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Single-molecule fluorescence reveals sequence-specific misfolding in multidomain proteins.

ABSTRACT: A large range of debilitating medical conditions is linked to protein misfolding, which may compete with productive folding particularly in proteins containing multiple domains. Seventy-five per cent of the eukaryotic proteome consists of multidomain proteins, yet it is not understood how interdomain misfolding is avoided. It has been proposed that maintaining low sequence identity between covalently linked domains is a mechanism to avoid misfolding. Here we use single-molecule Förster resonance energy transfer to detect and quantify rare misfolding events in tandem immunoglobulin domains from the I band of titin under native conditions. About 5.5 per cent of molecules with identical domains misfold during refolding in vitro and form an unexpectedly stable state with an unfolding half-time of several days. Tandem arrays of immunoglobulin-like domains in humans show significantly lower sequence identity between neighbouring domains than between non-adjacent domains. In particular, the sequence identity of neighbouring domains has been found to be preferentially below 40 per cent. We observe no misfolding for a tandem of naturally neighbouring domains with low sequence identity (24 per cent), whereas misfolding occurs between domains that are 42 per cent identical. Coarse-grained molecular simulations predict the formation of domain-swapped structures that are in excellent agreement with the observed transfer efficiency of the misfolded species. We infer that the interactions underlying misfolding are very specific and result in a sequence-specific domain-swapping mechanism. Diversifying the sequence between neighbouring domains seems to be a successful evolutionary strategy to avoid misfolding in multidomain proteins.

SUBMITTER: Borgia MB

PROVIDER: S-EPMC3160465 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Single-molecule fluorescence reveals sequence-specific misfolding in multidomain proteins.

Borgia Madeleine B MB Borgia Alessandro A Best Robert B RB Steward Annette A Nettels Daniel D Wunderlich Bengt B Schuler Benjamin B Clarke Jane J

Nature 20110529 7353

A large range of debilitating medical conditions is linked to protein misfolding, which may compete with productive folding particularly in proteins containing multiple domains. Seventy-five per cent of the eukaryotic proteome consists of multidomain proteins, yet it is not understood how interdomain misfolding is avoided. It has been proposed that maintaining low sequence identity between covalently linked domains is a mechanism to avoid misfolding. Here we use single-molecule Förster resonance ...[more]

PMID: 21623368

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Project description:We address the problem of homology identification in complex multidomain families with varied domain architectures. The challenge is to distinguish sequence pairs that share common ancestry from pairs that share an inserted domain but are otherwise unrelated. This distinction is essential for accuracy in gene annotation, function prediction, and comparative genomics. There are two major obstacles to multidomain homology identification: lack of a formal definition and lack of curated benchmarks for evaluating the performance of new methods. We offer preliminary solutions to both problems: 1) an extension of the traditional model of homology to include domain insertions; and 2) a manually curated benchmark of well-studied families in mouse and human. We further present Neighborhood Correlation, a novel method that exploits the local structure of the sequence similarity network to identify homologs with great accuracy based on the observation that gene duplication and domain shuffling leave distinct patterns in the sequence similarity network. In a rigorous, empirical comparison using our curated data, Neighborhood Correlation outperforms sequence similarity, alignment length, and domain architecture comparison. Neighborhood Correlation is well suited for automated, genome-scale analyses. It is easy to compute, does not require explicit knowledge of domain architecture, and classifies both single and multidomain homologs with high accuracy. Homolog predictions obtained with our method, as well as our manually curated benchmark and a web-based visualization tool for exploratory analysis of the network neighborhood structure, are available at http://www.neighborhoodcorrelation.org. Our work represents a departure from the prevailing view that the concept of homology cannot be applied to genes that have undergone domain shuffling. In contrast to current approaches that either focus on the homology of individual domains or consider only families with identical domain architectures, we show that homology can be rationally defined for multidomain families with diverse architectures by considering the genomic context of the genes that encode them. Our study demonstrates the utility of mining network structure for evolutionary information, suggesting this is a fertile approach for investigating evolutionary processes in the post-genomic era.

Dataset Information

Single-molecule fluorescence reveals sequence-specific misfolding in multidomain proteins.

Publications

Single-molecule fluorescence reveals sequence-specific misfolding in multidomain proteins.

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