Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences.

ABSTRACT:

Background

Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences.

Results

The proposed MODular Approach to Structural class prediction (MODAS) method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutiona

SUBMITTER: Mizianty MJ 

PROVIDER: S-EPMC2805645 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature