Building A Supercluster To Fight SARS

By Roland Piquepaille

Yuan-Ping Pang is not your average chemist. At Mayo Clinic, in Rochester, Minnesota, he designed and built a supercluster composed of 800 Xeon processors. With this computing power at his disposal, he modeled the SARS viral enzyme. "Pang analyzed the SARS viral genome and built, atom by atom, the instantaneous 3D structures of the viral enzyme -- each of which is composed of 8,113 atoms -- just 20 days after the SARS viral genome was made public." The next step is to find anti-SARS drugs to prevent SARS and to cure SARS patients. For this, he will need even more power. But as he says, "in 2002, we developed the computing technology that performs 1.1 trillion floating point operations per second. Now, we are working on new technologies that will give 1000x improvement and more ..."

Here are more details.

A Mayo Clinic researcher is the first to develop a series of three-dimensional (3D) models of an enzyme responsible for the replication of the deadly SARS (Severe Acute Respiratory syndrome) virus. These instantaneous "structures-in-time" are central to designing an anti-SARS drug -- and are therefore a welcome advance as the virus continues to threaten public health.

Mayo Clinic researcher Yuan-Ping Pang, Ph.D., a chemist and head of the Computer-Aided Molecular Design Laboratory, reports results produced by the terascale computer he designed, built and managed. Using 800 PC processors harnessed together, Dr. Pang analyzed the SARS viral genome and built, atom by atom, the instantaneous 3D structures of the viral enzyme -- each of which is composed of 8,113 atoms -- just 20 days after the SARS viral genome was made public.

	Here you can see Yuan-Ping Pang standing in front of his supercluster. (Photo: Curt Sanders, Credit: Mayo Clinic). You'll find some more information, even if not up to date, on the Facilities page of Pang's lab.
	And here is a "close-up view of the computer-derived SARS viral enzyme (surface model in green) in complex with its peptide target (stick model in orange, blue and red) that will be cleaved by the enzyme upon binding." (Credit: Mayo Clinic).

What will be the next step?

Now that he knows the attributes of the SARS viral enzyme, Dr. Pang uses his customized computers to assess a Mayo in-house chemicals database -- a kind of "dictionary of small molecules" -- that his team built. It contains attributes such as molecular weight, shape and polarity of 2.5 million unique chemical structures. His goal is to match their properties with the computer-revealed dynamic properties of the key SARS viral enzyme -- and by so doing, discover an anti-SARS drug. He is also pushing toward faster computer systems, aiming at petaflops speed -- that's one thousand trillion floating-point operations per second.

For more scientific information, Pang's research paper was published by Proteins: Structure, Function, and Bioinformatics on August 13, 2004. Here is a link to the abstract of the paper called "Three-dimensional model of a substrate-bound SARS chymotrypsin-like cysteine proteinase predicted by multiple molecular dynamics simulations: Catalytic efficiency regulated by substrate binding."

Dr. Pang and Andrea Dooley, a summer undergraduate student from Massachusetts Institute of Technology, have finished this search at Mayo and just sent 20 computer-identified small molecules to Southern Research Institute in Birmingham, Ala. for further testing as anti-SARS drugs.

Sources: Mayo Clinic news release, via EurekAlert!, August 16, 2004; Mayo Clinic website