YSM Issue 90.1

computational biology
NEWS
SOLVING THE PROTEIN REPACKING PUZZLE
Tinkering with the building blocks of life
►BY KEVIN CHANG
www.yalescientific.org
IMAGE COURTESY OF WIKIMEDIA COMMONS
►Before the advent of computational methods, biologists
and biochemists had to rely on bouncing x-rays off of protein
crystals in order to determine the 3D structure of a protein.
Proteins play an important role in all life processes. From
catalyzing reactions to protecting our body to supporting
cell structure, proteins have a wide variety of functions
based on each specific protein’s structure. Naturally-occurring
proteins are perfectly evolved for their specific functions
in each organism. Synthetically designed proteins,
however, have the potential to solve the multitude of global
problems facing the world today. For example, engineered
bacteria can make enzymes that help decompose plastics
and reduce landfill waste, or produce designer proteins that
can harvest energy from sunlight for clean energy.
Direct experimental methods for designing synthetic
proteins can be used for creating new proteins with the
desired activities, but they are expensive and labor intensive.
Another strategy is to employ computer simulations,
which have the potential to greatly streamline the process
and reduce costs. However, despite a number of successes,
computational protein design software still frequently
makes inaccurate predictions of protein structure and interactions.
To solve this problem, two Yale groups are combining
their expertise in an interdisciplinary effort led by Corey
O’Hern, an associate professor of Mechanical Engineering
& Materials Science, and Lynne Regan, a professor of Molecular
Biophysics & Biochemistry and Chemistry.
In a recent Protein Engineering, Design, and Selection
paper published in July 2016, the team of researchers described
a new computational model that helps solve the
“repacking” problem, allowing them to accurately predict
how each amino acid side chain fits into the core of a protein.
Amino acids are the fundamental building blocks of
proteins, so understanding how they are positioned within
proteins is crucial to understanding protein structure. “It
may sound trivial, but it is not because you have to try all
side chain conformations to determine which one will fit.
Our simple model performed as well as the state of the art
software in repacking amino acid side chains,” O’Hern said.
Other approaches include all possible energetic contributions
to protein structure, such as steric interactions, electrostatic
effects, van der Waals attractions, and hydrogen
bonding. In contrast, the O’Hern and Regan team used a
somewhat unconventional approach to modeling proteins
by only considering steric interactions—repulsive forces
that prevent atomic overlaps. In their approach, the amino
acids are modeled as 3D puzzle pieces that are arranged to
fit into the protein core without overlaps. The model can
accurately predict how each amino acid must be positioned
to best fit into the core, just like the way Tetris pieces in
the 1980s video game need to be in certain orientations to
tightly fit together and not overlap.
“Our intention was to determine how far we could go in
protein structure prediction using the simplest model and
only add in additional factors when the simplest model can
no longer predict the experimentally observed data. That
was our idea: a bottom-up approach rather than throwing
everything in at the beginning,” Regan said. “Surprisingly,
we found that our model performs extremely well simply
by avoiding steric overlaps. We didn’t need to explicitly put
in any attraction or hydrogen bonding [or other factors].”
The team discovered that their simple model worked well
on many more amino acids than they anticipated. Even
so, they were able to identify its limits and simultaneously
learn much about the dominant forces that determine protein
structure. This point is well illustrated by comparing
the two hydroxyl functional group-containing amino acids,
threonine and serine, which are typically considered
similar in biochemistry textbooks. Although the position
of the threonine side chain can be predicted by steric interactions
alone, inclusion of hydrogen bonding is required to
correctly position the serine side chain. O’Hern and Regan
propose that this is because the steric interactions of the
additional methyl group on threonine are dominant.
The team has already expanded their original studies to
successfully repack multiple amino acid side chains simultaneously,
and they are working on calculating the energetic
cost of mutating amino acids in protein cores and at
interfaces. The O’Hern and Regan team are poised to apply
their novel approach and combined expertise to design
proteins for sustainability, biomedical, and pharmaceutical
applications.
December 2016
Yale Scientific Magazine
9