A Strategic Application Collaboration for Molecular Dynamics

Over the last two decades, an increasing number of chemists have turned to the computer to predict the results of experiments beforehand or to help interpret the results of experiments. Skepticism on the part of laboratory chemists has gradually evaporated as the computational results have made contact with, and even anticipated, experimental findings. When the 1998 Nobel Prize in Chemistry was awarded recently to two scientists, Walter Kohn and John Pople, who originated some of the first successful methods in computational chemistry, the award was seen as an affirmation of the value of computational chemistry to the field of chemistry.

"We've come a long way," said Peter Kollman of the Department of Pharmaceutical Chemistry at UC San Francisco (UCSF). "But while we've come a long way, we can see that we've still got a long way to go."

Now, as part of an NPACI Strategic Application Collaboration, AMBER's performance is being improved by 50 percent to 65 percent.

AMBER stands for Assisted Model Building with Energy Refinement. The code's successes include its use to study protein folding, to study the relative free energies of binding of two ligands to a given host (or two hosts to a given ligand), to investigate the sequence-dependent stability of proteins and nucleic acids, and to find the relative solvation free energies of different molecules in various liquids. Hundreds of contributions to the scientific literature reflect the use of AMBER.

(This news summarized from the San Diego Super Computing Center and original full text can be reached their web site)

Solving The Protein Folding Problem with HPC

The University of Florida uses high-performance computing to simulate protein folding and help in the fight against disease.

Challenge: The Protein Folding Problem
Just like a road map, there are many ways to fold a protein molecule but only one is right. Misfold a map and the only penalty is inconvenience; but misfold a protein and the penalty can be a bad disease. How does a protein know the shape into which it is supposed to fold? High-performance computing can help answer this question.

Low free energy is good. Laboratory experiments can probe around only the unfolded and folded regions of the energy curve. Computer experiments can probe the whole thing. Professor Adrian Roitberg and Seonah Kim are doing just that on the UF High Performance Computing (HPC) Cluster at the University of Florida. The cluster depends on the high performance and reliability of the Cisco® InfiniBand fabric that connects the AMD Opteron based Rackable servers and storage subsystem. Kim has run more than 45 days on 100 processors and isn't done yet.

The simulation uses the highly parallelized Assisted Model Building with Energy Refinement (AMBER) package of molecular simulation programs. Why so long to study just two proteins? For one thing, biology involves a lot of water. The pinkish cloud is 7000 water molecules (21,000 atoms) surrounding a 14-residue peptide molecule (the bluish "worm" in the middle). The AMBER simulation works by calculating the motions of all these molecules. They bend, rotate, and move through space, avoiding or bouncing off one another. The simulation divides time into little steps and uses Newton's laws of physics to calculate the motion of the thousands of atoms at each step.

The High-Performance Computing Initiative at UF is an innovative approach to such needs. The design is a computing grid, linking specialized research computing clusters to a central parallel cluster over a dedicated high-speed network. Funding from the National Science Foundation and a cooperative agreement with Cisco provided the routers and switches for that grid.

(This news summarized from Cisco and original text can be reach their website)