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Use of designed sequences in protein structure recognition

Kumar, Gayatri and Mudgal, Richa and Srinivasan, Narayanaswamy and Sandhya, Sankaran (2018) Use of designed sequences in protein structure recognition. In: BIOLOGY DIRECT, 13 .

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Official URL: https://dx.doi.org/10.1186/s13062-018-0209-6


Background: Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. Results: We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. Conclusion: The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as `linkers', where natural linkers between distant proteins are unavailable.

Item Type: Journal Article
Additional Information: Copy right of this article belong to BIOMED CENTRAL LTD, 236 GRAYS INN RD, FLOOR 6, LONDON WC1X 8HL, ENGLAND
Department/Centre: Division of Biological Sciences > Molecular Biophysics Unit
Depositing User: Id for Latest eprints
Date Deposited: 13 Jun 2018 15:25
Last Modified: 13 Jun 2018 15:25
URI: http://eprints.iisc.ac.in/id/eprint/60015

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