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(A)
FOLDING AND FORMATION OF STRUCTURE
1.
Protein Folding, Misfolding, and Aggregation:
How proteins
self-assemble into their native state (responsible for biological function)
has been a much studied problem for over a decade. Progress has been made
into how simple models of proteins fold as well as means to design protein
sequences de novo. However, these models ignore much protein detail which
is likely crucial for understanding how real proteins fold. Thus, the
current challenge lies in understanding how particular chemical detail
in proteins (such as hydrogen bonding and hydrophic interactions) lead
to particular protein folding mechanisms.
We have developed techniques which allows us to make fundamental advances
in simulations of protein folding, by speeding atomistic simulations 100
to 1,000 times. This speedup allows us to simulate tens of microseconds
and thus simulate the folding of the fastest folding proteins in all-atom
detail. However, these methods are extremely computationally demanding,
and require 1000's to 10,000's of computers. To
solve this problem, we have released our software as a screen saver and
have gathered over 10,000 collaborators who run our software. This project,
called Folding@home has
already lead to great initial results (the folding of proteins in atomistic
detail on the microseconds timescale) and we are now continuing to use
this technique on other systems as well, including the folding of RNA
and non-biological polymers as well as the aggregation of proteins associated
with diseases, such as Altzheimer's and Mad Cow (see below).
2.
Protein design and structure prediction:
We have also started another distributed computing project to use protein
design to generate new "virtual genomes."
Our project, Genome@home,
studies real genomes and proteins directly, by designing new sequences
for existing 3-D protein structures, which come from real genomes. The
protein structure files that are sent out as work contain the Cartesian
atomic coordinates of a protein. This data was obtained experimentally
through X-ray crystallography or NMR techniques. Note that this was not
done by us; thousands of scientists have spent decades compiling this
data, which is generously made freely available to the public. By designing
new sequences that could form these specific protein structures, we're
setting the stage to attack a number of significant contemporary issues
in structural biology, genetics, and medicine. For example, the Genome@home
data will be used to:
- Try to unravel a fundamental issue in the "protein folding problem"
(which itself lies at the heart of a huge amount of modern biomedical
research): the fact that thousands of different sequences can all form
the same three-dimensional structure.
- Predict the functions of newly discovered genes and protein structures.
Modern approaches to structural biology, known as "proteomics" or "structural
genomics", often solve protein structures without knowing what the proteins
do. Because techniques for function prediction tend to work best with
large amounts of sequence data, a virtual library of sequences for a
new protein structure will be an invaluable resource.
- Potentially design and make new versions of existing proteins for
use in medical therapy.
3.
RNA Folding:
While protein folding has garnered much attention over the last decade,
RNA folding has received much less interest. From a theoretical point
of view, one reason for this is the large molecular weight of RNA chains
and role of electrostatics and counter ions in RNA folding. However, with
recent techniques developed in protein folding, we have started to tackle
the RNA problem.
We are currently collaborating with several experimental groups at Stanford
(Herschlag, Doniach, and Chu) to combine and compare our simulation results
to experiment. This allows us to validate our simulations and allows one
to refine the experimental data to yield more information about the structure
and nature of folding.
4.
Folding of biomimetic heteropolymers:
Can we apply our understanding gleaned from our study of proteins and
RNA to design protein-like heteropolymers -- heteropolymers which can
fold into particular structures? If so, how do these polymers fold as
compared with proteins? Finally, can we take advantage of new polymer
architechtures, such as branched chains, in order to design synthetic
polymers with novel folding and material properties?
5.
Lipid membranes, lipid-protein systems, lipid vesicle fusion:
Lipid
membranes also play a fundamental role in biochemistry, serving as the
structural units which encapsulate cells, organelles, viruses, etc. In
particular, lipid membranes must fuse in order for such systems to combine
(endocytosis) or detach (exocytosis). This physical process is also a
first order phase transition, but is heavily mediated by proteins in biological
systems. We are currently studing how lipid vesicles fuse with and without
the affect of biological machinery (fusion peptides and proteins; see
below).
(B)
FUNCTION
1.
Ligand binding and drug design:
One of the biggest challenges in computational drug design is the accurate
calculation of the free energy of binding of small ligands. Currently,
typical errors in these calculations make them unusable to distinguish
between strong binders (which would potentially make good drugs) and non-specific
binders (which wouldn't). We are using distributed computing methods to
greatly increase the accuracy of such calculations.
2.
Protein-protein interactions:
Related to our work on protein folding and protein design, we are also
interested in protein-protein interactions. While this is a new area for
our lab, we are leveraging our unique methods and capabilities in protein
folding thermodynamics, kinetics, and design.
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