Literature DB >> 16796556

Large-scale prediction of protein structure and function from sequence.

S C E Tosatto1, S Toppo.   

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.

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Year:  2006        PMID: 16796556     DOI: 10.2174/138161206777585238

Source DB:  PubMed          Journal:  Curr Pharm Des        ISSN: 1381-6128            Impact factor:   3.116


  3 in total

1.  Improving the quality of protein structure models by selecting from alignment alternatives.

Authors:  Ingolf Sommer; Stefano Toppo; Oliver Sander; Thomas Lengauer; Silvio C E Tosatto
Journal:  BMC Bioinformatics       Date:  2006-07-27       Impact factor: 3.169

2.  Rapid annotation of anonymous sequences from genome projects using semantic similarities and a weighting scheme in gene ontology.

Authors:  Paolo Fontana; Alessandro Cestaro; Riccardo Velasco; Elide Formentin; Stefano Toppo
Journal:  PLoS One       Date:  2009-02-27       Impact factor: 3.240

3.  Prediction of Protein-Protein Interactions from Amino Acid Sequences Based on Continuous and Discrete Wavelet Transform Features.

Authors:  Tao Wang; Liping Li; Yu-An Huang; Hui Zhang; Yahong Ma; Xing Zhou
Journal:  Molecules       Date:  2018-04-04       Impact factor: 4.411

  3 in total

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