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  4. Rosetta FunFolDes - A general framework for the computational design of functional proteins
 
research article

Rosetta FunFolDes - A general framework for the computational design of functional proteins

Bonet, Jaume  
•
Wehrle, Sarah  
•
Schriever, Karen
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November 1, 2018
PLoS Computational Biology

The robust computational design of functional proteins has the potential to deeply impact translational research and broaden our understanding of the determinants of protein function and stability. The low success rates of computational design protocols and the extensive in vitro optimization often required, highlight the challenge of designing proteins that perform essential biochemical functions, such as binding or catalysis. One of the most simplistic approaches for the design of function is to adopt functional motifs in naturally occurring proteins and transplant them to computationally designed proteins. The structural complexity of the functional motif largely determines how readily one can find host protein structures that are "designable", meaning that are likely to present the functional motif in the desired conformation. One promising route to enhance the "designability" of protein structures is to allow backbone flexibility. Here, we present a computational approach that couples conformational folding with sequence design to embed functional motifs into heterologous proteins-Rosetta Functional Folding and Design (FunFolDes). We performed extensive computational benchmarks, where we observed that the enforcement of functional requirements resulted in designs distant from the global energetic minimum of the protein. An observation consistent with several experimental studies that have revealed function-stability tradeoffs. To test the design capabilities of FunFolDes we transplanted two viral epitopes into distant structural templates including one de novo "functionless" fold, which represent two typical challenges where the designability problem arises. The designed proteins were experimentally characterized showing high binding affinities to monoclonal antibodies, making them valuable candidates for vaccine design endeavors. Overall, we present an accessible strategy to repurpose old protein folds for new functions. This may lead to important improvements on the computational design of proteins, with structurally complex functional sites, that can perform elaborate biochemical functions related to binding and catalysis.

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Type
research article
DOI
10.1371/journal.pcbi.1006623
Web of Science ID

WOS:000451835900047

Author(s)
Bonet, Jaume  
Wehrle, Sarah  
Schriever, Karen
Yang, Che
Billet, Anne
Sesterhenn, Fabian  
Scheck, Andreas  
Sverrisson, Freyr  
Veselkova, Barbora
Vollers, Sabrina  
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Date Issued

2018-11-01

Published in
PLoS Computational Biology
Volume

14

Issue

11

Article Number

e1006623

Subjects

Biochemical Research Methods

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Mathematical & Computational Biology

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Biochemistry & Molecular Biology

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Mathematical & Computational Biology

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de-novo design

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structure prediction

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binding

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epitope

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principles

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stability

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scaffolds

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docking

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motif

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ph

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LPDI  
Available on Infoscience
December 14, 2018
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/152962
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