A Hierarchical Model To Understand the Processing of Polysaccharides/Protein-Based Films in Ionic Liquids.

In recent years, biomaterials from abundant and renewable sources have shown potential in medicine and materials science alike. In this study, we combine theoretical modeling, molecular dynamics simulations, and several experimental techniques to understand the regeneration of cellulose/silk-, chitin/silk-, and chitosan/silk-based biocomposites after dissolution in ionic liquid and regeneration in water. We propose a novel theoretical model that correlates the composite's microscopic structure to its bulk properties. We rely on modeling non-cross-linked biopolymers that present layer-like structures such as ß-sheets and we successfully predict structural, thermal, and mechanical properties of a mixture of these biomolecules. Our model and experiments show that the solubility of the pure substance in the chosen solvent can be used to modulate the amount of crystallinity of the biopolymer blend, as measured by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). Thermogravimetric analysis (TGA) shows that the decomposition temperature of the blended biocomposites compared to their pure counterparts is reduced in accordance with our theoretical predictions. The morphology of the material is further characterized through scanning electron microscopy (SEM) and shows differently exposed surface area depending on the blend. Finally, differential scanning calorimetry (DSC) is performed to characterize the residual water content in the material, essential for explaining the regeneration process in water. As a final test of the model, we compare our model's prediction of the Young's modulus with existing data in the literature. The model correctly reproduces experimental trends observed in the Young's modulus due to varying the concentration of silk in the biopolymer blend.

Computational and experimental analysis of short peptide motifs for enzyme inhibition.

The metabolism of living systems involves many enzymes that play key roles as catalysts and are essential to biological function. Searching ligands with the ability to modulate enzyme activities is central to diagnosis and therapeutics. Peptides represent a promising class of potential enzyme modulators due to the large chemical diversity, and well-established methods for library synthesis. Peptides and their derivatives are found to play critical roles in modulating enzymes and mediating cellular uptakes, which are increasingly valuable in therapeutics. We present a methodology that uses molecular dynamics (MD) and point-variant screening to identify short peptide motifs that are critical for inhibiting ß-galactosidase (ß-Gal). MD was used to simulate the conformations of peptides and to suggest short motifs that were most populated in simulated conformations. The function of the simulated motifs was further validated by the experimental point-variant screening as critical segments for inhibiting the enzyme. Based on the validated motifs, we eventually identified a 7-mer short peptide for inhibiting an enzyme with low µM IC50. The advantage of our methodology is the relatively simplified simulation that is informative enough to identify the critical sequence of a peptide inhibitor, with a precision comparable to truncation and alanine scanning experiments. Our combined experimental and computational approach does not rely on a detailed understanding of mechanistic and structural details. The MD simulation suggests the populated motifs that are consistent with the results of the experimental alanine and truncation scanning. This approach appears to be applicable to both natural and artificial peptides. With more discovered short motifs in the future, they could be exploited for modulating biocatalysis, and developing new medicine.

Impact of Phosphorylation and Pseudophosphorylation on the Early Stages of Aggregation of the Microtubule-Associated Protein Tau.

The microtubule-associated protein tau regulates the stability of microtubules within neurons in the central nervous system. In turn, microtubules are responsible for the remodeling of the cytoskeleton that ultimately leads to the formation or pruning of new connections among neurons. As a consequence, dysfunction of tau is associated with many forms of dementia as well as Alzheimer's disease. In the brain, tau activity is regulated by its phosphorylation state. Phosphorylation is a post-translational modification of proteins that adds a phosphate group to the side chain of an amino acid. Phosphorylation at key locations in the tau sequence leads to a higher or lower affinity for microtubules. In Alzheimer's disease, tau is present in an abnormal phosphorylation state. However, studying the effect of phosphorylation experimentally has been extremely challenging as there is no viable way of exactly selecting the location and the number of phosphorylated sites. For this reason, researchers have turned to pseudophosphorylation. In this technique, actual phosphorylation is mimicked by mutating the selected amino acid into glutamate or aspartate. Whether this methodology is equivalent to actual phosphorylation is still open to debate. In this study, we will show that phosphorylation and pseudophosphorylation are not exactly equivalent. Although for larger aggregates the two techniques lead to similar structures, the kinetics of the process may be altered. In addition, very little is known about the impact that this may have on the early stages of aggregation, such as nucleation and conformational rearrangement. In this study, we show that the two methods may produce a similar ensemble of conformations, even though the kinetic and chemical details that lead to it are quite different.