Literature DB >> 27914055

An Evolution-Based Approach to De Novo Protein Design.

Jeffrey R Brender1, David Shultis1, Naureen Aslam Khattak1, Yang Zhang2,3.   

Abstract

EvoDesign is a computational algorithm that allows the rapid creation of new protein sequences that are compatible with specific protein structures. As such, it can be used to optimize protein stability, to resculpt the protein surface to eliminate undesired protein-protein interactions, and to optimize protein-protein binding. A major distinguishing feature of EvoDesign in comparison to other protein design programs is the use of evolutionary information in the design process to guide the sequence search toward native-like sequences known to adopt structurally similar folds as the target. The observed frequencies of amino acids in specific positions in the structure in the form of structural profiles collected from proteins with similar folds and complexes with similar interfaces can implicitly capture many subtle effects that are essential for correct folding and protein-binding interactions. As a result of the inclusion of evolutionary information, the sequences designed by EvoDesign have native-like folding and binding properties not seen by other physics-based design methods. In this chapter, we describe how EvoDesign can be used to redesign proteins with a focus on the computational and experimental procedures that can be used to validate the designs.

Entities:  

Keywords:  Circular dichroism; Evolutionary profile; Experimental protein validation; Nuclear magnetic resonance; Protein design; Protein structure modeling; Recombinant expression

Mesh:

Substances:

Year:  2017        PMID: 27914055      PMCID: PMC5667548          DOI: 10.1007/978-1-4939-6637-0_12

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


  74 in total

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Authors:  Yang Zhang; Jeffrey Skolnick
Journal:  J Comput Chem       Date:  2004-04-30       Impact factor: 3.376

2.  Rapid assessment of protein structural stability and fold validation via NMR.

Authors:  Bernd Hoffmann; Christian Eichmüller; Othmar Steinhauser; Robert Konrat
Journal:  Methods Enzymol       Date:  2005       Impact factor: 1.600

3.  Backrub-like backbone simulation recapitulates natural protein conformational variability and improves mutant side-chain prediction.

Authors:  Colin A Smith; Tanja Kortemme
Journal:  J Mol Biol       Date:  2008-05-17       Impact factor: 5.469

4.  Computational protein design and large-scale assessment by I-TASSER structure assembly simulations.

Authors:  Andrea Bazzoli; Andrea G B Tettamanzi; Yang Zhang
Journal:  J Mol Biol       Date:  2011-02-15       Impact factor: 5.469

5.  A large-scale experiment to assess protein structure prediction methods.

Authors:  J Moult; J T Pedersen; R Judson; K Fidelis
Journal:  Proteins       Date:  1995-11

6.  Profile scanning for three-dimensional structural patterns in protein sequences.

Authors:  M Gribskov; M Homyak; J Edenfield; D Eisenberg
Journal:  Comput Appl Biosci       Date:  1988-03

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Authors:  Elizabeth H Kellogg; Andrew Leaver-Fay; David Baker
Journal:  Proteins       Date:  2010-12-03

8.  TM-align: a protein structure alignment algorithm based on the TM-score.

Authors:  Yang Zhang; Jeffrey Skolnick
Journal:  Nucleic Acids Res       Date:  2005-04-22       Impact factor: 16.971

Review 9.  Recombinant protein expression in Escherichia coli: advances and challenges.

Authors:  Germán L Rosano; Eduardo A Ceccarelli
Journal:  Front Microbiol       Date:  2014-04-17       Impact factor: 5.640

10.  Principles for designing ideal protein structures.

Authors:  Nobuyasu Koga; Rie Tatsumi-Koga; Gaohua Liu; Rong Xiao; Thomas B Acton; Gaetano T Montelione; David Baker
Journal:  Nature       Date:  2012-11-08       Impact factor: 49.962

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  5 in total

Review 1.  Recent advances in automated protein design and its future challenges.

Authors:  Dani Setiawan; Jeffrey Brender; Yang Zhang
Journal:  Expert Opin Drug Discov       Date:  2018-04-25       Impact factor: 6.098

2.  Landscape of variable domain of heavy-chain-only antibody repertoire from alpaca.

Authors:  Zhui Tu; Xiaoqiang Huang; Jinheng Fu; Na Hu; Wei Zheng; Yanping Li; Yang Zhang
Journal:  Immunology       Date:  2020-06-30       Impact factor: 7.397

3.  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

4.  Protein Binder (ProBi) as a New Class of Structurally Robust Non-Antibody Protein Scaffold for Directed Evolution.

Authors:  Phuong Ngoc Pham; Maroš Huličiak; Lada Biedermannová; Jiří Černý; Tatsiana Charnavets; Gustavo Fuertes; Štěpán Herynek; Lucie Kolářová; Petr Kolenko; Jiří Pavlíček; Jiří Zahradník; Pavel Mikulecky; Bohdan Schneider
Journal:  Viruses       Date:  2021-01-27       Impact factor: 5.818

5.  A general-purpose protein design framework based on mining sequence-structure relationships in known protein structures.

Authors:  Jianfu Zhou; Alexandra E Panaitiu; Gevorg Grigoryan
Journal:  Proc Natl Acad Sci U S A       Date:  2019-12-31       Impact factor: 11.205

  5 in total

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