Searching for three-dimensional secondary structural patterns in proteins with ProSMoS
Author(s) -
Shuoyong Shi,
Yi Zhong,
Indraneel Majumdar,
Sanjeev Krishna,
Nick V. Grishin
Publication year - 2007
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/btm121
Subject(s) - protein data bank , structural motif , grasp , closeness , structural similarity , computer science , protein data bank (rcsb pdb) , antiparallel (mathematics) , structural alignment , motif (music) , protein secondary structure , protein structure , structural bioinformatics , theoretical computer science , artificial intelligence , computational biology , sequence alignment , mathematics , biology , genetics , peptide sequence , chemistry , physics , stereochemistry , mathematical analysis , biochemistry , quantum mechanics , magnetic field , gene , acoustics , programming language
Many evolutionarily distant, but functionally meaningful links between proteins come to light through comparison of spatial structures. Most programs that assess structural similarity compare two proteins to each other and find regions in common between them. Structural classification experts look for a particular structural motif instead. Programs base similarity scores on superposition or closeness of either Cartesian coordinates or inter-residue contacts. Experts pay more attention to the general orientation of the main chain and mutual spatial arrangement of secondary structural elements. There is a need for a computational tool to find proteins with the same secondary structures, topological connections and spatial architecture, regardless of subtle differences in 3D coordinates.
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