FY2010 - Oak Ridge National Laboratory

Director’s R&D Fund—
Ultrascale Computing and Data Science
05282
High-Throughput Computational Screening Approach
for Systems Medicine
Pratul K. Agarwal
Project Description
High-performance computing continues to revolutionize biology. Computational thinking and techniques
will have a significant impact on the future biological research as it is substantially reducing the time
between data acquisition and knowledge discovery. Human health, in particular, is poised to benefit
considerably from the impact of computational modeling and simulations. The search for new medicines
is based on the identification of potential drug candidates that bind to and change the activity of disease
targets (proteins). Traditionally this search has centered upon the active site of an enzyme or binding site
of a receptor. Recently, we have demonstrated that protein sites on the surface (allosteric sites) are
capable of altering protein activity in much the same way as traditional drug agents in the buried active
site. However, due to the size of the energy space of the protein as well as the chemical space of the
compounds, screening presents a challenging problem.
Here, we propose a joint effort between the computational and structural biologists and medicinal and
computational drug design chemists to develop new high-throughput methods for approaching rational
drug design and drug discovery. High-performance computing will be used to predict the location of
allosteric sites in protein targets and to simulate the interaction between drug-like small molecules and
target sites. In silico–based screening of drug candidates will lead to a considerable cost and time saving
for the expensive wet-lab screening and therefore accelerate critical steps in systems medicine.
Mission Relevance
Computational biology is an important component of DOE’s Genomic Science (formerly GTL:Genomics)
initiative. The project will allow development of high-performance computing tools and software for
characterization of biomolecular-biomolecular interactions, which is an important components of
Genomic Science Program goals. The fundamental understanding of the biological processes occurring at
the molecular level in the living cell, as enabled by the project, has fundamental implications in energy
and environmental research. The project is relevant to the DOE Office of Biological and Environmental
Research (DOE BER) as well as the Office of Advanced Scientific Computing Research (DOE ASCR).
The proposed research for development of tools and software for systems medicine is relevant to human
health. Therefore, it is relevant to the mission of the National Institutes of Health (NIH), in particular to
the National Institute of General Medical Sciences (NIGMS). The outcome of the research would lower
time and cost for discovery of new medicine and, therefore, promote human health.
Results and Accomplishments
Our underlying approach for identification of the allosteric sites is based on the characterization of protein
dynamics (or slow conformational fluctuations) in relation to the rate-limiting steps in the catalytic cycle
of enzymes. We have developed and used theoretical modeling and computational simulations that allow
refining of the factors that enable the identification of allosteric sites. Specifically, we have focused on
mapping the protein residues from the active-site to surface regions that are the prospective allosteric
sites.
Using the developed approach, we have successfully identified allosteric sites for two medically
important target enzymes. Enzyme dihydrofolate reductase (DHFR) is an anticancer target, while the
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