Scientists Create 3D Model of Intrinsically Disordered Protein with Titan Supercomputer, Spallation Neutron Source

October 7, 2019

OAK RIDGE, Tenn., Oct. 7, 2019— Using the Titan supercomputer and the Spallation Neutron Source at the Department of Energy’s Oak Ridge National Laboratory, scientists have created the most accurate 3D model yet of an intrinsically disordered protein, revealing the ensemble of its atomic-level structures.

As its name indicates, an IDP does not adopt an ordered, static structure like other proteins; instead, it’s flexible and can adopt multiple 3D structures. This lack of a unique structure is necessary for the IDP’s biological function but makes it technically challenging to study. IDPs may be a whole protein or a domain of an otherwise structured protein, and they make up a large portion of human, microbe, and plant proteins.

Loukas Petridis, a staff scientist at the Center for Molecular Biophysics at ORNL, has directed a team of researchers to a new way to create accurate physical models of such flexible biosystems, which can lead to a better understanding of their biological functions. Over the past three years, the team has combined neutron scattering experiments with enhanced sampling molecular dynamics (MD) simulations so computationally demanding that they required the processing power of Titan, the recently decommissioned 27-petaflop Cray XK7 at the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility at ORNL.

“To study these IDPs is quite difficult, from both perspectives of experiments and modeling,” said Utsab Shrestha, the lead author of the team’s paper, recently published in the Proceedings of the National Academy of Sciences. “We not only thought about it from experiment or simulation alone, we planned in a way that we would synergize both of these approaches—combine them in a way that we could get more precise information on IDPs. Specifically, simulations helped us to generate an accurate ensemble of IDP at atomic resolution, which is difficult to determine from experiments alone.”

Typically, researchers conduct experiments such as small-angle neutron scattering, small-angle x-ray scattering, or nuclear magnetic resonance to probe flexible biological systems. However, these methods do not provide a detailed atomic-level picture of an IDP’s 3D structures, known as its configurational ensemble. Furthermore, they can only produce ensemble-averaged data, rather than the specific underlying protein structure configurations. Scientists have also performed computer simulations of IDP and compared them with such experiments, hoping to get the same results in order to verify the accuracy of their models.

“But they end up not agreeing with the experiments,” Petridis said. “And because of the discrepancy between the simulations and the experiments, they have to reweight the simulations—they have to adjust the simulation results to make them match the experiments, which is frustrating. That was the state of the art until our work.”

Computer MD simulations conducted by Shrestha used enhanced sampling methods that succeeded in matching not only neutron scattering experiments—conducted by Viswanathan Gurumoorthy and his colleagues at SNS, a DOE Office of Science User Facility at ORNL—but also previously published NMR data. These MD simulations use physics to determine how proteins move. Key to the team’s success was running many MD simulations in parallel on Titan, allowing the simulations to communicate with each other and exchange information.

“This is very important because it allows the simulation to sample a larger configurational space, explore more of the three-dimensional structures in a more efficient way,” Petridis said. “That’s why this enhanced-sampling MD can produce results that the normal MD simulation cannot. We’d have to run a normal MD simulation for years to obtain the same results.”

The IDP that the team chose to study is the N-terminal domain of c-Src kinase, which is a major signaling protein in humans. Mutations in this complex protein have been correlated with cancer, which also makes it an important drug target. While mapping this previously murky domain, the scientists were able to discover new information about its 3D structures that previous methods had not shown. For example, although it is largely disordered, this protein forms transient ordered structures, such as helices.

“The combination of neutron scattering experiments and simulation is very powerful,” Petridis said. “Validation of the simulations by comparison to neutron scattering experiments is essential to have confidence in the simulation results. The validated simulations can then provide detailed information that is not directly obtained by experiments.”

The detailed computer model of the IDP’s 3D structure ensemble opens the door to more experimentation. For example, scientists could simulate the effect of phosphorylation (the addition of a phosphate group to the protein that can regulate the protein’s function) to see what structural changes take place in c-Src kinase that could influence its function. The role of mutations could also be examined: If a researcher changes an amino acid in the chain, how does this affect the structure or the ensemble of structures?

“There are a lot of unanswered questions for c-Src kinase in particular that could be answered in terms of the interactions with other partners—the effect of phosphorylation, the effect of mutations,” Petridis said.

Beyond the potential scientific uses for the model itself, Petridis sees opportunities to apply the use of high-performance computing for running enhanced sampling MD to study the structures of many other important IDPs, which could give insight to their function. And more broadly, the team wants to develop simulation technologies that can reproduce small-angle neutron scattering profiles of even more complex biological systems.

“We don’t want to investigate only the disordered proteins—we want to have much bigger systems that contain ordered and disordered domains that may be interacting with membranes or DNA,” Petridis said. “Neutron scattering is, in my view, the best experimental technique to probe these multi-component systems—for example, a protein that interacts with a membrane or a protein that interacts with DNA. But, still, neutron scattering needs the accurate simulations to better interpret the data.”

Coauthors of this study include Utsab R. Shrestha, Puneet Juneja, Qiu Zhang, Viswanathan Gurumoorthy, Jose M. Borreguero, Volker Urban, Xiaolin Cheng, Sai Venkatesh Pingali, Jeremy C. Smith, Hugh M. O’Neill, and Loukas Petridis. Support for this project came from ORNL’s Laboratory Directed Research and Development Program and from DOE’s Office of Science. In addition to using the OLCF’s Titan supercomputer and Spallation Neutron Source, the team performed research at the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility at Lawrence Berkeley National Laboratory.

UT-Battelle LLC manages Oak Ridge National Laboratory for DOE’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE’s Office of Science is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science.


Source: Oak Ridge National Laboratory 

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire