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Stanford's goal: to understand protein folding, protein aggregation, and related diseases.



What are proteins and why do they "fold"? Proteins are biology's workhorses -- its "nanomachines." Before proteins can carry out their biochemical function, they remarkably assemble themselves, or "fold." The process of protein folding, while critical and fundamental to virtually all of biology, remains a mystery. Moreover, perhaps not surprisingly, when proteins do not fold correctly (i.e. "misfold"), there can be serious effects, including many well known diseases, such as Alzheimer's, Mad Cow (BSE), CJD, ALS, and Parkinson's disease.

What does Folding@Home do? Folding@Home is a distributed computing project which studies protein folding, misfolding, aggregation, and related diseases. Stanford uses novel computational methods and large scale distributed computing, to simulate timescales thousands to millions of times longer than previously achieved. This has allowed us to simulate folding for the first time, and to now direct Stanford's approach to examine folding related disease.



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  • Stickies: 0
  • News Articles: 158
  • Pages: 32
Folding@home highlighted in Biophysical Journal
King_N
[H]ard|Folding Administrator


Posts: 103
Points: 2,847,992
Work Units: 6,671

Posted: Wed Aug 27, 2014 12:46 pm
Recent work from Folding@home highlighted in Biophysical Journal

Quote:
by Vijay Pande

Our recent work on understanding how protein misfolding occurs (http://www.cell.com/biophysj/abstract/S0006-3495(14)00722-X) has shed light on the nature of misfolding and potential subsequent aggregation (relevant for protein misfolding disease), demonstrating that misfolded states are more prevalent than would be expected, especially due to their metastability (once you get into a misfolded state, its really hard to get out of it).



Full Article: here.


New results for Opa proteins

Quote:
by Peter Kasson

Were excited to share some recent results from our lab that combine simulation and experimental structural biology. This has been a wonderful collaboration with my colleague Linda Columbus, a Chemistry professor at the University of Virginia. We are interested in how Neisseria bacteria recognize and infect cells. This is an important problem #1 because Neisseria are becoming increasingly drug-resistance and #2 because these mechanisms can be borrowed for targeted drug delivery.


Full Article: here.

Folding/Chrome to Reveal the Secrets Behind the Type II Diabetes
King_N
[H]ard|Folding Administrator


Posts: 103
Points: 2,847,992
Work Units: 6,671

Posted: Thu Jul 24, 2014 03:33 am
Quote:
by Huang

In the past couple of years, Xuhui Huangs group at HKUST
(http://compbio.ust.hk/) has performed large-scale molecular dynamics
simulations at Folding@Home (Project 2974-2975) to investigate the
mis-folding of the hIAPP (human islet amyloid polypeptide, also called
amylin).

Like other misfolding peptides, hIAPP is generally unstructured in
water solution but adopts an alpha-helix structure when binds to the
cellular membrane. Around 95% of patients with Type II diabetes
exhibit large deposits of misfolded hIAPP (beta-sheet fibrils). The
aggregation of this peptide is suggested to induce apoptotic
cell-death in insulin-producing β-cells that may further cause the
development of the type II diabetes. Using Markov state models
constructed from many molecular dynamics simulations, we have
identified the metastable conformational states of the hIAPP monomer
and the dynamics of transitioning between them. We show that even
though the overall structure of the hIAPP peptide lacks a dominant
folded structure, there exist a large number of reasonably populated
metastable conformational states. Among them, a few states containing
substantial amounts of β-hairpin secondary structure and extended
hydrophobic surfaces may further induce the nucleation of hIAPP
aggregation and eventually form the fibrils. These results were
published at Qin, Bowman, and Huang, J. Am. Chem. Soc., 135 (43),
1609216101, (2013) (http://pubs.acs.org/doi/full/10.1021/ja403147m).



Full Article: here.
Update on drug design successes with Folding@home
King_N
[H]ard|Folding Administrator


Posts: 103
Points: 2,847,992
Work Units: 6,671

Posted: Sat Jun 28, 2014 08:53 am
Vijay gave a brief talk on drug design successes with Folding@home.

Quote:
by Vijay Pande

In the Stanford Big Data conference in 2014, I gave a talk which gives an update on our drug design efforts, summarizing a bit on how FAH works to design drugs and were we are in some areas (but not all alas, its only a 12 minute talk, so I had to be pretty brief).



Link to video here.
Stanford Webinar
King_N
[H]ard|Folding Administrator


Posts: 103
Points: 2,847,992
Work Units: 6,671

Posted: Mon May 26, 2014 03:11 am
Stanford is holding a "Webinar".

Quote:
by Vijay Pande

Please join us on June 3rd for a webinar presented by Vijay Pande, Professor of Chemistry, Structural Biology, and Computer Science at Stanford University and the founder of the Folding@Home project. Professor Pande will give a brief introduction to Folding@home and successes in the project so far. He will also discuss plans to greatly enhance Folding@home capabilities through new initiatives.


The webinar is scheduled to take place on June 3rd at 9am, it requires registration at the link below.

Registration Link

Progress on connecting computation with experiment
King_N
[H]ard|Folding Administrator


Posts: 103
Points: 2,847,992
Work Units: 6,671

Posted: Mon Apr 28, 2014 09:34 pm
Stanford has made progress with their experiment to capture millisecond events through Folding@Home and Markov state models.

Quote:
By Greg Bowman


Many biologically relevant conformational changes occur on milliseconds and slower timescales. Furthermore, many experimental techniques are only sensitive to milliseconds and slower timescales. Therefore, our ability to reliably capture millisecond timescale events through the use of Folding@home and Markov state models opens up a host of exciting possibilities.


Full Article: here.
  • Stickies: 0
  • News Articles: 158
  • Pages: 32
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