Protein structure comparisons using a combination of a genetic algorithm, dynamic programming and least-squares minimization

We introduce a completely automatic and objective procedure for the comparison of protein structures. A genetic algorithm is used to search for a near optimal solution of the rigid-body superposition of two whole protein structures. The specification of an initial set of equivalences is not required...

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Vydané v:Protein engineering Ročník 7; číslo 4; s. 475
Hlavní autori: May, A C, Johnson, M S
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England 01.04.1994
Predmet:
Algorithms
Amino Acid Sequence
Databases, Factual
Least-Squares Analysis
Mathematical Computing
Models, Molecular
Molecular Sequence Data
Nucleic Acid Conformation
Protein Structure, Tertiary
RNA, Transfer, Phe - chemistry
Sequence Alignment - methods
Sequence Homology, Amino Acid
Serine Endopeptidases - chemistry
Software
ISSN:0269-2139
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Popis
Shrnutí:We introduce a completely automatic and objective procedure for the comparison of protein structures. A genetic algorithm is used to search for a near optimal solution of the rigid-body superposition of two whole protein structures. The specification of an initial set of equivalences is not required. Topological equivalences in the final structural alignment are defined by a conventional dynamic programming routine, which is commonly used to compare protein sequences. A least-squares fitting algorithm is then used to optimize the fit between the final set of equivalences. We have applied our method to the comparison of ribonucleic acid structures, as well as protein structures. The structural alignments are generally consistent with those previously published. In fact, on most occasions our method defines at least the same number of topological equivalences as other procedures, but always with a lower r.m.s. distance between them.
Bibliografia:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0269-2139
DOI:10.1093/protein/7.4.475