Seminar by Prof. Ruxandra Dima

University of Cincinnati, USA

Start
18th April 2024 14:00 PM
End
18th April 2024 15:00 PM
Location
FZJ, 15.9V, room 4001B, Entrance 5

To cut or not to cut: a view into microtubule severing machines

Cellular homeostasis requires protein remodeling mechanisms, such as microtubule severing, which is accomplished by enzymes that induce internal breaks in microtubules resulting in pruning or amplification of microtubule arrays. Severing enzymes belong to the AAA+ family. Their action is driven by ATP hydrolysis, leading to transitions between conformations of the oligomeric state of the machine. Structures for the oligomeric states, one in a spiral and the other in a ring arrangement, for two severing proteins have been solved leading to a proposed power stroke microtubule cutting mechanism. Still, many questions remain about the molecular action of severing enzymes such as the motions that underlie functional changes in the machines, their mechanism of substrate engagement, and how the removal of subunits is accomplished. Experimental challenges in addressing these questions are the fact that severing deeper in the cell and in dense microtubule arrays is hardly visible by light microscopy, and because it is not possible to directly visualize the enzyme at severing sites. Computational challenges are the very large size of the substrate, the lack of knowledge of all states of the motors, and the long simulation times. We used the structures of motors and of microtubules in atomistic and minimalist models molecular simulations, combined with machine learning approaches, to yield results which are compared and contrasted with experiments. Our findings reveal information regarding the asymmetric pore motions and intra-ring interactions that support them and potential modes of interaction between enzymes and a microtubule leading to first steps in severing. We characterized the potential allosteric sites and the direction of structural and energetic changes of severing machines regions that are found, by machine learning approaches, to best describe the allosteric transitions. I will discuss the results in the context of existing models, experimental probes of microtubule severing, and data regarding the action of AAA+ motors.

Last Modified: 12.06.2024