NIH Awards $9.3M for Further Development of PHENIX Structural Biology Software

July 26, 2017

July 26, 2017 — The National Institutes of Health (NIH) has awarded $9.3 million to the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) to support ongoing development of PHENIX, a software suite for solving three-dimensional macromolecular structures.

Pavel Afonine in Berkeley Lab’s Molecular Physics and Integrated Bioimaging Division created a PHENIX tool to calculate difference maps in real space from cryo-EM data. This figure shows such a map for one adenosine triphosphate molecule in a complex called the 26S proteasome. (Credit: Pavel Afonine/Berkeley Lab)

PHENIX, which stands for Python-based Hierarchical ENvironment for Integrated Xtallography, uses modern programming concepts and advanced algorithms to automate the analysis of structural biology data. The grant is awarded through the National Institute of General Medical Sciences at NIH.

Officially launched in 2000 with NIH funding, the project is a collaboration among researchers based at Berkeley Lab, Los Alamos National Laboratory, Cambridge University, and Duke University.

“The impetus behind PHENIX is a desire to make the computational aspects of crystallography more automated, reducing human error and speeding solutions,” said PHENIX principal investigator Paul Adams, director of Berkeley Lab’s Molecular Biophysics and Integrated Bioimaging Division.

Knowing the precise location of each atom in a molecule in three dimensions is critical to understanding how the molecule functions and interacts with other molecules. The shapes of the proteins in a cell, for example, reveal a lot about the work they do—whether it’s providing structural support or motility, forming selectively permeable membrane channels, or powering the cell’s metabolism. DNA sequence alone still doesn’t give enough information about how a molecule folds, or how it changes conformation.

The software is openly and freely available for academic users. Over the years, the international community of crystallographers has contributed to PHENIX’s development through the open source Computational Crystallography Toolbox.

In the past 15 years, Adams noted, “the level of automation and computation algorithms that we’ve developed has really changed the way people do a lot of structural biology work.”

Recent improvements to PHENIX in the area of experimental phasing have enabled researchers to make use of noisier, lower resolution data that previously would have been discarded.

One major development in the field of structural biology over the past five years has been the ascendance of cryo-electron microscopy (cryo-EM), where a molecule is rapidly cooled and inserted into an electron microscope. The technology owes its current popularity to advances in electron detector technology, including a direct electron detector developed by Peter Denes and colleagues at the National Center for Electron Microscopy at Berkeley Lab’s Molecular Foundry, a DOE Office of Science User Facility.

“Even before this revolution, as they’re calling it, took place we thought that cryo-EM would be an important area for us to get involved in,” Adams said.

He added that half of the work proposed under the new grant will be developing new methods for building, refining, and validating models in cryo-EM. The other half, he said, will be continuing the themes of extending crystallographic methods to work at lower resolution and with weaker data, and making it possible to solve molecular structures when there’s no similar model in the database.

“This new cryo-EM approach can produce pictures that are nearly as clear as those from X-ray diffraction, but often with less work,” said Tom Terwilliger, whose group in the Bioscience Division at Los Alamos National Laboratory is a partner in the collaborative PHENIX project. “Our new tools will make it easier for researchers to interpret their pictures from cryo-EM, hopefully making this new technique as routine as X-ray crystallography is today.”

Adams noted that this kind of multi-institutional, multi-disciplinary, technology development is something at which the national labs excel.

“We are very grateful to NIH for recognizing the value of the project and graciously agreeing to continue funding it,” he said. “Their commitment has been long-term; it’s been very impressive and has had a big impact on the research community.”

Other Berkeley Lab Biosciences MBIB collaborators on PHENIX include: Pavel Afonine, Dorothee Liebschner, Nigel Moriarty, Billy Poon, and Oleg Sobolev.

About Berkeley Lab

Lawrence Berkeley National Laboratory addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel Prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science. For more, visit www.lbl.gov.

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.


Source: Berkeley Lab

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!

Glimpses of Today’s Total Solar Eclipse

August 21, 2017

Here are a few arresting images posted by NASA of today’s total solar eclipse. Such astronomical events have always captured our imagination and it’s not hard to understand why such occurrences were often greeted wit Read more…

By John Russell

Tech Giants Outline Battle Plans for Future HPC Market

August 21, 2017

Four companies engaged in a cage fight for leadership in the emerging HPC market of the 2020s are, despite deep differences in some areas, in violent agreement on at least one thing: the power consumption and latency pen Read more…

By Doug Black

Geospatial Data Research Leverages GPUs

August 17, 2017

MapD Technologies, the GPU-accelerated database specialist, said it is working with university researchers on leveraging graphics processors to advance geospatial analytics. The San Francisco-based company is collabor Read more…

By George Leopold

HPE Extreme Performance Solutions

Leveraging Deep Learning for Fraud Detection

Advancements in computing technologies and the expanding use of e-commerce platforms have dramatically increased the risk of fraud for financial services companies and their customers. Read more…

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Centers (IPCCs) has resulted in a new Big Data Center (BDC) that Read more…

By Linda Barney

Tech Giants Outline Battle Plans for Future HPC Market

August 21, 2017

Four companies engaged in a cage fight for leadership in the emerging HPC market of the 2020s are, despite deep differences in some areas, in violent agreement Read more…

By Doug Black

Microsoft Bolsters Azure With Cloud HPC Deal

August 15, 2017

Microsoft has acquired cloud computing software vendor Cycle Computing in a move designed to bring orchestration tools along with high-end computing access capabilities to the cloud. Terms of the acquisition were not disclosed. Read more…

By George Leopold

HPE Ships Supercomputer to Space Station, Final Destination Mars

August 14, 2017

With a manned mission to Mars on the horizon, the demand for space-based supercomputing is at hand. Today HPE and NASA sent the first off-the-shelf HPC system i Read more…

By Tiffany Trader

AMD EPYC Video Takes Aim at Intel’s Broadwell

August 14, 2017

Let the benchmarking begin. Last week, AMD posted a YouTube video in which one of its EPYC-based systems outperformed a ‘comparable’ Intel Broadwell-based s Read more…

By John Russell

Deep Learning Thrives in Cancer Moonshot

August 8, 2017

The U.S. War on Cancer, certainly a worthy cause, is a collection of programs stretching back more than 40 years and abiding under many banners. The latest is t Read more…

By John Russell

IBM Raises the Bar for Distributed Deep Learning

August 8, 2017

IBM is announcing today an enhancement to its PowerAI software platform aimed at facilitating the practical scaling of AI models on today’s fastest GPUs. Scal Read more…

By Tiffany Trader

IBM Storage Breakthrough Paves Way for 330TB Tape Cartridges

August 3, 2017

IBM announced yesterday a new record for magnetic tape storage that it says will keep tape storage density on a Moore's law-like path far into the next decade. Read more…

By Tiffany Trader

AMD Stuffs a Petaflops of Machine Intelligence into 20-Node Rack

August 1, 2017

With its Radeon “Vega” Instinct datacenter GPUs and EPYC “Naples” server chips entering the market this summer, AMD has positioned itself for a two-head Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Leading Solution Providers

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This