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  • richardmitnick 2:33 pm on January 23, 2017 Permalink | Reply
    Tags: , , Baker Lab, , , Stable versions of synthetic peptides, Tailor-made drug molecules   

    From ALCF: “A rising peptide: Supercomputing helps scientists come closer to tailoring drug molecules” 

    Argonne Lab
    News from Argonne National Laboratory

    ANL Cray Aurora supercomputer
    Cray Aurora supercomputer at the Argonne Leadership Computing Facility

    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility
    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility


    January 23, 2017
    Robert Grant

    An artificial peptide made from a mixture of natural L-amino acids (the right half of the molecule) and non-natural, mirror-image D-amino acids (the left half of the molecule), designed computationally using INCITE resources. This peptide is designed to fold into a stable structure with a topology not found in nature, featuring a canonical right-handed alpha-helix packing against a non-canonical left-handed alpha-helix. Since structure imparts function, the ability to design non-natural structures permits scientists to create exciting new functions never explored by natural proteins. This peptide was synthesized chemically, and its structure was solved by nuclear magnetic resonance spectroscopy to confirm that it does indeed adopt this fold. The peptide backbone is shown as a translucent gold ribbon, and amino acid side-chains are shown as dark sticks. The molecular surface is shown as a transparent outline. Credit: Vikram Mulligan, University of Washington

    A team of researchers led by biophysicists at the University of Washington have come one step closer to designing tailor-made drug molecules that are more precise and carry fewer side effects than most existing therapeutic compounds.

    With the help of the Mira supercomputer, located at the Argonne Leadership Computing Facility at the U.S. Department of Energy’s (DOE) Argonne National Laboratory, the scientists have successfully designed and verified stable versions of synthetic peptides, components that join together to form proteins.

    They published their work in a recent issue of Nature.

    The computational protocol, which was validated by assembling physical peptides in the chemistry lab and comparing them to the computer models, may one day enable drug developers to craft novel, therapeutic peptides that precisely target specific disease-causing molecules within the body. And the insights the researchers gleaned constitute a significant advance in the fundamental understanding of protein folding.

    “That you can design molecules from scratch that fold up into structures, some of which are quite unlike what you see in nature, demonstrates a pretty fundamental understanding of what goes on at the molecular level,” said David Baker, the University of Washington biophysicist who led the research. “That’s certainly one of the more exciting things about this work.”

    Baker Lab

    David Baker
    David Baker

    The majority of drugs that humans use to treat the variety of ailments we suffer are so-called “small molecules.” These tiny compounds easily pass through different body systems to target receptor proteins studded in the membranes of our cells.

    Most do their job well, but they come with a major drawback: “Most drugs in use right now are small molecules, which are very tiny and nonspecific. They bind to lots of different things, which produces lots of side effects,” said Vikram Mulligan, a postdoctoral researcher in Baker’s lab and coauthor on the paper.

    More complex protein drugs ameliorate this problem, but they less readily disperse throughout the body because the more bulky molecules have a harder time passing through blood vessels, the linings of the digestive tract and other barriers.

    And proteins, which are giant on the molecular scale, have several layers of structure that all overlap to make them less static and more dynamic, making predicting their binding behavior a tricky prospect.

    But between the extremes of small, but imprecise, molecules and floppy, but high-specificity proteins, there exists a middle ground – peptides. These short chains of amino acids, which normally link together to make complex proteins, can target specific receptors, diffuse easily throughout the body and also sustain a rigid structure.

    Some naturally-occurring peptides are already used as drugs, such as the immunosuppressant ciclosporin, but researchers could open up a world of pharmaceutical opportunity if they could design and synthesize peptides.

    That’s precisely what Baker and his team did, tweaking the Rosetta software package that they built for the design of protein structures to accommodate synthetic amino acids that do not exist in nature, in addition to the 20 natural amino acids.

    After designing the chemical building blocks of peptides, the researchers used the supercomputer Mira, with its 10 petaflops of processing power and more than 780,000 cores, to model scores of potential shapes, or conformations, that specific backbone sequences of amino acids might take.

    “We basically sample millions and millions of these conformations,” said Yuri Alexeev, a project specialist in computational science at the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility. “At the same time you also improve the energy functions,” which are measurements to describe the efficiency and stability of each possible folding arrangement.

    Though he was not a coauthor on the Nature paper, Alexeev helped Baker’s team scale up previous programs it had used to design proteins for modeling peptides on Mira.

    Executing so many calculations simultaneously would be virtually impossible without Mira’s computing power, according to Mulligan.

    “The big challenge with designing peptides that fold is that you have a chain of amino acids that can exist in an astronomical number of conformations,” he said.

    Baker and his colleagues had tasked Mira with modeling millions of potential peptide conformations before, but this study stands out for two reasons.

    First, the researchers arrived at a handful of peptides with specific conformations that the computations predicted would be stable.

    Second, when Baker’s lab created seven of these peptides in their physical wet lab, the reality of the peptides’ conformations and stability corresponded remarkably well with the computer models.

    “At best, what comes out of a computer is a prediction, and at worst what comes out of a computer is a fantasy. So we never really consider it a result until we’ve actually made the molecule in the wet lab and confirmed that it actually has the structure that we designed it to have,” said Mulligan.

    “That’s exactly what we did in this paper,” he said. “We made a panel of these peptides that were designed to fold into very specific shapes, diverse shapes, and we experimentally confirmed that all of them folded into the shapes that we designed.”

    While this experiment sought to create totally new peptides in stable conformations as a proof of concept, Mulligan says that the Baker lab is now moving on to design functional peptides with specific targets in mind.

    Further research may bring the team closer to a protocol that could actually be used to design peptide drugs that target a specific receptor, such as those that make viruses like Ebola or HIV susceptible to attack.

    Computer time was awarded by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program; the project also used resources of the Environmental Molecular Sciences Laboratory, a DOE Office of Science User Facility at Pacific Northwest National Laboratory.

    See the full article here .

    Please help promote STEM in your local schools.
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    Stem Education Coalition

    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    About ALCF

    The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community.

    We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and expertise.

    ALCF projects cover many scientific disciplines, ranging from chemistry and biology to physics and materials science. Examples include modeling and simulation efforts to:

    Discover new materials for batteries
    Predict the impacts of global climate change
    Unravel the origins of the universe
    Develop renewable energy technologies

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

  • richardmitnick 5:27 pm on May 10, 2016 Permalink | Reply
    Tags: , Baker Lab, , ,   

    From BOINC project Rosetta at U Washington: “A breakthrough paper” 



    BOINC WallPaper

    May 10, 2016

    We’ve come out with a breakthrough paper in Science titled ‘De novo design of protein homo-oligomers with modular hydrogen-bond network-mediated specificity’.

    This is an exciting and significant breakthrough for de novo protein design. A particular challenge for current protein design methods has been the accurate design of polar binding sites or polar binding interfaces, both of which require hydrogen bonding interactions. Hydrogen bond networks are governed by complex physics and energetic coupling, that until now, could not be computed within the scope of design. The computational method described in this paper, HBNet, now provides a general method to accurately design in hydrogen bond networks. This new capacity should be useful in the design of new enzymes, proteins that bind small molecules, and polar protein interfaces. Thanks Rosetta@home community for your participation and help!

    See the full article here or here .

    Please help promote STEM in your local schools.

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    Stem Education Coalition

    Rosetta@home needs your help to determine the 3-dimensional shapes of proteins in research that may ultimately lead to finding cures for some major human diseases. By running the Rosetta program on your computer while you don’t need it you will help us speed up and extend our research in ways we couldn’t possibly attempt without your help. You will also be helping our efforts at designing new proteins to fight diseases such as HIV, Malaria, Cancer, and Alzheimer’s (See our Disease Related Research for more information). Please join us in our efforts! Rosetta@home is not for profit.

    About Rosetta

    One of the major goals of Rosetta is to predict the shapes that proteins fold up into in nature. Proteins are linear polymer molecules made up of amino acid monomers and are often refered to as “chains.” Amino acids can be considered as the “links” in a protein “chain”. Here is a simple analogy. When considering a metal chain, it can have many different shapes depending on the forces exerted upon it. For example, if you pull its ends, the chain will extend to a straight line and if you drop it on the floor, it will take on a unique shape. Unlike metal chains that are made of identical links, proteins are made of 20 different amino acids that each have their own unique properties (different shapes, and attractive and repulsive forces, for example), and in combination, the amino acids exert forces on the chain to make it take on a specific shape, which we call a “fold.” The order in which the amino acids are linked determines the protein’s fold. There are many kinds of proteins that vary in the number and order of their amino acids.

    To predict the shape that a particular protein adopts in nature, what we are really trying to do is find the fold with the lowest energy. The energy is determined by a number of factors. For example, some amino acids are attracted to each other so when they are close in space, their interaction provides a favorable contribution to the energy. Rosetta’s strategy for finding low energy shapes looks like this:

    Start with a fully unfolded chain (like a metal chain with its ends pulled).
    Move a part of the chain to create a new shape.
    Calculate the energy of the new shape.
    Accept or reject the move depending on the change in energy.
    Repeat 2 through 4 until every part of the chain has been moved a lot of times.

    We call this a trajectory. The end result of a trajectory is a predicted structure. Rosetta keeps track of the lowest energy shape found in each trajectory. Each trajectory is unique, because the attempted moves are determined by a random number. They do not always find the same low energy shape because there are so many possibilities.

    A trajectory may consist of two stages. The first stage uses a simplified representation of amino acids which allows us to try many different possible shapes rapidly. This stage is regarded as a low resolution search and on the screen saver you will see the protein chain jumping around a lot. In the second stage, Rosetta uses a full representation of amino acids. This stage is refered to as “relaxation.” Instead of moving around a lot, the protein tries smaller changes in an attempt to move the amino acids to their correct arrangment. This stage is regarded as a high resolution search and on the screen saver, you will see the protein chain jiggle around a little. Rosetta can do the first stage in a few minutes on a modern computer. The second stage takes longer because of the increased complexity when considering the full representation (all atoms) of amino acids.

    Your computer typically generates 5-20 of these trajectories (per work unit) and then sends us back the lowest energy shape seen in each one. We then look at all of the low energy shapes, generated by all of your computers, to find the very lowest ones. This becomes our prediction for the fold of that protein.

    To join this project, download and install the BOINC software on which it runs. Then attach to the project. While you are at BOINC, look at some of the other projects to see what else might be of interest to you.

    Rosetta screensaver


  • richardmitnick 4:49 pm on January 20, 2016 Permalink | Reply
    Tags: , Baker Lab, ,   

    From Science Node: “Solving a protein puzzle” 

    Science Node bloc
    Science Node

    20 Jan, 2016
    Greg Moore

    Temp 1
    Stacking up the proteins. After decades of attempts, scientists finally succeeded in unraveling the TIM-barel protein. Here is a graphic depiction of how their simulations fared against the Astral SCOPe 2.04 database. Courtesy Po-Ssu Huang.

    Computational models open up new possibilities for designing proteins for targeted disease treatment. Using the Open Science Grid (OSG), Baker Lab researchers at the University of Washington have simulated a protein that has stymied scientists for the last 25 years, and have opened the way for a new generation of custom-designed enzymes.

    The cylindrical TIM-barrel (triosephosphate isomerase-barrel) protein occurs widely in enzymes and is an attractive goal for research. But ever since it was first targeted in a European Molecular Biology Organization workshop on protein design in 1987, modeling this structure has been an elusive goal. Even the shortest TIM-barrel structure is highly complex.

    Now, thanks to OSG resources, the Baker Lab has generated large numbers of TIM-barrel structures as starting points for enzyme design calculations. Published in Nature Chemical Biology, their results will aid de novo design of custom-made catalysts or binders without the need to negotiate the structural complexity of naturally occurring proteins.

    To scale up simulations for the TIM-barrel computational model, the research team used the OSG, which is supported by the US National Science Foundation and the US Department of Energy’s Office of Science.

    “The massive computing power of the OSG allowed us to quickly get answers,” says Po-Ssu Huang, one of the lead researchers on the paper and a research scientist at the Baker Lab. In the past year, the researchers used an average of 46,000 core OSG hours per week — a total of around 2.4 million core hours.

    “Baker Lab has its own local HTCondor submit host that is connected to the OSG virtual organization HTCondor infrastructure,” says Mats Rynge, a computer scientist at the Information Sciences Institute of the University of Southern California and a member of the OSG User Support team. “Jobs submitted on the host are automatically scheduled onto available resources across the OSG.”

    Temp 2
    Stability comparisons. Strands are sequentially colored from blue to red, and for the orange layer configurations, side chain packing is shown with space-fill spheres. The stabilities of the six different variants correlate strongly with the configurations in the hydrophobic packing layer. Courtesy Po-Ssu Huang.

    The benefit of this setup (submit locally, compute globally) is that a group can maintain their local host – and still manage users, access, and upgrades – but not have to worry about maintaining the entire OSG computing infrastructure.

    “What we do involves computational algorithms, but at the same time everything we design is actually tested here in the lab. We take virtual simulations to practical applications — turning these molecules into new functional molecules for the real world,” says Huang. “The TIM-barrel computational model is an example of taking what we learn to build new proteins for other applications.”

    Applications include disease sensors and drug detectors using proteins as binders for small molecules.

    “The Holy Grail here is to understand enough to build new things,” Huang says. “This breakthrough has implications for neuroscience, industrial applications, biotech, enzymes for drug delivery, vaccines for HIV, and proteins that can inhibit Ebola. It’s just a huge field. This is where computer simulation comes in, and the faster the better. The OSG definitely fits the need.”

    See the full article here .

    Please help promote STEM in your local schools.
    STEM Icon

    Stem Education Coalition

    Science Node is an international weekly online publication that covers distributed computing and the research it enables.

    “We report on all aspects of distributed computing technology, such as grids and clouds. We also regularly feature articles on distributed computing-enabled research in a large variety of disciplines, including physics, biology, sociology, earth sciences, archaeology, medicine, disaster management, crime, and art. (Note that we do not cover stories that are purely about commercial technology.)

    In its current incarnation, Science Node is also an online destination where you can host a profile and blog, and find and disseminate announcements and information about events, deadlines, and jobs. In the near future it will also be a place where you can network with colleagues.

    You can read Science Node via our homepage, RSS, or email. For the complete iSGTW experience, sign up for an account or log in with OpenID and manage your email subscription from your account preferences. If you do not wish to access the website’s features, you can just subscribe to the weekly email.”

  • richardmitnick 11:33 am on June 27, 2012 Permalink | Reply
    Tags: , , Baker Lab, , ,   

    From Argonne Lab APS: “Computer-Designed Proteins to Disarm a Variety of Flu Viruses” 

    News from Argonne National Laboratory

    JUNE 18, 2012
    No Writer Credit

    Computer-designed proteins are under construction to fight the flu. Researchers who carried out studies at the U.S. Department of Energy Office of Science’s Advanced Photon Source at Argonne National Laboratory are demonstrating that proteins that are found in nature, but do not normally bind the influenza virus, can be engineered to act as broad-spectrum antiviral agents against a variety of flu virus strains, including the H1N1 pandemic influenza.

    Close-up view of the F-HB80.4-SC1918/hemagglutinin interface as determined at . From T.A. Whitehead et al., Nat. Biotech. 30(6), 543 (6 June 2012).

    ‘One of these engineered proteins has a flu-fighting potency that rivals that of several human monoclonal antibodies,’ said David Baker, professor of Biochemistry at the University of Washington, in a report in Nature Biotechnology.

    The research team in this study, from the University of Washington, The Scripps Research Institute, and the Naval Health Research Center is making major inroads in optimizing the function of computer-designed influenza inhibitors. These proteins are constructed via computer modeling to fit exquisitely into a specific nano-sized target on flu viruses. By binding the target region like a key into a lock, they keep the virus from changing shape, a tactic that the virus uses to infect living cells. The research efforts, akin to docking a space station but on a molecular level, are made possible by computers that can describe the landscapes of forces involved on the submicroscopic scale.”

    Dr David Baker heads up the Baker Laboratory at The University of Washington. The Baker Lab is the home of the Rosetta@home project, a Public Distributed Computing project which runs on BOINC software. Rosetta research studies “… the 3-dimensional shapes of proteins in research that may ultimately lead to finding cures for some major human diseases…” using the combined resources of thousands of personal computers at home and at work, which give over their unused CPU cycles for the processing of data.

    See the full article here.

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

  • richardmitnick 1:03 pm on April 30, 2012 Permalink | Reply
    Tags: , Baker Lab, , , , , ,   

    From David Baker at Rosetta@home: Rosetta Chosen for the BOINC Pentathlon 

    This is a post from Dr. David Baker, The Baker Lab at the University of Washington, the site of rosetta@home.

    Dr. David Baker

    “I have just been told the very good news that Rosetta@home will be the first project of the BOINC pentathlon, and would like to thank all of the participating teams. I also just learned from the discussion thread that Rosetta@home will be the project of the month for BOINC synergy-this is more excellent news!!

    Your increased contributions to rosetta@home could not come at a better time! We’ve been testing our improved structure prediction methodology in a recently started challenge called CAMEO. For most of the targets, the Rosetta@home models are extremely good, but for a minority of targets the predictions are not good at all. We’ve now tracked down the source of these failures and it is what we are calling “workunit starvation”; in the limited amount of time the Rosetta server has to produce models (2-3 days) in these cases very few models were made-this happens because many targets are being run on the server so that only a fraction of your cpu power is focused on any one target. while we are working to fix this internally, by far the best solution is to have more total CPU throughput so each target gets more models.

    You can follow how we are doing at http://www.cameo3d.org/. You will see that Rosetta is one of the few servers whose name is not kept secret-this is because Rosetta is a public project. Our server receives targets from CAMEO and soon CASP, sends the required calculations out to your computers through Rosetta@home, and then processes the returned results and submits the lowest energy models.

    We are excited that the workunit starvation problem may go away through your increased efforts for Rosetta@home. Thanks!!!”

    David’s post is here.


    BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing, developed at UC Berkeley.

    Visit the BOINC web page, click on Choose projects and check out some of the very worthwhile studies you will find. Then click on Download and run BOINC software/ All Versons. Download and install the current software for your 32bit or 64bit system, for Windows, Mac or Linux. When you install BOINC, it will install its screen savers on your system as a default. You can choose to run the various project screen savers or you can turn them off. Once BOINC is installed, in BOINC Manager/Tools, click on “Add project or account manager” to attach to projects. Many BOINC projects are listed there, but not all, and, maybe not the one(s) in which you are interested. You can get the proper URL for attaching to the project at the projects’ web page(s) BOINC will never interfere with any other work on your computer.


    SETI@home The search for extraterrestrial intelligence. “SETI (Search for Extraterrestrial Intelligence) is a scientific area whose goal is to detect intelligent life outside Earth. One approach, known as radio SETI, uses radio telescopes to listen for narrow-bandwidth radio signals from space. Such signals are not known to occur naturally, so a detection would provide evidence of extraterrestrial technology.

    Radio telescope signals consist primarily of noise (from celestial sources and the receiver’s electronics) and man-made signals such as TV stations, radar, and satellites. Modern radio SETI projects analyze the data digitally. More computing power enables searches to cover greater frequency ranges with more sensitivity. Radio SETI, therefore, has an insatiable appetite for computing power.

    Previous radio SETI projects have used special-purpose supercomputers, located at the telescope, to do the bulk of the data analysis. In 1995, David Gedye proposed doing radio SETI using a virtual supercomputer composed of large numbers of Internet-connected computers, and he organized the SETI@home project to explore this idea. SETI@home was originally launched in May 1999.”

    SETI@home is the birthplace of BOINC software. Originally, it only ran in a screensaver when the computer on which it was installed was doing no other work. With the powerand memory available today, BOINC can run 24/7 without in any way interfering with other ongoing work.

    The famous SET@home screen saver, a beauteous thing to behold.

    einstein@home The search for pulsars. “Einstein@Home uses your computer’s idle time to search for weak astrophysical signals from spinning neutron stars (also called pulsars) using data from the LIGO gravitational-wave detectors, the Arecibo radio telescope, and the Fermi gamma-ray satellite. Einstein@Home volunteers have already discovered more than a dozen new neutron stars, and we hope to find many more in the future. Our long-term goal is to make the first direct detections of gravitational-wave emission from spinning neutron stars. Gravitational waves were predicted by Albert Einstein almost a century ago, but have never been directly detected. Such observations would open up a new window on the universe, and usher in a new era in astronomy.”

    MilkyWay@Home Milkyway@Home uses the BOINC platform to harness volunteered computing resources, creating a highly accurate three dimensional model of the Milky Way galaxy using data gathered by the Sloan Digital Sky Survey. This project enables research in both astroinformatics and computer science.”

    Leiden Classical “Join in and help to build a Desktop Computer Grid dedicated to general Classical Dynamics for any scientist or science student!”

    World Community Grid (WCG) World Community Grid is a special case at BOINC. WCG is part of the social initiative of IBM Corporation and the Smarter Planet. WCG has under its umbrella currently eleven disparate projects at globally wide ranging institutions and universities. Most projects relate to biological and medical subject matter. There are also projects for Clean Water and Clean Renewable Energy. WCG projects are treated respectively and respectably on their own at this blog. Watch for news.

    Rosetta@home “Rosetta@home needs your help to determine the 3-dimensional shapes of proteins in research that may ultimately lead to finding cures for some major human diseases. By running the Rosetta program on your computer while you don’t need it you will help us speed up and extend our research in ways we couldn’t possibly attempt without your help. You will also be helping our efforts at designing new proteins to fight diseases such as HIV, Malaria, Cancer, and Alzheimer’s….”

    GPUGrid.net “GPUGRID.net is a distributed computing infrastructure devoted to biomedical research. Thanks to the contribution of volunteers, GPUGRID scientists can perform molecular simulations to understand the function of proteins in health and disease.” GPUGrid is a special case in that all processor work done by the volunteers is GPU processing. There is no CPU processing, which is the more common processing. Other projects (Einstein, SETI, Milky Way) also feature GPU processing, but they offer CPU processing for those not able to do work on GPU’s.

    These projects are just the oldest and most prominent projects. There are many others from which you can choose.

    There are currently some 300,000 users with about 480,000 computers working on BOINC projects That is in a world of over one billion computers. We sure could use your help.

    My BOINC


  • richardmitnick 11:04 am on September 19, 2011 Permalink | Reply
    Tags: , Baker Lab, ,   

    The Rosetta project points us to The Scientist article about Rosetta’s Foldit 


    David Baker of the Baker Lab tells us “Today’s issue of Nature Structural Biology reports the determination of the structure of a protein by FoldIt players. This is exciting because it is perhaps the first example of a long standing scientific problem solved by non-scientists. You might read about this in your newspaper; here is a report that does a good job in explaining how FoldIt came out of Rosetta@home…”

    “Public Solves Protein Structure
    Players of an online game that allows users to adjust how proteins are folded have solved a decade-long protein structure mystery.”

    See the article here.

    Rosetta@home runs on BOINC software from UC Berkeley

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