Literature DB >> 27914050

Multistate Computational Protein Design with Backbone Ensembles.

James A Davey1, Roberto A Chica2.   

Abstract

The ability of computational protein design (CPD) to identify protein sequences possessing desired characteristics in vast sequence spaces makes it a highly valuable tool in the protein engineering toolbox. CPD calculations are typically performed using a single-state design (SSD) approach in which amino-acid sequences are optimized on a single protein structure. Although SSD has been successfully applied to the design of numerous protein functions and folds, the approach can lead to the incorrect rejection of desirable sequences because of the combined use of a fixed protein backbone template and a set of rigid rotamers. This fixed backbone approximation can be addressed by using multistate design (MSD) with backbone ensembles. MSD improves the quality of predicted sequences by using ensembles approximating conformational flexibility as input templates instead of a single fixed protein structure. In this chapter, we present a step-by-step guide to the implementation and analysis of MSD calculations with backbone ensembles. Specifically, we describe ensemble generation with the PertMin protocol, execution of MSD calculations for recapitulation of Streptococcal protein G domain β1 mutant stability, and analysis of computational predictions by sequence binning. Furthermore, we provide a comparison between MSD and SSD calculation results and discuss the benefits of multistate approaches to CPD.

Entities:  

Keywords:  Multistate analysis; Multistate design; PertMin; Protein G; Protein stability prediction; Receiver operating characteristic; Single-state design

Mesh:

Substances:

Year:  2017        PMID: 27914050     DOI: 10.1007/978-1-4939-6637-0_7

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  9 in total

1.  Rational design of proteins that exchange on functional timescales.

Authors:  James A Davey; Adam M Damry; Natalie K Goto; Roberto A Chica
Journal:  Nat Chem Biol       Date:  2017-10-23       Impact factor: 15.040

2.  Comparison of Rosetta flexible-backbone computational protein design methods on binding interactions.

Authors:  Amanda L Loshbaugh; Tanja Kortemme
Journal:  Proteins       Date:  2019-08-10

3.  Computational Design of Miniprotein Binders.

Authors:  Younes Bouchiba; Manon Ruffini; Thomas Schiex; Sophie Barbe
Journal:  Methods Mol Biol       Date:  2022

Review 4.  The stability and dynamics of computationally designed proteins.

Authors:  Natali A Gonzalez; Brigitte A Li; Michelle E McCully
Journal:  Protein Eng Des Sel       Date:  2022-02-17       Impact factor: 1.952

5.  Expanding the space of protein geometries by computational design of de novo fold families.

Authors:  Xingjie Pan; Michael C Thompson; Yang Zhang; Lin Liu; James S Fraser; Mark J S Kelly; Tanja Kortemme
Journal:  Science       Date:  2020-08-28       Impact factor: 47.728

6.  Computational design of a modular protein sense-response system.

Authors:  Anum A Glasgow; Yao-Ming Huang; Daniel J Mandell; Michael Thompson; Ryan Ritterson; Amanda L Loshbaugh; Jenna Pellegrino; Cody Krivacic; Roland A Pache; Kyle A Barlow; Noah Ollikainen; Deborah Jeon; Mark J S Kelly; James S Fraser; Tanja Kortemme
Journal:  Science       Date:  2019-11-22       Impact factor: 47.728

7.  Multi-state design of flexible proteins predicts sequences optimal for conformational change.

Authors:  Marion F Sauer; Alexander M Sevy; James E Crowe; Jens Meiler
Journal:  PLoS Comput Biol       Date:  2020-02-07       Impact factor: 4.475

8.  Generation of bright monomeric red fluorescent proteins via computational design of enhanced chromophore packing.

Authors:  Sandrine Legault; Derek P Fraser-Halberg; Ralph L McAnelly; Matthew G Eason; Michael C Thompson; Roberto A Chica
Journal:  Chem Sci       Date:  2022-01-11       Impact factor: 9.825

Review 9.  Dynamics, a Powerful Component of Current and Future in Silico Approaches for Protein Design and Engineering.

Authors:  Bartłomiej Surpeta; Carlos Eduardo Sequeiros-Borja; Jan Brezovsky
Journal:  Int J Mol Sci       Date:  2020-04-14       Impact factor: 5.923

  9 in total

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