Supercomputers Help Design Mutant Enzyme That Eats Plastic Bottles

June 27, 2018

June 27, 2018 — A dump truck’s worth of plastic empties into the ocean every minute. Worldwide, humankind produces over 300 million tons of plastic each year, much of which is predicted to last centuries to millennia and pollutes both aquatic and terrestrial environments. PET plastic, short for polyethylene terephthalate, is the fourth most-produced plastic and is used to make things like beverage bottles and carpets, most of which are not being recycled. Some scientists are hoping to change that, using supercomputers to engineer an enzyme that breaks down PET. They say it’s a step on a long road toward recycling PET and other plastics into commercially valuable materials at industrial scale.

Supercomputers helped study the binding of a plastic-degrading enzyme, PETase, which could lead to developing industrial-scale plastic recycling for throw-away bottles and carpet. Electrostatic potential distribution of PETase structure courtesy of Gregg Beckham.

“We’re ideally going from a place where plastics are hard to recycle to a place where we use nature and millions of years of evolution to direct things in a way that make plastic easy to recycle,” said Lee Woodcock, an Associate Professor of Chemistry at the University of South Florida. Woodcock co-authored a study on the structure of an enzyme to degrade PET and was published March of 2018 in the Proceedings of the National Academy of Sciences.

The study builds on a discovery in 2016 by Yoshida et al.of a bacterium, Ideonella sakaiensis 201-F6, that feeds on PET plastic as its source of carbon and energy. The PNAS study authors focused on the bacteria’s plastic-degrading enzyme, called PETase. Team members at the University of Portsmouth, led by Professor John McGeehan, used X-ray crystallography at the Diamond Light Source in the UK to solve the high resolution crystal structure of PETase.

“We then used computer simulations to understand how a polymeric ligand like PET would be able to bind to the enzyme,” said study co-author Gregg Beckham, a Senior Research Fellow and Group Leader at the US National Renewable Energy Laboratory (NREL). “We also conducted experimental work to show that indeed, the PETase can break down water or soda bottles, industrially relevant PET films, and another plastic, polyethylene furanoate.”

After doing this work on the structure and function of the PETase enzyme, the authors next tried to understand its evolution and look to a similar enzyme, a family of cutinases, which degrade the waxy polymer cutin found on the surface of plants.

“We developed the hypothesis that if we make the PETase enzyme more like a cutinase, then we should make the enzyme worse. When we did this work, in fact we ended up making the enzyme slightly better by doing that,” Woodcock said.

“It was incredibly surprising to us,” Beckham explained. “When we made it more cutinase-like, the enzyme was modestly improved. That’s actually one of the key aspects of where computation came in, because it allowed us to essentially predict or suggest aromatic-aromatic interactions in the enzyme with the aromatic polyester PET could potentially be responsible for its improved activity. But it was quite a surprise to us,” Beckham said.

Supercomputers allowed them to tackle tough science questions on PETase, such as the details of how it interacts on a molecular scale bound to a substrate, something beyond the scope of what could be determined by knowing its crystal structure.

The researchers took advantage for this study of computational resources of XSEDE, the Extreme Science and Engineering Discovery Environment, funded by the National Science Foundation.

“Having access to XSEDE resources really opens up the possibility of being able to model and being able to study what type of large-scale conformational or even local, small structural changes occur as a function of both binding to the substrate and, additionally, what are the structural changes the large-scale or local, small scale structural changes that occur in the enzyme after we make the mutations. That was a big part of what we were looking at,” Woodcock said.

Woodcock explained that they simulated the long timescales of the enzyme using the Chemistry at Harvard Macromolecular Mechanics (CHARMM) force field and program itself, as well as Nanoscale Molecular Dynamics (NAMD) software.

XSEDE awarded Gregg Beckham allocations on the Stampede1 and Stampede2 systems at the Texas Advanced Computing Center (TACC) and on the Comet system at the San Diego Supercomputer Center (SDSC).

“Our experience to date on Stampede2 has been absolutely wonderful,” Beckham said. “For all the codes on there that we use, it’s been a fantastic machine. We get through the queues quickly. We’re producing a lot of great science across the spectrum of what our groups are collectively doing together using Stampede2 right now. Certainly, for the research on the plastics-degrading enzyme, we’re using it for manuscripts and studies going forward on this same topic.”

“One nice thing about Comet,” Woodcock said, “is that you have, for jobs that you need to get through in a high-throughput fashion, SDSC has a shared queue, which allows you to submit much smaller jobs but do it in a very high-throughput fashion, as they can share cores on the nodes at Comet. This was particularly helpful.”

Both researchers agreed that computation helps make scientific discoveries. “Experimentalists and computational scientists are working hand-in-hand ever more frequently,” Woodcock said. “And without access to resources like this, this would really take us a step back, or multiple steps back in producing the highest levels of science and really being able to address the world’s most challenging problems, which is what we did in this particular study, done by partnering with top level experimental groups like our collaborators in the UK and with us here in the US.”

Beckham said that their work has just begun on enzymes that clean up plastic pollution. “We’re just starting to understand how this enzyme has evolved,” Beckham said. He wants to use computation to take advantage of large databases of genomics and metagenomics on enzymes to find the needles in the haystack that can degrade plastics.

“The other thing too that we’re interested in,” Beckham said, “is if we’re able to do this at much higher temperature, that would be able to accelerate the degradation of PET and get us into realms that potentially could be industrially relevant in terms of using an enzyme to degrade PET and then convert that into the higher value materials, which could incentivize higher rates of reclamation, especially in the developing world where lots of plastic waste goes into the ocean.”

Lee Woodcock sees new computational techniques as a game-changer in modeling non-druglike forcefields that tackle polymer interactions more realistically than CHARMM and NAMD can today. “I’m working with colleagues at NREL on making sure that we can improve the force fields in a very rapid fashion, so that if somebody comes in and says that we need to look at this polymer next, we have confidence that we can put together a modeling strategy in a very short amount of time to get that a quick turnaround when we have to model many different polymers.

The scientists are hopeful their work will one day make the world outside of the lab a better place. “Understanding how we can better design processes to recycle plastics and reclaim them is a dire global problem and it’s something that the scientific and engineering community has to come up with solutions for,” Beckham said.

The study, “Characterization and engineering of a plastic-degrading aromatic polyesterase,” was published in March 2018 in the Proceedings of the National Academy of Sciences. The authors are Harry P. Austin, Mark D. Allen, Alan W. Thorne, John E. McGeehan of the University of Portsmouth; Bryon S. Donohoe, Rodrigo L. Silveira, Michael F. Crowley, Antonella Amore, Nicholas A. Rorrer, Graham Dominic, William E. Michener, Christopher W. Johnson, Gregg T. Beckham of the National Renewable Energy Laboratory; Fiona L. Kearns, Benjamin C. Pollard, H. Lee Woodcock of the University of South Florida; Munir S. Skaf of the University of Campinas; Ramona Duman, Kamel El Omari, Vitaliy Mykhaylyk, Armin Wagner of the Diamond Light Source, Harwell Science and Innovation Campus. The National Renewable Energy Laboratory Directed Research and Development Program funded the study, with computer time provided by the Extreme Science and Engineering Discovery Environment (XSEDE) allocation MCB-090159.


Source: TACC

Subscribe to HPCwire's Weekly Update!

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

NSF Extends Access to Its Leadership Systems Blue Waters & Frontera

December 14, 2018

The National Science Foundation is seeking supplemental requests for access on its leadership-class computers Blue Waters and Frontera to enable "fundamental science and engineering research that would otherwise not be p Read more…

By Staff

CFD on ORNL’s Titan Simulates Cleaner, Low-MPG ‘Opposed Piston’ Engine

December 13, 2018

Pinnacle Engines is out to substantially improve vehicle gasoline efficiency and cut greenhouse gas emissions with a new motor based on an “opposed piston” design that the company hopes will be widely adopted while t Read more…

By Doug Black

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC) is procuring from Atos in two phases over the next year-an Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

AI Can Be Scary. But Choosing the Wrong Partners Can Be Mortifying!

As you continue to dive deeper into AI, you will discover it is more than just deep learning. AI is an extremely complex set of machine learning, deep learning, reinforcement, and analytics algorithms with varying compute, storage, memory, and communications needs. Read more…

IBM Accelerated Insights

4 Ways AI Analytics Projects Fail — and How to Succeed

“How do I de-risk my AI-driven analytics projects?” This is a common question for organizations ready to modernize their analytics portfolio. Here are four ways AI analytics projects fail—and how you can ensure success. Read more…

Nvidia Leads Alpha MLPerf Benchmarking Round

December 12, 2018

Seven months after the launch of its AI benchmarking suite, the MLPerf consortium is releasing the first round of results based on submissions from Nvidia, Google and Intel. Of the seven benchmarks encompassed in version Read more…

By Tiffany Trader

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC Read more…

By Tiffany Trader

Nvidia Leads Alpha MLPerf Benchmarking Round

December 12, 2018

Seven months after the launch of its AI benchmarking suite, the MLPerf consortium is releasing the first round of results based on submissions from Nvidia, Goog Read more…

By Tiffany Trader

IBM, Nvidia in AI Data Pipeline, Processing, Storage Union

December 11, 2018

IBM and Nvidia today announced a new turnkey AI solution that combines IBM Spectrum Scale scale-out file storage with Nvidia’s GPU-based DGX-1 AI server to pr Read more…

By Doug Black

Mellanox Uses Univa to Extend Silicon Design HPC Operation to Azure

December 11, 2018

Call it a corollary to Murphy’s Law: When a system is most in demand, when end users are most dependent on the system performing as required, when it’s crunch time – that’s when the system is most likely to blow up. Or make you wait in line to use it. Read more…

By Doug Black

Topology Can Help Us Find Patterns in Weather

December 6, 2018

Topology--the study of shapes--seems to be all the rage. You could even say that data has shape, and shape matters. Shapes are comfortable and familiar concepts, so it is intriguing to see that many applications are being recast to use topology. For instance, looking for weather and climate patterns. Read more…

By James Reinders

Zettascale by 2035? China Thinks So

December 6, 2018

Exascale machines (of at least a 1 exaflops peak) are anticipated to arrive by around 2020, a few years behind original predictions; and given extreme-scale performance challenges are not getting any easier, it makes sense that researchers are already looking ahead to the next big 1,000x performance goal post: zettascale computing. Read more…

By Tiffany Trader

Robust Quantum Computers Still a Decade Away, Says Nat’l Academies Report

December 5, 2018

The National Academies of Science, Engineering, and Medicine yesterday released a report – Quantum Computing: Progress and Prospects – whose optimism about Read more…

By John Russell

Revisiting the 2008 Exascale Computing Study at SC18

November 29, 2018

A report published a decade ago conveyed the results of a study aimed at determining if it were possible to achieve 1000X the computational power of the the Read more…

By Scott Gibson

Quantum Computing Will Never Work

November 27, 2018

Amid the gush of money and enthusiastic predictions being thrown at quantum computing comes a proposed cold shower in the form of an essay by physicist Mikhail Read more…

By John Russell

Cray Unveils Shasta, Lands NERSC-9 Contract

October 30, 2018

Cray revealed today the details of its next-gen supercomputing architecture, Shasta, selected to be the next flagship system at NERSC. We've known of the code-name "Shasta" since the Argonne slice of the CORAL project was announced in 2015 and although the details of that plan have changed considerably, Cray didn't slow down its timeline for Shasta. Read more…

By Tiffany Trader

IBM at Hot Chips: What’s Next for Power

August 23, 2018

With processor, memory and networking technologies all racing to fill in for an ailing Moore’s law, the era of the heterogeneous datacenter is well underway, Read more…

By Tiffany Trader

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Read more…

By John Russell

AMD Sets Up for Epyc Epoch

November 16, 2018

It’s been a good two weeks, AMD’s Gary Silcott and Andy Parma told me on the last day of SC18 in Dallas at the restaurant where we met to discuss their show news and recent successes. Heck, it’s been a good year. Read more…

By Tiffany Trader

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

TACC’s ‘Frontera’ Supercomputer Expands Horizon for Extreme-Scale Science

August 29, 2018

The National Science Foundation and the Texas Advanced Computing Center announced today that a new system, called Frontera, will overtake Stampede 2 as the fast Read more…

By Tiffany Trader

Leading Solution Providers

SC 18 Virtual Booth Video Tour

Advania @ SC18 AMD @ SC18
ASRock Rack @ SC18
DDN Storage @ SC18
HPE @ SC18
IBM @ SC18
Lenovo @ SC18 Mellanox Technologies @ SC18
NVIDIA @ SC18
One Stop Systems @ SC18
Oracle @ SC18 Panasas @ SC18
Supermicro @ SC18 SUSE @ SC18 TYAN @ SC18
Verne Global @ SC18

HPE No. 1, IBM Surges, in ‘Bucking Bronco’ High Performance Server Market

September 27, 2018

Riding healthy U.S. and global economies, strong demand for AI-capable hardware and other tailwind trends, the high performance computing server market jumped 28 percent in the second quarter 2018 to $3.7 billion, up from $2.9 billion for the same period last year, according to industry analyst firm Hyperion Research. Read more…

By Doug Black

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC Read more…

By Tiffany Trader

Nvidia’s Jensen Huang Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can do. Animated. Backstopped by a stream of data charts, product photos, and even a beautiful image of supernovae... Read more…

By John Russell

Germany Celebrates Launch of Two Fastest Supercomputers

September 26, 2018

The new high-performance computer SuperMUC-NG at the Leibniz Supercomputing Center (LRZ) in Garching is the fastest computer in Germany and one of the fastest i Read more…

By Tiffany Trader

Houston to Field Massive, ‘Geophysically Configured’ Cloud Supercomputer

October 11, 2018

Based on some news stories out today, one might get the impression that the next system to crack number one on the Top500 would be an industrial oil and gas mon Read more…

By Tiffany Trader

Intel Confirms 48-Core Cascade Lake-AP for 2019

November 4, 2018

As part of the run-up to SC18, taking place in Dallas next week (Nov. 11-16), Intel is doling out info on its next-gen Cascade Lake family of Xeon processors, specifically the “Advanced Processor” version (Cascade Lake-AP), architected for high-performance computing, artificial intelligence and infrastructure-as-a-service workloads. Read more…

By Tiffany Trader

Google Releases Machine Learning “What-If” Analysis Tool

September 12, 2018

Training machine learning models has long been time-consuming process. Yesterday, Google released a “What-If Tool” for probing how data point changes affect a model’s prediction. The new tool is being launched as a new feature of the open source TensorBoard web application... Read more…

By John Russell

The Convergence of Big Data and Extreme-Scale HPC

August 31, 2018

As we are heading towards extreme-scale HPC coupled with data intensive analytics like machine learning, the necessary integration of big data and HPC is a curr Read more…

By Rob Farber

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This