Protein storytelling to fight the pandemic



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Protein storytelling to fight the pandemic

CMP modeling of COVID-19 infecting the human cell. Credit: Lucy Fallon, Laufer Center

Over the past five decades, we’ve learned a lot about the secret life of proteins – how they work, what they interact with, the mechanisms that make them work – and the pace of discovery is accelerating.

The first three-dimensional protein structure began to emerge in the 1970s. Today, the Protein Data Bank, a global repository of information on the 3D structures of large biological molecules, contains information on hundreds of thousands of proteins. Once again this week, the company DeepMind shocked the protein structure world with its precise AI-based predictions.

But the 3-D structure is often not enough to really understand what a protein does, says Ken Dill, director of the Laufer Center for Physical and Quantitative Biology at Stony Brook University and a member of the National Academy of Sciences. “It’s like someone asks how an automobile works, and a mechanic opens the hood of a car and says, ‘See, there’s the engine, that’s how it works.'”

In the decades that followed, computer simulations drew on and enriched understanding of protein behavior by setting these 3D molecular machines in motion. The analysis of their energetic landscapes, their interactions and their dynamics has taught us even more about these main drivers of life.

“We’re really trying to ask the question: how does it work? Not just what does it look like?” Dill said. “This is the essence of why you want to know protein structures in the first place, and one of the biggest applications of this is drug discovery.”

Write in Science magazine in November 2020, Dill and his Stony Brook colleagues Carlos Simmerling and Emiliano Brini shared their views on the evolution of the field.

“Computational molecular physics is an increasingly powerful tool for telling the stories of the actions of protein molecules,” they wrote. “Systematic improvements in force fields, improved sampling methods and accelerators have enabled [computational molecular physics] to achieve timescales of important biological actions … At this rate, in the next quarter century, we will be telling stories of protein molecules over the entire lifespan, tens of minutes, of a bacterial cell . “

Speed ​​simulations

However, decades after the first dynamic models of proteins, computational biophysicists still face major challenges. To be useful, simulations must be accurate; and to be precise, the simulation must progress atom by atom and femtosecond (10-12 seconds) per femtosecond. To match the timescales that matter, simulations need to span microseconds or milliseconds, that is, millions of time steps.

“Computational molecular physics has developed at a relatively fast pace, but not enough to get us through the time, size and range of motion that we need to see,” he said.

One of the main methods used by researchers to understand proteins in this way is molecular dynamics. Since 2015, with support from the National Institutes of Health and the National Science Foundation, Dill and his team have been working to accelerate molecular dynamics simulations. Their method, called MELD, speeds up the process by providing vague but important information about the system under study.

Dill likens the method to a treasure hunt. Instead of asking someone to find a treasure that could be anywhere, they provide a map with clues, saying, “It’s either near Chicago or Idaho.” In the case of real proteins, this could mean telling the simulation that part of an amino acid chain is close to another part of the chain. This narrowing of the field of research can considerably speed up simulations – sometimes more than 1000 times faster – allowing new studies and new perspectives.

Protein Structure Predictions for COVID-19

One of the most important uses of biophysical modeling in our daily lives is drug discovery and development. Three-dimensional models of viruses or bacteria help identify weak spots in their defenses, and molecular dynamics simulations determine which small molecules can bind to these attackers and erase their work without having to test all possibilities in the lab.

The team at Dill’s Laufer Center are involved in a number of efforts to find drugs and treatments for COVID-19, with support from the White House-organized COVID-19 HPC consortium, an effort between the government federal government, industry, and university leaders to provide access to the world’s most powerful high-performance computing resources in support of COVID-19 research.

“Everyone has dropped other things to work on COVID-19,” Dill recalls.

The first step the team took was to use MELD to determine the 3D shape of the unknown proteins of the coronavirus. Only three of the 29 proteins of the virus have been definitively resolved so far. “Most of the structures are not known, which is not a good start for drug discovery,” he said. “Can we predict structures that are not known? This is the main thing we used Frontera for.”

The Texas Advanced Computing Center (TACC) Frontera supercomputer – the fastest of any university in the world – allowed Dill and his team to make structure predictions for 19 more proteins. Each of these elements could serve as a path for the development of new drugs. They have made their structure predictions publicly available and are working with teams to experimentally test their accuracy.

While it looks like the vaccine race is already on the verge of declaring the winner, the first round of vaccines, drugs and treatments is just the start of a recovery. As with HIV, it is likely that the first drugs developed will not work for everyone, or will be outperformed by more effective drugs with fewer side effects in the future.

Dill and his team at the Laufer Center play the long game, hoping to find more promising targets and mechanics than those already in development.

Recycle drugs and explore new approaches

A second project by the Laufer Center group is using Frontera to analyze millions of small, commercially available molecules to verify their effectiveness against COVID-19, in collaboration with Dima Kozakov’s group at Stony Brook University.

“By focusing on the reuse of commercially available molecules, it is possible, in principle, to shorten the time required to find a new drug,” he said. “Kozakov’s group has the ability to quickly screen thousands of molecules to identify the top 100. We use our physical modeling to further filter this pool of candidates, reducing the options that experimenters have to test.

A third project is investigating an interesting cellular protein known as PROTAC that directs the “waste collecting proteins” of human cells to take up specific target proteins that they would not usually suppress.

“Our cell has smart ways of identifying proteins that need to be destroyed. It sits next to it, puts a sticker on it, and the proteins that collect the waste take it away,” he explained. “Initially, PROTAC molecules were used to target cancer-related proteins. There is now a push to transfer this concept to the proteins of SARS-CoV-2.”

Together with Stony Brook chemist Peter Tonge, they are working to simulate the interaction of the new PROTACS with the COVID-19 virus. “These are some of our most ambitious simulations, both in terms of the size of the systems we’re tackling and in terms of chemical complexity,” he said. “Frontera is a critical resource to give us sufficient turnaround times. For a simulation, we need 30 GPUs and four to five days of continuous calculations.”

The team is developing and testing their protocols on a non-COVID testing system to compare their predictions. Once they settle on a protocol, they will apply that design procedure to COVID systems.

Every protein has a story to tell, and Dill, Brini and their collaborators build and apply the tools that help unravel those stories. “There are issues in protein science where we think the real challenge is to fully understand physics and math,” Dill concluded. “We are testing this hypothesis on COVID-19.”


A race to solve the COVID protein puzzle


More information:
Emiliano Brini et al, Protein narrative through physics, Science (2020). DOI: 10.1126 / science.aaz3041

Provided by the University of Texas at Austin

Quote: Protein storytelling to address the pandemic (2020, December 4) retrieved December 4, 2020 from https://phys.org/news/2020-12-protein-storytelling-pandemic.html

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