Research
Computer simulations of molecular phenomena are increasingly successful aids to chemical engineering, bioengineering, and materials science. Simulation is particularly suited for providing all-atom insight that is inaccessible through experiment and for investigating large numbers of chemical entities and conditions that are expensive or difficult to physically create. As computer power continues to increase exponentially, atomistic simulation will become an even more important tool in the scientific and engineering arsenal. In the Shirts group, we are working on improved methods for design of new materials and more efficient thermodynamic property predictions to add to the scientific and engineering arsenal.


Computed-aided drug design
Drug resistance is one of the biggest challenges in the pharmacological treatment of infectious diseases, and current informatics based drug discovery methods are not well suited to rapidly develop new drug variants that can successfully overcome resistance. Our research has demonstrated that statistical mechanical methods can predict ligand binding affinities to within 1 kcal/mol in simple atomistically detailed systems, a level that becomes useful for the pharmaceutical industry. However, significant effort is necessary to make such methods work in more typical drug systems and to make them scale efficiently enough to be useful in general practice.
Design of novel heteropolymeric materials
The wide physical and chemical diversity of biomolecular processes strongly suggests that the possibilities for novel function in human-engineered materials are far, far beyond our current capabilities. Designed materials can draw from a much larger range of chemical structure and functionality than exists biologically; if we can add significant chemical diversity to nature's already impressive toolkit, what else can be created?
Improvements in molecular simulation and property prediction
The most pressing problem in the atomic-level simulation of polymers, macromolecules, and other complicated dense fluids is the lack of sufficient sampling to accurately measure and observe physical phenomena. Without sufficient conformational sampling, it is impossible even to verify if models are sufficiently faithful to experiment, let alone explore behavior of either long time scales or of larger molecular systems. It is currently only possible to simulate the equivalent of a few microseconds of all but the smallest biological systems, with some heroically expensive extensions to milliseconds with large supercomputers. In the Shirts group, we have made important contributions to efficient analysis of free energy calculations and other thermodynamic data; our current research focuses on methods for sampling both chemical and configuration space of heteropolymers and complex fluids.