Integrated Calendar

The Physics of a “Smart” Bio‐Gel:
 
Direct Force Measurements on Self‐Assembled Neurofilament Hydrogels 
 
Roy Beck, University of California Santa Barbara 
 
Understanding biological systems poses huge theoretical and experimental challenges, attributable to their complexity, dynamics and many different elementary lengths scales involved in their interactions. These interactions scale from specific atomic‐scale covalent bonds through non‐specific long‐ranged electrostatics. The complexity of biological systems is multi‐scaled as well, as even a single cell is composed from many different, very complicated building‐blocks.
   
In this talk, I will introduce our recent results about neurofilament hydrogel, a very basic component of the neurons’ cytoskeleton. After we purify the three different subunit proteins from bovine spinal‐cord, they self‐assemble to form supra‐macromolecules filaments with a ‘bottlebrush’‐like geometry. When assembled at high density, these neurofilaments form a liquid‐crystalline hydrogels and serve as the matrix for the neuron’s long processes (axons and dendrites). They impart mechanical stability and act as structural scaffolds. Using synchrotron small angle x‐ray scattering under osmotic pressure coupled with various microscopy techniques, we directly measure the interfilament forces responsible for the mechanical properties of neurofilament hydrogels.
  
We show that the “smart” mechanical properties of neurofilament gels can be tuned by variation of the subunit proteins and osmotic pressure. Such modifications have been recorded for different stages in neuron development and correlated to numerous neurodegenerative iseases. Surprisingly, under certain conditions, such as critical pressure or specific subunit protein ratios, negatively net‐charged and sterically repulsing filaments show attractive interactions. We are able to explain these results via a competition between long‐ and short‐ranged interactions, with a key combination from electrostatic interaction between altering positive and negative charged residues along the neuroflament brushes.
 
  

Through a practical example, this presentation describes the interplay between phases competing for stability at the nano-scale, pollution of an active nanocluster and the product of the catalytic reaction. The method can be extended to address the effect of size in the thermodynamic limits of catalysts.Fe and Fe:Mo nanoclusters are becoming the standard catalysts for growing single-walled carbon nanotubes (SWCNTs) via chemical vapor decomposition (CVD). Contrary to the Gibbs-Thomson formalism, experimental results show that reducing the size of the catalyst beyond a certain limit requires increasing the (minimum) growth temperature. This apparent paradox is addressed in terms of solubility of C in Fe nanoclusters. By using first principles calculations, an innovative thermodynamic model is constructed to determine the behavior of the phases competing for stability. As a function of particle size, there are three scenarios: steady state-, limited-, or no-growth of SWCNTs, corresponding to unaffected, reduced, and zero solubility of C in the clusters. The results are extended to Fe-Mo binary catalysts. The 15+ year long-standing question about the effects of Mo concentration on the growth capability is finally answered.

Research sponsored by ACS and Honda. References: Phys. Rev. Lett. 100, 195502 (2008), Phys. Rev. B, 77, 115450 (2008), Phys. Rev. B 75, 205426 (2007).

Protein folding can be described by Langevin dynamics. This dynamics can in turn be represented by a "path integral" (analogous to a Feynmann path integral in quantum mechanics), which is a weighted sum over all paths joining the denatured state to the native state of the protein. We show how one can compute the dominant paths (paths with largest weight) and how one can calculate dynamical quantities such as rates or transition path times from these paths. The method is illustrated on various simple examples.