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Protein Design

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Attention for Chapter 14: Computational Redesign of Metalloenzymes for Catalyzing New Reactions.
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Chapter title
Computational Redesign of Metalloenzymes for Catalyzing New Reactions.
Chapter number 14
Book title
Protein Design
Published in
Methods in molecular biology, January 2014
DOI 10.1007/978-1-4939-1486-9_14
Pubmed ID
Book ISBNs
978-1-4939-1485-2, 978-1-4939-1486-9
Authors

Per Jr Greisen, Sagar D Khare, Per Jr. Greisen, Sagar D. Khare

Abstract

The ability to design novel activities in existing metalloenzyme active sites is a stringent test of our understanding of enzyme mechanisms, sheds light on enzyme evolution, and would have many practical applications. Here, we describe a computational method in the context of the macromolecular modeling suite Rosetta to repurpose active sites containing metal ions for reactions of choice. The required inputs for the method are a model of the transition state(s) for the reaction and a set of crystallographic structures of proteins containing metal ions. The coordination geometry associated with the metal ion (Zn(2+), for example) is automatically detected and the transition state model is aligned to the open metal coordination site(s) in the protein. Additional interactions to the transition state model are made using RosettaMatch and the surrounding amino acid side chain identities are optimized for transition state stabilization using RosettaDesign. Validation of the design is performed using docking and molecular dynamics simulations, and candidate designs are generated for experimental validation. Computational metalloenzyme repurposing is complementary to directed evolution approaches for enzyme engineering and allows large jumps in sequence space to make concerted sequence and structural changes for introducing novel enzymatic activities and specificities.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 31%
Student > Ph. D. Student 3 23%
Student > Postgraduate 2 15%
Professor > Associate Professor 1 8%
Professor 1 8%
Other 0 0%
Unknown 2 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 23%
Agricultural and Biological Sciences 2 15%
Chemical Engineering 1 8%
Computer Science 1 8%
Chemistry 1 8%
Other 1 8%
Unknown 4 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 May 2015.
All research outputs
#20,236,620
of 22,763,032 outputs
Outputs from Methods in molecular biology
#9,865
of 13,088 outputs
Outputs of similar age
#264,836
of 305,294 outputs
Outputs of similar age from Methods in molecular biology
#405
of 597 outputs
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So far Altmetric has tracked 13,088 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 597 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.