Research
The Biophysics of Protein Design
Proteins serve as the primary means of an organism’s ability to sense and respond to its internal and external environment. To achieve this, proteins undergo thermodynamically accessible conformational changes that initiate biological processes downstream. Mutations and external stimuli like metals can alter the thermodynamic landscapes of proteins, which can result in a host of diseases like neurodegeneration and cancer. While some of the mechanisms of these conformational changes are understood through studies such as deep mutational scanning, it is not yet possible to predict, engineer or therapeutically alter these changes beyond a subset of well-studied systems. Our lab addresses these problems in two separate, but parallel approaches. One arm of the lab focuses on methods development for protein conformational modeling, utilizing cryo-EM, physics-based simulation, and machine learning to build more robust and accurate predictions of protein flexibility and energetics. The second arm of the lab utilizes our own methods along with existing methods to tune the energetics of de novo designed proteins with the goal of making functional, dynamic biosensors and biomaterials.
Modeling protein conformation with cryo-EM and simulation
Methods like cryo-EM, provide rich information about the conformational landscape of the molecular system. Cryo-EM, while a promising method, can typically resolve only a handful of the most probable states. Less probable conformations like transition states, while likely present in these cryo-EM samples, are almost never resolved. However, machine learning methods have been making great strides in resolving more states for this low signal to noise data. Our laboratory seeks to integrate these machine learning methods with molecular dynamics simulation to investigate protein conformation, misfolding and allosteric modulation of proteins.
Newer machine learning methods like cryoFIRE can capture rare states of larger assemblies like the splicesosome
Biophysically tunable de novo protein functions
We also use de novo protein design and protein engineering to recreate environmentally responsive proteins from our most basic understanding of protein biophysics. We utilize these methods to build generalizable models of protein function to determine how stimuli like metals, peptides and small molecules alter the behavior of proteins.
One goal in the lab are to generate proteins that can generate conformation changes in response to any stimulus relevant to biology or the environment (left). Another goal is to tune the kinetics or relative affinity of minibinder proteins to native macromolecules (right). Both of these problems require an intricate understanding of the energetic landscape of a proteins shape or interface, and how these energetics changes as function of surface chemistry of backbone geometry.
Facilities
The Bethel Lab maintains its own private cluster of >500 CPUs and 60 GPUs. We also have allocations of the Triton Shared Computing Cluster and the Comet Supercomputer hosted at UCSD. Additionally, we are users of the Cryo-EM facility, the Thermo Fisher Sandbox, and the Janelia Cores hosted by Howard Hughes Medical Institute.
