In Vitro Monitoring Conformational Changes of Polypeptide Monolayers Using Infrared Plasmonic Nanoantennas
Abstract
Proteins and peptides play a predominant role in biochemical reactions of living cells. In these complex environments, not only the constitution of the molecules but also their three-dimensional configuration defines their functionality. This so-called secondary structure of proteins is crucial for understanding their function in living matter. Misfolding, for example, is suspected as the cause of neurodegenerative diseases such as Alzheimer's and Parkinson's disease. Ultimately, it is necessary to study a single protein and its folding dynamics. Here, we report a first step in this direction, namely ultrasensitive detection and discrimination of in vitro polypeptide folding and unfolding processes using resonant plasmonic nanoantennas for surface-enhanced vibrational spectroscopy. We utilize poly-l-lysine as a model system which has been functionalized on the gold surface. By in vitro infrared spectroscopy of a single molecular monolayer at the amide I vibrations we directly monitor the reversible conformational changes between α-helix and β-sheet states induced by controlled external chemical stimuli. Our scheme in combination with advanced positioning of the peptides and proteins and more brilliant light sources is highly promising for ultrasensitive in vitro studies down to the single protein level.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
With machine learning, decoupling IR fingerprint absorption and refractive index change has been reported to monitor protein dynamics of secondary structure α-helix and β-sheet and recognition of glucose and fructose.
“With the aid of machine learning (ML), decoupling the IR fingerprint absorption and refractive index change induced by molecules has been reported to monitor protein dynamics of secondary structure α-helix and β-sheet48 and recognition of physiological bio-marker of glucose and fructose49.”
From Wavelength-multiplexed hook nanoantennas for machine learning enabled mid-infrared spectroscopy (2022) · cites this paper as [48]
Using the design principle of wavelength multiplexing, the WMHNA can be designed to cover all IR fingerprint ranges by engineering the antenna length for specific molecular monitoring like proteins, sugars, lipids, nucleic acids, and volatile organic compounds (VOCs).
“Using the design principle of wavelength multiplexing, the WMHNA can be designed to cover all IR fingerprint ranges by engineering the antenna length for specific molecular monitoring like proteins48, sugars49, lipids17, nucleic acids57, and volatile organic compounds (VOCs)58.”
From Wavelength-multiplexed hook nanoantennas for machine learning enabled mid-infrared spectroscopy (2022) · cites this paper as [48]
Cites
Infrared spectroscopy of proteins
Barth, A. (2007) · Biochimica et Biophysica Acta (BBA) - Bioenergetics · doi:10.1016/j.bbabio.2007.06.004 · Cited by 5,129 · see citing works
The amyloid state and its association with protein misfolding diseases.
Knowles, T. P. J., Vendruscolo, M., & Dobson, C. M. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3810 · Cited by 2,382 · see citing works
Adato, R., & Altug, H. (2013) · Nature Communications · doi:10.1038/ncomms3154 · Cited by 406 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Wavelength-multiplexed hook nanoantennas for machine learning enabled mid-infrared spectroscopy
Ren, Z., Zhang, Z., Wei, J., Dong, B., & Lee, C. (2022) · Nature Communications · doi:10.1038/s41467-022-31520-z · Cited by 132 · see citing works
- Authors
- Semenyshyn, R., Hentschel, M., Stanglmair, C., Teutsch, T., Tarin, C., Pacholski, C., Giessen, H., & Neubrech, F.
- Affiliations
- University of Stuttgart (DE)
- Max Planck Institute for Intelligent Systems (DE)
- Institute for System Dynamics, University of Stuttgart, Waldburgstraße 17/19, 70563 Stuttgart, Germany
- University of Potsdam (DE)
- Corresponding author
- Neubrech, Frank
- ORCID
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-08-02
- Volume
- 19
- Issue
- 1
- Pages
- 1-7
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2885936826
- Cited by
- 60
- References
- 3
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 9 · 2023: 5 · 2022: 5 · 2021: 14 · 2020: 13 · 2019: 6
- FWCI
- 2.47
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nano Letters (publishedVersion)
- PubMed (publishedVersion)
- publish.UP (University of Potsdam) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Bundesministerium f?r Bildung und Forschung (03IS2101E)
- Deutsche Forschungsgemeinschaft (286735196, SPP1391)
- Max-Planck-Gesellschaft
- Ministerium f?r Wissenschaft, Forschung und Kunst Baden-W?rttemberg
- Baden-W?rttemberg Stiftung
- FP7 Ideas: European Research Council
- Topics
- Physical Sciences › Materials Science › Electronic, Optical and Magnetic Materials › Gold and Silver Nanoparticles Synthesis and Applications
- Physical Sciences › Engineering › Biomedical Engineering › Plasmonic and Surface Plasmon Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
- Keywords
- protein secondary structure, protein folding and unfolding, plasmonic nanoantennas, poly-L-lysine, gold surface functionalization, amide I vibrations, alpha-helix to beta-sheet transition, single-molecule detection, conformational change
- MeSH terms
- Protein Conformation, alpha-Helical, Protein Conformation, beta-Strand, Humans, Peptides, Proteins, Spectrophotometry, Infrared, Protein Structure, Secondary, Protein Folding, Nanotechnology, Nanostructures, Proteostasis Deficiencies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review