#### Faculty Mentor

Christopher M. Summa, David Mobley

#### Location

Library 3E

#### Session

Session 5

#### Start Date

13-4-2013 11:00 AM

#### End Date

13-4-2013 12:00 PM

#### Description

Calculation of the relative binding free energies of drug compounds to their cognate proteins is an extremely computationally intensive process, with each calculation taking perhaps weeks of processor time. With large datasets, minimizing the number of free energy calculations becomes an important undertaking. We present a graph-theoretic approach to planning these calculations, modeled as the optimization of a fully connected graph where the nodes represent the drug compounds in the dataset, and the edges represent a free energy calculation that must be performed. We show that our technique significantly outperforms other approaches for graph optimization within this problem domain.

Binding Free Energy Calculation Planning Using Graph Theoretic Techniques

Library 3E

Calculation of the relative binding free energies of drug compounds to their cognate proteins is an extremely computationally intensive process, with each calculation taking perhaps weeks of processor time. With large datasets, minimizing the number of free energy calculations becomes an important undertaking. We present a graph-theoretic approach to planning these calculations, modeled as the optimization of a fully connected graph where the nodes represent the drug compounds in the dataset, and the edges represent a free energy calculation that must be performed. We show that our technique significantly outperforms other approaches for graph optimization within this problem domain.