Using pseudo amino acid composition to predict transmembrane regions in protein: cellular automata and Lempel-Ziv complexity

Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions. Moreover, knowledge about topology of these proteins often provides crucial hints toward their function. Due to the difficulties in experime...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Amino acids Ročník 34; číslo 1; s. 111 - 117
Hlavní autoři:	Diao, Y, Ma, D, Wen, Z, Yin, J, Xiang, J, Li, M
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Vienna Vienna : Springer-Verlag 2008 Springer-Verlag Springer Nature B.V
Témata:	Amino acid composition Amino acid sequence amino acid sequences Amino acids Amino Acids - chemistry Amino Acids - metabolism Analytical Chemistry Augmented covariant-discriminant algorithm Automata theory Biochemical Engineering Biochemistry Biomedical and Life Sciences Cellular automata Cellular structure Chou's invariance theorem Complexity Composition Computational Biology data collection drugs Eukaryotes eukaryotic cells Genetics Lempel-Ziv complexity Life Sciences Mathematical models Membrane proteins Membrane Proteins - chemistry Membrane Proteins - metabolism Membranes Models, Molecular Neurobiology prediction Protein structure Protein Structure, Secondary Protein Structure, Tertiary Proteins Proteomics Pseudo amino acid composition Sequence Analysis, Protein Source code Structure-function relationships Topology Transmembrane regions Keywords: Cellular automata – Pseudo amino acid composition – Lempel-Ziv complexity – Augmented covariant-discriminant algorithm – Chou’s invariance theorem – Transmembrane regions
ISSN:	0939-4451, 1438-2199, 1438-2199
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	Transmembrane (TM) proteins represent about 20-30% of the protein sequences in higher eukaryotes, playing important roles across a range of cellular functions. Moreover, knowledge about topology of these proteins often provides crucial hints toward their function. Due to the difficulties in experimental structure determinations of TM protein, theoretical prediction methods are highly preferred in identifying the topology of newly found ones according to their primary sequences, useful in both basic research and drug discovery. In this paper, based on the concept of pseudo amino acid composition (PseAA) that can incorporate sequence-order information of a protein sequence so as to remarkably enhance the power of discrete models (Chou, K. C., Proteins: Structure, Function, and Genetics, 2001, 43: 246-255), cellular automata and Lempel-Ziv complexity are introduced to predict the TM regions of integral membrane proteins including both α-helical and β-barrel membrane proteins, validated by jackknife test. The result thus obtained is quite promising, which indicates that the current approach might be a quite potential high throughput tool in the post-genomic era. The source code and dataset are available for academic users at liml@scu.edu.cn.
Bibliografie:	http://dx.doi.org/10.1007/s00726-007-0550-z ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23
ISSN:	0939-4451 1438-2199 1438-2199
DOI:	10.1007/s00726-007-0550-z