Stats system update includes a new feature: monthly leaderboards

In our regular updating of FAH systems, we’ve done a recent update of the stats website internals to help speed them up and bring them to new infrastructure that should be more reliable.  Along the way, lead FAH Programmer Joseph Coffland added a suggestion from FAH Marketing Relations lead Anton Thynell to include a new sort of competition: a monthly leaderboard.

This monthly leaderboard will naturally give the top donor and top team for each month and we will collect the top leaders for each month for recognition over the year.  Our intent was to give new donors a way to more directly see their contribution immediately and to in general encourage more friendly competition that helps us push forward our science even faster.

The updated page is found here:

Retiring Core15, OpenMM 7.0 on its way to FAH

OpenMM is our main GPU code, fully open sourced, that drives FAH.  OpenMM has its roots in the original FAH GPU code, the first GPU code for molecular dynamics.  Core15 represents that very long history and it’s time for us to move on and retire that Core as its code is old and outdated.  Unfortunately, that means that some older GPUs (that are not supported by OpenMM) will no longer be supported by FAH.

OpenMM 7.0 has just been released and represents several key advances in speed and science.  We’re working to bring this into a new FAH core shortly to continue pushing the envelope of what FAH can do.  Look for that core in more extensive testing shortly.

New paper on MDM2: lid region dynamics and computational docking

The so-called “guardian of the genome”, p53 is a tumor suppression protein involved in regulating cell repair and apoptosis.  Many cancer cells are able to proliferate because they have mutations to p53, making it the focus of intense interest for cancer researchers.

In the cell, levels of p53 are usually kept low through the action of another protein, MDM2, which binds to the transactivation domain (TAD) of p53 and recruits it for degradation.  Upon binding, the p53 TAD folds into a helix and packs into a binding cleft of MDM2.   Over the last ten years, there have been many efforts to develop cancer-fighting molecules that can mimic the p53 helix and competitively bind MDM2, resulting in the up-regulation of p53.

MDM2 is interesting for another reason:  NMR experiments show that in the absence of p53, the disordered N-terminal region becomes partially structured and associates with the cleft.   This so-called “lid region” can be seen making key interactions with MDM2 ligands in co-crystal structures, which suggest that the ability to predict likely lid conformations might be very important to rational drug design.

mdm2-lidIn a new paper in Scientific Reports, researchers from the Voelz lab have applied the power of distributed computing through Folding@home to study the conformational dynamics of the MDM2 lid region, to discover just how important modeling the lid region may be.  Markov State Models (MSMs) built from simulated trajectories of the lid region show that the lid associates with the binding cleft in a two-state manner consistent with experiment, and furthermore that this motion is coupled to the opening up of the binding cleft.   Since the published NMR structure of MDM2 has a closed cleft, the researchers then went on to see if known ligands could be successfully docked into the simulated MDM2 receptor structures.  Remarkably, this procedure was highly successful, comparable to the “gold standard” of cross-docking ligands across a set of high-resolution co-crystal structures.

These results have important implications.  For one, they suggest that large-scale simulations can help refine “bad” receptor structures for the purpose drug design.  This might be particularly important for homology models of protein structures, for which computational docking often fails.  The results also suggest that modeling disordered regions in proteins might be more important that previously thought.


Mukherjee, S., Pantelopulos, G. A., & Voelz, V. A. (2016). Markov models of the apo-MDM2 lid region reveal diffuse yet two-state binding dynamics and receptor poses for computational docking. Scientific Reports, 1–10. doi:10.1038/srep31631



Heads up: Scheduled Maintenance is Over

The stats system has now returned to normal operation. Sorry for the delay and any inconvenience this outage may have caused.

Heads up: Scheduled Maintenance

A handful of Stanford-hosted FAH servers—including a stats server— will be undergoing scheduled maintenance starting today until Thursday. Assignments and points should not be affected; however, points may not be correctly reported on the website until after maintenance is completed.

fah-web down, rebuild in motion

Our main web server for stats ( went down over the weekend due to a double failure.  Our sysadmins are working on this today and expect it to be up later this evening.  In the process and due to previous issues, we have also made plans to upgrade the hardware on this machine.

New FAH software client: V7.4.15 in open beta testing

I am happy to announce we have a new client ready for beta testing. This client makes some important improvements over the v7.4.4 release. In addition to a number of bug fixes, this release adds better support for matching the number of CPUs available on a system to the number of CPUs projects can actually handle. This will get some Folding@home clients, which are currently not getting work, folding again.

We also have added our first 64-bit release for Windows. Due to the number of Windows clients, we have prioritized the Windows beta test, but the OSX release should be available for testing soon. Finally, we have made improvements to GPU detection but more works remains. We hope to solve the current problems with multi-GPU detection during this open-beta test.

Our internal testing team has worked extensively testing this new release. We believe it is in good shape but it is essential that we test the code on a broader variety of machines. If you do run in to problems with this beta software please post a message at with your OS version, the client package you installed, what you expected to happen and what actually happened. Posting log files is also very helpful.

As always, we greatly appreciate the efforts of those who help us test our software. Correctly functioning and efficient software is a huge part of making Folding@home successful and ultimately finding cures for diseases. We look forward to hearing from you in the forums!

More details can be found in the forum: FAHClient V7.4.15 (Open-Beta)

Out with the old psummary, reminder of the new

Our projects page is a key way for donors to see the most up to date information about what is running on Folding@home.

About a year and a half ago we updated our project summary page.  We posted about it here: As promised in that post, we are now deprecating the old psummary.  For most people this change will be transparent.  However, if any 3rd party tools are still using the old psummary they will have to update their code.

The new psummary can now be found in the following places:    and

You can also access this data in JSON format:

Where can I see more detail about what’s going on in FAH?

For those new to FAH, here’s a reminder for where the nitty gritty details can be found if people are interested to learn more than what’s on our web site.

In terms of new projects and more detailed (less high level) announcements, they’re here on the FCF:

For code updates, our science code development is done in the open on github, open source: and our other mature projects are on github.

For updates on Pande Group papers, here’s a good link that’s automatically kept up to date: .  And for a sense of the most important works, this one is useful:

As you can see from those links, there’s a ton of activity going on behind the scenes.  Feel free to drop by the FCF or follow us on Github if you’re curious to learn more.

Closing in on 100 Petaflops

It’s been a while since we updated the FLOP per GPU report (since Tue, 26 Feb 2013 in fact).  A lot of progress has been made in 3+ years in GPU-land.  Over the last 3 years, FAH has seen a few trends, especially consolidation into people to GPUs and the increase in power from those GPUs.  The upshot is that today, FAH is running off the power of about 40,000 GPUs.  While that’s not a ton of donors, due to the power of GPUs, this is an immense amount of compute power.  In terms of FLOPs, we’re getting close to 100 Petaflops, which would be a major milestone in computing.  In terms of our ability to tackle complex systems, we’re simulating considerably bigger, more complex systems for longer timescales than ever before, which perhaps is the most important part of this beyond just the numbers.

Thanks to everyone who has helped make this possible.  And we’ll do a better job of more frequent updating of this page so these big jumps don’t catch people by surprise.

Add your computer's power to over 327,000 others that are helping us find cures to Alzheimer's, Huntington's, Parkinson's and many cancers ...

... in just 5 minutes.

Step 1.

Download protein folding simulation software called



Step 2.

Run the installation. The software will automatically start up and open a web browser with your control panel.

Step 3.

Follow the instructions to Start Folding.

Stanford University

will send your computer a folding problem to solve. When your first job is completed, your computer will swap the results for a new job.

Download the protein folding simulation software that fits your machine.


Installation guide
Or download Folding@home for your Android (4.4+) phone.