An approach to improving multiple alignments of protein sequences using predicted secondary structure

The object of this work was to improve multiple sequence alignments using p ublic domain software and methods as far as possible. A method is described where the secondary structure of proteins is predicted and this informatio n, coupled with a simplified description of the amino acids, is used to pro duce multiple sequence alignments. This method improved the accuracy of the resulting alignments by between 5 and 14% when compared with full sequence profile alignments (as scored against structural alignments). These improv ed alignments were used to predict the secondary structure of the sequences they contain. The resultant predictions were more accurate than those prod uced from less optimal alignments. An improvement of 6% for a three-state ( helix, sheet and coil) prediction was observed when using the best alignmen t from the method presented here and the alignment obtained using sequence only. The method makes use of public domain software and all the associated files required to repeat the work are available from the primary author.