ArticleAnalytical chemistry2023
Determination of Secondary Structure of Proteins by Nanoinfrared Spectroscopy.
Article in Analytical chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Protein-lipid interactions in food matrices and their roles in gastrointestinal lipid digestion.Food chemistry: X · 2026Review
- Spectroscopic Insights into Lysozyme Structural Modulation by Polyphenols: A Combined FTIR and VCD Study.Molecules (Basel, Switzerland) · 2026Article
- Structural Properties and Anti-Inflammatory Activity of GLP-P, a Kefir-Derived Neutral Glycopeptide.Foods (Basel, Switzerland) · 2025Article
- Enzyme-Support Interactions ofACS applied materials & interfaces · 2025Article
- Cashew nut oligopeptide inhibits mast cell degranulation by suppressing activation of the NF-Κb signalling pathway.Food chemistry: X · 2025Article
- Impact of Multi-Factor Features on Protein Secondary Structure Prediction.Biomolecules · 2024Article
- An end-to-end approach for single-cell infrared absorption spectroscopy of bacterial inclusion bodies: from AFM-IR measurement to data interpretation of large sample sets.Journal of nanobiotechnology · 2024Article
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Authors and funding
5 authors.
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Abstract
Nanoscale infrared spectroscopy (AFMIR) is becoming an important tool for the analysis of biological sample, in particular protein assemblies, at the nanoscale level. While the amide I band is usually used to determine the secondary structure of proteins in Fourier transform infrared spectroscopy, no tool has been developed so far for AFMIR. The paper introduces a method for the study of secondary structure of protein based on a protein library of 38 well-characterized proteins. Ascending stepwise linear regression (ASLR) and partial least square (PLS) regression were used to correlate spectrum characteristic bands with the major secondary structures (α-helixes and β-sheets). ASLR appears to provide better results than PLS. The secondary structure predictions are characterized by a root mean square standard error in a cross validation of 6.39% for α-helixes and 6.23% for β-sheets.
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