Thanks for the heads-up Erika

@lawrencehardin

It is much cheaper to run these tests on a computer than physically combining the materials in a lab. But computers are not 100% accurate and will sometimes give false positives - something that looks like a cure or a step in the right direction...but it's not. Things that look like potential cures have to be physically tested in a lab which isn't cheap and takes a long(?) amount of time. Also as budgets are always tight, scientists might run the risk of having 50 possible "hits" or possible cures, but only enough money to test 20 in a year.

The Scripps people, taking part in the SAMPL4 competition, found a way to make the computer modeling more accurate = less false positives = less time/money wasted as there are less bad computer results that need to be checked in a lab. The more accurate these things are the better future WUs can be at finding drug candidates for diseases.

edit: "I didn't even get past the title of the paper !!!"
Honestly the title is way too technical for me too! Which brings up the idea to create not just the "Lay Person Abstract" but the "Lay person Title!" My personal attempt would be "Making AutoDock Vina WUs more accurate: The results of a science challenge" I know that is really simplifying things but I couldn't get through the technical version

Cheers :)

Indeed we have recently published two papers, with another about to be submitted that couples our Docking codes, AutoDock and AutoDock Vina with the BEDAM software from the Levy Laboratory (now at Temple University). A brief rationale and explanation of the computations follows:

Docking software produces two kinds of results: 1) the predicted pose of a ligand molecule bound to the target receptor (protein or other biomolecule); and 2) a score for that pose, which represents the strength of the binding interaction, and which is used during the docking to pick out the best pose. Because docking typically requires computing millions of poses, and evaluating a score for each pose, the score evaluation must be very fast, and thus we must trade accuracy for speed. Because of this, while the pose of the ligand tends to be pretty accurate, the score (which is interpreted as a binding free energy) is not. When it comes to actually obtaining the best ranked chemical compounds (either through purchase or synthesis) based solely on the docking score, we tend to get a number of "false positives" -- compounds that docking predicts will bind strongly, but when tested in the laboratory, actually do not. False positives are costly and time-consuming in the drug development pipeline.

The Levy group had developed software called BEDAM (Binding Energy Analysis Method) which uses molecular dynamics (in implicit solvent) to sample the energetics of reorganization that occurs upon ligand binding. This includes both the reorganization of solvent (water), and of the region of the target protein involved in the binding. It also gives a better accounting of the entropic change of the system. Needless to say these computations are very expensive in terms of computer time, and cannot be run during the docking itself. However, since the poses produced by the docking are more reliable than the docking score, they are a good starting point for the BEDAM computations. Thus we use our docking scores to pick the best 100 or so poses, then submit them to BEDAM for recalculation of the binding free energy of the interaction. The papers that have been published describe the results of this procedure, which show a very significant reduction in the number of false positives.

We are now in the process, in collaboration with the Levy Group, of getting the BEDAM code ported to the FightAIDS@Home Project on the World Community Grid. With the computing power that volunteers make available for our research, this should greatly improve the results of our virtual screening experiments.

Wonderful news and congratulations on the improved accuracy and new publications!



Really quick I want to say Please please please contact the forces that be in charge of this page: http://boinc.berkeley.edu/wiki/Publications_b...ects#World_Community_Grid and get your information updated. This seems to be the definitive list of BOINC related publications and for me personally was big motivation for me to join WCG and this project.