Computer Model Sheds Light on HIV Development


New analysis may lead to the development of new antiviral HIV drugs.

Scientists developed an HIV computer model to gain further information on how the virus matures and becomes infective, opening doors for developing new antiviral drugs.

To understand the life cycle of the virus, researchers looked at what the proteins do inside living cells; however, even with the most powerful imaging technologies it is very difficult. In a study published in Nature Communications, researchers came up with a new and innovative computer model that helps take an additional step in understanding HIV.

“Understanding the details of viral maturation is considered a holy grail,” said model developer Gregory Voth. “It has a set of processes that are incredibly hard to stop. With our model, we've discovered a key set of dynamical steps in the maturation process. And we think we've identified two core aspects of HIV.”

Part of the virus becoming mature involves growing the capsid.

“This is the thing that’s going to get shot into a new cell and release its contents,” Voth said. “The capsid is like a little armor plated container that carries with it the genetic material of the virus. And it is a diabolical delivery device.”

The size of the capsid makes it difficult to see how it grows in HIV; however, the new model can now provide that detail.

“That’s where computer stimulations are so powerful,” Voth said. “And in computer simulations you can turn things on and off, which you can’t do in reality. It makes a huge difference in what you learn. It’s not reality, but if the model’s good it can be pretty darn close.”

Once a cell is infected with HIV, a bud forms on the cell surface that contains some cell membrane, proteins, and the virus RNA.

The bud breaks through the cell as the virion and begins to travel throughout the body, where important proteins inside the bud are cut into pieces by HIV protease. The protein pieces (about 1200) pair together into the capsid, enclosing the RNA.

Once the protein bits are inside the virion, it can be crowded and determines if a capsid can form or not.

“With our simulations we can make it more and less crowded and you see a remarkable sensitivity to that,” Voth said.

When there is too little crowding the proteins are more likely to move past each other without interacting, while too much causes them to grow useless pieces. Even when researchers were able to meet that sweet spot in the amount of crowding in their model, the capsid still didn’t grow how it was supposed to.

“We’d grow too much,” Voth said. “Or we’d start growing multiple pieces of the shell and they wouldn’t stick together in the right way, so you’d get a bunch of crazy-looking structures. We were fundamentally missing something.”

After further research that took a year, researchers found that before the bits of protein paired and entered into the capsid shell they were in constant motion. In order to achieve this process, researchers needed to have the correct orientation, and only a few of them could be part of building the structure at any given time.

“We discovered that the contortions of these proteins are very important to limiting how fast these structures can grow, so it’s just right,” Voth said. “When we built that into the model, guided by published experimental data, that was the secret.”

Although researchers developed methods to help simplify the calculations and retain their physical essence, the HIV capsid model is still extremely complex. In fact, it took millions of computer time hours on the National Science Foundation Supercomputer Blue Waters, in order to run the simulations.

“I don’t think anyone’s got close to simulating something of this complexity before,” said researcher John Grime. “I think it’s a very significant advance in terms of what you can do with those sorts of models. We could do this for Zika Virus, for Ebola. Viruses have a capsid and that capsid contains their genetic material. So these sets of methodologies could be applied to any of them. We just need enough information and computer power.”

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