Literature DB >> 12696050

Increased detection of structural templates using alignments of designed sequences.

Stefan M Larson1, Amit Garg, John R Desjarlais, Vijay S Pande.   

Abstract

Protein structure prediction by comparative modeling benefits greatly from the use of multiple sequence alignment information to improve the accuracy of structural template identification and the alignment of target sequences to structural templates. Unfortunately, this benefit is limited to those protein sequences for which at least several natural sequence homologues exist. We show here that the use of large diverse alignments of computationally designed protein sequences confers many of the same benefits as natural sequences in identifying structural templates for comparative modeling targets. A large-scale massively parallelized application of an all-atom protein design algorithm, including a simple model of peptide backbone flexibility, has allowed us to generate 500 diverse, non-native, high-quality sequences for each of 264 protein structures in our test set. PSI-BLAST searches using the sequence profiles generated from the designed sequences ("reverse" BLAST searches) give near-perfect accuracy in identifying true structural homologues of the parent structure, with 54% coverage. In 41 of 49 genomes scanned using reverse BLAST searches, at least one novel structural template (not found by the standard method of PSI-BLAST against PDB) is identified. Further improvements in coverage, through optimizing the scoring function used to design sequences and continued application to new protein structures beyond the test set, will allow this method to mature into a useful strategy for identifying distantly related structural templates. Copyright 2003 Wiley-Liss, Inc.

Mesh:

Substances:

Year:  2003        PMID: 12696050     DOI: 10.1002/prot.10346

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


  15 in total

Review 1.  Pretty good guessing: protein structure prediction at CASP5.

Authors:  Rosemarie Swanson; Jerry Tsai
Journal:  J Bacteriol       Date:  2003-07       Impact factor: 3.490

2.  A de novo redesign of the WW domain.

Authors:  Christina M Kraemer-Pecore; Juliette T J Lecomte; John R Desjarlais
Journal:  Protein Sci       Date:  2003-10       Impact factor: 6.725

3.  Improving computational protein design by using structure-derived sequence profile.

Authors:  Liang Dai; Yuedong Yang; Hyung Rae Kim; Yaoqi Zhou
Journal:  Proteins       Date:  2010-08-01

4.  Improvement of comparative model accuracy by free-energy optimization along principal components of natural structural variation.

Authors:  Bin Qian; Angel R Ortiz; David Baker
Journal:  Proc Natl Acad Sci U S A       Date:  2004-10-18       Impact factor: 11.205

5.  Toward full-sequence de novo protein design with flexible templates for human beta-defensin-2.

Authors:  Ho Ki Fung; Christodoulos A Floudas; Martin S Taylor; Li Zhang; Dimitrios Morikis
Journal:  Biophys J       Date:  2007-09-07       Impact factor: 4.033

6.  Computational protein design and large-scale assessment by I-TASSER structure assembly simulations.

Authors:  Andrea Bazzoli; Andrea G B Tettamanzi; Yang Zhang
Journal:  J Mol Biol       Date:  2011-02-15       Impact factor: 5.469

Review 7.  Computational methods for de novo protein design and its applications to the human immunodeficiency virus 1, purine nucleoside phosphorylase, ubiquitin specific protease 7, and histone demethylases.

Authors:  M L Bellows; C A Floudas
Journal:  Curr Drug Targets       Date:  2010-03       Impact factor: 3.465

8.  Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.

Authors:  Marcel Schmidt Am Busch; Audrey Sedano; Thomas Simonson
Journal:  PLoS One       Date:  2010-05-05       Impact factor: 3.240

9.  Recognition of beta-structural motifs using hidden Markov models trained with simulated evolution.

Authors:  Anoop Kumar; Lenore Cowen
Journal:  Bioinformatics       Date:  2010-06-15       Impact factor: 6.937

10.  A correspondence between solution-state dynamics of an individual protein and the sequence and conformational diversity of its family.

Authors:  Gregory D Friedland; Nils-Alexander Lakomek; Christian Griesinger; Jens Meiler; Tanja Kortemme
Journal:  PLoS Comput Biol       Date:  2009-05-29       Impact factor: 4.475

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