Official Project Description
Can molecular simulation be used for virtual affinity-maturation of de novo designed protein binders? That’s the question this project aims to address.
The Bahl Lab at the Institute for Protein Innovation has had some amazing success using computational design to develop high-affinity mini-proteins that can inhibit protein targets by tightly binding to them.
In practice, the current approach requires the experimental screening of thousands of computational designs to discover a few tight binders, and similarly expensive experimental screens to optimize their binding (i.e.
“affinity maturation”).
If we can make more accurate predictions of how sequence mutations affect binding affinity, we may be able to offload this expensive task to computers, boosting the efficiency of these efforts considerably. In this project, we use relative free energy calculations to predict how single-point mutations of a computationally designed mini-protein alter the binding affinity to the periplasmic protease LapG, an important regulator of bacterial biofilm formation.
These predictions will be compared to high-throughput experimental measurements of binding affinity provided by the Bahl lab.
An important end goal of this work is to develop new classes of inhibitors to make antibiotic therapies more successful.
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