Protein Secondary Structures: Prediction

Abstract

Secondary structure prediction methods are computational algorithms that predict the secondary structure of a protein (i.e. α helices, β strands and turns) from the primary structure (the amino acid sequence).

Keywords: neural networks; nearest neighbour; secondary structure prediction

References

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Further Reading

Barton GJ (1995) Protein secondary structure prediction. Current Opinion in Structural Biology 5: 372–376.

Bohm G (1996) New approaches in molecular structure prediction. Biophysical Chemistry 59: 1–32.

Bowie JU, Luthy R and Eisenberg D (1991) A method to identify protein sequences that fold into a known three‐dimensional structure. Science 253: 164–170.

Fischer D and Eisenberg D (1996) Protein fold recognition using sequence‐derived predictions. Protein Science 5: 947–955.

Kabsch W and Sander C (1983) How good are predictions of protein secondary structure? FEBS Letters 155: 179–182.

Rost B and O'Donoghue S (1997) Sisyphus and prediction of protein structure. Computer Applications in the Biosciences 13: 345–356.

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Chandonia, John‐Marc(Apr 2001) Protein Secondary Structures: Prediction. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1038/npg.els.0003039]