Embedded Files
Computer aided drug design
Computer aided drug design
Molecular simulations can serve as a computational microscope for revealing dynamics of biochemical processes. Appreciating protein dynamics has led to identification of cryptic, druggable pockets not visible in static experimental structures. We use multiscale simulations, enhanced sampling techniques, and machine learning to understand inhibition and drug resistance mechanisms, and design molecules for addressing pharmaceutical targets such as those caused by bacteria and viruses.
Protein engineering
Protein engineering
Proteins are the biological machines that carry out essential functions for life. They possess the capacity to serve as materials, sensors, catalysts, and more, offering a versatile range of applications in the medicinal, environmental, and industrial fields. Our long term goal is to uncover fundamental properties of the protein sequence-structure-function relationship and harness the capacity to create molecules with desired properties. We use a variety of experimental and computational techniques to design proteins with a large focus on biofuels and bioenergy.
Simulation and AI
Simulation and AI
The rapidly expanding application of AI to the physical sciences represents an exciting opportunity to reach unprecedented levels of predictive power. We use machine learning to parse data obtained from high throughput experiments, and generated by computational simulations to identify important patterns. This helps us understand the fundamental properties of complex, multi-dimensional systems, and automate tasks for maximum research efficiency.
Page updated
Report abuse