Exploring the sequence patterns in the α-helices of proteins
被引:47
作者:
Wang, JW
论文数: 0引用数: 0
h-index: 0
机构:Temple Univ, Dept Chem, Philadelphia, PA 19122 USA
Wang, JW
Feng, JA
论文数: 0引用数: 0
h-index: 0
机构:Temple Univ, Dept Chem, Philadelphia, PA 19122 USA
Feng, JA
机构:
[1] Temple Univ, Dept Chem, Philadelphia, PA 19122 USA
[2] Temple Univ, Ctr Biotechnol, Philadelphia, PA 19122 USA
来源:
PROTEIN ENGINEERING
|
2003年
/
16卷
/
11期
关键词:
alpha-helix;
propensity;
protein structures;
secondary structure;
sequence pattern;
D O I:
10.1093/protein/gzg101
中图分类号:
Q5 [生物化学];
Q7 [分子生物学];
学科分类号:
071010 ;
081704 ;
摘要:
This paper reports an extensive sequence analysis of the alpha-helices of proteins. alpha-Helices were extracted from the Protein Data Bank (PDB) and were divided into groups according to their sizes. It was found that some amino acids had differential propensity values for adopting helical conformation in short, medium and long alpha-helices. Pro and Trp had a significantly higher propensity for helical conformation in short helices than in medium and long helices. Trp was the strongest helix conformer in short helices. Sequence patterns favoring helical conformation were derived from a neighbor-dependent sequence analysis of proteins, which calculated the effect of neighboring amino acid type on the propensity of residues for adopting a particular secondary structure in proteins. This method produced an enhanced statistical significance scale that allowed us to explore the positional preference of amino acids for alpha-helical conformations. It was shown that the amino acid pair preference for alpha-helix had a unique pattern and this pattern was not always predictable by assuming proportional contributions from the individual propensity values of the amino acids. Our analysis also yielded a series of amino acid dyads that showed preference for alpha-helix conformation. The data presented in this study, along with our previous study on loop sequences of proteins, should prove useful for developing potential 'codes' for recognizing sequence patterns that are favorable for specific secondary structural elements in proteins.