Tripeptide analysis of protein structures.
BACKGROUND
An efficient building block for protein structure prediction can be tripeptides. 8000 different tripeptides from a dataset of 1220 high resolution (<or= 2.0 degrees A) structures from the Protein Data Bank (PDB) have been looked at, to determine which are structurally rigid and non-rigid. This data has been statistically analyzed, discussed and summarized. The entire data can be utilized for the building of protein structures.


RESULTS
Tripeptides have been classified into three categories: rigid, non-rigid and intermediate, based on the relative structural rigidity between Calpha and Cbeta atoms in a tripeptide. We found that 18% of the tripeptides in the dataset can be classified as rigid, 4% as non-rigid and 78% as intermediate. Many rigid tripeptides are made of hydrophobic residues, however, there are tripeptides with polar side chains forming rigid structures. The bulk of the tripeptides fall in the intermediate class while very small numbers actually fall in the non-rigid class. Structurally all rigid tripeptides essentially form two structural classes while the intermediate and non-rigid tripeptides fall into one structural class. This notion of rigidity and non-rigidity is designed to capture side chain interactions but not secondary structures.


CONCLUSIONS
Rigid tripeptides have no correlation with the secondary structures in proteins and hence this work is complementary to such studies. Tripeptide data may be used to predict plausible structures for oligopeptides and for denovo protein design.
Anishetty
Sharmila
S
AU-KBC Research Centre, Anna University, Chennai-44, India. sharmila@au-kbc.org
Pennathur
Gautam
G
Anishetty
Ramesh
R
D015394:Molecular Structure; D009842:Oligopeptides / Q000737:chemistry* / Q000145:classification; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein
D009842:Oligopeptides; D011506:Proteins