Issues with FahCore21

We’ve discovered that the new FahCore_21 is producing more errors than we consider acceptable for some clients.  The error rate seems to depend on several factors but most noticeable is that it doesn’t work well with second generation Maxwell GPUs.  A few projects have made their way through Advanced testing have been distributed to everyone under the default “FAH” client-type setting.  To allow donors to limit this exposure, those projects have been reclassified as “Advanced” which is appropriate for a FahCore that is still under development.

As has always been the case, the “Advanced” setting will give you access to newer projects which may have a higher error rate.  It is our intention to provide only the safest assignments with the default setting or you can choose to configure your system to run these advanced projects depending on how frequently you encounter these errors.

These conditions are expected to improve as new projects, new versions of that FahCore, or new versions of the drivers incorporate whatever fixes are required.  In the meantime, Work Units which are completed successfully allow scientific research to progress toward even more challenging projects than we’ve done so far.

mTOR: Projects 10491-10499

In projects 10491-10499, the Chodera lab takes a look at mTOR, a serine/threonine kinase. The MTOR gene was originally discovered in yeast in 1991 and named TOR1/2 because it was the target of rapamycin, an anti-fungal small molecule isolated from the soil of Easter Island in the 1970s. In 1994, the mammalian target of rapamycin (mTOR) was discovered by Drs. Sabatini, Snyder, Abraham, and Schreiber.

mtorpicmTOR integrates multiple signal inputs to control processes such as cell growth and metabolism, among others. Due to its role in controlling a number of cellular processes, mTOR has clinical significance in neurodegenerative diseases, diabetes and cancer. In the Chodera lab, we are working with the Hsieh lab at MSKCC to understand mTOR’s role in cancer and the development of new and better therapeutics that target it.

Currently, the FDA has approved treatment for metastatic clear cell Renal Cell Carcinoma (ccRCC) that includes mTOR inhibitors such as Everolimus and Temsirolimus. An effort to understand the patient-to-patient variation in response to these drugs by studying how extraordinary responders lead to the characterization of mTOR activating missense mutations in these patients. These mutants cluster in two domains of mTOR: the kinase and FAT domains. These projects will allow us to generate a model of the conformations available to mTOR and ultimately to investigate how these clinically relevant mutations might influence the protein’s structure.

Both the mTOR kinase domain and the larger construct including the FAT domain are very large systems, exploiting the latest OpenMM GPU core (0×21) and push the capabilities of latest-generation GPUs to their full extent.


Happy 15th Birthday, Folding@home!

I’m happy to announce that October 1, 2015 is Folding@home’s 15th birthday.  It’s amazing for me to look back at all we’ve done together, all we’ve built, and all that’s come out of it.  From CPUs to GPUs to PS3 to NaCl to Mobile.  And today we’re in the midst of an update of the FAH web site, rollout of new mobile and other (yet unannounced) clients, as well as new projects in cancer and Alzheimer’s.

And we look forward to celebrating the changes to come over the next 15 years!

A global view of FAH Mobile Client usage

People around the world are continuing to help advance research by downloading and running Folding@home mobile.

Here is an image of the global usage distribution of our Mobile Client created by Pande group member Muneeb Sultan. This shows all current connections from mobile phones to our Workserver here at Stanford University during a given time period.


Simulating protein dynamics to find binding-competent states

Mutation to the tumor-suppressor protein p53 is a common feature in most cancers. MDM2–a protein whose job it is to downregulate p53 via their direct binding interaction–has therefore become a prime target for cancer therapeutics. Normally, a small helical region of p53 binds the MDM2 receptor site, but if a molecule with a similar shape can bind the receptor site of MDM2 strongly enough, it can prevent p53 from binding, thus making more p53 available to perform its tumor suppression abilities.

Many different kinds of molecular mimics of the p53 helix have been designed to disrupt the p53-MDM2 interaction, including stapled peptides, cyclic hairpin peptides, beta-peptides, peptoids (N-substituted oligoglycines), oligoarylamides, and spiroligomers, just to name a few. These molecules are much larger than typical small-molecule drugs, and have interesting folding properties that must be overcome to achieve tight binding. Stapled peptides, for instance, feature a hydrocarbon “staple” that helps rigidify the helical conformation in solution, which in turn enhances the binding affinity.

Using molecular simulations on Folding@home, we have been studying the coupled folding and binding of the p53 helix to MDM2 to address several key questions. One goal is to understand the roles the conformational dynamics in shaping the binding mechanism – such information can ultimately help to design better-binding molecular mimics.

Another question is whether or not molecular dynamics simulations can be used to discover binding-competent receptor conformations of MDM2 in the absence of a bound crystal structure. In new work from our lab (Pantelopulos et al. Proteins 2015), we show that ligand-free simulations of MDM2 starting from conformations with a closed binding cleft can sample open-cleft conformations capable of binding. We also tested the performance of several recent force field models in predicting experimental NMR measurements. We found that that all of the force fields perform similarly well, but that longer simulations (out to a microsecond) result in better agreement with experiment.

You can read about our work in the latest issue of Proteins:

Microsecond simulations of MDM2 and its complex with p53 yield insight into force field accuracy and conformational dynamics George A. Pantelopulos and Vincent A. Voelz. Proteins: Structure, Function and Bioinformatics, Accepted (2015)

First full version of our Folding@Home client for Android Mobile phones

We’re proud to announce the first full version of our Folding@Home client for Android Mobile phones.  This version is available to all Android Mobile phones with version 4.4 (Kitkat) and above.  Thanks to suggestions by donors we have redesigned the user interface and added new features such as:

  • contribute processing time continuously: just connect to a WiFi network and a charger.
  • one can login to Google Game Services, earn collaboration achievements, compete against his / her friends in processing time.
  • collaborate processing time from multiple devices under the same Google Game Services account.
  • settings screen has been removed. No need to configure anything!
  • details about the currently selected research type can be queried by touching the Research Type title on main screen, or by choosing “Active Research” on menu.

Scientifically, as in our previous beta run, we continue to focus on breast cancer with our mobile app. In this project, we’re investigating the nature of drug resistance mutations in key proteins (kinases) that are targets for breast cancer drugs. By studying the nature of how these mutations change these key drug targets, we will be able to both advance our basic biophysical understanding of these key proteins as well as build a tool to be used for patient specific breast cancer treatment— by sequencing the tumor and seeing what mutations are present, our tool seeks to recommend the best drug for a specific patient.

The beta has been a success with positive feedback from our community. We plan to add additional features in the comming months to further enhance the user interface and experience. The beta version has been downloaded more than 170,000 times worldwide, with more than 62,000 mobile phones contributing at the same time. We want to thank our community for your feedback and continued support.

We’ve also added a new movie to advertise and highlight the app.  It’s on YouTube here:

Problem with NaCl Client

We see that there is an issue with our NaCl Client (at, with donors seeing this error:

Warning: Unexpected response to AS assignment request: error,DB ERROR: IO error: log.leveldb/016519.ldb: Too many open files

The server is being overloaded and our sysadmin team will take a look at it when they get back on Monday.  Long term, it looks like it’s time for us to upgrade the server this is running on since it’s getting overloaded.  We have been moving to get new servers ready for this and so getting to that should happen in about a week (servers are here and the sysadmin team has been working to getting them ready for their new roles in FAH).

New Core tech update: OpenMM (GPU) and Gromacs (CPU)

We’ve been pushing hard to improve the performance of OpenMM, especially in OpenCL as it’s now used in Folding@home.  We’ve got some great news hot off of the presses.  These are the benchmarks described at  They’re using the very latest OpenMM code, what will be in OpenMM 6.3.  They’re using CUDA 6.5 and running on Titan X.  All numbers are in ns/day.

Benchmark Calculation    CUDA   OpenCL
Implicit, 2 fs 471 366
Implicit, 5 fs 684 589
Explicit-RF, 2 fs 305 265
Explicit-RF, 5 fs 508 460
Explicit-PME, 2 fs 161 164
Explicit-PME, 5 fs 318 354


We’re especially pleased with those OpenCL PME numbers.  OpenMM Lead Developer Peter Eastman has put a lot of work into that for this release, and it now is actually faster than CUDA (For the Titan X).  Curiously, that is not the case on GTX 980.  It’s still slower than CUDA there, although it comes a lot closer than it used to.

This will be spun into an updated Folding@home core.  The upshot for GPU donors is that PPD for that new core should increase, due to the expanded capabilities of the new code.

It’s important to stress that SMP/CPU donors aren’t left out of new performance (and therefore PPD) updates either: FAH Lead Developer Joseph Coffland has been working hard on a new Gromacs core and that should also see performance benefits, as we roll out AVX support for FAH.

Introducing Shukla Group@Illinois

Shukla group ( at University of Illinois at Urbana-Champaign has just configured new Folding@home servers (ds01[a-d], which would help us carry out exciting computational experiments in collaboration with the vibrant F@H community.

Before joining Illinois in January 2015, I was a post-doctoral fellow in Pande Lab, working on conformational change mechanism of proteins related to a variety of diseases including cancer, neurodegenerative & cardiovascular disorders. Some of the key results obtained using Folding@home resources on conformational change mechanisms of G-Protein Coupled Receptors and Kinases are highlighted in previous blog posts.

The mission of my group is to combine theory, computation, and experiments to develop quantitative models of biological phenomena relevant for health, energy and environmental challenges. These grand challenges would not only require new scientific methodologies and insights but also development of platforms that enable broader participation of the community of informed citizens in the pursuit of the solutions. Folding@home is one such unique platform that enables engagement with volunteers and donors to help us solve challenging scientific problems. Our group is excited to be a part of the Folding@home team and we look forward to working with all of you on projects related to key challenges in human health. Specific project details will be posted soon on folding forum and F@H blog.

Shukla Group

Multi-core CPU jobs

We’ve been getting reports that FAH is low on CPU jobs.  We’re in the process of adding more multi-core jobs to existing projects.

Also, currently lead developer Joseph Coffland’s main project is to get a new Gromacs CPU core out to enable some new science on CPU cores (that’s currently only easily doable on GPU cores).  We expect a rough ETA for the first testing of that new core to be in a few weeks.

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.