Speaker
Description
In the field of structure-based drug design, there is enormous interest in determining the binding characteristics and physical orientations of putative therapeutic ligands within the binding sites of the proteins they target. A primary tool to investigate this binding interaction involves characterizing the structure of the protein bound to its ligand, typically using X-ray crystallography and Cryo-EM as structural methods. In this work, we take a modeling approach to the problem, using tools from spatial stochastic processes and stochastic geometry to understand the dynamics and shape configurations underlying this problem. We use percolation theory to model aspects of ligand contact with the protein target, coupled with Voronoi geometry (and its dual, Delaunay tessellation) to capture protein pocket geometry and ligand orientation effects. Percolation theory is a mathematical formalism that deals with how connected clusters occur in random graphs/networks. It is employed for modeling a wide array of problems involving disordered or porous media, such as protein crystalline arrays used in ligand structural studies. Our work addresses new challenges in applied percolation, including comparing diffusional versus invasive percolation, and specific problems arising from definition of boundary conditions for the percolation process.
