Chemical Engineering April 2016 - 49

automated general-purpose strainconstruction
fabs are all converging.
From a business perspective, this
means that value creation will be
shifting from making natural organisms
more efficient to designing synthetic
biocatalysts and organisms
capable of producing the most valuable
chemicals, even if the natural
starting organism does not " know "
how to make them (Figure 3).
Technologies that leverage largescale
cloud computing and big
data to design novel biocatalysts
and fermentation strains in order
to produce chemicals have started
to appear in recent years. Developing
a designer cell-factory that
produces a new chemical generally
entails being able to rationally
engineer a cell at multiple levels. At
the lowest level, the production of a
target small-molecule generally requires
the design of new enzymes
that catalyze - efficiently and specifically
- new chemical reactions.
Each natural enzyme is encoded
by a gene sequence that specifies
the catalytic active site within the
enzyme macromolecule. The need
to create enzymes for new chemical
reactions is usually referred to as
the " enzyme design " problem.
Natural enzymes are extremely
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efficient at catalyzing very difficult
chemical reactions under mild conditions
that differ drastically from
what conventional chemical catalysis
often requires. Textbook enzyme
examples, such as orotidine decarboxylases,
show catalytic rate enhancements
at ph 7.0 and 30˚C of
1 × 1018 times the non-catalyzed
reactions. however, predicting the
genetic sequence that will lead to
an enzyme capable of performing a
specific reaction that is not catalyzed
in nature has been one of the most
recalcitrant problems in biochemistry
for decades, and is largely responsible
for some of the failures in biobased
chemicals.
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48
Frances Arnold at the California
Institute of Technology (Caltech;
Pasadena; www.caltech.edu) and
commercial work by Willem " Pim "
Stemmer formalized the technique
of " directed evolution. " The concept
involves starting with an enzyme that
catalyzes the desired chemical reaction,
and painstakingly reproducing
nature's evolutionary mechanism to
accumulate mutations until a DNA
sequence results that encodes for
an optimized enzyme. This method
still requires, however, screening
vast amount of natural genes to find
starting points having the initial desired
activity.
Another concept, known as computational
enzyme design, has
been pioneered in the academic
laboratories of David Baker at the
University of Washington (Seattle;
www.uw.edu) and Steve Mayo at
Caltech, and is being commercialized
by the author's company Arzeda
Corp. (Seattle, Wash.; www.arzeda.
com). Computational protein design
bridges the gaps in directed evolution
and makes it possible to design new
enzymatic activities. Computational
enzyme design uses vast amounts
ChemiCal engineering www.Chemengonline.Com april 2016
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Chemical Engineering April 2016

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