2014 Synthetic Biology: Engineering, Evolution & Design (SEED)
Rational Design for Enzyme Engineering Using a Next Generation Gene Synthesis Approach to Generate Combinatorial Variant Libraries
ACS Synthetic Biology
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Rational Design for Enzyme Engineering Using a Next Generation Gene Synthesis Approach to Generate Combinatorial Variant Libraries
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ACS Synthetic Biology |
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Draft |
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Viewpoint |
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n/a |
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Complete List of Authors: |
Saaem, Ishtiaq; Gen9, Inc., Hudson, Michael; Gen9, Inc., Kung, Li; Gen9, Inc., Schindler, Daniel; Gen9, Inc., Guido, Nicholas; Gen9, Inc., Leake, Devin; Gen9, Inc., |
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ACS Synthetic Biology
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3 Rational Design for Enzyme Engineering Using a Next Generation Gene Synthesis Approach to Generate
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5 Combinatorial Variant Libraries
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7 Ali Saaem, Mike Hudson, Li Kung , Dan Schindler, Nick Guido, Devin Leake
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9 Gen9, Inc., 840 Memorial Drive, Cambridge, MA 02139
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11 The need for novel enzymes with a wide-range of activities has dramatically increased recently, and
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13 enzyme engineering strategies are evolving with innovative ways for creating combinatorial DNA
14 libraries, advanced HTS strategies, and computational design approaches. The challenge for successful
15 enzyme engineering is often narrowing the exploration of sequence space from the impractical size of all
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17 possible sequence permutations to a manageable number of variants. To increase the rate of success,
18 researchers generate libraries that target specific regions of the target enzyme, or even individual
19 positions, and create variants within these regions or positions. Designed libraries therefore aim at
20 increasing the ratio of advantageous to deleterious mutations, increasing the â??smart-nessâ? and utility of
22 the library. One method for generating this type of rationally designed library uses next generation gene
23 synthesis. With the BioFab® process as a starting point, we have developed a method that allows for a
24 rational design of high variant combinatorial libraries to be used for enzyme engineering. This unique
26 approach to the creation of high variant libraries shows a number of advantages to traditional
27 approaches, including a lack of representation bias. Here, we show that using a next generation gene
28 synthesis approach we are able to very rapidly create highly specific and diverse libraries.
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