Biology Reference
In-Depth Information
In this chapter, we will first delineate where we expect CPD to have the biggest potential
impact on synthetic biology. Then, we will give an overview of the general models and
algorithms most often used in computational design. Next, we will give an introduction to
the design of novel and specificity-changed binding proteins and enzymes, together with a
brief description of the specialized computational algorithms used for these problems.
Then, we will give examples of computational thermostabilization of proteins, followed by
a brief overview of the design of novel protein folds. Finally, we will compare the relative
strengths and weaknesses of computational design versus directed evolution, and finish
with an outlook on where computational protein design could have the most imminent
impact on synthetic biology.
The Potential Impact of CPD on Synthetic Biology
CPD is still a relatively young technique, and so far most synthetic applications rely on
reusing and recombining existing natural proteins as building blocks.
1
However, as we will
show in this chapter, the successes achieved with CPD over the last decade forecast the types
of synthetic biology applications and devices that CPD will help enable. We anticipate an
impact of CPD in six ways:
1.
The design of novel protein
small molecule interactions will allow
for the manipulation of signaling cascades to modify gene expression in response to
designed, unnatural stimuli.
2.
The design of protein
protein and protein
protein interactions will also allow for the creation of tailor-made
proteins that bind to protein targets and can either inhibit or elicit responses not related
to gene expression in a target organism.
3.
The design of novel catalytic activities will allow for novel biosynthetic pathways for
compounds of interest, and will also enable the creation of synthetic organisms that
break down environmental pollutants or toxins.
4.
The design of protein
102
small molecule interactions will allow for the creation of novel
biosensors for compounds of interest.
5.
The design of self-assembling proteins could lead to the creation of novel biomaterials,
such as delivery containers for drugs or conductive fibers or sheets for bioenergy
applications.
6.
CPD enables the thermostabilization of proteins with relative ease, and therefore could
contribute to increased robustness of synthetic biology applications.
For some of these applications, successes using computationally designed proteins have
already been reported (
Table 6.1
). For example, regarding point 2, CPD has been used to
create proteins that inhibit viral infection or the build-up of amyloid fibrils.
2
Regarding
point 3, one case has been reported where a computationally designed enzyme could be
used in a novel biosynthetic pathway,
3
and another novel enzyme was designed to break
down a component representative of a class of pollutants.
4
For point 6, several examples
have been reported where proteins have been stabilized, leading to higher expression or
increased half-lives.
5
And for the types of applications where no examples have been
reported yet, it is conceivable that designs can be achieved with the required functionality
using computational algorithms very similar to the ones used to obtain the successful
results. We are thus hopeful that CPD will have a broad impact on synthetic biology, and
will put applications within reach that could not be created otherwise.
METHODS OVERVIEW
The term computational protein design (CPD) as used in this chapter describes the design
of amino acid sequences based on computational structural modeling of the to-be-designed
protein. While some results have been reported with design algorithms that are not based
