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Enzyme optimization: moving from blind evolution to statistical exploration of sequence–function space

Paper ID Volume ID Publish Year Pages File Format Full-Text
37626 45377 2008 7 PDF Available
Title
Enzyme optimization: moving from blind evolution to statistical exploration of sequence–function space
Abstract

Directed evolution is a powerful tool for the creation of commercially useful enzymes, particularly those approaches that are based on in vitro recombination methods, such as DNA shuffling. Although these types of search algorithms are extraordinarily efficient compared with purely random methods, they do not explicitly represent or interrogate the genotype–phenotype relationship and are essentially blind in nature. Recently, however, researchers have begun to apply multivariate statistical techniques to model protein sequence–function relationships and guide the evolutionary process by rapidly identifying beneficial diversity for recombination. In conjunction with state-of-the-art library generation methods, the statistical approach to sequence optimization is now being used routinely to create enzymes efficiently for industrial applications.

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Enzyme optimization: moving from blind evolution to statistical exploration of sequence–function space
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Publisher
Database: Elsevier - ScienceDirect
Journal: - Volume 26, Issue 3, March 2008, Pages 132–138
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us