of specifically capturing β2m from the surface–liquid interface with micromolar affinity, hence providing a viable proof-of-concept for our approach to peptide design. View Full-Text
Keywords: peptides; beta-2-Microglobulin; DNA; atomic force microscopy (AFM); computational design; self-assembly; biosensor peptides; beta-2-Microglobulin; DNA; atomic force microscopy (AFM); computational design; self-assembly; biosensor
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MDPI and ACS Style

Adedeji Olulana, A.F.; Soler, M.A.; Lotteri, M.; Vondracek, H.; Casalis, L.; Marasco, D.; Castronovo, M.; Fortuna, S. Computational Evolution of Beta-2-Microglobulin Binding Peptides for Nanopatterned Surface Sensors. Int. J. Mol. Sci. 2021, 22, 812. https://doi.org/10.3390/ijms22020812

AMA Style

Adedeji Olulana AF, Soler MA, Lotteri M, Vondracek H, Casalis L, Marasco D, Castronovo M, Fortuna S. Computational Evolution of Beta-2-Microglobulin Binding Peptides for Nanopatterned Surface Sensors. International Journal of Molecular Sciences. 2021; 22(2):812. https://doi.org/10.3390/ijms22020812

Chicago/Turabian Style

Adedeji Olulana, Abimbola F., Miguel A. Soler, Martina Lotteri, Hendrik Vondracek, Loredana Casalis, Daniela Marasco, Matteo Castronovo, and Sara Fortuna. 2021. "Computational Evolution of Beta-2-Microglobulin Binding Peptides for Nanopatterned Surface Sensors" International Journal of Molecular Sciences 22, no. 2: 812. https://doi.org/10.3390/ijms22020812

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