PSIC: profile extraction from sequence alignments with position-specific counts of independent observations

Sequence weighting techniques are aimed at balancing redundantobserved information from subsets of similar sequences in multiplealignments. Traditional approaches apply the same weight toall positions of a given sequence, hence equal efficiency ofphylogenetic changes is assumed along the whole sequence. Thisrestrictive assumption is not required for the new method PSIC(position-specific independent counts) described in this paper.The number of independent observations (counts) of an aminoacid type at a given alignment position is calculated from theoverall similarity of the sequences that share the amino acidtype at this position with the help of statistical concepts.This approach allows the fast computation of position-specificsequence weights even for alignments containing hundreds ofsequences. The PSIC approach has been applied to profile extractionand to the fold family assignment of protein sequences withknown structures. Our method was shown to be very productivein finding distantly related sequences and more powerful thanHidden Markov Models or the profile methods in WiseTools andPSI-BLAST in many cases. The profile extraction routine is availableon the WWW (http://www.bork.embl-heidelberg.de/PSIC or http://www.imb.ac.ru/PSIC).