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  • richardmitnick 2:44 pm on September 4, 2014 Permalink | Reply
    Tags: , , World Community Grid   

    From WCG: Please welcome World Community Grid’s newest partner 

    Please welcome World Community Grid’s newest partner – ANEPF (Association Nationale des Etudiants en Pharmacie de France)! ANEPF represent the interests of French pharmacy students, with health policy and education being key focus areas. You can check out their team here: http://ow.ly/B63fB

    anepf

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.


    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.

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding

    FightAIDS@Home

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
    ibm

    IBM – Smarter Planet
    sp

    ScienceSprings relies on technology from

    MAINGEAR computers

    Lenovo
    Lenovo

    Dell
    Dell

     
  • richardmitnick 8:53 am on September 3, 2014 Permalink | Reply
    Tags: , , World Community Grid   

    From WCG: Last Month’s Activity 

    Last month, #WCGrid volunteers donated over 12,000 years of computing time & over 30 million results to our humanitarian projects!

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    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.

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding

    FightAIDS@Home

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
    ibm

    IBM – Smarter Planet
    sp

    ScienceSprings relies on technology from

    MAINGEAR computers

    Lenovo
    Lenovo

    Dell
    Dell

     
  • richardmitnick 3:13 pm on August 4, 2014 Permalink | Reply
    Tags: , , World Community Grid   

    From World Community Grid: A Banner Month 

    Last month, World Community Grid volunteers donated almost 13,000 years of computer run time and over 37 million results were returned towards our humanitarian projects! Thank you all for your continued support, and please, recruit a friend or two to join this great cause!

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    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.

    CAN ONE PERSON MAKE A DIFFERENCE? YOU BETCHA!!

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding

    FightAIDS@Home

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
    ibm

    IBM – Smarter Planet
    sp

    ScienceSprings relies on technology from

    MAINGEAR computers

    Lenovo
    Lenovo

    Dell
    Dell

     
  • richardmitnick 2:28 pm on July 29, 2014 Permalink | Reply
    Tags: , , , World Community Grid   

    From WCG: “Calling all climate change scientists” 

    29 Jul 2014

    Summary
    In response to President Obama’s call to action on the Climate Data Initiative, we invite scientists studying climate change issues to submit proposals for accessing massive supercomputing power to advance their research.

    Extreme weather events caused by climate change, such as floods and droughts, can have a drastic impact on food production. For example, production costs for maize and other grains could double by 2030. How can individuals, communities, organizations and governments prepare to handle future climate impacts on food security and other key issues? To address this challenge, President Obama today announced the second phase of the Climate Data Initiative calling on private and philanthropic organizations to develop data-driven tools to plan for and mitigate the effects of climate change. In response, World Community Grid invites scientists studying issues affected by climate change, such as the resilience of staple food crops, and watershed management to submit research proposals. In addition, IBM is participating in a roundtable discussion convened by the White House today to discuss joint efforts to further advance the Initiative’s goals.

    To date, over 300,000 World Community Grid volunteers have already provided sustainability scientists with the equivalent of almost 100,000 years of computing power to support researchers in numerous fields, including energy, water and agricultural science:

    The University of Virginia’s Computing for Sustainable Water project is shedding new light on the effects of human activity on the Chesapeake Bay watershed. Organizations and policymakers will be able to use this data-driven insight to guide their efforts to support the restoration and health of the area.

    water

    The University of Washington’s Nutritious Rice for the World project studied rice proteins that could help farmers breed new strains with higher yields and greater disease and pest resistance. New crops like these will be vital in areas that face changing climate conditions.

    rice

    In what we believe to be the most extensive quantum chemical investigation to date, Harvard University’s Clean Energy Project has discovered 35,000 materials with the potential to double carbon-based solar cell efficiency after screening more than two million organic materials on World Community Grid. These discoveries could result in solar cells that are cheaper, easier to produce and more efficient than ever before.
    cep

    We invite sustainability researchers who could benefit from massive supercomputing power to advance their work to submit a project proposal. In addition, anyone can contribute to understanding climate change and mitigating its impacts by joining World Community Grid and supporting our current research projects. Take a minute right now to start supporting cutting-edge climate science.

    See the full article here.

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    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.

    CAN ONE PERSON MAKE A DIFFERENCE? YOU BETCHA!!

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding

    FightAIDS@Home

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
    ibm

    IBM – Smarter Planet
    sp


    ScienceSprings is powered by MAINGEAR computers

     
  • richardmitnick 10:16 pm on July 21, 2014 Permalink | Reply
    Tags: , , , , , , World Community Grid   

    From WCG: “Pioneering a Molecular Approach to Fighting AIDS” 

    World Community Grid

    Dr. Arthur Olson
    Professor, The Scripps Research Institute
    21 Jul 2014

    Summary
    World Community Grid is being featured at the 20th International AIDS Conference which begins today in Melbourne, Australia. Dr. Arthur Olson, FightAIDS@Home principal investigator, shares his perspective on how World Community Grid is helping his team develop therapies and a potential cure for AIDS.

    The Scripps Research Institute’s FightAIDS@Home initiative is a large-scale computational research project whose goal is to use our knowledge of the molecular biology of the AIDS virus HIV to help defeat the AIDS epidemic. We rely on World Community Grid to provide massive computational power donated by people around the world to speed our research. The “virtual supercomputer” of World Community Grid enables us to model the known atomic structures of HIV molecules to help us design new drugs that could disrupt the function of these molecules. World Community Grid is an essential tool in our quest to understand and subvert the HIV virus’s ability to infect, spread and develop resistance to drug therapies.

    FightAidsOlsonLab@home

    Since the early 1980s – when AIDS was first recognized as a new epidemic and a serious threat to human health – our ability to combat the HIV virus has evolved. Using what we call “structure-based drug discovery,” researchers have been able to use information about HIV’s molecular component to design drugs to defeat it. Critical to this process has been our ability to develop and deploy advanced computational models to help us predict how certain chemical compounds could affect the HIV virus. The development of our AutoDock modelling application – combined with the computational power of World Community Grid – represents a significant breakthrough in our ability to fight HIV.

    By the mid 1990s, the first structure-based HIV protease inhibitors were approved for the treatment of AIDS. These inhibitors enabled the development of highly active antiretroviral therapy (HAART), which in turn resulted in a rapid decline of AIDS deaths where such treatment was available. In the intervening years, thanks in part to the U.S. National Institute of General Medical Sciences AIDS-related Structural Biology Program, we have learned a lot about the molecular structure of HIV. But the more we understand the structure of the virus, the more complex our computational models need to be to unlock the secrets of HIV.

    World Community Grid has enabled our research to progress well beyond what we could have dreamed of when we started our HIV research in the early 1990s. Through our FightAIDS@Home project, we can screen millions of chemical compounds to evaluate their effectiveness against HIV target proteins – including those known to be drug-resistant. By deploying these and other methods, we have significantly increased our understanding of HIV and its ability to evolve to resist treatment. Using these computational capabilities, we have just begun working with an HIV Cure researcher to help us move beyond treatment in search of a cure.

    See the full article here.

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    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.

    CAN ONE PERSON MAKE A DIFFERENCE? YOU BETCHA!!

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding

    FightAIDS@Home

    Computing for Sustainable Water

    Mapping Cancer Markers
    Mapping Cancer Markers Banner

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
    ibm

    IBM – Smarter Planet
    sp


    ScienceSprings is powered by MAINGEAR computers

     
  • richardmitnick 8:57 pm on July 20, 2014 Permalink | Reply
    Tags: , , , , , , World Community Grid   

    From Mapping Cancer Markers at WCG: “Project roadmap and first phase results from the Mapping Cancer Markers team” 

    Mapping Cancer Markers

    Mapping Cancer Markers Banner

    Mapping Cancer Markers

    By: The Mapping Cancer Markers research team
    10 Jul 2014

    Summary
    The lead researcher for Mapping Cancer Markers presents a roadmap for the project to analyze signatures for 4 types of cancer: lung, ovarian, prostate and sarcoma; an update on his team’s progress thus far, and an invitation to join the research team in an August cancer fundraiser.

    On behalf of the Mapping Cancer Markers team, we want to start by saying thank you! In just 7 months, World Community Grid members have donated over 60,000 years of processing time to support our research. As a result, we are nearly done with the “benchmarking” portion of the project, which determines the characteristics of our search space. Over the coming months and years, we will pursue more targeted approaches to discover relevant gene signatures. Today we want to give you both a high-level roadmap and some further detail about what is happening with the project.

    Project roadmap

    The project is anticipated to run for two years, and we plan to analyze signatures for 4 different types of cancer. At the moment, we’re enlisting your help to process research tasks for lung cancer, and will move on to ovarian cancer, prostate cancer and sarcoma.

    Currently, the Mapping Cancer Markers project has two phases:

    In the first phase we have been attempting to set a benchmark for further experiments.
    The second phase will be geared towards finding clinically useful molecular signatures, initially focusing on gene signatures that can predict the occurrence of various types of cancer.

    We expect a smooth transition between the two phases, with no interruption in work. The “benchmarking” phase of our project is important not only for our own research, but for other researchers around the world. Every year, numerous groups worldwide develop and publish interesting molecular signatures for various diseases, including multiple cancers. One of the challenges of interpreting these findings is that many of the reports are not directly comparable to each other. The benchmarking phase of our project is designed to set a standard benchmark so that we and other groups can estimate how well individual signatures perform.

    You can think of this benchmarking phase as a bit like designing an IQ test. By establishing a standard test and scoring system, we can evaluate any person’s intelligence. The results from the first phase of Mapping Cancer Markers will allow us to create such a test for existing and future gene signatures, so that we can tell which ones have the best predictive ability.

    Benchmarking

    Our preliminary analysis of the work units processed so far (roughly 26 billion gene signatures) is focused on the nature of genes in the signatures, measuring their quality by assessing how accurately they contribute to identifying patients with poor prognosis. On the analytics side, we have also been evaluating the use of a software package to aid with post-processing our results.

    One of the goals of the first project phase is to understand if some genes might have better predictive ability than others. To do this, we took the top 0.1% of the gene signatures and identified the individual genes that make up each signature. For each gene, we looked at how many times it occurred within top scoring signatures and plotted the scores of those signatures (see figure below). The blue line shows the average of all of the genes together. The red line highlights the worst-performing single gene while the green line indicates our best-performing gene. The average of all the genes is very similar to the worst single gene. This is not surprising, because most genes are likely to have poor predictive ability. However, we are looking for the few genes that stand out from the field. In other words, if we have 1 million potential gene signatures, and we look at the top 1,000 scoring signatures, we can find groups of genes such as the one shown in green, which have better predictive ability.

    This information is important because if we know which genes have the best predictive ability, it may help us and other researchers to evaluate the value of other signatures: if an unknown signature has one of the top genes in it, it is likely to be a useful signature for identifying, assessing, predicting or treating a disease.

    As a side note, this benchmarking process is why members may have experienced shorter or longer than usual runtimes over the past several months. The core algorithm of the Mapping Cancer Markers engine, used to evaluate each potential gene signature, has a processing time that is highly dependent on the statistical characteristics of each signature. The search space targeted by a single work unit can sometimes contain time-consuming signatures, which together lead to a longer total runtime. This also means variability with the size of Mapping Cancer Markers results. A typical work unit will evaluate tens of thousands of potential gene signatures, many of which are of low quality. Signatures below a certain quality threshold are removed from the returned results. However, the search space targeted by a single work unit can sometimes contain a high proportion of high-quality gene signatures. If this happens, the result file is larger than usual.

    Funding & Fundraising

    We’re happy to report that there are several potential sources for further funding. Applications are in progress with the Ontario Research Fund, the Canada Foundation for Innovation, and the US Department of Defense. Of course, the free computing power provided by World Community Grid volunteers is absolutely essential to our research. However, additional funding will help us to both leverage contributions from volunteers, and fully utilize findings of the Mapping Cancer Markers computations, with a primary focus on lung and ovarian cancer.

    Finally, if you will be in Ontario between 15-17 August, please consider donating to, or cheering on the Team Ian Ride from Kingston to Montreal, which raises money for the Ian Lawson Van Toch Cancer Informatics Fund at the Princess Margaret Cancer Centre (if you are interested, please contact us about joining the Team Ian ride this or next year). If you can join us, it will give you the chance to meet some of the research team, as well as raise money for a worthy cause and participate in an outstanding event. For more details visit:http://www.team-ian.org/

    Cancers, one of the leading causes of death worldwide, come in many different types and forms in which uncontrolled cell growth can spread to other parts of the body. Unchecked and untreated, cancer can spread from an initial site to other parts of the body and ultimately lead to death. The disease is caused by genetic or environmental changes that interfere with biological mechanisms that control cell growth. These changes, as well as normal cell activities, can be detected in tissue samples through the presence of their unique chemical indicators, such as DNA and proteins, which together are known as “markers.” Specific combinations of these markers may be associated with a given type of cancer.

    The pattern of markers can determine whether an individual is susceptible to developing a specific form of cancer, and may also predict the progression of the disease, helping to suggest the best treatment for a given individual. For example, two patients with the same form of cancer may have different outcomes and react differently to the same treatment due to a different genetic profile. While several markers are already known to be associated with certain cancers, there are many more to be discovered, as cancer is highly heterogeneous.

    Mapping Cancer Markers on World Community Grid aims to identify the markers associated with various types of cancer. The project is analyzing millions of data points collected from thousands of healthy and cancerous patient tissue samples. These include tissues with lung, ovarian, prostate, pancreatic and breast cancers. By comparing these different data points, researchers aim to identify patterns of markers for different cancers and correlate them with different outcomes, including responsiveness to various treatment options.

    This project runs on BOINC software. Visit BOINC or WCG, download and install the software and attach to the project. While you are at BOINC and WCG, look over the other projects for some that you might find of interest.

    WCG

    BOINC


    ScienceSprings is powered by MAINGEAR computers

     
  • richardmitnick 11:18 am on July 19, 2014 Permalink | Reply
    Tags: , , , , , , , , World Community Grid   

    Mapping Cancer Markers From WCG 

    Mapping Cancer Markers

    Mapping Cancer Markers Banner

    Mapping Cancer Markers

    Cancers, one of the leading causes of death worldwide, come in many different types and forms in which uncontrolled cell growth can spread to other parts of the body. Unchecked and untreated, cancer can spread from an initial site to other parts of the body and ultimately lead to death. The disease is caused by genetic or environmental changes that interfere with biological mechanisms that control cell growth. These changes, as well as normal cell activities, can be detected in tissue samples through the presence of their unique chemical indicators, such as DNA and proteins, which together are known as “markers.” Specific combinations of these markers may be associated with a given type of cancer.

    The pattern of markers can determine whether an individual is susceptible to developing a specific form of cancer, and may also predict the progression of the disease, helping to suggest the best treatment for a given individual. For example, two patients with the same form of cancer may have different outcomes and react differently to the same treatment due to a different genetic profile. While several markers are already known to be associated with certain cancers, there are many more to be discovered, as cancer is highly heterogeneous.

    Mapping Cancer Markers on World Community Grid aims to identify the markers associated with various types of cancer. The project is analyzing millions of data points collected from thousands of healthy and cancerous patient tissue samples. These include tissues with lung, ovarian, prostate, pancreatic and breast cancers. By comparing these different data points, researchers aim to identify patterns of markers for different cancers and correlate them with different outcomes, including responsiveness to various treatment options.

    This project runs on BOINC software. Visit BOINC or WCG, download and install the software and attach to the project. While you are at BOINC and WCG, look over the other projects for some that you might find of interest.

    WCG

    BOINC


    ScienceSprings is powered by MAINGEAR computers

     
  • richardmitnick 3:22 pm on July 16, 2014 Permalink | Reply
    Tags: , , , , , World Community Grid   

    From FAAH@home: “Improved efficiency and processing capabilities for FightAIDS@Home” 

    FAAH
    FightAIDS@home

    16 Jul 2014
    The FightAIDS@Home research team

    Summary
    New methods and processes help the research team process World Community Grid data more efficiently and provide more accurate docking techniques.

    As the volume of data generated by World Community Grid volunteers for our FightAIDS@Home (FAAH) project has increased, so has our need to optimize how we handle and store that data. In this project update, we discuss new improvements in how we process the extremely high result data rate you generate, which is allowing us to focus more resources toward the analysis of FAAH data. Further, improved docking techniques are being created and applied from the results of deeper analysis coupled with ongoing experimental data from our collaborators.

    model
    Example of repositioned side-chain, histidine, by Vina cycling through the original space-filling representation, original stick representation (orange), and new position compared to old position (dotted black lines).

    Processing your results faster

    Managing the very large data throughput generated by World Community Grid volunteers for FAAH is a great challenge. Beside the scientific results we have achieved over the years, we also have developed novel software and protocols to process, analyze and store the results you generate quickly and efficiently.

    Recently, we exploited the parallel computational resources available at Scripps. In the last few months, we have shifted our processing of the incoming World Community Grid data to our local High Performance Computing cluster, Garibaldi. Since the implementation of the AutoDock Vina software for FAAH last year, you have generated several terabytes of compressed docking results each month, which was putting a strain on our storage system. Until recently, most of our work and resources have been focused on processing this data to make it suitable for deeper analysis. We had to devote most of our local computational power to this processing. With our new methods, we have increased the processing rate by several orders of magnitude with the use of multiple processors and the optimization of processing scripts. Processing a batch that used to take between 30 minutes to few hours now takes just a few minutes. Streamlined scripts and parallel processing has yielded 180,000 processed batches in two weeks.

    We have created new analysis programs using structural and statistical methods to mine more information from the results you generate. Statistical analysis tools will first be used to reduce over 5 million docked compounds to a few thousand top-ranking candidates. Structural information will then be used to cull the list further by filtering for key intermolecular interactions and against unfavorable interactions. A new database structure that will incorporate these programs is being developed to handle this large and fast-growing flood of results. Once optimized, the whole processing and analysis workflow will be fully automated.

    Importantly, what we have learned and are learning from these refined methods to handle big data will be made available in the AutoDockTools suite, which is utilized by many research labs worldwide.

    Improved protein-ligand binding modeling capabilities

    Proteins are typically large molecules and often can bend or flex in various ways at various points and at normal temperatures they rapidly bend to many or all of the possible configurations (bent shapes). When searching for ligands that might attach to a protein target, the ligand might not match the shape of the protein in one of its configurations, but might match in another configuration of the protein. By considering more configurations of the protein, it is more likely that a ligand can be found which matches one of the protein’s configurations. Since February 2014, we have been running flexible receptor side-chain Vina jobs on FAAH, which we expect to enhance our docking results. While our typical docking methods hold the protein structure rigid, the flexibility feature in AutoDock Vina allows selected residue side chain conformations to be sampled along with the flexible ligand molecule. This enables the protein pocket to adopt alternate shapes to better model protein-ligand binding and the so-called “induced fit”, minimizing the bias of using a rigid target structure. Currently, we are testing this approach on several sites (LEFGF, FBP, and Y3) in HIV integrase.

    The downside of performing flexible receptor calculations is that the search complexity increases, and computing run-times are therefore 5 to 10 times longer. The World Community Grid staff has been adjusting their methods to account for the different Flexible Vina work unit. Once these dockings have finished and the analyses performed, we will be able to optimize our application of Flexible Vina on World Community Grid and extend it to other targets.

    Another way to minimize rigid-protein bias in traditional docking is to dock to an ensemble of protein structures. Two ways to generate these ensembles, both used in FAAH dockings, are molecular dynamics (MD) simulations and simply using multiple available structures for a given protein receptor. The last hundred experiments have included ensembles ranging from tens to sometimes hundreds of receptor structures. Ensembles add another layer of analysis with the goal of achieving a more accurate ranking of compounds from several sources of data.

    Further experimentation

    Despite the encouraging results on the first hits previously reported, we are encountering experimental issues that are making the process of identifying hits very challenging. As often happens in science (and particularly in HIV-related experiments!), it is hard to achieve robust and consistent statistics from biological assays.

    See the full article here.

    FightAIDS@Home is a project run by the Olson Laboratory that uses distributed computing to contribute your computer’s idle resources to accelerate research into new drug therapies for HIV, the virus that causes AIDS. FightAIDS@Home made history in September 2000 when it became the first biomedical Internet-based grid computing project. FightAIDS@Home was started with Scott Kurowski, founder of Entropia. People all around the World continue to donate their home computer’s idle cycles to running our AutoDock software on HIV-1 protease inhibitor docking problems. With the generous assistance of IBM, we joined World Community Grid in late 2005, and launched FightAIDS@Home on World Community Grid on 21 November, 2005.

    How do I join the FightAIDS@Home Project?

    All you need to do is download and install the free client software. Once you have done this, your computer is then automatically put to work and you can continue using your computer as usual.

    Faah Screensaver


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  • richardmitnick 1:04 pm on July 14, 2014 Permalink | Reply
    Tags: , , , , World Community Grid   

    From WCG: “GO Fight Against Malaria update: promising early findings for malaria & drug-resistant tuberculosis” 

    14 Jul 2014
    Dr. Alexander L. Perryman

    Summary
    Dr. Alexander Perryman describes the analysis and initial findings from the first phase of GO Fight Against Malaria, which include the discovery of several promising hits against key drug targets for treating both malaria and drug-resistant strains of tuberculosis. They are conducting further analysis and experimentation on the massive amount of data generated by World Community Grid volunteers.

    Dear fellow volunteers of World Community Grid,

    In under two years, World Community Grid volunteers performed the world’s largest docking project, carrying out over 1 billion calculations to help us identify chemical compounds to advance the treatment of increasingly drug-resistant strains of malaria and other diseases – a process that would have taken over a hundred years on the type of computer clusters currently available at most universities.

    Since we completed GO Fight Against Malaria (GFAM) calculations on World Community Grid a year ago, we’ve been analyzing the generated data. Although that process will continue for some time still, early analysis has revealed several promising findings.

    gfam

    First, we identified the first “œsmall molecule” inhibitor (i.e., drug-like compound) to block the activity of a particular malaria enzyme involved in infection, the first step in developing a potential treatment or prevention aimed at this malaria drug target.

    Also, a subset of your calculations was conducted against a drug target for malaria which shares a similar atomic structure to a Mycobacterium tuberculosis enzyme. With extensively drug-resistant strains of tuberculosis on the rise, there is a pressing need to identify more effective treatments. We therefore included this particular tuberculosis drug target in our GFAM experiments. In doing so, we have identified several chemical compounds as potential inhibitors of this enzyme and have confirmed these results with initial laboratory tests. A very impressive number of the promising chemical compounds identified through the virtual screenings you computed on World Community Grid have gone on to perform well in additional lab testing: 20% were “hits”, vs. less than 1% on average for other experimental (“œwet lab”) high-throughput tuberculosis experiments.

    We are now designing and synthesizing new derivatives of these inhibitors to further refine them as viable drug candidates. Read on for more details about this early analysis work, and we’ll be able to share more information once we publish our findings. In the meantime, I want to thank GFAM volunteers for allowing us to advance this important and often neglected area of research.

    Largest set of computational docking experiments ever performed

    GFAM was launched on IBM’s World Community Grid on November 16, 2011. Malaria is one of the three deadliest infectious diseases on Earth (the other two are HIV and tuberculosis). Plasmodium falciparum (Pfal, or Pf), the species that causes the worst form of malaria, kills more people than any other parasite on the planet. Over 200,000,000 clinical cases of malaria occur each year, and over one million people are killed by malaria every year. Over three billion people (almost half of all humans) are at risk of becoming infected with malaria, and every 30 seconds, another child dies of malaria.

    GFAM ran on World Community Grid for 19 months, during which the tremendous computational power provided by World Community Grid volunteers like you helped us generate massive data sets against 22 different types of drug targets, to seed the discovery of new drugs to treat malaria. We performed “docking calculations,” which explore how well different “small molecules” (pieces of drug-like compounds) are able to bind and potentially block the activity of critical pieces of the molecular machinery that the pathogens use to survive, replicate, and spread throughout humanity. Docking calculations use flexible models of these small molecules to explore the energetic landscape of atomic-scale models (on the scale of 0.0000000001 meters) of proteins that perform critical functions for the parasite’™s lifecycle and infection process. These calculations predict how tightly a compound might bind to the target (that is, how potent it might be), where the compound probably prefers to bind, and what specific types of interactions might be formed between the compound and the drug target. One docking calculation refers to the process of docking a flexible model of a single compound against one particular version of one target. In this first phase of GFAM, World Community Grid volunteers performed 1.16 billion different docking calculations that explored the potential activity of 5.6 million different compounds against drug targets from malaria (and against some targets for treating drug-resistant tuberculosis, Methicillin-Resistant Staphylococcus aureus (MRSA), filariasis, and bubonic plague, when the targets from those other pathogens had structural similarity to the targets from malaria). With the computing power that you generously donated, GFAM was the first project to ever perform a billion different docking calculations. Performing this many calculations could have taken over a hundred years on the type of computer clusters currently available at most universities. We could not have accomplished this feat without your help. We are also grateful for the $50,000 in seed funding provided by the IBM International Foundation, from part of the prize money that IBM’s computer Watson won on Jeopardy!™. Thus far, that seed money has been the only funding that the project has received, but we are currently writing grants that focus on analyzing and extending the GFAM data.

    Finding a “œhit” that inhibits a critical protein involved in malaria infections

    “Hits” are compounds that have some inhibitory effect on the biological activity of one of these drug targets. But finding a hit is only the beginning of the process (a complicated process that can take several years to a couple of decades to complete). Scientists from around the world called “medicinal chemists” can then work with structure-based computational chemists like us to try to increase the potency and decrease the potential toxic side effects of these compounds, which involves processes called “hit-to-lead development” and then “œlead optimization”. “œLeads” are larger, more structurally complex, potential drug candidates that generally display nanomolar potency (that is, they are around 1,000 times more potent than “œhits”, which means that only a tiny amount of a leading compound is required to affect the activity of the target). In collaboration with Professor Mike Blackman’s lab in the Division of Parasitology at the Medical Research Council’s (or “MRC’s”) National Institute for Medical Research (or “œNIMR”), in London, UK, and with InhibOx, Ltd, we searched for the first small molecule inhibitors of the potential drug target “œPfSUB1″ (see target class #6 on http://gofightagainstmalaria.scripps.edu/index.php/how-we-will-discover-potential-malaria-drugs). When the Blackman lab solved the first crystal structure of PfSUB1 (that is, the atomically-detailed, 3-D map of where all of its atoms are), they shared that unpublished structure with us, which allowed us to perform virtual screens against PfSUB1. These virtual screens are searching for “small molecule” inhibitors (that is, compounds with some similarity to pieces of known drugs) that can block the activity of this malarial enzyme. When malaria parasites replicate themselves inside a red blood cell, the “daughter” parasites eventually rupture the infected host cell, which allows the new parasites to escape and then invade and infect other red blood cells. The subtilisin-like serine proteases from Plasmodium falciparum (also known as PfSUB1) are involved in this ability of the malaria parasites to escape (or “œegress”) an infected red blood cell. The Blackman lab has shown that the PfSUB1 enzyme has an additional role in “priming” the merozoite stage of the parasite prior to its invasion of red blood cells (in other words, it is involved in processing certain other malarial proteins in order to prepare and activate them, so that the parasite can invade our blood cells). Thus, PfSUB1 is involved in both the egress and the infection process. In the results of GFAM Experiment 27, we discovered the first small molecule inhibitor of PfSUB1 ever identified, and it displayed a proper “dose-response curve” (that is, at higher concentrations of the inhibitor, it shuts down the activity of PfSUB1 more and more effectively), which indicates that it is likely a “œspecific” inhibitor, instead of a non-specific compound that randomly happens to impede activity a bit for many different types of proteins (but this will have be tested against other types of proteins to know for sure). This compound, nicknamed “GF13″, is a fairly weak inhibitor: at a 200 micromolar concentration, it blocks activity of PfSUB1 50%. Strong hits will block 50% of the target’s activity in the 1 to 50 micromolar range (the smaller the # of micromoles per liter that are needed to shut down activity, the more potent a compound is).

    See the full article here.

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    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.

    CAN ONE PERSON MAKE A DIFFERENCE? YOU BETCHA!!

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding

    FightAIDS@Home

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
    ibm

    IBM – Smarter Planet
    sp


    ScienceSprings is powered by MAINGEAR computers

     
  • richardmitnick 12:26 pm on July 14, 2014 Permalink | Reply
    Tags: , , , , , World Community Grid   

    FROM WCG: “Better tools for AIDS drug research” 

    FAAH
    FightAIDS@home

    FightAIDS@Home is a project run by the Olson Laboratory that uses distributed computing to contribute your computer’s idle resources to accelerate research into new drug therapies for HIV, the virus that causes AIDS. FightAIDS@Home made history in September 2000 when it became the first biomedical Internet-based grid computing project. FightAIDS@Home was started with Scott Kurowski, founder of Entropia. People all around the World continue to donate their home computer’s idle cycles to running our AutoDock software on HIV-1 protease inhibitor docking problems. With the generous assistance of IBM, we joined World Community Grid in late 2005, and launched FightAIDS@Home on World Community Grid on 21 November, 2005.

    How do I join the FightAIDS@Home Project?

    All you need to do is download and install the free client software. Once you have done this, your computer is then automatically put to work and you can continue using your computer as usual.


    ScienceSprings is powered by MAINGEAR computers

    24 Jun 2014

    Summary
    The Scripps research team published a paper proving the effectiveness of a method to more accurately predict bindings between protein targets and drug candidates, which could benefit FightAIDS@Home and other World Community Grid drug discovery projects.

    Paper Title:

    “Virtual screening with AutoDock Vina and the common pharmacophore engine of a low diversity library of fragments and hits against the three allosteric sites of HIV integrase: participation in the SAMPL4 protein–ligand binding challenge”

    Lay Person Abstract:

    The Olson Lab at The Scripps Institute collaborated to participate in the “SAMPL4 Challenge” which evaluated methods to predict protein target to drug candidate bindings. Olson’s lab in cooperation with Levy’s lab at Rutgers University were able to prove the utility of a method to reduce false positives and therefore potentially reduce the amount of laboratory work required to validate computational results. This should ultimately be a benefit to research projects such as FightAIDS@Home and other drug search projects on World Community Grid.

    A link to the paper is here.
    See the full article here.

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    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.

    CAN ONE PERSON MAKE A DIFFERENCE? YOU BETCHA!!

    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-

    Say No to Schistosoma
    sch

    GO Fight Against Malaria
    mal

    Drug Search for Leishmaniasis
    lish

    Computing for Clean Water
    c4cw

    The Clean Energy Project
    cep2

    Discovering Dengue Drugs – Together
    dengue

    Help Cure Muscular Dystrophy
    md

    Help Fight Childhood Cancer
    hccf

    Help Conquer Cancer
    hcc

    Human Proteome Folding
    hpf

    FightAIDS@Home
    faah

    Computing for Sustainable Water

    Computing for Sustainable Water

    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation
    ibm

    IBM – Smarter Planet
    sp


    ScienceSprings is powered by MAINGEAR computers

     
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