GAME-THEORETIC METHODS FOR DESIGNING DRUGS

Carnegie-Mellon University, Pittsburgh PA

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Abstract

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. In game theory, a Correlated Equilibrium (CE) is an equilibrium concept that generalizes the more well-known Nash Equilibrium. If the game is represented as a graphical game, the computational complexity of computing an optimum CE is exponential in the tree-width of the graph. In settings where this exact computation is not feasible, it is desirable to approximate the properties of the CE such as its expected social utility and marginal probabilities. We have recently developed a method for computing approximate CE under NSF grant IIS-0905193. Our method was implemented and tested on blacklight (as a 'friendly user') on the task of drug design. Here the 'game'is to develop drugs that remain effective against the moves (i.e., mutations) made by the target molecule. A successful design is one where the drug evades resistance. Preliminary experiments on PDZ domains are promising. This startup request on blacklight will be used to further validate the method on additional benchmark targets, including HIV-1 protease. As previously mentioned, the algorithm has been implemented and run on blacklight prior to its deployment on the teragrid.