Probing the origin of tubulin rigidity with molecular simulations

Abstract

Tubulin heterodimers are the building blocks of microtubules, a major component of the cytoskeleton, whose mechanical properties are fundamental for the life of the cell. We uncover the microscopic origins of the mechanical response in microtubules by probing features of the energy landscape of the tubulin monomers and tubulin heterodimer. To elucidate the structures of the unfolding pathways and reveal the multiple unfolding routes, we performed simulations of a self-organized polymer (SOP) model of tubulin. The SOP representation, which is a coarse-grained description of chains, allows us to perform force-induced simulations at loading rates and time scales that closely match those used in single-molecule experiments. We show that the forced unfolding of each monomer involves a bifurcation in the pathways to the stretched state. After the unfolding of the C-term domain, the unraveling continues either from the N-term domain or from the middle domain, depending on the monomer and the pathway. In contrast to the unfolding complexity of the monomers, the dimer unfolds according to only one route corresponding to the unraveling of the C-term domain and part of the middle domain of ␤-tubulin. We find that this surprising behavior is due to the viscoelastic properties of the interface between the monomers. We map precise features of the complex energy landscape of tubulin by surveying the structures of the various metastable intermediates, which, in the dimer case, are characterized only by changes in the ␤-tubulin monomer.coarse-grained simulations ͉ dynamic instability ͉ forced unfolding ͉ single molecule ͉ unfolding pathways T he mechanical properties of microtubules (MTs) play crucial roles in processes such as cell division and matrix remodeling induced by mechanical loading of connective tissues. Because of their dynamic instability, i.e., stochastic alternation of slow growth and rapid shrinking phases between MTs and soluble tubulin subunits, MTs are able to transport chromosomes and other cellular organelles inside the cell (1). Blockage of dynamic instability by drugs such as taxol, which reduce the flexibility of the MT structure, promotes mitotic arrest and leads to cell death (2, 3). This behavior makes MTs a main target for cancer drugs (2), but efforts to design effective drugs are hampered, in part, by the lack of clear understanding of the microscopic origin of MT instability and of the MT behavior under tension (4).MTs are hollow cylinders, with large persistence lengths (5), composed of protofilaments aligned in parallel and joined laterally through mostly electrostatic contacts (6). Each protofilament consists of ␣-␤ tubulin dimers assembled in a head-totail fashion and joined noncovalently by hydrophobic and polar bonds along the longitudinal axis of the filament. The plus end of a MT is composed of ␤-tubulin (␤-tub), whereas the minus end consists of ␣-tubulin (␣-tub). During interphase, the minus end is attached to the centrosome, whereas the plus end has a GTP cap that contains at least one l...

Mechanism of Fibrin(ogen) Forced Unfolding

“…We utilized the SOP model and Langevin simulations (Dima and Joshi, 2008; Veitshans et al, 1997; Zhmurov et al, 2010b) on a GPU (SOP-GPU package; Section II.3 in Supplemental Experimental Procedures) (Zhmurov et al, 2010a). It took ~10 days of “GPU-time” to generate five 0.2 s trajectories (5 3 10 9 simulation steps) for the fibrinogen monomer ( N = 1913 amino acids) on a single GPU GeForce GTX 480 (NVidia) using the many-runs-per-GPU approach (Zhmurov et al, 2010a).…”

Mechanical Transition from α-Helical Coiled Coils to β-Sheets in Fibrin(ogen)

“…Biomolecular simulations provide a detailed nano-scale picture of structural transitions in proteins. 23,24 Yet, due to the very large system size (from 500 amino acid residues for a single coiled-coil portion to 2,868 residues for the full-length Fg molecule), theoretical modeling of fibrin(ogen) remains challenging. We utilized all-atom Molecular Dynamics (MD) simulations implemented on Graphics Processing Units (GPUs) to speed up the simulations.…”

Are protein-protein interfaces special regions on a protein’s surface?

“…Often due to inaccuracies in the force field, such lower resolution descriptors perform better than detailed atomic approaches. [25][26][27][28][29] We adopt this same philosophy in what follows.…”

“…If so, ideas from coarse-graining as applied to other protein problems including protein structure prediction and ligand virtual screening might be appropriate. [25][26][27][28][29] These methods identify key descriptors of a system which capture the essential physics. Often due to inaccuracies in the force field, such lower resolution descriptors perform better than detailed atomic approaches.…”