Thanks for a great 2019

Thanks to everyone who has contributed to Folding@home over the past year! We greatly appreciate the computer time, human time, and financial resources you contribute to support our science.

With your help, we’ve been tackling a range of tough problems, including translational research that aims directly at improving clinicians’ ability to diagnose and treat diseases and basic research that provides a foundation for these advances. Some highlights from the past year and opportunities they create for the coming years include:

  1. Discovery of new druggable sites for combating antibiotic resistance. Rational drug design is often based on a single snapshot of what a protein typically looks like. However, proteins have many moving parts. We (i.e. the Bowman lab) have been interested in uncovering these moving parts and exploiting these insights to devise new ways of targeting proteins with drugs. In one recent example, we examined the motions of a protein called β-lactamase, which is a key player in antibiotic resistant infections. As you may have heard in the news, antibiotic resistance is a growing health threat that currently costs our nation billions of dollars and tens of thousands of lives every year. One of the most common ways bacterial infections achieve antibiotic resistance is by producing β-lactamase proteins that chop up antibiotics, thereby preventing them from killing bacteria. Our simulations of this protein have revealed a portion of the structure that opens up, creating what we call a “cryptic” pocket because it is absent in known structures of the protein. In subsequent experiments, we showed that drug-like molecules can bind in this pocket and reduce β-lactamase’s ability to chop up antibiotics. An open access version of the paper is available here ( In the future, we plan to apply these methods to proteins that are currently considered ‘undruggable’ to find ways to render them viable drug targets.
  2. Understanding the mechanisms of proteins whose malfunction causes cancer. The Chodera lab has made nice headway on understanding how a protein called SETD8 works. Mutations of this protein that increase (or decrease) its function can result in cancer or neurological diseases. Understanding how SETD8 normally works is an important step towards understanding how it malfunctions and how we can develop therapeutics. Towards this end, the Chodera lab and their experimental collaborators uncovered motions of SETD8 that are important for its natural function. An open access version of the paper is available here ( Future work will help uncover how mutations lead to cancer and how we can mitigate these effects with drugs.
  3. Improved simulation algorithms. The calculations we perform on Folding@home are extremely demanding from a computational perspective. So, we’re always looking for ways to make the most effective use of the computing resources our volunteers provide. One general approach that remains of great interest is “adaptive sampling”, in which we iterate between running simulations and deciding which of the structures we have discovered so far it would be most useful to run more simulations from. The Voelz lab recently published a paper on how to do this effectively. An open access version of the paper is available here ( These methods will be useful for many of the simulations we perform in the coming years.