General

Please only run Folding@home on machines you either own or on which you have the permission of the owner to run our software. If there is any doubt (eg you want to run on computers at work), we suggest you get written approval (eg get your superior to sign a letter giving authorization); we have found that written documentation of this sort is important if there is ever any dispute of whether permission was indeed granted. Please do not assume that permission is granted by the owner. Any other use of Folding@home violates our end user license agreement (EULA), and just isn’t a good idea in general.

All computers can contribute to Folding@home. However, if the computer is too slow (e.g. wasn’t built in the last 5 years or so), the computer might not be fast enough to make the deadlines of typical work units. A Pentium 4 or newer equivalent computer (with SSE) is able to complete work units before they expire.

Folding part time (less than 24 hours a day) will increase the minimum system requirements to make the deadlines.  In this case, it is up to the donor to determine how many hours a day are required to fold and still meet the deadlines with each computer.

We will attempt to contact the donor if there is some suspicion of a EULA violation. Many donors use their email as their donor name and this is helpful. If do not have any information on hand and we have been presented with a sufficiently strong case that there was a EULA violation, we will zero the points of the donor and not allow clients to run under the name of that donor. This decision can be reversed if there is sufficient information to exonerate the donor. The donor should contact one of the Pande Group members or Forum Moderators at our forum to get in touch with us in such a situation.

We’ve simulated a wide variety of proteins and other molecules. We divide the simulations into packets called “Work Units,” (WUs) each of which is sent to a computer for processing. We then assemble all the WUs from a project into a completed simulation. We keep many types of statistics of users and work accomplished in our Stats section. You can check your Individual stats, Team stats, and overall Project stats. Please also review the Results and Awards sections.

We have been able to fold several proteins into the 1.5 millisecond time range with experimental validation of our folding kinetics. This is a timescale a thousand times longer than any previous atomic-level simulation, and represents a fundamental advance over previous work. We are now simulating important proteins used in structural biology studies of folding as well as proteins involved in disease. We’ve been able to perform detailed simulations of many of these proteins at biologically-relevant timescales, giving us insights that had previously been unobtainable. We’ve also identified several potential drug candidates which may be able to fight Alzheimer’s, cancer, and infection by viruses. Peer-reviewed scientific papers detailing our results are posted on our Results page, and many of them are published in top journals such as Science, Nature, PNAS, and JMB. These publications are highly detailed and often technical, but summaries of their findings can be found on Results page as well as the Folding@home article on Wikipedia.

Distributed Computing is a method of computer processing in which different parts of a program, or different portions of data, are processing simultaneously on two or more computers. We are able to use this approach to significantly accelerate our research. Folding@home is one of the largest, most powerful, and most widely distributed computing networks.

Folding@home is a distributed computing project, that very simply stated, studies protein folding and misfolding. Protein folding is explained in more detail in the scientific background section. It also helps us develop drugs to combat disease.

Folding@home is run by an academic institution (specifically the Pande Group, at Stanford University’s Chemistry Department), which is a nonprofit institution dedicated to science research and education. We will not sell the data or make any money from it. Moreover, we will make the data available for others to use. In particular, the results from Folding@home will be made available on several levels. Most importantly, analysis of the simulations will be submitted to scientific journals for publication, and these journal articles will be posted on the web page after publication.

Following the publications of these scientific articles, we will make the raw data of the folding runs available to other researchers upon request. The data sets from some of our most prominent simulations are already publicly available. We’ve also striven to share our key technologies with other scientists, to assist their research as well.

Most of the critical parts of FAH are publicly available. The Tinker and Gromacs source codes can be downloaded and run. Unlike many computer projects, the paramount concern is not functionality, but the scientific integrity, and posting the source code in a way that would allow people to reverse engineer the code to produce bogus scientific results would make the whole project pointless. However, we stress that the vast majority of our code is already open source. We have an Open Source FAQ with more details.

Modern supercomputers are essentially clusters of hundreds of processors linked by fast networking. The speed of these processors is comparable to (and often slower than) those found in PCs! Supercomputers are not only very expensive to operate, but they are often simultaneously shared by many different research groups, and it is a challenge to scale a molecular simulation to all of their processors. Protein folding dynamics is statistical in nature, so a single long simulation from a supercomputer would not be sufficient to fully understand the folding process. Folding@home is one of the most powerful computing systems on the planet, and we use novel methods to utilize its network to statistically analyse the dynamics of protein folding. Hence, the calculations performed on Folding@home would not be possible by any other means! This is possible since PC processors are now very fast and there are hundreds of millions of PCs sitting idle in the world.