  Protein structure prediction remains a challenge in the field of
computational biology. Traditional protein structure prediction approaches
include template-based modelling (say, homology modelling, and threading), and
ab initio. A threading algorithm takes a query protein sequence as input,
recognizes the most likely fold, and finally reports the alignments of the
query sequence to structure-known templates as output. The existing threading
approaches mainly utilizes the information of protein sequence profile, solvent
accessibility, contact probability, etc., and correctly recognize folds for
some proteins. However, the existing threading approaches show poorly
performance for remote homology proteins. How to improve the fold recognition
for remote homology proteins remains to be a difficult task for protein
structure prediction.
