Literature DB >> 14579333

Predictions without templates: new folds, secondary structure, and contacts in CASP5.

Patrick Aloy1, Alexander Stark, Caroline Hadley, Robert B Russell.   

Abstract

We present the assessment of CASP5 predictions in the new fold category. For coordinate predictions, we considered five targets with new folds and eight lying on the fold recognition borderline. We performed detailed visual and numerical comparisons between predicted and experimental structures to assess prediction accuracy. The two procedures largely agreed, but the visual inspection identified instances where metrics, such as GDT_TS, ranked what we considered incorrect predictions highly. We found the quality of the best predictions to be very good: for nearly every target at least one group predicted a structure close to the correct one. However, selection of the best of five models is still problematic. The group of David Baker once again proved to be best overall, with many individual highlights. However, high quality and consistency were also seen from others, suggesting that the community is moving toward general procedures to predict accurate structures for proteins showing no resemblance to anything seen before. Predictions for secondary structure showed at best limited progress since CASP4. The number of targets is probably too small to spot differences in performance between methods, suggesting that such predictions might be better evaluated with schemes involving more proteins. For contact predictions, accuracies are still low, although there were several instances of accurate and useful contacts predicted de novo, and new approaches hint at future progress. Copyright 2003 Wiley-Liss, Inc.

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Year:  2003        PMID: 14579333     DOI: 10.1002/prot.10546

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  31 in total

1.  An automatic method for CASP9 free modeling structure prediction assessment.

Authors:  Qian Cong; Lisa N Kinch; Jimin Pei; Shuoyong Shi; Vyacheslav N Grishin; Wenlin Li; Nick V Grishin
Journal:  Bioinformatics       Date:  2011-10-12       Impact factor: 6.937

2.  Genomics-aided structure prediction.

Authors:  Joanna I Sułkowska; Faruck Morcos; Martin Weigt; Terence Hwa; José N Onuchic
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-12       Impact factor: 11.205

3.  Molecular Simulations Find Stable Structures in Fragments of Protein G.

Authors:  Tjaša Urbič; Tomaž Urbič; Franc Avbelj; Ken A Dill
Journal:  Acta Chim Slov       Date:  2008-01-26       Impact factor: 1.735

4.  Protein loop modeling by using fragment assembly and analytical loop closure.

Authors:  Julian Lee; Dongseon Lee; Hahnbeom Park; Evangelos A Coutsias; Chaok Seok
Journal:  Proteins       Date:  2010-09-24

5.  Gaussian-weighted RMSD superposition of proteins: a structural comparison for flexible proteins and predicted protein structures.

Authors:  Kelly L Damm; Heather A Carlson
Journal:  Biophys J       Date:  2006-03-24       Impact factor: 4.033

6.  The code-based physics of formation of alpha-helices and beta-hairpins in water-soluble proteins.

Authors:  B V Shestopalov
Journal:  Dokl Biochem Biophys       Date:  2007 Sep-Oct       Impact factor: 0.788

Review 7.  Exploiting protein structure data to explore the evolution of protein function and biological complexity.

Authors:  Russell L Marsden; Juan A G Ranea; Antonio Sillero; Oliver Redfern; Corin Yeats; Michael Maibaum; David Lee; Sarah Addou; Gabrielle A Reeves; Timothy J Dallman; Christine A Orengo
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-03-29       Impact factor: 6.237

8.  A comprehensive assessment of sequence-based and template-based methods for protein contact prediction.

Authors:  Sitao Wu; Yang Zhang
Journal:  Bioinformatics       Date:  2008-02-22       Impact factor: 6.937

9.  In silico chaperonin-like cycle helps folding of proteins for structure prediction.

Authors:  Tadaomi Furuta; Yoshimi Fujitsuka; George Chikenji; Shoji Takada
Journal:  Biophys J       Date:  2008-01-04       Impact factor: 4.033

10.  Structure similarity measure with penalty for close non-equivalent residues.

Authors:  Ruslan I Sadreyev; ShuoYong Shi; David Baker; Nick V Grishin
Journal:  Bioinformatics       Date:  2009-03-25       Impact factor: 6.937

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