Amino acid side chain contribution to protein FTIR spectra: impact on secondary structure evaluation
| Autor: | Erik Goormaghtigh, Joëlle De Meutter |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Amino acid side chain Biophysics Analytical chemistry FTIR spectroscopy Secondary structure Protein spectroscopy Protein microarrays Amino acid side chain 01 natural sciences Protein Structure Secondary Absorbance 03 medical and health sciences chemistry.chemical_compound Amide Secondary structure Partial least squares regression Spectroscopy Fourier Transform Infrared Side chain Fourier transform infrared spectroscopy Amino Acids Protein secondary structure chemistry.chemical_classification Chemistry 010401 analytical chemistry Protein microarrays Proteins General Medicine Amides 0104 chemical sciences Amino acid Protein spectroscopy FTIR spectroscopy 030104 developmental biology Original Article DSSP (hydrogen bond estimation algorithm) |
| Zdroj: | European Biophysics Journal |
| ISSN: | 1432-1017 0175-7571 |
| Popis: | Prediction of protein secondary structure from FTIR spectra usually relies on the absorbance in the amide I–amide II regionof the spectrum. It assumes that the absorbance in this spectral region, i.e., roughly 1700–1500 cm−1 is solely arising fromamide contributions. Yet, it is accepted that, on the average, about 20% of the absorbance is due to amino acid side chains.The present paper evaluates the contribution of amino acid side chains in this spectral region and the potential to improvesecondary structure prediction after correcting for their contribution. We show that the β-sheet content prediction is improvedupon subtraction of amino acid side chain contributions in the amide I–amide II spectral range. Improvement is relativelyimportant, for instance, the error of prediction of β-sheet content decreases from 5.42 to 4.97% when evaluated by ascendingstepwise regression. Other methods tested such as partial least square regression and support vector machine have alsoimproved accuracy for β-sheet content evaluation. The other structures such as α-helix do not significantly benefit from sidechain contribution subtraction, in some cases prediction is even degraded. We show that co-linearity between secondarystructure content and amino acid composition is not a main limitation for improving secondary structure prediction. Wealso show that, even though based on different criteria, secondary structures defined by DSSP and XTLSSTR both arrive atthe same conclusion: only the β-sheet structure clearly benefits from side chain subtraction. It must be concluded that sidechain contribution subtraction benefit for the evaluation of other secondary structure contents is limited by the very roughdescription of side chain absorbance which does not take into account the variations related to their environment. The studywas performed on a large protein set. To deal with the large number of proteins present, we worked on protein microarraysdeposited on BaF2slides and FTIR spectra were acquired with an imaging system. |
| Databáze: | OpenAIRE |
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