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Thread: Messages from Prof. Vijay Pande
11-17-2011, 03:40 PM #91
Well said Black!!RIG:i7-3770k @4.6Ghz/ASUS P8Z77 Deluxe/GSkill DDR3-2400/2xHD7970/Vertex 4/SSonic Plat 1000/H100/HAF XB
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11-18-2011, 04:47 PM #92Senior Member Achievements:
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I understand why Scott is doing it, and have no problem with it, but it was just to illustrate that in the end points still matter in many cases, which are not directly related to F@H, but rather to the communities built around it.
Regarding bigadv, the limitation of number of cores is arbitrary, and I don't understand why it's necessary. If someone can hit the deadlines with a massively overclocked 6 core or 4 core, what's wrong with that?
11-18-2011, 09:40 PM #93
that's a question only the powers that be at F@H can answer.The path to universal understanding starts here: Say what you mean, and mean what you say.
12-14-2011, 07:40 PM #94
December 13, 2011
Update on outage – FAH has been up as of Sunday, stats back on line now
Here's our (I think) last update on this recent outage. This was a major disaster at Stanford affecting the whole campus and I'm grateful for our team coming in on Sunday to get things back up. The workservers have been up since then and work and stats have been saved. The stats updating was put on hold until we can make sure everything looked ok. We've turned it back on. Please note that there is no stats loss while we turn off updates. People should see a big bump in their stats shortly. Thanks for bearing with us through this.The path to universal understanding starts here: Say what you mean, and mean what you say.
02-22-2012, 01:54 AM #95
I have been sorely lacking in my responsiblities here, and do appologize. many updates to post starting with;
February 07, 2012 Update on "bigadv-16", the new bigadv rollout As we've mentioned earlier, we have been preparing changes to the bigadv system –– both an increase in the number of cores required (and a shortening of deadlines to match) and the release of some new bigadv projects. The motivation for the core changes is as follows:
Bigadv is intentionally intended for the most powerful machines, which makes it naturally a moving target. Our goal with bigadv is to utilize the most powerful segment of (CPU-based) machines in the FAH project to work on projects that are particularly large (memory utilization, upload/download requirement) and require a large amount of computation. We are all fortunate in that processors get faster over time, so the highest-performing tier of donor machines also gets faster over time. We have a lot of exciting science being enabled by FAH donors, and it takes place at all levels of computational requirement and performance sensitivity. So it wouldn't help the project to have 50% of machines running bigadv. But it also wouldn't be a good match to have some of the older and/or bandwidth-limited machines running these most performance-sensitive projects.
As previously announced, our plan is to shorten the deadlines of the BA projects. As a result, assignments will have a 16 core minimum. We've been developing the new projects for the new "bigadv-16". This development has taken a bit longer than we expected, but we are now completing internal testing and reading beta projects for bigadv-16. We are bringing a new server online for bigadv-16. It will start by offering a new class of bigadv projects, but we will soon add in a number of projects on the same server that are more similar to bigadv projects donors have already seen. We want to make these work units available for testing, but at the same time we are still examining the points yield of these bigadv projects. So the points valuation remains a work in progress; we may alter points, bonuses, and/or deadlines in the process of testing.
Please expect a beta announcement soon for testing these new bigadv-16 work units. Then, after the new bigadv-16 projects stabilize, we will bring the bigadv-12 projects into line (points, deadlines) with the bigadv-16 projects and convert all projects to bigadv-16. We are not sure of the timescale for this yet, as we'd like to test the new projects in a thorough manner. We will endeavor to be as transparent as we can regarding upcoming changes in the bigadv program. Bigadv-8 projects will likely be phased out (and indeed are mostly not being assigned at this time).
As a side note, we recognize that the number of cores is a somewhat crude measure for system performance. Long-term, we have some ideas on how we'd like to improve this and use better metrics. But in the near term, we are using this admittedly imperfect metric.
Thank you for folding and for your support of the bigadv program and FAH more generally.
Last edited by Blacksmith1; 03-18-2012 at 05:37 AM.The path to universal understanding starts here: Say what you mean, and mean what you say.
02-22-2012, 01:55 AM #96
February 11, 2012 stats back up – we're looking into missing interval The stats system went down last night and is now back up. We are working on recrediting the WUs that came in last night. WUs coming in now should be getting credit as always.
Last edited by Blacksmith1; 03-18-2012 at 05:38 AM.The path to universal understanding starts here: Say what you mean, and mean what you say.
02-22-2012, 01:56 AM #97
February 13, 2012 LTMD: Key new technology for accelerating folding and misfolding simulations in FAH
Here's an update one one of our key projects looking into protein folding, performed in collaboration with Prof. Jesus Izaguirre's lab at Notre Dame. Below is an update from Prof. Izaguirre on the progress of this project.
The Izaguirre Lab at the University of Notre Dame (http://www.nd.edu/~lcls) has been collaborating with the Pande Lab at Notre Dame to produce a new GPU core that leverages the amazing speed of OpenMM implicit-solvent force calculations (the heart of the GPU core in Folding@home) with new Long Timestep Molecular Dynamics (LTMD). This combination currently allows nearly a 10-fold speedup over OpenMM for systems as small as the WW domain (35 residues, 544 atoms) up to the Lambda repressor (80 residues, 2000 atoms). This translates into about 10 microseconds per day of simulation, which brings single trajectory millisecond simulations closer to FAH.
In collaboration with Cauldron Development (lead by Joseph Coffland, primary developer of the Folding@home client and also some cores), we hope to produce a GPU core that might be the first hybrid CPU-GPU core. There are technical questions on how to best do this, and we will engage our enthusiastic beta-tester GPU donors to discuss how to best approach this core when we are closer to production mode.
Going forward, we will continue to improve the LTMD GPU technology to obtain larger speedups for ever larger and biomedically relevant systems. A particularly excitement development will be the extension of LTMD GPU technology to explicit solvent simulations.
As far as scientific simulations, we are simulating the folding of about 80 mutants of the Pin1 WW domain, a protein implicated in some cancers and Alzheimer's disease. Understanding the role of mutations on misfolding can have important biomedical consequences, since many diseases have at least some component of misfolding of proteins. Another exciting project we are about to start is to simulate the dimerization during folding of proinsulin and proinsulin mutants, which results in some types of Type IA young and adult onset diabetes.
Thanks to the FAH donors, testers, and to the Pande Lab for their generosity and leadership which has allowed our technological developments and simulations to come this far.
An image of the Pin WW domain.
Last edited by Blacksmith1; 03-18-2012 at 05:40 AM.The path to universal understanding starts here: Say what you mean, and mean what you say.
02-22-2012, 01:56 AM #98
February 20, 2012 Update from Hong Kong University of Science and Technology
Here's a guest post from Prof. Xuhui Huang's lab at Hong Kong University of Science and Technology, another collaborating labortory in the Folding@home consortium. Prof. Huang and his lab have made several important methodological applications to FAH (for more details, see this review article) as well as important research into the molecular nature of Huntington's Disease. Here's an update from Prof. Huang:
In the past a couple of years, the FAH has greatly helped us on our research on understanding the mechanisms of the molecular recognition processes. Molecular recognition, such as enzymes need to recognize their substrates and drugs have to be designed to specifically bind to certain receptors, is crucial to biology and medicine. Experimentally probing the chemical details of molecular recognition events is challenging, while computer simulations have the potential to provide a detailed picture of such events. With the help of the FAH donors, we are performing large-scale simulations on a group of Periplasmic Binding Proteins aiming to reveal the general relationships between protein structures, its intrinsic dynamics, and mechanism of recognition process.
The FAH projects related to the above research are between 7700 and 7712. We greatly appreciate the help from all the FAH donors, beta testers, and the rest of the FAH team to make our research on molecular recognition possible.
Last edited by Blacksmith1; 03-18-2012 at 05:40 AM.The path to universal understanding starts here: Say what you mean, and mean what you say.
03-18-2012, 05:43 AM #99
A bit late , but here it is.
February 24, 2012 Protein folding and viral infection
Understanding protein folding has many possible areas of biological and biomedical impact. For example, consider one of the major research areas of the Kasson lab at the University of Virginia, namely how the influenza virus infects cells. In the past, Dr. Kasson and Dr. Pande have studied two aspects of this: how the influenza virus recognizes cell-surface receptors so it infects the "right" cell types and how small vesicles fuse.
Dr. Kasson's group is now looking at the function of the viral protein that controls cell entry, a protein called hemagglutinin. The hemagglutinin protein interacts with cell membranes: one piece inserts into the membrane, refolds, and alters the membrane in some unknown manner to promote viral entry. Another piece links the viral and cell membranes and refolds to bring the two together. We are running simulations on Folding@Home to examine each of these pieces. Dr. Kasson's laboratory also looks at these processes experimentally.
Both of these problems involve protein folding. This extends the problem of understanding folding beyond the "canonical" model of an unstructured protein in water taking on a final shape but instead in the first case a small protein inserting into a lipid membrane and changing shape in response to its environment and in the second case a large protein changing from one shape to another in response to physiological cues. One could consider these special cases of protein folding or how viruses use protein folding to infect cells.
Future posts will address methods we have developed to assist in these studies as well as other important problems we work on. We are also doing methodological work that will improve the efficiency of running Folding@Home simulations and analyzing the results. The Folding@home community has made an important contribution in providing the computing power for these studies (you can see some of our published work on the FAH papers page), and we are grateful to all involvedThe path to universal understanding starts here: Say what you mean, and mean what you say.
03-18-2012, 05:47 AM #100
February 27, 2012 New methods for computational drug design
A key aspect of Folding@home research has been using computational methods to design new drugs, especially for Alzheimer’s Disease. At the University of Virginia, the Shirts lab is developing methods to leverage the power of Folding@home to develop new drugs to fight disease. Generally, small molecules work as drugs by binding very specifically to certain locations on important proteins. For example, an antibiotic works by binding to a protein on a bacteria, thus interfering with the pathogen's internal workings seriously enough to disable or kill it. By targeting only protein sites that are unique to the pathogen, drugs can act extremely specifically, rather than harming the human body or desired microbes. The exact same principles can toggle very specific parts of our own body's protein machinery on or off, allowing development of drugs that fight diseases of caused by breakdown, mutation, or malfunction our own cellular machinery, like Alzheimer’s Disease, heart disease, diabetes, and many other conditions.
However, it is very hard to calculate exactly how tightly a given small molecule will bind to a target protein, or even exactly where and by what mechanism it will bind. A number of computational methods are used in industry today to estimate the binding affinity of small molecules in the process of drug design, but they mostly rely on approximations that are computationally cheap and very approximate, rather than more expensive methods that have the potential to be much more accurate. With Folding@home, we now have the capability to perform rigorous evaluations of these more complete methods, understand their limits, and make them more efficient and reliable.
We have been developing our methods working mostly with well-understood model systems, such as FKBP, a protein on the immune system signaling pathway. Once the methods are well-understood, we will be moving on try to design small molecules to treat AIDS (the HIV reverse transcriptase enzyme, required for DNA to replicate) and influenza (various proteins involved in virus cell entry). Such molecules will still require significant effort to make into drugs, since drugs also have to dissolve easily, penetrate cells, and not be broken down to quickly, but being able to predict more easily which molecules interact tightly with the intended targets will be a huge step in the right direction.
As part of our efforts to improve Folding@home infrastructure, we are also working to port new versions of the Gromacs molecular simulation platform to Folding@home and improving the interface and integration between Gromacs and Folding@home.
03-26-2012, 02:16 AM #101
March 20, 2012 Stanford scientists and collaborators boost potency, reduce side effects of IL-2 protein used to treat cancer Today, I'm highlighting the work primarily out of Chris Garcia's lab at Stanford Medical School. The Garcia lab had a very exciting idea on how to re-engineer a very important protein and the Pande lab played a part by providing computer simulations to help understand the mechanism by which the new protein worked. The results are very exciting. Check out the link below for more details.
SUMMARY. The utility of a naturally occurring protein given, sometimes to great effect, as a drug to treat advanced cancers is limited by the severe side effects it sometimes causes. But a Stanford University School of Medicine scientist has generated a mutant version of the protein whose modified shape renders it substantially more potent than the natural protein while reducing its toxicity.The path to universal understanding starts here: Say what you mean, and mean what you say.
03-26-2012, 02:19 AM #102
March 21, 2012 FAH simulations lead to a new therapeutic strategy for Alzheimer's Disease I'm very excited to finally talk about some key new results from our lab. These results have been a long time in coming and in many ways represents a major achievement for Folding@home (FAH) in general, demonstrating that the approach we started 10 years ago can make significant steps forward in our long term goals.
Specifically, our long term goals have been to 1) develop new methods to tackle the computational challenges of simulating protein folding; 2) apply these methods to gain new insights into protein folding; 3) use these methods and new insights to simulate Aß protein misfolding, a key process in the toxicity of Alzheimer's Disease (AD); and finally 4) to use those simulations to develop new small molecule drug candidates for AD. In the early years of FAH, we concentrated on the first two goals above. In the last 5-7 years, we have worked to accomplish the third goal. I'm now very excited to report our progress on the last goal –– using FAH for the development of new therapeutic strategies for AD.
In a paper just published in the Journal of Medicinal Chemistry, we report on tests of predictions from earlier Folding@home simulations, and how these predictions have led to a new strategy to fight Alzheimer's Disease. While this is not a cure, it is a major step towards our final goal, some light at the end of the tunnel.
The next steps, now underway in our lab, are to take this lead compound and help push it towards a viable drug. It's too early to report on our preliminary results there (I like to only talk publicly about work after it's passed through peer review), I'm very excited that the directions set out in this paper do appear to be bearing fruit in terms of a viable drug (not just a drug candidate). I hope I'll have more to say in the coming months!
Design of β-Amyloid Aggregation Inhibitors from a Predicted Structural Motif
Paul A. Novick†, Dahabada H. Lopes‡, Kim M. Branson†, Alexandra Esteras-Chopo§, Isabella A. Graef§, Gal Bitan‡, and Vijay S. Pande†*
† Department of Chemistry, Stanford University, Stanford, California 94305, United States
‡ Department of Neurology, UCLA, Los Angeles, California 90095, United States; Brain Research Institute, UCLA, Los Angeles, California 90095, United States; Molecular Biology Institute, UCLA, Los Angeles, California 90095, United States
§ Department of Pathology, Stanford University, Stanford, California 94305, United States
Drug design studies targeting one of the primary toxic agents in Alzheimer’s disease, soluble oligomers of amyloid β-protein (Aβ), have been complicated by the rapid, heterogeneous aggregation of Aβ and the resulting difficulty to structurally characterize the peptide. To address this, we have developed [Nle35, d-
Pro37]Aβ42, a substituted peptide inspired from molecular dynamics simulations which forms structures stable enough to be analyzed by NMR. We report herein that [Nle35, d-Pro37]Aβ42 stabilizes the trimer and prevents mature fibril and β-sheet formation. Further, [Nle35, d-Pro37]Aβ42 interacts with WT Aβ42 and reduces aggregation levels and fibril formation in mixtures. Using ligand-based drug design based on [Nle35, d-Pro37]Aβ42, a lead compound was identified with effects on inhibition similar to the peptide. The ability of [Nle35, d-Pro37]Aβ42 and the compound to inhibit the aggregation of Aβ42 provides a novel tool to study the structure of Aβ oligomers. More broadly, our data demonstrate how molecular dynamics simulation can guide experiment for further research into AD.
The path to universal understanding starts here: Say what you mean, and mean what you say.
03-26-2012, 02:21 AM #103
March 22, 2012 Web page revamp and v7 rollout We're installing a new web page for our main site http://folding.stanford.edu. While we're not done quite yet, the main changes are in. Hopefully the new site is cleaner and simpler, both in aesthetics and in ability to navigate.
This also coincides with our official rollout of the version 7 (v7) client software for Folding@home. This new client is a complete rewrite with the intention to make it much easier for donors to contribute to Folding@home. In particular, the new client unifies the classic, SMP, and GPU clients into a single download. Also, installation (especially of the more high performance clients such as SMP and GPU) is much easier than before. Finally, the revamped viewer should also be a much better user experience for FAH donors.
All in all, our hope is that these combined changes make it much easier for people to understand what we're about and to help contribute to Folding@homeThe path to universal understanding starts here: Say what you mean, and mean what you say.
07-16-2012, 05:26 PM #104
1 out of 1 members found this post helpful.
July 16, 2012-New GPU-powered algorithms
Guest post from Dr. Xuhui Huang, Hong Kong University of Science and Technology
In this post, I want to introduce a new GPU-powered clustering algorithm we recently developed to analyze the large molecular dynamics simulation datasets generated by Folding@home. Folding@home can generate enormous sets of protein structures. A critical step in analyzing these large datasets involves some form of reduction in the dataset, usually in the form of clustering. We recently developed a GPU powered clustering algorithm using the intrinsic properties of a metric space to rapidly accelerate the clustering. Overall, our algorithm is up to two orders of magnitude faster than the CPU implementation, and holds even more promise with the ever increasing performance in GPU hardware.
This algorithm should facilitate numerous applications. For example, one of the systems we tested our code on is the human islet amyloid polypeptide (hIAPP) peptide, whose aggregation is implicated in Type 2 diabetes. We hope further analysis of this data will provide insights that will inform the development of treatments for diabetes.
07-23-2012, 10:55 PM #105
July 23, 2012-Bonus for A4-core based projects –– now in effect
A brief update to our previous blog post on the A4 bonus: the bonus is now in effect.
the previous blog post;
Bonus for A4-core based projects
We've noticed a significant number of high priority projects are trailing behind existing projects. Newer projects are aimed at interpreting and guiding experiments where the full power of Folding@home (F@h) is essential to continue pushing the boundaries of scientific and medical discoveries.
The main cause of this issue is the core version needed to run these simulations. Many of our newer SMP projects use the A4 core, which has several scientific advancements, while existing projects use the still important A3 core. The A4 core is not compatible with Clients below version 6.34 and many donors are still running these older Client versions.
This presents an opportunity to encourage people to donate their cycles towards these vital A4 projects. To emphasize the scientific importance of these work units, we are boosting the base points of all A4 work units by 10% when uploaded (Note that this bonus will not be reported by V7 or by the 3rd party applications which project PPD but the points will appear when your statistics are credited). The quick return bonuses will be calculated on top of the increased base points. This will start on Monday July 23, 2012, and we will keep this 10% bonus in effect for at least 3 months as a trial period, but plan to keep it longer, as needed.
To participate, donors should be running a recent version of the F@h Client. We strongly encourage Windows users to update to the much improved V7 Client. Although F@h Client v6.34 or newer is sufficient to participate for any supported operating system. Please note the Linux and OSX V7 Clients are a work in progress and feedback is welcomed.
Windows/Linux: Visit our home page, http://folding.stanford.edu/English/HomePage
Mac OSX: v7 for OSX is still in testing. For a beta copy: https://fah-web.stanford.edu/project...ki/BetaRelease
Old v6.34+ Clients
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