Exploiting heterogeneous features to improve in silico prediction of peptide status - amyloidogenic or non-amyloidogenic.

ABSTRACT:

Background

Prediction of short stretches in protein sequences capable of forming amyloid-like fibrils is important in understanding the underlying cause of amyloid illnesses thereby aiding in the discovery of sequence-targeted anti-aggregation pharmaceuticals. Due to the constraints of experimental molecular techniques in identifying such motif segments, it is highly desirable to develop computational methods to provide better and affordable in silico predictions.

Results

Accurate in silico prediction techniques of amyloidogenic peptide regions rely on the cooperation between informative features and classifier design. In this research article, we propose one such efficient fibril prediction implementation exploiting heterogeneous features based on bio-physio-chemical (BPC)

SUBMITTER: Nair SS 

PROVIDER: S-EPMC3278838 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature