PubAg

Main content area

Accurate statistical model of comparison between multiple sequence alignments

Author:
Sadreyev, Ruslan I., Grishin, Nick V.
Source:
Nucleic acids research 2008 v.36 no.7 pp. 2240-2248
ISSN:
0305-1048
Subject:
databases, germplasm conservation, nucleic acids, prediction, protein secondary structure, sequence alignment, sequence diversity, statistical models
Abstract:
Comparison of multiple protein sequence alignments (MSA) reveals unexpected evolutionary relations between protein families and leads to exciting predictions of spatial structure and function. The power of MSA comparison critically depends on the quality of statistical model used to rank the similarities found in a database search, so that biologically relevant relationships are discriminated from spurious connections. Here, we develop an accurate statistical description of MSA comparison that does not originate from conventional models of single sequence comparison and captures essential features of protein families. As a final result, we compute E-values for the similarity between any two MSA using a mathematical function that depends on MSA lengths and sequence diversity. To develop these estimates of statistical significance, we first establish a procedure for generating realistic alignment decoys that reproduce natural patterns of sequence conservation dictated by protein secondary structure. Second, since similarity scores between these alignments do not follow the classic Gumbel extreme value distribution, we propose a novel distribution that yields statistically perfect agreement with the data. Third, we apply this random model to database searches and show that it surpasses conventional models in the accuracy of detecting remote protein similarities.
Agid:
2078224