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Surveying the manifold divergence of an entire protein class for statistical clues to underlying biochemical mechanisms.

Abstract：

:Certain residues have no known function yet are co-conserved across distantly related protein families and diverse organisms, suggesting that they perform critical roles associated with as-yet-unidentified molecular properties and mechanisms. This raises the question of how to obtain additional clues regarding these mysterious biochemical phenomena with a view to formulating experimentally testable hypotheses. One approach is to access the implicit biochemical information encoded within the vast amount of genomic sequence data now becoming available. Here, a new Gibbs sampling strategy is formulated and implemented that can partition hundreds of thousands of sequences within a major protein class into multiple, functionally-divergent categories based on those pattern residues that best discriminate between categories. The sampler precisely defines the partition and pattern for each category by explicitly modeling unrelated, non-functional and related-yet-divergent proteins that would otherwise obscure the analysis. To aid biological interpretation, auxiliary routines can characterize pattern residues within available crystal structures and identify those structures most likely to shed light on the roles of pattern residues. This approach can be used to define and annotate automatically subgroup-specific conserved domain profiles based on statistically-rigorous empirical criteria rather than on the subjective and labor-intensive process of manual curation. Incorporating such profiles into domain database search sites (such as the NCBI BLAST site) will provide biologists with previously inaccessible molecular information useful for hypothesis generation and experimental design. Analyses of P-loop GTPases and of AAA+ ATPases illustrate the sampler's ability to obtain such information.

journal_name

Stat Appl Genet Mol Biol

journal_title

Statistical applications in genetics and molecular biology

authors

Neuwald AF

doi

10.2202/1544-6115.1666

subject

Has Abstract

pub_date

2011-01-01 00:00:00

pages

Article 36

eissn

2194-6302

issn

1544-6115

journal_volume

pub_type

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Surveying the manifold divergence of an entire protein class for statistical clues to underlying biochemical mechanisms.