Though the results must still be verified experimentally, computational chemistry allows scientists to ask more complex questions and get faster, more detailed answers without mixing the first chemical. The technique provides clues to chemical engineering mysteries that cannot be investigated any other way, and reduces trial-and-error in research.

At the new research center, Georgia Tech researchers study protein folding, anti-cancer drugs, molecules key to the vision process and the polymerization process.

"If you can do the experiments on the computer and try all the 'what-ifs' that way, at the very end, the one reaction you really need can be done in chemistry," said Rigoberto Hernandez, assistant professor in Georgia Tech's School of Chemistry and Biochemistry. "By finding the very best solution on the computer, you can limit the waste products by eliminating trial and error. This doesn't do away with experimentation, but it gives the chemist another tool."

Hernandez studies non-equilibrium reactions in which the reacting chemicals form a large part of the overall environment. In common chemical processes, the reactants make up a small part of the overall environment, which remains in equilibrium, not changing substantially as the reaction proceeds.

But in non-equilibrium systems, the environment changes as the reaction proceeds, affecting the chemistry in ways that are difficult to model and study. This complex interaction between reaction and changing environment affects the outcome in important ways.

"In many cases, the final properties of the material are determined by their history," he explained. "I want to understand how things are formed, not just to characterize their properties once they are formed."

Protein folding provides an important example. After being created, proteins fold through a complex chemical process that involves as many as 200 different amino acid residues. Different folds give the proteins different properties. In some cases, such as amyloidogenic proteins associated with Mad Cow Disease, a wrong fold creates a harmful protein: the scrapie form of prions.

"There is increasing evidence that the wrong folds are due to a kinetic or dynamic process," Hernandez added. "We as dynamicists are asking how a sequence with a given structure goes to that folded structure. By understanding those dynamics, we would be able to say something about altering the sequence and preventing it from folding that way."

David Sherrill, an assistant professor in the School of Chemistry and Biochemistry and Hernandez's collaborator at the center, studies electronic structure theory and its application to photochemistry and highly reactive systems. His work has implications for improving anti-cancer drugs, understanding the process of vision and tracing the role of copper in the body.

The enediyne family of anti-cancer drugs provides a vital weapon in the battle against the dread disease. The highly reactive chemicals contain two radicals that steal hydrogen atoms from the DNA of cancer cells, triggering destruction of the cells.

Although experiments have shown the basic steps of the diradical reaction, detailed computer models could give new insights into how to tune the reactivity by adjusting the chemical structures of the drugs. Having that information would help scientists produce better anti-cancer drugs.

These computational studies will require the development of new theoretical techniques because current models can't accurately describe the highly reactive diradicals, or more generally, any bond-making or bond-breaking processes.

"To get a very detailed understanding of the whole process, going from reactants to products and watching it happen in-between, you usually are breaking chemical bonds," Sherrill explained. "You would like to be able to describe that theoretically, including the entire reaction path, not just the beginning and the end."

The IBM SP supercomputer installed at the center in October promises a dramatic increase in the speed at which simulations run, doing in a few hours what would have taken a week of number crunching on smaller computer workstations. It also allows researchers to undertake more complex and accurate simulations that they could not even attempt before.

"This will allow us to do some very high accuracy calculations on some benchmark molecules that were inaccessible before," said Sherrill. "It will make a tremendous difference."

Because the reactions Hernandez and Sherrill study are so complex, limits on computing power have forced them to rely on approximations that do not take into account all the variables that could influence the outcome. The supercomputer will alter that trade-off, enabling simulations with fewer compromises.

By speeding up the simulations, the machine will also change the way in which the researchers work, allowing them to be more productive and creative in following up unexpected results.

"If you have a calculation that takes a week for you to complete, you've got to have a lot of different things going on at once while you're waiting for the calculations to be done," Sherrill explained. "But if you could get the results in a couple of hours, you could immediately see what didn't work and how to change it. You could be a lot more interactive, and recover more quickly from mistakes."

Based on IBM's new copper chip technology, the machine will be shared with other researchers at Georgia Tech's College of Sciences.

Note: If no author is given, the source is cited instead.

• Chemistry
• Organic Chemistry
• Biochemistry

• Computer Modeling
• Computer Science
• Distributed Computing

• Autocatalysis
• Catalysis
• Computer simulation
• Chemical bond
• Chemistry
• Organic chemistry