Folding@home Diseases Studied FAQ

Table of Contents


The Folding@home project (FAH) is dedicated to understanding protein folding, the diseases that result from protein misfolding and aggregation, and novel computational ways to develop new drugs in general. Here, we briefly describe our goals, what we are doing, and some highlights so far.

We feel strongly that a Distributed Computing project must not just run calculations on millions of PC's, but DC projects must produce results, especially in the form of peer reviewed publications, public lectures, and other ways to disseminate the results from FAH to the greater scientific community. Below, we also detail our progress in these areas as well.

What is protein folding and how is it related to disease?

Proteins are necklaces of amino acids, long chain molecules.

Proteins are the basis of how biology gets things done. As enzymes, they are the driving force behind all of the biochemical reactions that make biology work. As structural elements, they are the main constituent of our bones, muscles, hair, skin and blood vessels. As antibodies, they recognize invading elements and allow the immune system to get rid of the unwanted invaders. For these reasons, scientists have sequenced the human genome -- the blueprint for all of the proteins in biology -- but how can we understand what these proteins do and how they work?

However, only knowing this sequence tells us little about what the protein does and how it does it. In order to carry out their function (e.g. as enzymes or antibodies), they must take on a particular shape, also known as a "fold." Thus, proteins are truly amazing machines: before they do their work, they assemble themselves! This self-assembly is called "folding."

What happens if proteins don't fold correctly?

Diseases such as Alzheimer's disease, Huntington's disease, cystic fibrosis, BSE (Mad Cow disease), an inherited form of emphysema, and even many cancers are believed to result from protein misfolding. When proteins misfold, they can clump together ("aggregate"). These clumps can often gather in the brain, where they are believed to cause the symptoms of Mad Cow or Alzheimer's disease.

Which diseases or biomedical problems are you currently studying?

Alzheimer's Disease (AD)

AD is caused by the aggregation of relatively small (42 amino acid) proteins, called Abeta peptides. These proteins form aggregates which even in small clumps appear to be toxic to neurons and cause neuronal cell death involved in Alzheimer's Disease and the horrible neurodegenerative consequences.

We have many calculations being performed on AD. Our primary goals are the prediction of AD aggregate structure for rational drug design approaches as well as further insight into how AD aggregates form kinetically (hopefully paving the way for a method to stop the AD aggregate formation).

There have been many projects, including 500 series and 700 series. So far, all of them are either Tinker WUs or normal (not bigWU) Gromacs WUs.

July 2005: We are currently in the process of submitting our first paper on FAH results.

October 2005: FAH researchers Vishal Vaidyanathan and Nick Kelley present the recent FAH results on AD at BCATS 2005. Their work won the best talk award in 2005.

November 2005: Prof. Vijay Pande presented recent FAH work on AD at the National Parkinson's Foundation conference (in the session on AD and its connections to PD).

July 2006: Our first paper on AD is ready to submit. We hope to start publicly talking about these results very soon.

September 2006: We have submitted our first paper for peer review and we're working on the next 2 paper right now. We're very excited about the results!

April 2007: We have made some significant progress experimentally testing our computational predictions using NMR.

November 2007: We are writing up our NMR results with a hope to send the paper off to peer review soon.

Huntington's Disease (HD)

HD is caused by the aggregation of a different type of proteins. Some proteins have a repeat of a single amino acid (glutamine, often abbreviated as "Q"). These poly-Q repeats, if long enough, form aggregates which cause HD. We are studying the structure of poly-Q aggregates as well as predicting the pathway by which they form. Similar to AD, these HD studies, if successful, would be useful for rational drug design approaches as well as further insight into how HD aggregates form kinetically (hopefully paving the way for a method to stop the HD aggregate formation).

July 2005: We are currently in the process of submitting our first paper on FAH results.

September 2007: Nick has been working on a new collaboration with Judith Frydman's group to computationally test a new hypothesis for HD aggregation found in the Frydman lab.

November 2007: Nick has been wrapping up the next stage of our first HD paper.

Cancer and P53

Half of all known cancers involve some mutation in p53, the so-called guardian of the cell. P53 is a tumor suppressor which signals for cell death if their DNA gets damaged. If these cells didn't die, their damaged DNA would lead to the strange and unusual growths found in cancer tumors and this growth would continue unchecked, until death. When p53 breaks down and does not fold correctly (or even perhaps if it doesn't fold quickly enough), then DNA damage goes unchecked and one can get cancer. We have been studying specific domains of p53 in order to predict mutations relevant in cancer and to study known cancer related mutants.

January 2005: Our first work on cancer has recently been published.

February 2005: We are expanding FAH's p53 work to other related p53 systems

July 2005: We are getting some interesting results from recent new FAH p53 projects.

October 2005: Two new sets of projects have completed and two new papers are being readied for peer-reviewed publication.

November 2005: FAH researcher Dr. Lillian Chong presented her work on p53 at a lecture at the University of Pittsburgh.

December 2005: FAH researcher Dr. Lillian Chong presented her work on p53 at a lecture at Duke University.

Osteogensis imperfecta

In collaboration with other groups at Stanford (especially Dr. Teri Klein's group at Stanford University Medical Center), we are looking at Collagen folding and misfolding. Collagen is the most common protein in the body and mutations in collagen leads to a very nasty disease called Osteogenesis Imperfecta (or OI for short). In many cases, OI is lethal and leads to miscarriage. However, 1 in 10,000 people have some sort of mutational in collagen. For many, where the mutation is not very serious, it lies unknown and misdiagnosed and leads to brittle bones and other more subtle problems. In others, however, mutations lead to more serious morphological disorders (as shown on the right).

We are starting to model collagen folding and misfolding in the 1000 series projects. Follow the link for more information.

June 2005: FAH's first work on collagen has been accepted for publication

January 2006: FAH researcher Dr. Sangyhun Park presents his work on collagen at a lecture at Duke University

September 2007: Our paper on collagen folding has been accepted for publication.

December 2007: Our paper on collagen folding should be coming out for publication.

Parkinson's Disease (PD)

We have also performed preliminary studies on a key protein implicated in Parkinson's disease. Alpha-synuclein is a natively unfolded protein and its folding/misfolding (see figure on the right for misfolded aggregates) appears to be critically linked to PD. We are evaluating the application of various FAH methods to this problem.

July 2005: We have only done a pilot study on PD and are looking for funding to continue our work in this area.

November 2005: Prof. Vijay Pande presented recent FAH work on AD at the National Parkinson's Foundation conference (in the session on AD and its connections to PD).


The Ribosome is an amazing molecular machine and plays a critical role in biology, as it is the machine that synthesizes proteins. Because of this critical role, and some small but fundamental differences in the ribosomes of mammals and bacteria, the ribosome is the target for about half of all known antibiotics. These antibiotics typically work by preventing bacterial ribosomes from making new proteins, thus killing them. We have several projects on going to study the ribosome. Since the ribosome is so huge, these WUs are big WUs and have required us to push the state of the art of FAH calculations. However, with these new bigWUs, FAH is set up to study more and more complex problems, and if successful, with greater and greater biomedical impact.

July 2005: We are working on our first paper resulting from FAH's ribosome simulations.

July 2005: Prof. Pande presents ribosome results at a protein folding conference at U Penn.

October 2005: Prof. Pande presents ribosome results at a lecture at University of California at San Francisco (UCSF) Medical School.

December 2005: Prof. Pande presents ribosome results at a lecture at Rice University.

April 2005: Prof. Pande presents ribosome result at the NIH Roadmap center on Nanomedicine.

June 2006: We are just about to submit our first paper on the ribosome.

December 2006: Our first work units for antibiotic drug design calculations are now running on Folding@home.

April 2007: We have received a grant from Stanford University to design and study novel antibiotics. This grant is joint with the labs of Chaitan Khosla at Stanford's Chemistry Department (who does small molecule synthesis, design, and some characterization) and Jody Puglisi at the Stanford Medical School (who studies the ribosome and antibiotics experimentally)

How are these advances possible?

In order to make breakthroughs using distributed computing, new methods are critical. Distributed computing is an unusual way to perform large-scale calculations. While it gives computer resources much greater than a typical supercomputer (e.g. the almost 200,000 actively processing CPUs in FAH vs. 5,000 in a typical supercomputer), these processors are connected by the Internet, not the high speed, low latency interconnects found in supercomputers. Thus, we must develop new methods to use FAH's unusual computational paradigm and capabilities. Moreover, these methods must be tested.

Much of our work in the first years of FAH has been to develop and test these methods on model systems: small proteins that can be easily studied experimentally. With these experimental comparisons, we can test and validate our methods, as well as find out their limitations (which is critical for improving our methods).

To date, FAH has been very successful, with over 40 published works (as of July 2006) directly stemming from FAH calculations. We will continue to work on all fronts: new scientific cores, new server side algorithms, new models for proteins, and new questions related to testing our methods and applications to disease and other biomedical questions.

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Last Updated on April 19, 2009, at 01:11 PM