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Carlos Simmerling, Ph.D.
Assistant Professor of Chemistry.
Funding through the National Institutes of Health, NIGMS.
Figure 1. Unfolded (left) and folded
(right) structures for the Trp-cage mini-protein studied in
the Simmerling lab. Simulations were carried out with thousands
of explicit water molecules. These simulations allowed the lab
to predict the structure of the Trp-cage protein, which was
subsequently verified by experiment. This was the first successful
blind prediction of protein structure at the atomic level and
led to international publicity for the Simmerling lab. |
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The recent success of genome sequencing projects has provided the genetic
code for many organisms. These genomes provide the amino-acid sequences
for all of the proteins that comprise that machinery of life for an organism.
However, this code does not supply the complex three-dimensional structure
that each protein adopts. Atomic-detail structural information is vital
to our understanding of the function of each protein, and the design of
potential therapeuitic compounds that can modify this function. While
experimental approaches such as NMR or X-ray crystallography can provide
these structures, these methods are difficult and costly, and the number
of proteins with known structure is still a small fraction of known sequences.
Professor Simmerling’s laboratory focuses on the development of
computational algorithms and programs that permit direct simulation of
the folding process and prediction of accurate three-dimensional structures
(Figure 1).
In addition to studying the folding of small proteins, several other
areas of research are being investigated in the Simmerling lab. Each project
is carried out in close collaboration with experimental research in other
labs. Projects include 1) design of new drug candidates for tuberculosis,
which kills over 2 million people each year, 2) simulations of damaged
DNA, recognition of damage by repair enzymes, and how malfunction of this
repair machinery leads to cancer and 3) development of computer graphics
approaches to analysis of the vast data generated by biomolecular simulations.
This laboratory would provide an ideal placement for an undergraduate
who has a background in chemistry or structural biology, with a strong
interest in computers. Approximately ½ of the lab members work
on algorithm development and programming, while the others are more focused
on application of the tools to specific biological problems. Both types
of students are encouraged to apply to the program.
Contact Information
email:
url: http://www.stonybrook.edu/chemistry/faculty
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