Folding@home

FAH logo mosaic

We wanted to find a way to express in a single picture the immense collective effort that FAH donors and FAH teams comprise.  We had several ideas internally and this is one of my favorite: we made a photo mosaic of the FAHicon out of team logos.  We also have a link to a high res version.

Peptoids

GUEST POST:  Prof. Vincent Voelz, Temple University

One of the projects we're excited about in the Voelz Lab is molecular simulation of synthetic polymers called peptoids. These are biomimetic molecules that can fold like proteins, but they have different structural properties. Several peptoids have been identified that can fold into unique three-dimensional structures, but better computational modeling is needed to identify the driving forces for folding and predict stable peptoid structures. If we can develop tools to do this, peptoids have the potential to be an amazing platform to design functionalized nanostructures that can be used for all kinds of applications, from biotherapeutics to nanomaterials.

So far, we have shown that modern forcefields can accurately fold peptoids (DOI: http://dx.doi.org/10.1002/bip.21575) and are working with experimental collaborators on blind predictions of peptoid structure (stay tuned for more results here soon). This summer, we hope to be using Folding@home to commence large-scale simulations of peptoid folding for many peptoid sequences, in order to better understand peptoid folding mechanisms and design principles. We look forward to working closely with Folding@Home donors and testers on moving these projects forward -- you will no doubt see us on the forums frequently!

One of the projects we're excited about in the  <a href="http://voelzlab.org/">Voelz Lab</a> is molecular simulation of synthetic polymers called <a href="http://en.wikipedia.org/wiki/Peptoid">peptoids</a>.  These are biomimetic molecules that can fold like proteins, but they have different structural properties.  Several peptoids have been identified that can fold into unique three-dimensional structures, but better computational modeling is needed to identify the driving forces for folding and predict stable peptoid structures.  If we can develop tools to do this, peptoids have the potential to be an amazing platform to design functionalized nanostructures that can be used for all kinds of applications, from biotherapeutics to nanomaterials.

 

So far, we have shown that modern forcefields can accurately fold peptoids (DOI: http://dx.doi.org/10.1002/bip.21575) and are working with experimental collaborators on blind predictions of peptoid structure (stay tuned for more results here soon).  This summer, we hope to be using Folding@Home to commence large-scale simulations of peptoid folding for many peptoid sequences, in order to better understand peptoid folding mechanisms and design principles.  We look forward to working closely with Folding@Home donors and testers on moving these projects forward -- you will no doubt see us on the forums frequently!

Brief network outage – stats update down for 2 hours

We will have a brief network outage in one of our server rooms today at 7pm PDT.  This will not affect Folding@home other than to delay the normal hourly stats update.  Once the outage is over, we will restart the update and the stats will be inserted into the db.  So, this won't affect donor stats, other than to briefly delay our hourly update this morning.

Introducing the Voelz lab at Temple, a new member of the FAH Consortium

GUEST POST:  Prof. Vincent Voelz, Temple University

The Voelz Lab just started this past August in the Department of Chemistry at Temple University in Philadelphia, PA. We have just installed two Folding@home servers, and are gearing up to run simulations this summer (which I hope to talk about in future blog posts). In the meantime we have been very lucky to work with the Institute for Computational Molecular Science here at Temple, and a new high-peformance computing cluster to generate some initial data.

One of our interests is using molecular simulation to do computational design of folding and binding properties. Design efforts require looking at folding for lots of different possible protein sequences, which is a natural task for a distributed computing platform like Folding@home. We're working on ways to leverage Markov State Models of conformational dynamics to do efficient estimation of the effects of sequence perturbations. A good starting point to test these ideas are to look at proteins for which many sequences have been characterized, to see if we can predict sequence-dependent changes. Many of these sequence mutations are important in human diseases, so we hope to gain insight into these process as well.

Understanding the folding of hIAPP, the peptide linked to the Type 2 diabetes

Here's an update from Prof. Xuhui Huang's lab at Hong Kong University of Science and Technology, another collaborating labortory in the Folding@home consortium.

In addition to the molecular recognition processes, another project his lab is working on at the Folding@home platform is to explore the folding free energy landscape of the human islet amyloid polypeptide (hIAPP).  hIAPP (also called amylin) is a 37-residue peptide and its aggregation reduces working β-cells in patients with Type 2 diabetes.  As an intrinsically disordered protein, hIAPP monomer does not have a folded global minimum in its folding free energy landscape, but contains many stable local minimums.  Thus understanding the nature of these locally metastable states can help us to understand the mechanisms of the hIAPP aggregation, and further design small molecules to inhibit the amyloid formation.  

Just as we have seen in the Pande lab simulations of the Aß peptide in Alzheimer's run on Folding@home previously, this research may offer potential therapeutic agents for Type 2 diabetes.  At Folding@home, we are currently running extensive molecular dynamics (MD) simulations and construct Markov State Model to elucidate the free energy landscape of the hIAPP monomer.  Projects 2974 and 2975 are related to the above project. We would like to thank all the Folding@home donors for your help to make our research possible.

 

Email updates

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Support for new GPUs (such as Kepler) in the v7 FAH client

In the past, support for specific GPUs was built into the client.  We are working on ways to automatically update this information more easily within the v7 client to support new GPUs, such as the Kepler GPUs which have just came out.  While the automatic update isn't ready yet, here is how one can manually do this:

1) Download the GPUs.txt file from https://fah-web.stanford.edu/file-releases/public/GPUs.txt

2) Copy the downloaded GPUs.txt file to the client's run directory.  The run directory is also called the data directory. In Windows there is a link to this directory in the start menu.

3) After installing the file you must restart your client.

The client has a built-in GPUs.txt which it will use if it does not find one on disk.  The client will print a message to the log, very early on, when it reads GPUs.txt from the run directory.

In a future version of the v7 client, this will happen automatically, but for now, we are updating this file on our web site and donors can do this update manually for new hardware.

Receptor Binding by the Influenza Virus

The Kasson group has recently published an article in the journal Biochemistry on how influenza binds cell-surface receptors.  In this article, we discuss how computational techniques can be used for further analysis of structural and biochemical data on glycan binding by influenza.  We review prior work that we have done in collaboration with the Pande group, including research using Folding@home.  Those earlier papers can be found here and here.

The table-of-contents graphic from our recent paper illustrates the binding dynamics the glycan (sugar) residues on the surface of the influenza hemagglutinin protein.  20 structures of the glycan molecules are superimposed on the receptor-binding pocket of hemagglutinin.

Web page revamp and v7 rollout

We're installing a new web page for our main site http://folding.stanford.edu.  While we're not done quite yet, the main changes are in.  Hopefully the new site is cleaner and simpler, both in aesthetics and in ability to navigate.  

This also coincides with our official rollout of the version 7 (v7) client software for Folding@home.  This new client is a complete rewrite with the intention to make it much easier for donors to contribute to Folding@home.  In particular, the new client unifies the classic, SMP, and GPU clients into a single download.  Also, installation (especially of the more high performance clients such as SMP and GPU) is much easier than before.  Finally, the revamped viewer should also be a much better user experience for FAH donors.  

All in all, our hope is that these combined changes make it much easier for people to understand what we're about and to help contribute to Folding@home.

 

FAH simulations lead to a new therapeutic strategy for Alzheimer's Disease

I'm very excited to finally talk about some key new results from our lab.  These results have been a long time in coming and in many ways represents a major achievement for Folding@home (FAH) in general, demonstrating that the approach we started 10 years ago can make significant steps forward in our long term goals.

Specifically, our long term goals have been to 1) develop new methods to tackle the computational challenges of simulating protein folding; 2) apply these methods to gain new insights into protein folding; 3) use these methods and new insights to simulate Aß protein misfolding, a key process in the toxicity of Alzheimer's Disease (AD); and finally 4) to use those simulations to develop new small molecule drug candidates for AD. In the early years of FAH, we concentrated on the first two goals above.  In the last 5-7 years, we have worked to accomplish the third goal.  I'm now very excited to report our progress on the last goal –– using FAH for the development of new therapeutic strategies for AD.

In a paper just published in the Journal of Medicinal Chemistry, we report on tests of predictions from earlier Folding@home simulations, and how these predictions have led to a new strategy to fight Alzheimer's Disease.  While this is not a cure, it is a major step towards our final goal, some light at the end of the tunnel.

The next steps, now underway in our lab, are to take this lead compound and help push it towards a viable drug.  It's too early to report on our preliminary results there (I like to only talk publicly about work after it's passed through peer review), I'm very excited that the directions set out in this paper do appear to be bearing fruit in terms of a viable drug (not just a drug candidate).  I hope I'll have more to say in the coming months!

 

Design of β-Amyloid Aggregation Inhibitors from a Predicted Structural Motif

Paul A. Novick†, Dahabada H. Lopes‡, Kim M. Branson†, Alexandra Esteras-Chopo§, Isabella A. Graef§, Gal Bitan‡, and Vijay S. Pande†*

† Department of Chemistry, Stanford University, Stanford, California 94305, United States

‡ Department of Neurology, UCLA, Los Angeles, California 90095, United States; Brain Research Institute, UCLA, Los Angeles, California 90095, United States; Molecular Biology Institute, UCLA, Los Angeles, California 90095, United States

§ Department of Pathology, Stanford University, Stanford, California 94305, United States

*Corresponding author.

Abstract

Drug design studies targeting one of the primary toxic agents in Alzheimer’s disease, soluble oligomers of amyloid β-protein (Aβ), have been complicated by the rapid, heterogeneous aggregation of Aβ and the resulting difficulty to structurally characterize the peptide. To address this, we have developed [Nle³⁵, d-
Pro³⁷]Aβ₄₂, a substituted peptide inspired from molecular dynamics simulations which forms structures stable enough to be analyzed by NMR. We report herein that [Nle³⁵, d-Pro³⁷]Aβ₄₂ stabilizes the trimer and prevents mature fibril and β-sheet formation. Further, [Nle³⁵, d-Pro³⁷]Aβ₄₂ interacts with WT Aβ₄₂ and reduces aggregation levels and fibril formation in mixtures. Using ligand-based drug design based on [Nle³⁵, d-Pro³⁷]Aβ₄₂, a lead compound was identified with effects on inhibition similar to the peptide. The ability of [Nle³⁵, d-Pro³⁷]Aβ₄₂ and the compound to inhibit the aggregation of Aβ₄₂ provides a novel tool to study the structure of Aβ oligomers. More broadly, our data demonstrate how molecular dynamics simulation can guide experiment for further research into AD.