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Database of homology‐derived protein structures and the structural meaning of sequence alignment
Author(s) -
Sander Chris,
Schneider Reinhard
Publication year - 1991
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.340090107
Subject(s) - structural alignment , loop modeling , protein structure database , homology (biology) , structural classification of proteins database , database , sequence alignment , homology modeling , threading (protein sequence) , sequence database , structural similarity , protein structure , protein secondary structure , sequence (biology) , similarity (geometry) , computational biology , biology , peptide sequence , protein structure prediction , genetics , computer science , artificial intelligence , amino acid , gene , biochemistry , image (mathematics) , enzyme
The database of known protein three‐dimensional structures can be significantly increased by the use of sequence homology, based on the following observations. (1) The database of known sequences, currently at more than 12,000 proteins, is two orders of magnitude larger than the database of known structures. (2) The currently most powerful method of predicting protein structures is model building by homology. (3) Structural homology can be inferred from the level of sequence similarity. (4) The threshold of sequence similarity sufficient for structural homology depends strongly on the length of the alignment. Here, we first quantify the relation between sequence similarity, structure similarity, and alignment length by an exhaustive survey of alignments between proteins of known structure and report a homology threshold curve as a function of alignment length. We then produce a database of homology‐derived secondary structure of proteins (HSSP) by aligning to each protein of known structure all sequences deemed homologous on the basis of the threshold curve. For each known protein structure, the derived database contains the aligned sequences, secondary structure, sequence variability, and sequence profile. Tertiary structures of the aligned sequences are implied, but not modeled explicity. The database effectively increases the number of known protein structures by a factor of five to more than 1800. The results may be useful in assessing the structural significance of matches in sequence database searches, in deriving preferences and patterns for structure prediction, in elucidating the structural role of conserved residues, and in modeling three‐dimensional detail by homology.