1997
DOI: 10.1002/pro.5560061206
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Linkers of secondary structures in proteins

Abstract: Linkers that connect repeating secondary structures fall into conformational classes based on distance and main-chain torsion clustering. A data set of 300 unique protein chains with low painvise sequence identity was clustered into only a few groups representing the preferred motifs. The linkers of two to eight residues for the nonredundant data set are designated H-Ln-H, H-Ln-E, E-Ln-H, E-Ln-E, where n is the length, H stands for a-helices, and E for P-strands. Most of the clusters identified here corroborat… Show more

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Cited by 12 publications
(1 citation statement)
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“…Geetha and Munson [214,215] used a set of 330 proteins sharing less than 45% of sequence identity and a resolution better than 2.25 Å. The clustering algorithm proceeded with the use of two criteria: C α distance within the loop fragments and dihedral angles of the protein backbone.…”
Section: Secondary Structuresmentioning
confidence: 99%
“…Geetha and Munson [214,215] used a set of 330 proteins sharing less than 45% of sequence identity and a resolution better than 2.25 Å. The clustering algorithm proceeded with the use of two criteria: C α distance within the loop fragments and dihedral angles of the protein backbone.…”
Section: Secondary Structuresmentioning
confidence: 99%