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A comprehensive analysis of the structure-function relationship in proteins based on local structure similarity

Hvidsten, Torgeir; Lægreid, Astrid; Kryshtafovych, Andriy; Andersson, Gunnar; Fidelis, Krzysztof; Komorowski, J
Peer reviewed
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http://hdl.handle.net/11250/2382089
Utgivelsesdato
2009
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  • Institutt for klinisk og molekylær medisin [2599]
  • Publikasjoner fra CRIStin - NTNU [26591]
Originalversjon
PLoS ONE 2009, 4(7):e6266   10.1371/journal.pone.0006266
Sammendrag
Background:Sequence similarity to characterized proteins provides testable functional hypotheses for less than 50% of the

proteins identified by genome sequencing projects. With structural genomics it is believed that structural similarities may

give functional hypotheses for many of the remaining proteins.

Methodology/Principal Findings:We provide a systematic analysis of the structure-function relationship in proteins using

the novel concept of local descriptors of protein structure. A local descriptor is a small substructure of a protein which

includes both short- and long-range interactions. We employ a library of commonly reoccurring local descriptors general

enough to assemble most existing protein structures. We then model the relationship between these local shapes and Gene

Ontology using rule-based learning. Our IF-THEN rule model offers legible, high resolution descriptions that combine local

substructures and is able to discriminate functions even for functionally versatile folds such as the frequently occurring TIM

barrel and Rossmann fold. By evaluating the predictive performance of the model, we provide a comprehensive

quantification of the structure-function relationship based only on local structure similarity. Our findings are, among others,

that conserved structure is a stronger prerequisite for enzymatic activity than for binding specificity, and that structurebased predictions complement sequence-based predictions. The model is capable of generating correct hypotheses, as

confirmed by a literature study, even when no significant sequence similarity to characterized proteins exists.

Conclusions/Significance:Our approach offers a new and complete description and quantification of the structure-function

relationship in proteins. By demonstrating how our predictions offer higher sensitivity than using global structure, and

complement the use of sequence, we show that the presented ideas could advance the development of meta-servers in

function prediction.
Utgiver
Public Library of Science
Tidsskrift
PLoS ONE

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