By Massimiliano Bonomi, Institut Pasteur, Université Paris Cité, France
Understanding the molecular mechanisms by which biological systems carry out their functions is often essential for the rational targeting of associated diseases. In many cases, determining the three-
dimensional (3D) structure of these systems provides valuable insights. However, it is often the interplay between structural and dynamical properties that determines the behavior of complex systems. While both
experimental and computational methods are invaluable for studying protein structure and dynamics, the limitations of each individual technique can hinder their capabilities [1].
Here, I present our lab’s work on developing integrative computational-experimental approaches that combine experimental data with molecular dynamics (MD) simulations to determine accurate protein structural ensembles of biological systems [2,3]. I will showcase the capabilities of these methods through various applications to systems of significant interest. First, I will demonstrate how accurate protein structural ensembles can be obtained from 3D cryo-electron microscopy maps using our recently developed EMMIVox approach [4]. Then, I will highlight how we characterize the structural and dynamic properties of the CyaA toxin by integrating coarse-grained MD simulations with Hydrogen/Deuterium eXchange Mass Spectrometry (HDX-MS), Small-Angle X-ray Scattering (SAXS), and 2D single-particle cryo-EM data.
Finally, I will show how structural information provided by Artificial Intelligence approaches, such as AlphaFold, can be synergistically combined with low-resolution experimental data to generate accurate
models of protein complexes.
References:
[1] M. Bonomi, G. T. Heller, C. Camilloni, M. Vendruscolo. Curr. Opin. Struct. Biol. 42 (2017) 106
[2] M. Bonomi, C. Camilloni, A. Cavalli, M. Vendruscolo. Sci. Adv. 2 (2016) e1501177
[3] P. Cossio, G. Hummer. J. Struct. Biol. 184 (2013) 427
[4] S. E. Hoff, F. E. Thomasen, K. Lindorff-Larsen, M. Bonomi. PLoS Comput. Biol. 20 (2024) e1012180
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