Literature DB >> 15609306

Ab initio prediction of the three-dimensional structure of a de novo designed protein: a double-blind case study.

John L Klepeis1, Yinan Wei, Michael H Hecht, Christodoulos A Floudas.   

Abstract

Ab initio structure prediction and de novo protein design are two problems at the forefront of research in the fields of structural biology and chemistry. The goal of ab initio structure prediction of proteins is to correctly characterize the 3D structure of a protein using only the amino acid sequence as input. De novo protein design involves the production of novel protein sequences that adopt a desired fold. In this work, the results of a double-blind study are presented in which a new ab initio method was successfully used to predict the 3D structure of a protein designed through an experimental approach using binary patterned combinatorial libraries of de novo sequences. The predicted structure, which was produced before the experimental structure was known and without consideration of the design goals, and the final NMR analysis both characterize this protein as a 4-helix bundle. The similarity of these structures is evidenced by both small RMSD values between the coordinates of the two structures and a detailed analysis of the helical packing.

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Year:  2005        PMID: 15609306     DOI: 10.1002/prot.20338

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


  17 in total

1.  New compstatin variants through two de novo protein design frameworks.

Authors:  M L Bellows; H K Fung; M S Taylor; C A Floudas; A López de Victoria; D Morikis
Journal:  Biophys J       Date:  2010-05-19       Impact factor: 4.033

2.  A multi-objective evolutionary approach to the protein structure prediction problem.

Authors:  Vincenzo Cutello; Giuseppe Narzisi; Giuseppe Nicosia
Journal:  J R Soc Interface       Date:  2006-02-22       Impact factor: 4.118

3.  An improved hybrid global optimization method for protein tertiary structure prediction.

Authors:  Scott R McAllister; Christodoulos A Floudas
Journal:  Comput Optim Appl       Date:  2010-03-01       Impact factor: 2.167

Review 4.  Progress and challenges in protein structure prediction.

Authors:  Yang Zhang
Journal:  Curr Opin Struct Biol       Date:  2008-04-22       Impact factor: 6.809

Review 5.  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

6.  Dead-end elimination with perturbations (DEEPer): a provable protein design algorithm with continuous sidechain and backbone flexibility.

Authors:  Mark A Hallen; Daniel A Keedy; Bruce R Donald
Journal:  Proteins       Date:  2012-09-18

7.  Forcefield_PTM: Ab Initio Charge and AMBER Forcefield Parameters for Frequently Occurring Post-Translational Modifications.

Authors:  George A Khoury; Jeff P Thompson; James Smadbeck; Chris A Kieslich; Christodoulos A Floudas
Journal:  J Chem Theory Comput       Date:  2013-12-10       Impact factor: 6.006

8.  Contact prediction for beta and alpha-beta proteins using integer linear optimization and its impact on the first principles 3D structure prediction method ASTRO-FOLD.

Authors:  R Rajgaria; Y Wei; C A Floudas
Journal:  Proteins       Date:  2010-06

9.  Mutations affecting the oligomerization interface of G-protein-coupled receptors revealed by a novel de novo protein design framework.

Authors:  Martin S Taylor; Ho K Fung; Rohit Rajgaria; Marta Filizola; Harel Weinstein; Christodoulos A Floudas
Journal:  Biophys J       Date:  2008-01-04       Impact factor: 4.033

10.  Interplay of I-TASSER and QUARK for template-based and ab initio protein structure prediction in CASP10.

Authors:  Yang Zhang
Journal:  Proteins       Date:  2013-08-31
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