Folding@home

From Free net encyclopedia

Image:FoldingHomeLogo.jpg Image:Fah.PNG Folding@home is a distributed computing project designed to perform computationally intensive simulations of protein folding. It was launched on October 1, 2000, and is currently managed by the Pande Group, within Stanford University's Chemistry department, under the supervision of Professor Vijay S. Pande. Folding@home is now the second largest distributed computing project after SETI@home.

On March 8, 2004, Genome@home was terminated and was merged into Folding@home.

1 Project significance
2 Folding@home vs. Rosetta@home
3 How it works
4 Progress and future
5 Bibliography
6 See also
7 External links

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Project significance

Accurate simulations of protein folding and misfolding enable the scientific community to better understand the development of many diseases, including Alzheimer's disease, BSE (mad cow disease), cancer, and cystic fibrosis. So far, the Folding@home project has successfully simulated folding in the 5-10 microsecond range—a time scale thousands of times larger than was previously thought possible.

Many scientific research papers have been published using the project's work. [1]

University of Illinois at Urbana-Champaign report on October 22, 2002 states that their distributed simulations of protein folding are demonstrably accurate.

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Folding@home vs. Rosetta@home

Quote from Mr. Vijay Pande http://forum.folding-community.org/viewtopic.php?p=125338#125338

I know Baker and Ranganathan and their work very well and (like the rest of the protein community) find their work very important and impressive. However, Rosetta@home and Folding@Home are addressing very different problems.

Rosetta only predicts the final folded state, not how do proteins fold (and Rosetta has nothing to do with protein misfolding). Thus, those methods are not useful for the questions we're interested in and the diseases we're tackling (Alzheimer's Disease and other aggregation related diseases).

Also, one should note that accurate computational protein structure prediction is still very challenging compared to what one can do experimentally, whereas the information obtained from Folding@home on the nature of folding and misfolding pathways matches experiment (eg with quantitative validation in rates, free energy, etc) and then goes beyond what experiment can tell us in that arena. While Rosetta has gone a long way and is a very impressive project, given the choice between a Rosetta predicted structure and a crystal structure, one would always chose the crystal structure. I bet that will be changing due to their great efforts, but that may still be a ways off for that dream to be realized.

So, both are valuable projects IMHO, but addressing very different questions. I think there are some misunderstandings out there, though. Some people think FAH is all about structure prediction (which it is not -- that's Rosetta's strength) and some think Rosetta is about misfolding related disease (which it's not, that's Folding@Home's strength). Hopefully this post helps straighten some of that out.

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How it works

Folding@home does not rely on powerful supercomputers for its data processing; instead, the primary contributors to the Folding@home project are many thousands of personal computer users who have installed a small client program. The client runs in the background, and makes use of the CPU when it is not busy. In most modern personal computers, the CPU is rarely used to its full capacity at all times; the Folding@home client takes advantage of this unused processing power.

The Folding@home client periodically connects to a server to retrieve "work units," which are packets of data upon which to perform calculations. Each completed work unit is then sent back to the server. As data integrity is a major concern for all distributed computing projects, all work units are validated through the use of a 2048 bit digital signature.

The Folding@home client utilizes modified versions of four molecular simulation programs for calculation: Tinker, Gromacs, AMBER, and QMD.

Contributors to Folding@home may have user names used to keep track of their contributions. Each user may be running the client on one or more CPUs; for example, a home user with two computers could run the client on both of them. Users may also contribute under one or more team names; many different users may join together to form a team. Contributors are assigned a score indicating the number and difficulty of completed work units. Rankings and other statistics are posted to the Folding@home website.

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Progress and future

As of February 9, 2006, more than 220,000 CPUs were actively participating in Folding@Home (active CPUs are defined as those returning work units within the last 50 days), with over 1,500,000 CPUs registered. This level of participation makes the Folding@home distributed supercomputer one of the most powerful supercomputers in the world capable of a sustained computational level of over 210 teraFLOPS. Shortly after breaking the 200,000 active CPU count on September 20, 2005, the Folding@Home project celebrated its fifth anniversary on October 1, 2005.

There is already cooperation between Folding@home and Google Labs. This comes in the form of Google Compute. However, with the new Google Toolbar, this platform is no longer actively supported, but older releases of the toolbar will still function. [2]

Image:Folding@Home-Googlebar.png

Current research is aimed at accelerating computational power by utilizing a computer's GPU (the graphics processing unit) in addition to the CPU. News about the progress of porting Folding@Home onto GPU's can be found in the High performance client FAQ section of the Folding@Home FAQ pages. Recent test data indicate performance gains of up to 40x that of an Intel Pentium 4 CPU are possible (note: this performance varies with different GPU's).

Folding@Home is currently developing a BOINC version in the hopes of attracting a wider base of users.

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Bibliography

{{cite journal

|author=P. Bradley et al |title=Toward high-Resolution de Novo Structure Prediction for Small Proteins |journal=Science |year=2005 |volume=309 |issue=16 Sep. |pages= 1868–1871}}

{{cite journal

|author=M. Socolich et al |title=Evolutionary Information for Specifying a Protein Fold |journal=Nature |year=2005 |volume=437 |issue=22 Sep. |pages= 512–518}}

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