Folding@home

Protein Folding Conference

Guest post: Dr. Greg Bowman, UC Berkeley

We just had a protein folding conference at Stony Brook University in New York that was extremely encouraging.  Both the experimental and theoretical communities are very excited about the results we are generating with Folding@home.  In particular, they are excited about (i) our increasing ability to make quantitative connections with experiments and (ii) the long timescale dynamics for large proteins we are now able to capture.  For example, we recently succeeded in folding an 80-residue protein on 10 millisecond timescales (paper is here).  For reference, that’s about twice as many residues and about 1,000 times longer timescales than what most anybody else is able to achieve!    There are now multiple experimental groups who are asking us to make predictions for them to test.  So, we appreciate all your help and have plenty of new calculations for you to contribute to.

 

FAHcon 2012: Thinking about how far FAH has come

To start off FAHcon2012, I gave a talk which included a review of how far Folding@home has come in the last decade.  I showed a slide from the very first talk I gave about Folding@home results.  That talk was given at Columbia University in August of 2000, and I talked about results from our paper in Science entitled "Screen savers of the world, unite!".  That work described the folding of a very small protein (16 amino acids) on a very short timescale (10ns = 10 x 10^-9 seconds!), but still was a major accomplishment for the time.

It's exciting to see how far we've come.  One way to think about it is in terms of how long of a time scale and length scale we can simulate for protein folding and protein misfolding diseases (such as Aß aggregation in Alzheimer's Disease):

Time scales: advancing roughly 1000x every 5 years

2000: 1 to 10ns  (Fs peptide)

2005: 1 to 10µs  (villin, Aß aggregation of 4 chains)

2010: 1 to 10ms  (NTL9, Lambda repressor)

2015: 1 to 10s?

Just breaking past a microsecond was a big deal.  The fact that we can simulate 10's of milliseconds is very exciting, but I'm really excited about where this appears to be leading, allowing us to tackle really challenging and important problems.  It would also mean that through a combination of new methods, algorithms, and hardware advances, we've already increased our capabilities by a million fold in just 10 years (2000 to 2010).  We're looking forward to hopefully making it a billion fold in 2015!

Length scales: advancing roughly 2x every 5 years

2000: 16 amino acids (Fs)

2005:  35 amino acids (villin)

2010:  80 amino acids (lambda, ACBP)

2015:  160 amino acids?

It's also important to note that these are sizes for protein folding.  For other problems, such as protein conformational change, we've already tackled much bigger systems.

I'm really excited to see what the next 5 years will bring!

FAHcon 2012: Prof. Dr. Xuhui Huang

Here's a guest post from Prof. Dr. Xuhui Huang, from the Hong Kong University of Science and Technology.  

I had a great time attending the first annual FAH conference and enjoyed the nice summer weather in the Bay area.  We had plenty of discussions on the recent progress and future plans of FAH on both scientific and technique sides.  I look forward to the future FAH conferences. 

In my talk, I reported recent results on two projects from our lab.  The first one is the development of a new algorithm for the automatic construction of Markov State Model to investigate the conformational dynamics of multi-body systems.  This new algorithm holds great potential to help elucidate the aggregation mechanisms of multiple misfolded peptides to form oligomers and eventually fibrils.   In the future, we plan to apply this algorithm to study the human islet amyloid polypeptide (hIAPP) peptides, and its aggregation may result in reducing working β-cells in the Type 2 diabetes patients. 

I have also presented our recent results on applying Markov State Models to elucidate the molecular mechanisms of gene transcription.  Transcription is the first step in reading genomic DNA.  Transcriptional regulation plays a key role in cell differentiation and other fundamental processes. Misregulation of transcription is a major factor in cancer and other human diseases.  Thus, elucidating the mechanism of transcription is crucial for understanding these processes.  Our simulation results are able to provide dynamic information for the transcription, and this dynamic information is largely inaccessible to present experimental techniques.  

 

FAHcon 2012: Prof. Dr. Chris Snow

Dr. Snow, a new investigator at Colorado State University, gave a presentation focused on upcoming research. A unifying theme of this research is the engineering of new, synthetic proteins with applications in bioenergy & medicine. Specifically, Snow and colleagues are using computational protein design to engineer new cellulase enzymes for more efficient and economical biofuel production. To facilitate these calculations, the Snow group is developing software (SHARPEN) that could be deployed on the Folding@Home network. The technical barriers to developing a SHARPEN F@h core were discussed. Notably, F@h can still contribute to these design problems using existing molecular dynamics simulations.