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- παL
- παR
- π’αL
- πβ
- π‑NHB
- π‑HB
- SCH+β
- SCH-β
- I‑αRS
- I‑αLS
- II‑αRS
- II‑αLS
- I‑αLU
- I‑αRU
- II‑αLU
- II‑αRU
- I‑αC
- I
- I’
- II
- II’
- IV1 to 4
- VIa1
- VIa2
- VIb
- VIII
- Classic
- Inverse
- Family 1
- Family 2
- Family 3
- Family 4
- Family 5
- Family 6
Secondary Structure Elements
For many decades, the most prevalent application of Circular Dichroism spectroscopy has been the quantification of secondary structure in polypeptides. To this end, far-UV CD data are subjected to secondary structure decomposition analysis, which yields estimates for the fractional amounts of different secondary structure elements in the peptide or protein of interest. Usually, the results are expressed in percentages and always include at least numbers for helices, sheets, turns, and random coil secondary structure. But what exactly are these?
In brief, secondary structure refers to the local geometry of the polypeptide backbone and well-defined, often repetitive patterns of stabilising hydrogen bonds. Based on these criteria, different classes of secondary structure elements can be defined. To the left you can see an overview of most of these classes described in the literature. Explore this gallery of more than five dozen protein structures to learn about secondary structure element classes and subclasses and create a small peptide in our playground below to gain a better understanding of the underlying principles of classification.
After spending some time on this page, you will be able to appreciate that secondary structure is not just about α-helices and β-sheets. There are many known subclasses, some of which (shown in blue) are not even included in any of the tools availalbe for secondary structure decomposition analysis for far-UV CD data. This is one of the reasons why results obtained with this traditional data analysis approach should be considered estimates rather than accurate, definite answers.
In fact, not even secondary structure content based on 3d models obtained from x-ray crystallography or NMR is definite. Secondary structure assignments based on 3d structures are most often carried out using the DSSP algorithm developed by Kabsch and Sander in 1983. However, other valid algorithms for this purpose exist that make use of different criteria and won't yield the exact same assignments (Martin et al. 2005). Secondary structure assignments based on such algorithms are always employed for the compilation of reference far-UV CD data sets that secondary structure decomposition analysis relies upon. This poses another factor that ultimately affects the accuracy of this kind of analysis.