Conformational Ensembles from Experimental Data and Computer Simulations

Conformational Ensembles from Experimental Data and Computer Simulations

Poster Abstracts

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.

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