Identification of family-specific residue packing motifs and their use for structure-based protein function prediction: I. Method development.
Protein function prediction is one of the central problems in computational biology. We present a novel automated protein structure-based function prediction method using libraries of local residue packing patterns that are common to most proteins in a known functional family. Critical to this approach is the representation of a protein structure as a graph where residue vertices (residue name used as a vertex label) are connected by geometrical proximity edges. The approach employs two steps. First, it uses a fast subgraph mining algorithm to find all occurrences of family-specific labeled subgraphs for all well characterized protein structural and functional families. Second, it queries a new structure for occurrences of a set of motifs characteristic of a known family, using a graph index to speed up Ullman's subgraph isomorphism algorithm. The confidence of function inference from structure depends on the number of family-specific motifs found in the query structure compared with their distribution in a large non-redundant database of proteins. This method can assign a new structure to a specific functional family in cases where sequence alignments, sequence patterns, structural superposition and active site templates fail to provide accurate annotation.
Bandyopadhyay
Deepak
D
GlaxoSmithKline, Collegeville, PA, USA. Deepak.2.Bandyopadhyay@gsk.com
Huan
Jun
J
Prins
Jan
J
Snoeyink
Jack
J
Wang
Wei
W
Tropsha
Alexander
A
D000465:Algorithms; D020816:Amino Acid Motifs; D019295:Computational Biology; D030562:Databases, Protein; D008958:Models, Molecular; D015233:Models, Statistical; D011506:Proteins / Q000737:chemistry* / Q000145:classification / Q000378:metabolism*; D012680:Sensitivity and Specificity
D011506:Proteins