Literature DB >> 27181418

The unexpected structure of the designed protein Octarellin V.1 forms a challenge for protein structure prediction tools.

Maximiliano Figueroa1, Mike Sleutel2, Marylene Vandevenne3, Gregory Parvizi3, Sophie Attout3, Olivier Jacquin3, Julie Vandenameele4, Axel W Fischer5, Christian Damblon6, Erik Goormaghtigh7, Marie Valerio-Lepiniec8, Agathe Urvoas8, Dominique Durand8, Els Pardon9, Jan Steyaert9, Philippe Minard8, Dominique Maes2, Jens Meiler5, André Matagne4, Joseph A Martial3, Cécile Van de Weerdt10.   

Abstract

Despite impressive successes in protein design, designing a well-folded protein of more 100 amino acids de novo remains a formidable challenge. Exploiting the promising biophysical features of the artificial protein Octarellin V, we improved this protein by directed evolution, thus creating a more stable and soluble protein: Octarellin V.1. Next, we obtained crystals of Octarellin V.1 in complex with crystallization chaperons and determined the tertiary structure. The experimental structure of Octarellin V.1 differs from its in silico design: the (αβα) sandwich architecture bears some resemblance to a Rossman-like fold instead of the intended TIM-barrel fold. This surprising result gave us a unique and attractive opportunity to test the state of the art in protein structure prediction, using this artificial protein free of any natural selection. We tested 13 automated webservers for protein structure prediction and found none of them to predict the actual structure. More than 50% of them predicted a TIM-barrel fold, i.e. the structure we set out to design more than 10years ago. In addition, local software runs that are human operated can sample a structure similar to the experimental one but fail in selecting it, suggesting that the scoring and ranking functions should be improved. We propose that artificial proteins could be used as tools to test the accuracy of protein structure prediction algorithms, because their lack of evolutionary pressure and unique sequences features.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Artificial proteins; De novo design; Molecular modeling; Protein design

Mesh:

Substances:

Year:  2016        PMID: 27181418     DOI: 10.1016/j.jsb.2016.05.004

Source DB:  PubMed          Journal:  J Struct Biol        ISSN: 1047-8477            Impact factor:   2.867


  5 in total

1.  Overview of the experimental and computational approaches to protein design session at the 19th IUPAB congress and 11th EBSA congress.

Authors:  Elizabeth H C Bromley
Journal:  Biophys Rev       Date:  2017-08-12

Review 2.  Evolution, folding, and design of TIM barrels and related proteins.

Authors:  Sergio Romero-Romero; Sina Kordes; Florian Michel; Birte Höcker
Journal:  Curr Opin Struct Biol       Date:  2021-01-13       Impact factor: 6.809

3.  Ligand-induced conformational switch in an artificial bidomain protein scaffold.

Authors:  Corentin Léger; Thibault Di Meo; Magali Aumont-Nicaise; Christophe Velours; Dominique Durand; Ines Li de la Sierra-Gallay; Herman van Tilbeurgh; Niko Hildebrandt; Michel Desmadril; Agathe Urvoas; Marie Valerio-Lepiniec; Philippe Minard
Journal:  Sci Rep       Date:  2019-02-04       Impact factor: 4.379

4.  Biophysical characterization data of the artificial protein Octarellin V.1 and binding test with its X-ray helpers.

Authors:  Maximiliano Figueroa; Julie Vandenameele; Erik Goormaghtigh; Marie Valerio-Lepiniec; Philippe Minard; André Matagne; Cécile Van de Weerdt
Journal:  Data Brief       Date:  2016-07-26

5.  Highly active enzymes by automated combinatorial backbone assembly and sequence design.

Authors:  Gideon Lapidoth; Olga Khersonsky; Rosalie Lipsh; Orly Dym; Shira Albeck; Shelly Rogotner; Sarel J Fleishman
Journal:  Nat Commun       Date:  2018-07-17       Impact factor: 14.919

  5 in total

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