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The nanomachine from the ATPases associated with various cellular activities superfamily, called spastin, severs microtubules during cellular processes. To characterize the functionally important allostery in spastin, we employed methods from evolutionary information, to graph-based networks, to machine learning applied to atomistic molecular dynamics simulations of spastin in its monomeric and the functional hexameric forms, in the presence or absence of ligands. Feature selection, using machine learning approaches, for transitions between spastin states recognizes all the regions that have been proposed as allosteric or functional in the literature. The analysis of the composition of the Markov State Model macrostates in the spastin monomer, and the analysis of the direction of change in the top machine learning features for the transitions, indicate that the monomer favors the binding of ATP, which primes the regions involved in the formation of the inter-protomer interfaces for binding to other protomer(s). Allosteric path analysis of graph networks, built based on the cross-correlations between residues in simulations, shows that perturbations to a hub specific for the pre-hydrolysis hexamer propagate throughout the structure by passing through two obligatory regions: the ATP binding pocket, and pore loop 3, which connects the substrate binding site to the ATP binding site. Our findings support a model where the changes in the terminal protomers due to the binding of ligands play an active role in the force generation in spastin. The secondary structures in spastin, which are found to be highly degenerative within the network paths, are also critical for feature transitions of the classification models, which can guide the design of allosteric effectors to enhance or block allosteric signaling. 

Abstract Microtubule (MT)‐associated proteins regulate the dynamic behavior of MTs during cellular processes. MT severing enzymes are the associated proteins which destabilize MTs by removing subunits from the lattice. One model for how severing enzymes remove tubulin dimers from the MT lattice is by unfolding its subunits through pulling on the carboxy‐terminal tails of tubulin dimers. This model stems from the fact that severing enzymes are AAA+ unfoldases. To test this mechanism, we apply pulling forces on the carboxy‐terminal regions of MT subunits using coarse grained molecular simulations. In our simulations, we used different MT lattices and concentrations of severing enzymes. We compare our simulation results with data from in vitro severing assays and find that the experimental data is best fit by a model of cooperative removal of protofilament fragments by severing enzymes, which depends on the severing enzyme concentration and placement on the MT lattice.