Protein domains

Protein domains

This page is a placeholder, or under current development; it is here principally to establish the logical framework of the site. The material on this page is correct, but incomplete.

 

Contents

InterPro

Pfam

CDD

CATH

   

Further reading and resources

SMART domain and sequence analysis

Rekapalli et al. (2012) Dynamics of domain coverage of the protein sequence universe. BMC Genomics 13:634. (pmid: 23157439)

[ PubMed ] [ DOI ] Abstract BACKGROUND: The currently known protein sequence space consists of millions of sequences in public databases and is rapidly expanding. Assigning sequences to families leads to a better understanding of protein function and the nature of the protein universe. However, a large portion of the current protein space remains unassigned and is referred to as its "dark matter". RESULTS: Here we suggest that true size of "dark matter" is much larger than stated by current definitions. We propose an approach to reducing the size of "dark matter" by identifying and subtracting regions in protein sequences that are not likely to contain any domain. CONCLUSIONS: Recent improvements in computational domain modeling result in a decrease, albeit slowly, in the relative size of "dark matter"; however, its absolute size increases substantially with the growth of sequence data.

Zheng et al. (2013) Frustration in the energy landscapes of multidomain protein misfolding. Proc Natl Acad Sci U.S.A 110:1680-5. (pmid: 23319605)

[ PubMed ] [ DOI ] Abstract Frustration from strong interdomain interactions can make misfolding a more severe problem in multidomain proteins than in single-domain proteins. On the basis of bioinformatic surveys, it has been suggested that lowering the sequence identity between neighboring domains is one of nature's solutions to the multidomain misfolding problem. We investigate folding of multidomain proteins using the associative-memory, water-mediated, structure and energy model (AWSEM), a predictive coarse-grained protein force field. We find that reducing sequence identity not only decreases the formation of domain-swapped contacts but also decreases the formation of strong self-recognition contacts between β-strands with high hydrophobic content. The ensembles of misfolded structures that result from forming these amyloid-like interactions are energetically disfavored compared with the native state, but entropically favored. Therefore, these ensembles are more stable than the native ensemble under denaturing conditions, such as high temperature. Domain-swapped contacts compete with self-recognition contacts in forming various trapped states, and point mutations can shift the balance between the two types of interaction. We predict that multidomain proteins that lack these specific strong interdomain interactions should fold reliably.

Derbyshire et al. (2012) Annotation of functional sites with the Conserved Domain Database. Database (Oxford) 2012:bar058. (pmid: 22434827)

[ PubMed ] [ DOI ] Abstract The overwhelming fraction of proteins whose sequences have been collected in comprehensive databases may never be assessed for function experimentally. Commonly, putative function is assigned based on similarity to experimentally characterized homologs, either on the level of the entire protein or for single evolutionarily conserved domains. The annotation of individual sites provides more detailed insights regarding the correspondence between sequence and function, as well as context for the interpretation of sequence variation and the outcomes of experiments. In general, site annotation has to be extracted from the published literature, and can often be transferred to closely related sequence neighbors. The National Center for Biotechnology Information's Conserved Domain Database (CDD) provides a system for curators to record functional (such as active sites or binding sites for cofactors) or characteristic sites (such as signature motifs), which are conserved across domain families, and for the transfer of that annotation to protein database sequences via high-confidence domain matches. Recently, CDD curators have begun to sort-site annotations into seven categories (active, polypeptide binding, nucleic acid binding, ion binding, chemical binding, post-translational modification and other) and here we present a first comparative analysis of sites obtained via domain model matches, juxtaposed with existing site annotation encountered in high-quality data sets. Site annotation derived from domain annotation has the potential to cover large fractions of protein sequences, and we observe that CDD-based site annotation complements existing site annotation in many cases, which may, in part, originate from CDD's curation practice of collecting sites conserved across diverse taxa and supported by evidence from multiple 3D structures.