Literature DB >> 27659562

Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template.

Kristoffer E Johansson1, Nicolai Tidemand Johansen1, Signe Christensen1, Scott Horowitz2, James C A Bardwell2, Johan G Olsen1, Martin Willemoës1, Kresten Lindorff-Larsen1, Jesper Ferkinghoff-Borg3, Thomas Hamelryck4, Jakob R Winther1.   

Abstract

Despite the development of powerful computational tools, the full-sequence design of proteins still remains a challenging task. To investigate the limits and capabilities of computational tools, we conducted a study of the ability of the program Rosetta to predict sequences that recreate the authentic fold of thioredoxin. Focusing on the influence of conformational details in the template structures, we based our study on 8 experimentally determined template structures and generated 120 designs from each. For experimental evaluation, we chose six sequences from each of the eight templates by objective criteria. The 48 selected sequences were evaluated based on their progressive ability to (1) produce soluble protein in Escherichia coli and (2) yield stable monomeric protein, and (3) on the ability of the stable, soluble proteins to adopt the target fold. Of the 48 designs, we were able to synthesize 32, 20 of which resulted in soluble protein. Of these, only two were sufficiently stable to be purified. An X-ray crystal structure was solved for one of the designs, revealing a close resemblance to the target structure. We found a significant difference among the eight template structures to realize the above three criteria despite their high structural similarity. Thus, in order to improve the success rate of computational full-sequence design methods, we recommend that multiple template structures are used. Furthermore, this study shows that special care should be taken when optimizing the geometry of a structure prior to computational design when using a method that is based on rigid conformations.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Rosetta; computational protein design; de novo protein design; protein folding; protein stability

Mesh:

Substances:

Year:  2016        PMID: 27659562      PMCID: PMC5242314          DOI: 10.1016/j.jmb.2016.09.013

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  61 in total

1.  PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa Predictions.

Authors:  Mats H M Olsson; Chresten R Søndergaard; Michal Rostkowski; Jan H Jensen
Journal:  J Chem Theory Comput       Date:  2011-01-06       Impact factor: 6.006

2.  Energy functions for protein design: adjustment with protein-protein complex affinities, models for the unfolded state, and negative design of solubility and specificity.

Authors:  Navin Pokala; Tracy M Handel
Journal:  J Mol Biol       Date:  2005-01-20       Impact factor: 5.469

3.  WWW-query: an on-line retrieval system for biological sequence banks.

Authors:  G Perrière; M Gouy
Journal:  Biochimie       Date:  1996       Impact factor: 4.079

4.  De novo protein design: fully automated sequence selection.

Authors:  B I Dahiyat; S L Mayo
Journal:  Science       Date:  1997-10-03       Impact factor: 47.728

5.  Tertiary templates for proteins. Use of packing criteria in the enumeration of allowed sequences for different structural classes.

Authors:  J W Ponder; F M Richards
Journal:  J Mol Biol       Date:  1987-02-20       Impact factor: 5.469

6.  A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions.

Authors:  Maxim V Shapovalov; Roland L Dunbrack
Journal:  Structure       Date:  2011-06-08       Impact factor: 5.006

7.  Computational de novo design and characterization of a four-helix bundle protein that selectively binds a nonbiological cofactor.

Authors:  Frank V Cochran; Sophia P Wu; Wei Wang; Vikas Nanda; Jeffery G Saven; Michael J Therien; William F DeGrado
Journal:  J Am Chem Soc       Date:  2005-02-09       Impact factor: 15.419

8.  iMOSFLM: a new graphical interface for diffraction-image processing with MOSFLM.

Authors:  T Geoff G Battye; Luke Kontogiannis; Owen Johnson; Harold R Powell; Andrew G W Leslie
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  2011-03-18

9.  Computational de novo design and characterization of a protein that selectively binds a highly hyperpolarizable abiological chromophore.

Authors:  H Christopher Fry; Andreas Lehmann; Louise E Sinks; Inge Asselberghs; Andrey Tronin; Venkata Krishnan; J Kent Blasie; Koen Clays; William F DeGrado; Jeffery G Saven; Michael J Therien
Journal:  J Am Chem Soc       Date:  2013-09-05       Impact factor: 15.419

10.  Exploring the repeat protein universe through computational protein design.

Authors:  T J Brunette; Fabio Parmeggiani; Po-Ssu Huang; Gira Bhabha; Damian C Ekiert; Susan E Tsutakawa; Greg L Hura; John A Tainer; David Baker
Journal:  Nature       Date:  2015-12-16       Impact factor: 49.962

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  2 in total

1.  Knowledge-Based Unfolded State Model for Protein Design.

Authors:  Vaitea Opuu; David Mignon; Thomas Simonson
Journal:  Methods Mol Biol       Date:  2022

2.  A physics-based energy function allows the computational redesign of a PDZ domain.

Authors:  Vaitea Opuu; Young Joo Sun; Titus Hou; Nicolas Panel; Ernesto J Fuentes; Thomas Simonson
Journal:  Sci Rep       Date:  2020-07-07       Impact factor: 4.379

  2 in total

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