The University of Texas at Austin's Chandrajit Bajaj is using the computational horsepower of the Texas Advanced Computing Center to identify a small group of molecules that might have therapeutic potential.

Bajaj is using practically every piece of computing hardware at TACC to conduct his research, including TACC's Ranger and Lonestar supercomputers, the Longhorn remote visualization system, and Stallion, a super high-resolution tiled display in the TACC/ACES Visualization Laboratory.

"Computers are a good way to accelerate the process of drug design," Bajaj says. "It takes 10 years to proof out a drug, and a billion dollars or more. Hence computational drug discovery is not only timesaving, but economics tells you this is the way we should be going."

Using TACC's HPC resources — including both CPU and GPU-based systems — Bajaj and his colleagues were able to run their algorithms to detect secondary structures of proteins through intermediate and coarse resolution 3D maps that were reconstructed from single particle cryo-electron microscopy.

Bajaj, who regularly collaborates with big pharma, says that increasingly, computational drug discovery is becoming the de facto process of sorting through target compounds.

"They're moving into the computational drug screening arena, and more and more it's teams of people working together," he says. "The biophysicist, the biochemist, and the synthetic chemist are sitting together with the computational expert, and they say it's giving them clues as to what they should be doing next."

His recent research is described in the Journal of Structural Biology.

Matthew Dublin is a senior writer at Genome Technology.