The Chodera lab uses computation and experiment to develop quantitative, multiscale models of the effects of small molecules on biomolecular macromolecules and cellular pathways. To do this, the group utilizes physical models and rigorous statistical mechanics, with overall goals of engineering novel therapeutics and tools for chemical biology, as well as understanding the physical driving forces behind the evolution of resistance mutations. The group makes use of advanced algorithms for molecular dynamics simulations on GPUs and distributed computing platforms, in addition to robot-driven high-throughput experiments focusing on characterizing biophysical interactions between proteins and small molecules.
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Rational design of small molecules
We are using state-of-the-art alchemical free energy calculations coupled with automated robotic biophysical experiments to probe the physical determinants of small molecule recognition.
Functional biomolecular dynamics
We use stochastic dynamical models of biomolecular dynamics to understand the impact of small molecule binding on biomolecular function and interactions.
Multiscale modeling of cellular pathways
We are working to develop true multiscale methods that bridge atomistic models to biochemical pathways to predict the often complex effects of drugs with imperfect selectivity on cells.
Selective kinase inhibitors
We are performing kinome-wide computational and experimental studies as a route to the design of kinase inhibitors with desired selectivity profiles.
Drug resistance
We are building physical models of the emergence of resistance with the goal of developing therapeutics with drastically diminished potential to elicit drug resistance.
Design of allosteric modulators
We are using distributed computing techniques and advanced Markov state models to aid in the design of small-molecule allosteric modulators.
