Abstract 2100 UNCOVERING THE PROTEIN STRUCTURAL ENSEMBLE BY INTEGRATING MOLECULAR MODELING, ARTIFICIAL INTELLIGENCE, AND CRYO-EM

摘要: Cryogenic-sample electron microscopy (cryo-EM) has become a leading technique for determining the structure of biological macromolecules. However, many biological molecules are structurally heterogeneous, occupying a broad range of possible conformations. In principle, cryo-EM gives us the tools to extract this heterogeneity as well: biomolecules are trapped in the vitreous water in conformations close to the ones they adopt in solution. Our aim is to develop new algorithms that leverage our knowledge of protein biophysics to extract this information. To this aim, we present an approach towards analyzing cryo-EM experiments by comparing individual particle images with structures genereted through physical simulation. Initial results suggest that this approach can quantitatively recover the conformational probability distribution of a biomolecule from cryo-EM data. We then build on this prior work by …