Parameterization and classification of the protein universe via geometric techniques.
We present a scheme for the classification of 3487 non-redundant protein structures into 1207 non-hierarchical clusters by using recurring structural patterns of three to six amino acids as keys of classification. This results in several signature patterns, which seem to decide membership of a protein in a functional category. The patterns provide clues to the key residues involved in functional sites as well as in protein-protein interaction. The discovered patterns include a "glutamate double bridge" of superoxide dismutase, the functional interface of the serine protease and inhibitor, interface of homo/hetero dimers, and functional sites of several enzyme families. We use geometric invariants to decide superimposability of structural patterns. This allows the parameterization of patterns and discovery of recurring patterns via clustering. The geometric invariant-based approach eliminates the computationally explosive step of pair-wise comparison of structures. The results provide a vast resource for the biologists for experimental validation of the proposed functional sites, and for the design of synthetic enzymes, inhibitors and drugs.
Tendulkar
Ashish V
AV
Kanwal Rekhi School of Information Technology, Indian Institute of Technology, Bombay, Powai, Mumbai 400 076, India.
Wangikar
Pramod P
PP
Sohoni
Milind A
MA
Samant
Vivekanand V
VV
Mone
Chetan Y
CY
D000465:Algorithms; D000596:Amino Acids; D001665:Binding Sites; D019143:Evolution, Molecular; D008958:Models, Molecular; D008962:Models, Theoretical; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000145:classification* / Q000378:metabolism
D000596:Amino Acids; D011506:Proteins