YSM Issue 90.1
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computational biology<br />
NEWS<br />
SOLVING THE PROTEIN REPACKING PUZZLE<br />
Tinkering with the building blocks of life<br />
►BY KEVIN CHANG<br />
www.yalescientific.org<br />
IMAGE COURTESY OF WIKIMEDIA COMMONS<br />
►Before the advent of computational methods, biologists<br />
and biochemists had to rely on bouncing x-rays off of protein<br />
crystals in order to determine the 3D structure of a protein.<br />
Proteins play an important role in all life processes. From<br />
catalyzing reactions to protecting our body to supporting<br />
cell structure, proteins have a wide variety of functions<br />
based on each specific protein’s structure. Naturally-occurring<br />
proteins are perfectly evolved for their specific functions<br />
in each organism. Synthetically designed proteins,<br />
however, have the potential to solve the multitude of global<br />
problems facing the world today. For example, engineered<br />
bacteria can make enzymes that help decompose plastics<br />
and reduce landfill waste, or produce designer proteins that<br />
can harvest energy from sunlight for clean energy.<br />
Direct experimental methods for designing synthetic<br />
proteins can be used for creating new proteins with the<br />
desired activities, but they are expensive and labor intensive.<br />
Another strategy is to employ computer simulations,<br />
which have the potential to greatly streamline the process<br />
and reduce costs. However, despite a number of successes,<br />
computational protein design software still frequently<br />
makes inaccurate predictions of protein structure and interactions.<br />
To solve this problem, two Yale groups are combining<br />
their expertise in an interdisciplinary effort led by Corey<br />
O’Hern, an associate professor of Mechanical Engineering<br />
& Materials Science, and Lynne Regan, a professor of Molecular<br />
Biophysics & Biochemistry and Chemistry.<br />
In a recent Protein Engineering, Design, and Selection<br />
paper published in July 2016, the team of researchers described<br />
a new computational model that helps solve the<br />
“repacking” problem, allowing them to accurately predict<br />
how each amino acid side chain fits into the core of a protein.<br />
Amino acids are the fundamental building blocks of<br />
proteins, so understanding how they are positioned within<br />
proteins is crucial to understanding protein structure. “It<br />
may sound trivial, but it is not because you have to try all<br />
side chain conformations to determine which one will fit.<br />
Our simple model performed as well as the state of the art<br />
software in repacking amino acid side chains,” O’Hern said.<br />
Other approaches include all possible energetic contributions<br />
to protein structure, such as steric interactions, electrostatic<br />
effects, van der Waals attractions, and hydrogen<br />
bonding. In contrast, the O’Hern and Regan team used a<br />
somewhat unconventional approach to modeling proteins<br />
by only considering steric interactions—repulsive forces<br />
that prevent atomic overlaps. In their approach, the amino<br />
acids are modeled as 3D puzzle pieces that are arranged to<br />
fit into the protein core without overlaps. The model can<br />
accurately predict how each amino acid must be positioned<br />
to best fit into the core, just like the way Tetris pieces in<br />
the 1980s video game need to be in certain orientations to<br />
tightly fit together and not overlap.<br />
“Our intention was to determine how far we could go in<br />
protein structure prediction using the simplest model and<br />
only add in additional factors when the simplest model can<br />
no longer predict the experimentally observed data. That<br />
was our idea: a bottom-up approach rather than throwing<br />
everything in at the beginning,” Regan said. “Surprisingly,<br />
we found that our model performs extremely well simply<br />
by avoiding steric overlaps. We didn’t need to explicitly put<br />
in any attraction or hydrogen bonding [or other factors].”<br />
The team discovered that their simple model worked well<br />
on many more amino acids than they anticipated. Even<br />
so, they were able to identify its limits and simultaneously<br />
learn much about the dominant forces that determine protein<br />
structure. This point is well illustrated by comparing<br />
the two hydroxyl functional group-containing amino acids,<br />
threonine and serine, which are typically considered<br />
similar in biochemistry textbooks. Although the position<br />
of the threonine side chain can be predicted by steric interactions<br />
alone, inclusion of hydrogen bonding is required to<br />
correctly position the serine side chain. O’Hern and Regan<br />
propose that this is because the steric interactions of the<br />
additional methyl group on threonine are dominant.<br />
The team has already expanded their original studies to<br />
successfully repack multiple amino acid side chains simultaneously,<br />
and they are working on calculating the energetic<br />
cost of mutating amino acids in protein cores and at<br />
interfaces. The O’Hern and Regan team are poised to apply<br />
their novel approach and combined expertise to design<br />
proteins for sustainability, biomedical, and pharmaceutical<br />
applications.<br />
December 2016<br />
Yale Scientific Magazine<br />
9