Mining frequent patterns in protein structures: a study of protease families.

ABSTRACT:

Motivation

Analysis of protein sequence and structure databases usually reveal frequent patterns (FP) associated with biological function. Data mining techniques generally consider the physicochemical and structural properties of amino acids and their microenvironment in the folded structures. Dynamics is not usually considered, although proteins are not static, and their function relates to conformational mobility in many cases.

Results

This work describes a novel unsupervised learning approach to discover FPs in the protein families, based on biochemical, geometric and dynamic features. Without any prior knowledge of functional motifs, the method discovers the FPs for each type of amino acid and identifies the conserved residues in three protease subfamilies; chymotrypsin

SUBMITTER: Chen SC 

PROVIDER: S-EPMC1201446 | biostudies-literature | 2004 Aug

REPOSITORIES: biostudies-literature