Foolishness : Kidder

https://digitalcommons.library.umaine.edu/mmb-vp/1467/thumbnail.jp

Grid-based state space exploration for molecular binding

Binding processes are difficult to sample with molecular-dynamics (MD) simulations. In particular, the state space exploration is often incomplete. Evaluating the molecular interaction energy on a grid circumvents this problem but is heavily limited by state space dimensionality. Here, we make the first steps towards a low-dimensional grid-based model of molecular binding. We discretise the state space of relative positions and orientations of the two molecules under the rigid body assumption.The corresponding program is published as the Python package molgri. For the rotational component of the grids, we test algorithms based on Euler angles, polyhedra and quaternions, of which the polyhedra-based are the most uniform. The program outputs a sequence of molecular structures that can be easily processed by standard MD programs to calculate grid point energies. We demonstrate the grid-based approach on two molecular systems: a water dimer and a coiled-coil protein interacting with a chloride anion. For the second system we relax the rigid-body assumption and improve the accuracy of the grid point energies by an energy minimisation. In both cases, oriented bonding patterns and energies confirm expectations from chemical intuition and MD simulations. We also demonstrate how analysis of energy contributions on a grid can be performed and demonstrate that electrostatically-driven association is sufficiently resolved by point-energy calculations. Overall, grid-based models of molecular binding are potentially a powerful complement to molecular sampling approaches, and we see the potential to expand the method to quantum chemistry and flexible docking applications.Comment: 13 pages, 7 figure

How Chromophore Labels Shape the Structure and Dynamics of a Peptide Hydrogel

Biocompatible and functionalizable hydrogels have a wide range of (potential) medicinal applications. The hydrogelation process, particularly for systems with very low polymer weight percentages (<1 wt %), remains poorly understood, making it challenging to predict the self-assembly of a given molecular building block into a hydrogel. This severely hinders the rational design of self-assembled hydrogels. In this study, we demonstrate the impact of an N-terminal group on the self-assembly and rheology of the peptide hydrogel hFF03 (hydrogelating, fibril forming peptide 03) using molecular dynamics simulations, oscillatory shear rheology, and circular dichroism spectroscopy. We find that the chromophore and even its specific regioisomers have a significant influence on the microscopic structure and dynamics of the self-assembled fibril, and on the macroscopic mechanical properties. This is because the chromophore influences the possible salt bridges, which form and stabilize the fibril formation. Furthermore, we find that the solvation shell fibrils by itself cannot explain the viscoelasticity of hFF03 hydrogels. Our atomistic model of the hFF03 fibril formation enables a more rational design of these hydrogels. In particular, altering the N-terminal chromophore emerges as a design strategy to tune the mechanic properties of these self-assembled peptide hydrogels

How chromophore labels shape the structure and dynamics of a peptide hydrogel

Biocompatible and functionalizable hydrogels have a wide range of (potential) medicinal applications. In contrast to conventional hydrogels formed by interconnected or interlocked polymer chains, self-assembled hydrogels form from small building blocks like short peptide chains. This has the advantage that the building blocks can be functionalized separately and then mixed to obtain the desired properties. However, the hydrogelation process for these systems, especially those with very low polymer weight percentage (< 1 wt%), is not well understood, and therefore it is hard to predict whether a given molecular building block will self-assemble into a hydrogel. This severely hinders the rational design of self-assembled hydrogels. In this study, we demonstrate the impact of an N-terminal chromophore label amino-benzoic acid on the self-assembly and rheology of hydrogel hFF03 (hydrogelating, fibril forming) using molecular dynamics simulations, which self-assembles into {\alpha}-helical coiled-coils. We find that the chromophore and even its specific regioisomers have a significant influence on the microscopic structure and dynamics of the self-assembled fibril, and on the macroscopic mechanical properties. This is because the chromophore influences the possible salt-bridges which form and stabilize the fibril formation. Furthermore we find that the solvation shell fibrils by itself cannot explain the viscoelasticity of hFF03 hydrogels. Our atomistic model of the hFF03 fibril formation enables a more rational design of these hydrogels. In particular, altering the N-terminal chromophore emergesas a design strategy to tune the mechanic properties of these self-assembled peptide hydrogels.Comment: 15 pages, 15 including appendi

Impact of glycan nature on structure and viscoelastic properties of glycopeptide hydrogels

Mucus is a complex biological hydrogel that acts as a barrier for almost everything entering or exiting the body. It is therefore of emerging interest for biomedical and pharmaceutical applications. Besides water, the most abundant components are the large and densely glycosylated mucins, glycoproteins of up to 20 MDa and carbohydrate content of up to 80 wt%. Here, we designed and explored a library of glycosylated peptides to deconstruct the complexity of mucus. Using the well-characterized hFF03 coiled-coil system as a hydrogel-forming peptide scaffold, we systematically probed the contribution of single glycans to the secondary structure as well as the formation and viscoelastic properties of the resulting hydrogels. We show that glycan-decoration does not affect α-helix and coiled-coil formation while it alters gel stiffness. By using oscillatory macrorheology, dynamic light scattering microrheology, and fluorescence lifetime-based nanorheology, we characterized the glycopeptide materials over several length scales. Molecular simulations revealed that the glycosylated linker may extend into the solvent, but more frequently interacts with the peptide, thereby likely modifying the stability of the self-assembled fibers. This systematic study highlights the interplay between glycan structure and hydrogel properties and may guide the development of synthetic mucus mimetics

Human Cerebral Neuropathology of Type 2 Diabetes Mellitus

The cerebral neuropathology of Type 2 diabetes (CNDM2) has not been positively defined. This review includes a description of CNDM2 research from before the ‘Pubmed Era’. Recent neuroimaging studies have focused on cerebrovascular and white matter pathology. These and prior studies about cerebrovascular histopathology in diabetes are reviewed. Evidence is also described for and against the link between CNDM2 and Alzheimer\u27s disease pathogenesis. To study this matter directly, we evaluated data from University of Kentucky Alzheimer\u27s Disease Center (UK ADC) patients recruited while non-demented and followed longitudinally. Of patients who had come to autopsy (N = 234), 139 met inclusion criteria. These patients provided the basis for comparing the prevalence of pathological and clinical indices between well-characterized cases with (N = 50) or without (N = 89) the premortem diagnosis of diabetes. In diabetics, cerebrovascular pathology was more frequent and Alzheimer-type pathology was less frequent than in non-diabetics. Finally, a series of photomicrographs demonstrates histopathological features (including clinical–radiographical correlation) observed in brains of persons that died after a history of diabetes. These preliminary, correlative, and descriptive studies may help develop new hypotheses about CNDM2. We conclude that more work should be performed on human material in the context of CNDM2

The Impacts of Elicitation Mechanism and Reward Size on Estimated Rates of Time Preference

We run experiments with real monetary rewards ranging from $10 to$500 to estimate rates of time preference and test for hyperbolic discounting. Individuals become more patient with increasing reward sizes, which is consistent with a magnitude effect. This magnitude effect is robust across specifications including a nonparametric analysis and structural maximum likelihood estimation. Subjects are divided between two different elicitation mechanisms (one a matching task and one a choice task) that should both theoretically provide an incentive for participants to reveal their true time preferences. We find some evidence of differences between the rates from the matching and choice tasks but these differences disappear when appropriately modeling the behavioral noise. We uncover little to no evidence of present-biased time preferences