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

2021 ◽  
Vol 22 (2) ◽  
pp. 812
Author(s):  
Abimbola Feyisara Adedeji Olulana ◽  
Miguel A. Soler ◽  
Martina Lotteri ◽  
Hendrik Vondracek ◽  
Loredana Casalis ◽  
...  

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.

2008 ◽  
Vol 47 (7) ◽  
pp. 6085-6087 ◽  
Author(s):  
Daisuke Sawada ◽  
Takashi Namikawa ◽  
Masuhiro Hiragaki ◽  
Yoshiaki Sugimoto ◽  
Masayuki Abe ◽  
...  

2015 ◽  
Vol 112 (7) ◽  
pp. 1995-1999 ◽  
Author(s):  
Sam Emaminejad ◽  
Mehdi Javanmard ◽  
Chaitanya Gupta ◽  
Shuai Chang ◽  
Ronald W. Davis ◽  
...  

The controlled immobilization of proteins on solid-state surfaces can play an important role in enhancing the sensitivity of both affinity-based biosensors and probe-free sensing platforms. Typical methods of controlling the orientation of probe proteins on a sensor surface involve surface chemistry-based techniques. Here, we present a method of tunably controlling the immobilization of proteins on a solid-state surface using electric field. We study the ability to orient molecules by immobilizing IgG molecules in microchannels while applying lateral fields. We use atomic force microscopy to both qualitatively and quantitatively study the orientation of antibodies on glass surfaces. We apply this ability for controlled orientation to enhance the performance of affinity-based assays. As a proof of concept, we use fluorescence detection to indirectly verify the modulation of the orientation of proteins bound to the surface. We studied the interaction of fluorescently tagged anti-IgG with surface immobilized IgG controlled by electric field. Our study demonstrates that the use of electric field can result in more than 100% enhancement in signal-to-noise ratio compared with normal physical adsorption.


1999 ◽  
Vol 5 (6) ◽  
pp. 413-419 ◽  
Author(s):  
Bernardo R.A. Neves ◽  
Michael E. Salmon ◽  
Phillip E. Russell ◽  
E. Barry Troughton

Abstract: In this work, we show how field emission–scanning electron microscopy (FE-SEM) can be a useful tool for the study of self-assembled monolayer systems. We have carried out a comparative study using FE-SEM and atomic force microscopy (AFM) to assess the morphology and coverage of self-assembled monolayers (SAM) on different substrates. The results show that FE-SEM images present the same qualitative information obtained by AFM images when the SAM is deposited on a smooth substrate (e.g., mica). Further experiments with rough substrates (e.g., Al grains on glass) show that FE-SEM is capable of unambiguously identifying SAMs on any type of substrate, whereas AFM has significant difficulties in identifying SAMs on rough surfaces.


2017 ◽  
Vol 28 (45) ◽  
pp. 455603 ◽  
Author(s):  
Hitoshi Asakawa ◽  
Natsumi Inada ◽  
Kaito Hirata ◽  
Sayaka Matsui ◽  
Takumi Igarashi ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document