In silico reduction of conformational heterogeneity for single-particle cryo-EM

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Single-particle cryo-electron microscopy has become a powerful tool to study the structure of large macromolecules and complexes thereof. One of the biggest challenges in the analysis of cryo-EM images is the heterogeneity and flexibility of the molecules, which severely limits the achievable resolution. In the proposed project we will develop a computational approach to reduce the conformational variance of a set of single-particle images with the goal of increasing the resolution. We propose an approach that is based on a method to extract conformational fluctuations from a bootstrapping procedure, which we have developed earlier. The information on conformational variance is then used to extensively classify the images into a large number of different classes. In a next step, the individual 3D density reconstructions from all classes are combined into one single reconstruction by an appropriate averaging procedure. The goal is to improve the resolution and at the same time to gain a complete picture of the conformational variance of the macromolecule. The proposed method will then be applied to two different systems: 1) in collaboration with the group of Holger Stark we will study the SelB-ribosome complex, where domain 4 of SelB, which is responsible for recognition by the ribosome, at the moment cannot be resolved to high resolution due to a high degree of heterogeneity. And 2), with the group of Wah Chiu we will work on the GroEL/ES-RuBisCO complex. We recently published a structure of this complex showing the encapsulated substrate, which seems to be a mixture of several conformations. We aim to separate these different conformations and determine the structure of a folding intermediate within the GroEL/ES cavity.