Enhanced statistics for local alignment of multiple alignments improves prediction of protein function and structure

Milana Frenkel-Morgenstern, Hillary Voet, Shmuel Pietrokovski

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Motivation: Improved comparisons of multiple sequence alignments (profiles) with other profiles can identify subtle relationships between protein families and motifs significantly beyond the resolution of sequence-based comparisons. Results: The local alignment of multiple alignments (LAMA) method was modified to estimate alignment score significance by applying a new measure based on Fisher's combining method. To verify the new procedure, we used known protein structures, sequence annotations and cyclical relations consistency analysis (CYRCA) sets of consistently aligned blocks. Using the new significance measure improved the sensitivity of LAMA without altering its selectivity. The program performed better than other profile-to-profile methods (COM-PASS and Prof_sim) and a sequence-to-profile method (PSI-BLAST). The testing was large scale and used several parameters, including pseudo-counts profile calculations and local ungapped blocks or more extended gapped profiles. This comparison provides guidelines to the relative advantages of each method for different cases. We demonstrate and discuss the unique advantages of using block multiple alignments of protein motifs.

Original languageEnglish
Pages (from-to)2950-2956
Number of pages7
Issue number13
StatePublished - 1 Jul 2005
Externally publishedYes

Bibliographical note

Funding Information:
This research was supported by The Israel Science Foundation, founded by The Israel Academy of Sciences and Humanities, and the Weizmann Institute of Science Crown Human Genome, and Leon and Julia Forscheimer Molecular Genetics centers. S.P. holds the Ronson and Harris Career Development Chair.


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