A key aspect of Folding@home research has been using computational methods to design new drugs, especially for Alzheimer’s Disease. At the University of Virginia, the Shirts lab is developing methods to leverage the power of Folding@home to develop new drugs to fight disease. Generally, small molecules work as drugs by binding very specifically to certain locations on important proteins. For example, an antibiotic works by binding to a protein on a bacteria, thus interfering with the pathogen's internal workings seriously enough to disable or kill it. By targeting only protein sites that are unique to the pathogen, drugs can act extremely specifically, rather than harming the human body or desired microbes. The exact same principles can toggle very specific parts of our own body's protein machinery on or off, allowing development of drugs that fight diseases of caused by breakdown, mutation, or malfunction our own cellular machinery, like Alzheimer’s Disease, heart disease, diabetes, and many other conditions.
However, it is very hard to calculate exactly how tightly a given small molecule will bind to a target protein, or even exactly where and by what mechanism it will bind. A number of computational methods are used in industry today to estimate the binding affinity of small molecules in the process of drug design, but they mostly rely on approximations that are computationally cheap and very approximate, rather than more expensive methods that have the potential to be much more accurate. With Folding@home, we now have the capability to perform rigorous evaluations of these more complete methods, understand their limits, and make them more efficient and reliable.
We have been developing our methods working mostly with well-understood model systems, such as FKBP, a protein on the immune system signaling pathway. Once the methods are well-understood, we will be moving on try to design small molecules to treat AIDS (the HIV reverse transcriptase enzyme, required for DNA to replicate) and influenza (various proteins involved in virus cell entry). Such molecules will still require significant effort to make into drugs, since drugs also have to dissolve easily, penetrate cells, and not be broken down to quickly, but being able to predict more easily which molecules interact tightly with the intended targets will be a huge step in the right direction.
As part of our efforts to improve Folding@home infrastructure, we are also working to port new versions of the Gromacs molecular simulation platform to Folding@home and improving the interface and integration between Gromacs and Folding@home.
