Literature DB >> 22357762

Iterative approach to computational enzyme design.

Heidi K Privett1, Gert Kiss, Toni M Lee, Rebecca Blomberg, Roberto A Chica, Leonard M Thomas, Donald Hilvert, Kendall N Houk, Stephen L Mayo.   

Abstract

A general approach for the computational design of enzymes to catalyze arbitrary reactions is a goal at the forefront of the field of protein design. Recently, computationally designed enzymes have been produced for three chemical reactions through the synthesis and screening of a large number of variants. Here, we present an iterative approach that has led to the development of the most catalytically efficient computationally designed enzyme for the Kemp elimination to date. Previously established computational techniques were used to generate an initial design, HG-1, which was catalytically inactive. Analysis of HG-1 with molecular dynamics simulations (MD) and X-ray crystallography indicated that the inactivity might be due to bound waters and high flexibility of residues within the active site. This analysis guided changes to our design procedure, moved the design deeper into the interior of the protein, and resulted in an active Kemp eliminase, HG-2. The cocrystal structure of this enzyme with a transition state analog (TSA) revealed that the TSA was bound in the active site, interacted with the intended catalytic base in a catalytically relevant manner, but was flipped relative to the design model. MD analysis of HG-2 led to an additional point mutation, HG-3, that produced a further threefold improvement in activity. This iterative approach to computational enzyme design, including detailed MD and structural analysis of both active and inactive designs, promises a more complete understanding of the underlying principles of enzymatic catalysis and furthers progress toward reliably producing active enzymes.

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Year:  2012        PMID: 22357762      PMCID: PMC3309769          DOI: 10.1073/pnas.1118082108

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  28 in total

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Authors:  Gert Kiss; Daniela Röthlisberger; David Baker; K N Houk
Journal:  Protein Sci       Date:  2010-09       Impact factor: 6.725

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Journal:  Science       Date:  2010-07-16       Impact factor: 47.728

5.  Simple electrostatic model improves designed protein sequences.

Authors:  Eric S Zollars; Shannon A Marshall; Stephen L Mayo
Journal:  Protein Sci       Date:  2006-07-05       Impact factor: 6.725

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Authors:  B I Dahiyat; S L Mayo
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10.  The influence of protein dynamics on the success of computational enzyme design.

Authors:  Jory Z Ruscio; Jonathan E Kohn; K Aurelia Ball; Teresa Head-Gordon
Journal:  J Am Chem Soc       Date:  2009-10-07       Impact factor: 15.419

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  92 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-08       Impact factor: 11.205

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3.  BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design.

Authors:  Jonathan D Jou; Swati Jain; Ivelin S Georgiev; Bruce R Donald
Journal:  J Comput Biol       Date:  2016-01-08       Impact factor: 1.479

4.  A fast loop-closure algorithm to accelerate residue matching in computational enzyme design.

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Journal:  J Mol Model       Date:  2016-01-29       Impact factor: 1.810

5.  BIOPHYSICS. Response to Comments on "Extreme electric fields power catalysis in the active site of ketosteroid isomerase".

Authors:  Stephen D Fried; Steven G Boxer
Journal:  Science       Date:  2015-08-27       Impact factor: 47.728

6.  Computational biology: A recipe for ligand-binding proteins.

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Journal:  Nature       Date:  2013-09-04       Impact factor: 49.962

7.  A protein engineered to bind uranyl selectively and with femtomolar affinity.

Authors:  Lu Zhou; Mike Bosscher; Changsheng Zhang; Salih Ozçubukçu; Liang Zhang; Wen Zhang; Charles J Li; Jianzhao Liu; Mark P Jensen; Luhua Lai; Chuan He
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8.  Matriarch: A Python Library for Materials Architecture.

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Journal:  ACS Biomater Sci Eng       Date:  2015-08-11

Review 9.  Protein engineering for metabolic engineering: current and next-generation tools.

Authors:  Ryan J Marcheschi; Luisa S Gronenberg; James C Liao
Journal:  Biotechnol J       Date:  2013-04-16       Impact factor: 4.677

10.  Thermostability improvement of a streptomyces xylanase by introducing proline and glutamic acid residues.

Authors:  Kun Wang; Huiying Luo; Jian Tian; Ossi Turunen; Huoqing Huang; Pengjun Shi; Huifang Hua; Caihong Wang; Shuanghe Wang; Bin Yao
Journal:  Appl Environ Microbiol       Date:  2014-01-24       Impact factor: 4.792

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