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Nucleic Acids Research 2005 33(3):816-824; doi:10.1093/nar/gki233
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Published online 7 February 2005

© The Author 2005. Published by Oxford University Press. All rights reserved
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Article

Homology-extended sequence alignment

V. A. Simossis1, J. Kleinjung1 and J. Heringa1,2,*

1 Bioinformatics Section, Faculty of Sciences, Vrije Universiteit De Boelelaan 1081A, 1081 HV, Amsterdam, The Netherlands 2 Centre for Integrative Bioinformatics VU (IBIVU), Faculty of Sciences and Faculty of Earth and Life Sciences, Vrije Universiteit De Boelelaan 1081A, 1081 HV, Amsterdam, The Netherlands

*To whom correspondence should be addressed. Tel: +31 0 20 598 7649; Fax: +31 0 20 598 7653; Email: heringa{at}cs.vu.nl

Received November 26, 2004. Revised January 5, 2005. Accepted January 20, 2005.

We present a profile–profile multiple alignment strategy that uses database searching to collect homologues for each sequence in a given set, in order to enrich their available evolutionary information for the alignment. For each of the alignment sequences, the putative homologous sequences that score above a pre-defined threshold are incorporated into a position-specific pre-alignment profile. The enriched position-specific profile is used for standard progressive alignment, thereby more accurately describing the characteristic features of the given sequence set. We show that owing to the incorporation of the pre-alignment information into a standard progressive multiple alignment routine, the alignment quality between distant sequences increases significantly and outperforms state-of-the-art methods, such as T-COFFEE and MUSCLE. We also show that although entirely sequence-based, our novel strategy is better at aligning distant sequences when compared with a recent contact-based alignment method. Therefore, our pre-alignment profile strategy should be advantageous for applications that rely on high alignment accuracy such as local structure prediction, comparative modelling and threading.


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