A permissive secondary structure-guided superposition tool for clustering of protein fragments toward protein structure prediction via fragment assembly.
BACKGROUND
Secondary-Structure Guided Superposition tool (SSGS) is a permissive secondary structure-based algorithm for matching of protein structures and in particular their fragments. The algorithm was developed towards protein structure prediction via fragment assembly.


RESULTS
In a fragment-based structural prediction scheme, a protein sequence is cut into building blocks (BBs). The BBs are assembled to predict their relative 3D arrangement. Finally, the assemblies are refined. To implement this prediction scheme, a clustered structural library representing sequence patterns for protein fragments is essential. To create a library, BBs generated by cutting proteins from the PDB are compared and structurally similar BBs are clustered. To allow structural comparison and clustering of the BBs, which are often relatively short with flexible loops, we have devised SSGS. SSGS maintains high similarity between cluster members and is highly efficient. When it comes to comparing BBs for clustering purposes, the algorithm obtains better results than other, non-secondary structure guided protein superimposition algorithms.
Sackler Institute of Molecular Medicine, Department of Human Genetics, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
Gilad
G
Wainreb
Nurit
N
Haspel
Haim J
HJ
Wolfson
Ruth
R
Nussinov
D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011487:Protein Conformation; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D017386:Sequence Homology, Amino Acid; D012984:Software
D011506:Proteins