Pilar Cossio: Quantifying RNA Folding Ensembles from Unclassified Cryo-EM Particle Images

About this event

Many RNAs are dynamic and exist as an ensemble of conformations under biologically relevant conditions. Characterizing these ensembles requires determining both the structures of individual states and their relative populations. Single-particle cryo-electron microscopy (cryoEM) images of biomolecules represent noisy single-molecule samples from the ensemble distribution. Here, we present approaches for inferring RNA compositional and conformational ensembles from cryo-EM images and molecular dynamics simulations that avoid the need for prior image alignment or a pre-sampled ensemble. Our methods enables ensemble inference of flexible RNAs and other biomolecules for which conventional cryo-EM reconstruction is challenging and prior simulations are costly.

Bio:

Pilar Cossio joined the Center for Computational Mathematics in April 2021 as the Research Scientist and Project Leader for Biomolecular and Biophysical Inference (BBI). Previously, Cossio was Max Planck Tandem Group Leader associated with the University of Antioquia (Colombia) and the Max Planck Institute of Biophysics (Germany). She also has held postdoctoral positions at the National Institute of Health (NIH, USA) and the Max Planck Institute of Biophysics. Cossio focuses on the development of mathematical and computational methods to characterize proteins’ structures and dynamics from cryo-electron microscopy, single-molecule spectroscopy and biomolecular simulations. Cossio holds a Ph.D. in Physics and Chemistry of Biological Systems from the International School for Advanced Studies (SISSA) in Italy and a B.S. in Physics from the University of Antioquia.