CCeMMP Seminar Series – Dr. Slavica Jonic – Nov 2022

DeepHEMNMA approach for analyzing continuous conformational heterogeneity in single-particle cryo-EM images

Single-particle cryo-EM allows 3D reconstruction of multiple conformations of purified biomolecular complexes from their 2D images. The elucidation of different conformations is the key to understanding molecular mechanisms behind biological functions of the complexes and the key to novel drug discovery. The standard cryo-EM data analysis procedures involve many rounds of 2D and 3D classifications to disentangle and interpret the combined conformational, orientational and translational heterogeneity.  Gradual conformational transitions give rise to many intermediate conformational states.  Continuous conformational heterogeneity in cryo-EM data (a mixture of many intermediate conformational states), due to such gradual conformational transitions, is both an obstacle for high resolution 3D reconstruction of different states and an opportunity to obtain the information about multiple coexisting states at once. 

HEMNMA method, was specifically developed for analysing continuous conformational heterogeneity in cryo-EM data, determines the conformation, orientation, and position of the complex in each single particle image by analysing images using normal modes (motion directions simulated for a given atomic structure or EM map), which in turn allows determining the full conformational space of the complex but at the price of high computational cost. Recently, a deep learning extension of HEMNMA, referred to as DeepHEMNMA, was proposed, which speeds up HEMNMA by combining it with a deep learning approach. DeepHEMNMA will soon be available in ContinuousFlex, an open-source software package that her team is developing. ContinuousFlex provides a user-friendly graphical interface to several methods for analysing continuous conformational heterogeneity in vitro and in situ. ContinuousFlex is currently available as a plugin for Scipion.

Dr. Slavica Jonic

IMPMC-UMR 7590 CNRS, Sorbonne Université, Paris, France