One of the crucial steps in drug design is understanding how two molecules bind to each other. The two critical issues in a computational approach is speed and accuracy. Usually one has to trade one for the other and use a computationally efficient method like docking, at the cost of some accuracy, or use a computationally demanding method like free energy calculations, but at the cost of low throughput. With distributed computing and a set of complementary methods (both docking and free energy calculations), we can have it both ways — with the goals of high throughput and high accuracy. Distributed computing is a key aspect to this, as it allows us to do calculations otherwise impossible.
Most rational drug design efforts assume the target protein exists in a single structure and that the active site of the protein allows the protein to perform its function. With this in mind, the only way to manipulate a protein’s activity is with inhibitors that bind the active site tightly enough to block it from performing its intended function. Unfortunately, this strategy only works for ~15% of proteins, greatly limiting the number of proteins we can manipulate for therapeutic purposes.(Hopkins, 2002) My colleague, Dr. Gregory Bowman, has used Folding@home to show that proteins are actually flexible, and he has used a process called allostery to indirect manipulate the active site, ultimately affecting the protein’s activity.(Bowman, 2012)