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Conformational Ensembles from Experimental Data
and Computer Simulations
Poster Abstracts
52
19-POS
Board 19
Mass Spectrometry Based Modelling of Macromolecular Assemblies
Matteo T. Degiacomi
, Justin L. Benesch.
University of Oxford, Oxford, United Kingdom.
Small Heat-Shock Proteins (sHSP) are present in all kingdoms of life, and form assemblies
spanning a continuum of structures from mono- to polydisperse, with variable architecture.
These can bind unfolding proteins, preventing their potentially harmful denaturation. Since sHSP
oligomers can bind several proteins simultaneously, ensembles of >>100 sHSP:target
stoichiometries are often observed. This dynamic nature, seemingly critical to their cellular
function, makes these proteins intractable by most conventional biochemical approaches. Mass
Spectrometry (MS) is one of the few techniques able to separate these complexes and assess
them individually. By exploiting MS structural data, we generate plausible polyhedral models for
sHSPs, and describe a possible binding mode to their targets.
This work led to the development of novel computational tools of general applicability. These
include an accurate method to predict cross-linkable amino acids, adopting an ensemble
representation to account for both cross-linker and protein flexibility. Furthermore methods have
been developed to calculate the collision cross-section of electron density maps and to arrange
molecules according to arbitrary topologies. These are all integrated in BiobOx, a Python
package allowing the analysis and manipulation of molecular structures and ensembles at an
atomistic, super coarse-grain, or electron density level.
Overall, we show that protein ensemble representations coupled with MS data can be
successfully exploited for the modelling of protein assemblies and their interactions with specific
substrates.