Literature DB >> 12038994

De novo design of biocatalysts.

Daniel N Bolon1, Christopher A Voigt, Stephen L Mayo.   

Abstract

The challenging field of de novo enzyme design is beginning to produce exciting results. The application of powerful computational methods to functional protein design has recently succeeded at engineering target activities. In addition, efforts in directed evolution continue to expand the transformations that can be accomplished by existing enzymes. The engineering of completely novel catalytic activity requires traversing inactive sequence space in a fitness landscape, a feat that is better suited to computational design. Optimizing activity, which can include subtle alterations in backbone conformation and protein motion, is better suited to directed evolution, which is highly effective at scaling fitness landscapes towards maxima. Improved rational design efforts coupled with directed evolution should dramatically improve the scope of de novo enzyme design.

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Year:  2002        PMID: 12038994     DOI: 10.1016/s1367-5931(02)00303-4

Source DB:  PubMed          Journal:  Curr Opin Chem Biol        ISSN: 1367-5931            Impact factor:   8.822


  29 in total

1.  Local complexity of amino acid interactions in a protein core.

Authors:  Rajul K Jain; Rama Ranganathan
Journal:  Proc Natl Acad Sci U S A       Date:  2003-12-18       Impact factor: 11.205

2.  Three-body interactions improve the prediction of rate and mechanism in protein folding models.

Authors:  M R Ejtehadi; S P Avall; S S Plotkin
Journal:  Proc Natl Acad Sci U S A       Date:  2004-10-06       Impact factor: 11.205

3.  Improving computational protein design by using structure-derived sequence profile.

Authors:  Liang Dai; Yuedong Yang; Hyung Rae Kim; Yaoqi Zhou
Journal:  Proteins       Date:  2010-08-01

4.  Engineering a protein-protein interface using a computationally designed library.

Authors:  Gurkan Guntas; Carrie Purbeck; Brian Kuhlman
Journal:  Proc Natl Acad Sci U S A       Date:  2010-10-25       Impact factor: 11.205

5.  How mutational epistasis impairs predictability in protein evolution and design.

Authors:  Charlotte M Miton; Nobuhiko Tokuriki
Journal:  Protein Sci       Date:  2016-01-22       Impact factor: 6.725

6.  Combinatorial methods for small-molecule placement in computational enzyme design.

Authors:  Jonathan Kyle Lassila; Heidi K Privett; Benjamin D Allen; Stephen L Mayo
Journal:  Proc Natl Acad Sci U S A       Date:  2006-10-30       Impact factor: 11.205

Review 7.  Contributions of microorganisms to industrial biology.

Authors:  Arnold L Demain; Jose L Adrio
Journal:  Mol Biotechnol       Date:  2008-01       Impact factor: 2.695

8.  Biomimetic catalysis of diketopiperazine and dipeptide syntheses.

Authors:  Zheng-Zheng Huang; Luke J Leman; M Reza Ghadiri
Journal:  Angew Chem Int Ed Engl       Date:  2008       Impact factor: 15.336

9.  Using affinity chromatography to engineer and characterize pH-dependent protein switches.

Authors:  Martin Sagermann; Richard R Chapleau; Elaine DeLorimier; Margarida Lei
Journal:  Protein Sci       Date:  2009-01       Impact factor: 6.725

Review 10.  Energy functions in de novo protein design: current challenges and future prospects.

Authors:  Zhixiu Li; Yuedong Yang; Jian Zhan; Liang Dai; Yaoqi Zhou
Journal:  Annu Rev Biophys       Date:  2013-02-28       Impact factor: 12.981

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