Linear predictive coding representation of correlated mutation for protein sequence alignment

Background: Although both conservation and correlated mutation (CM) are important information reflecting the different sorts of context in multiple sequence alignment, most of alignment methods use sequence profiles that only represent conservation. There is no general way to represent correlated mutation and incorporate it with sequence alignment yet. Methods: We develop a novel method, CM profile, to represent correlated mutation as the spectral feature derived by using linear predictive coding where correlated mutations among different positions are represented by a fixed number of values. We combine CM profile with conventional sequence profile to improve alignment quality. Results: For distantly related protein pairs, using CM profile improves the profile-profile alignment with or without predicted secondary structure. Especially, at superfamily level, combining CM profile with sequence profile improves profile-profile alignment by 9.5% while predicted secondary structure does by...

• Type: Conference
• Year: 2009
• Where: CIKM
• Authors: Chan-seok Jeong, Dongsup Kim
• Keywords: CIKM 2009, CM Profile, Database, Sequence Alignments, Sequence Profiles