Issue 32, 2014

Understanding selective molecular recognition in integrated carbon nanotube–polymer sensors by simulating physical analyte binding on carbon nanotube–polymer scaffolds

Abstract

Macromolecular scaffolds made of polymer-wrapped single-walled carbon nanotubes (SWCNTs) have been explored recently (Zhang et al., Nature Nanotechnology, 2013) as a new class of molecular-recognition motifs. However, selective analyte recognition is still challenging and lacks the underlying fundamental understanding needed for its practical implementation in biological sensors. In this report, we combine coarse-grained molecular dynamics (CGMD) simulations, physical adsorption/binding theories, and photoluminescence (PL) experiments to provide molecular insight into the selectivity of such sensors towards a large set of biologically important analytes. We find that the physical binding affinities of the analytes on a bare SWCNT partially correlate with their distribution coefficients in a bulk water/octanol system, suggesting that the analyte hydrophobicity plays a key role in determining the binding affinities of the analytes considered, along with the various specific interactions between the analytes and the polymer anchor groups. Two distinct categories of analytes are identified to demonstrate a complex picture for the correlation between optical sensor signals and the simulated binding affinities. Specifically, a good correlation was found between the sensor signals and the physical binding affinities of the three hormones (estradiol, melatonin, and thyroxine), the neurotransmitter (dopamine), and the vitamin (riboflavin) to the SWCNT–polymer scaffold. The four amino acids (aspartate, glycine, histidine, and tryptophan) and the two monosaccharides (fructose and glucose) considered were identified as blank analytes which are unable to induce sensor signals. The results indicate great success of our physical adsorption-based model in explaining the ranking in sensor selectivities. The combined framework presented here can be used to screen and select polymers that can potentially be used for creating synthetic molecular recognition motifs.

Graphical abstract: Understanding selective molecular recognition in integrated carbon nanotube–polymer sensors by simulating physical analyte binding on carbon nanotube–polymer scaffolds

Supplementary files

Article information

Article type
Paper
Submitted
05 May 2014
Accepted
12 Jun 2014
First published
12 Jun 2014

Soft Matter, 2014,10, 5991-6004

Author version available

Understanding selective molecular recognition in integrated carbon nanotube–polymer sensors by simulating physical analyte binding on carbon nanotube–polymer scaffolds

S. Lin, J. Zhang, M. S. Strano and D. Blankschtein, Soft Matter, 2014, 10, 5991 DOI: 10.1039/C4SM00974F

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements