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Applying graph theory to protein structures: an Atlas of coiled coils
Author(s) -
Jack W. Heal,
Gail J. Bartlett,
Christopher W. Wood,
Andrew R. Thomson,
Derek N. Woolfson
Publication year - 2018
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/bty347
Subject(s) - computer science , coiled coil , atlas (anatomy) , structural motif , software suite , protein structure , theoretical computer science , artificial intelligence , software , data mining , programming language , biology , paleontology , biochemistry
To understand protein structure, folding and function fully and to design proteins de novo reliably, we must learn from natural protein structures that have been characterized experimentally. The number of protein structures available is large and growing exponentially, which makes this task challenging. Indeed, computational resources are becoming increasingly important for classifying and analyzing this resource. Here, we use tools from graph theory to define an Atlas classification scheme for automatically categorizing certain protein substructures.

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