SATURDAY, OCTOBER 1, 2016

Computer simulations yield greater understanding of HIV

A new computer model developed by a University of Central Florida assistant professor is helping scientists to better understand how HIV infects people, the university said on Thursday.

Bo Chen, a physics professor at UCF, came up with an advanced simulation model that helped several other research teams to map the elusive structure of the HIV's capsid, the virus' protective armor around its DNA-corrupting genomic materials. The complex process that forms HIV's protective shell includes thousands of individual proteins connecting in assembly within a few seconds.

"The speed makes it difficult to track and analyze experimentally, and even more challenging to simulate theoretically, because it involves a large amount of molecules and extends the time scale far too long for current computation resources," Chen said.

The simulation model captures the overall structure of the capsid protein without slowing down the speed, simulating how hundreds of the proteins assemble at the same time.

Chen worked with Peijun Zhang, an associate professor at the University of Pittsburgh's structural biology department, whose team used cryo-electron microscopy and Chen's simulation to determine how HIV creates its capsid.

"The mechanism is challenging to study and simulate," Chen said. "It involves hundreds and in some cases thousands of molecules working at the same time to assemble and construct new structures. And with our technology we've had limited success previously. But the cryoEM structure model from Dr. Zhang's group developed has greatly inspired our simulation work."

While the simulation is a major step in the right direction, the system is still unable to capture the entire HIV capsid system.

"Even with the world's biggest supercomputers, we can't do a simulation that keeps pace with the complexities involved in self assembly for more than a few microseconds," Chen said. "And most of these processes take up to several seconds to minutes. In time, I think we'll get there, but right now, we're limited by our current technology. Even so, our advances are helping scientists understand how it all works."