Large-Scale Prediction of Protein Structure and Function from Sequence

S.   C.E.   Tosatto; S.      Toppo

doi:10.2174/138161206777585238

Abstract

The identification of novel drug targets from genomic data involves the large-scale analysis of many protein sequences. Methods for automated structure and function prediction are an essential tool for this purpose. In this review we concentrate on the recent developments in the field of protein structure prediction and how these can be used to gain hints about the function of proteins. The current state-of-the-art is highlighted through recent community-wide experiments aimed at comparing different approaches. For structure prediction this allows the identification of key improvements to increase the crucial sequence to structure alignment needed for accurate models. Function prediction is a rapidly maturing field that is still being benchmarked. Definitions for protein function are presented and available methods, mostly concentrating on functional site descriptors and structural motifs, presented.

Keywords: Protein structure prediction, CASP, comparative modeling, fold recognition, function prediction, functional annotation

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