Developing and applying new methods for computational drug design has become a major thrust for FAH as our methods have matured and developed. It's become useful to test just how well our methods work. Last year, we participated in a prospective challenge to predict pharmaceutically relevant calculations associated with a challenge set up by OpenEye, a computational drug design calculation. We did well in our predictions and the results have been submitted for peer review.
This year, we're planning on participating again. The challenge has a new name -- the SAMPL challenge -- and more information can be found here. For those familiar with CASP (a protein structure prediction challenge), this is similar in the sense that predictions are made blind (i.e. we don't know the answers), which is an important test. There are several key differences discussed in the web page linked above. Most notably, instead of just predicting structure (which may eventually be useful in drug design), we're predicting which molecules would make useful drugs based on their affinity to their targets. While there's lots of other aspects to drug design (eg are these molecules toxic), this is a natural place to start and an area in which we've been working on for a while.
I'll post more are we go along. For now, I wanted donors to know about this important challenge and look forward to rallying the FAH community to help us do well on this new challenge! This will be an important test of FAH's methods and if successful would represent a major step towards FAH's goals, i.e. using computational methods to directly address the diseases we are studying.