43 research outputs found
Anomalous roughness with system size dependent local roughness exponent
We note that in a system far from equilibrium the interface roughening may
depend on the system size which plays the role of control parameter. To detect
the size effect on the interface roughness, we study the scaling properties of
rough interfaces formed in paper combustion experiments. Using paper sheets of
different width \lambda L, we found that the turbulent flame fronts display
anomalous multi-scaling characterized by non universal global roughness
exponent \alpha and the system size dependent spectrum of local roughness
exponents,\xi_q, whereas the burning fronts possess conventional multi-affine
scaling. The structure factor of turbulent flame fronts also exhibit
unconventional scaling dependence on \lambda These results are expected to
apply to a broad range of far from equilibrium systems, when the kinetic energy
fluctuations exceed a certain critical value.Comment: 33 pages, 16 figure
Computational Structure Prediction for Antibody-Antigen Complexes From Hydrogen-Deuterium Exchange Mass Spectrometry: Challenges and Outlook
Although computational structure prediction has had great successes in recent years, it
regularly fails to predict the interactions of large protein complexes with residue-level
accuracy, or even the correct orientation of the protein partners. The performance of
computational docking can be notably enhanced by incorporating experimental data from
structural biology techniques. A rapid method to probe protein-protein interactions is
hydrogen-deuterium exchange mass spectrometry (HDX-MS). HDX-MS has been
increasingly used for epitope-mapping of antibodies (Abs) to their respective antigens
(Ags) in the past few years. In this paper, we review the current state of HDX-MS in
studying protein interactions, specifically Ab-Ag interactions, and how it has been used to
inform computational structure prediction calculations. Particularly, we address the
limitations of HDX-MS in epitope mapping and techniques and protocols applied to
overcome these barriers. Furthermore, we explore computational methods that leverage
HDX-MS to aid structure prediction, including the computational simulation of HDX-MS
data and the combination of HDX-MS and protein docking. We point out challenges in
interpreting and incorporating HDX-MS data into Ab-Ag complex docking and highlight
the opportunities they provide to build towards a more optimized hybrid method, allowing
for more reliable, high throughput epitope identification