STAM: simple Transmembrane Alignment Method
Author(s) -
Yi Shafrir,
H. Robert Guy
Publication year - 2004
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btg482
Subject(s) - transmembrane protein , computer science , transmembrane domain , loop modeling , homology modeling , protein structure , sequence alignment , computational biology , simple (philosophy) , membrane protein , algorithm , protein structure prediction , peptide sequence , amino acid , biology , genetics , biochemistry , enzyme , philosophy , receptor , epistemology , gene , membrane
The database of transmembrane protein (TMP) structures is still very small. At the same time, more and more TMP sequences are being determined. Molecular modeling is an interim answer that may bridge the gap between the two databases. The first step in homology modeling is to achieve a good alignment between the target sequences and the template structure. However, since most algorithms to obtain the alignments were constructed with data derived from globular proteins, they perform poorly when applied to TMPs. In our application, we automate the alignment procedure and design it specifically for TMP. We first identify segments likely to form transmembrane alpha-helices. We then apply different sets of criteria for transmembrane and non-transmembrane segments. For example, the penalty for insertion/deletions in the transmembrane segments is much higher than that of a penalty in the loop region. Different substitution matrices are used since the frequencies of occurrence of the various amino acids differ for transmembrane segments and water-soluble domains.
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