Jian-Min Yuan

The thermodynamics and kinetics of protein folding and protein aggregation in vivo are of great importance in numerous scientific areas including fundamental biophysics research, nanotechnology, and medicine. However, these processes remain poorly understood in both in vivo and in vitro systems. Here we extend an established model for protein aggregation that is based on the kinetic equations for the moments of the polymer size distribution by introducing macromolecular crowding particles into the model using scaled-particle and transition-state theories. The model predicts that the presence of crowders can either speed up, cause no change to, or slow down the progress of the aggregation compared to crowder-free solutions, in striking agreement with experimental results from nine different amyloid-forming proteins that utilized dextran as the crowder. These different dynamic effects of macromolecular crowding can be understood in terms of the change of excluded volume associated with each reaction step.

Fatigue adversely impacts quality of life in old age. The relationship between subjective and objective measurements of fatigue, however, is poorly understood. We examined whether subjective fatigue moderated the expression of objective fatigue during locomotion. Associations between objective and subjective measures of fatigue were predicted to manifest only under dual-task conditions that maximized cognitive demands. Participants were 314 nondemented older adults (age = 76.8±6.7 years; % female = 56). Functional near-infrared spectroscopy was used to assess oxygenated hemoglobin (HbO2) levels during walking. A 4×14-foot Zeno electronic walkway was utilized to assess stride velocity (cm/s). Objective fatigue was operationalized as attenuation in HbO2 levels and decline in stride velocity (cm/s) during six continuous straight walks under single- (normal-walk) and dual-task (walk-while-talk) conditions. The Brief Fatigue Inventory assessed subjective fatigue. Worse subjective fatigue was associated with attenuated increase in HbO2 levels (estimate = 0.175; p < .05) but not with decline in stride velocity (estimate = 0.394; p > .05) from normal-walk to walk-while-talk conditions. Objective fatigue did not manifest and was not associated with subjective fatigue during the course of normal-walk. Worse subjective fatigue was associated with attenuated HbO2 levels in the fourth (estimate = -0.178; p < .05), fifth (estimate = -0.230; p < .01), and sixth (estimate = -0.231; p < .01) straight walks compared to the first during walk-while-talk. Dual-task walking paradigms provide a unique environment to simultaneously assess different facets of fatigue. The prefrontal cortex subserves both subjective and objective measurements of fatigue as defined in the context of attention-demanding locomotion.

The equilibrium and kinetic properties of protein aggregation systems in the presence of crowders are investigated using simple, illuminating models based on mass-action laws. Our model yields analytic results for equilibrium properties of protein aggregates, which fit experimental data of actin and ApoC-II with crowders reasonably well. When the effects of crowders on rate constants are considered, our kinetic model is in good agreement with experimental results for actin with dextran as the crowder. Furthermore, the model shows that as crowder volume fraction increases, the length distribution of fibrils becomes narrower and shifts to shorter values due to volume exclusion. (C) 2016 Elsevier B.V. All rights reserved.

Due to high fluctuations and quantum uncertainty, the processes of single-molecules should be treated by stochastic methods. To study fluorescence time series and their statistical properties, we have applied two stochastic methods, one of which is an analytic method to study the off-time distributions of certain fluorescence transitions and the other is Gillespie's method of stochastic simulations. These methods have been applied to study the optical transition properties of two single-molecule systems, GFPmut2 and a Dronpa-like molecule, to yield results in approximate agreement with experimental observations on these systems. Rigorous oscillatory time series of GFPmut2 before it unfolds in the presence of denaturants have not been obtained based on the stochastic method used, but, on the other hand, the stochastic treatment puts constraints on the conditions under which such oscillatory behavior is possible. Furthermore, a sensitivity analysis is carried out on GFPmut2 to assess the effects of transition rates on the observables, such as fluorescence intensities.

In this work, we present a kinetic analysis for protein aggregation using the kinetic Ising model, which serves as a new application of a previously proposed model [Liang et al., J. Chin. Chem. Soc. 2003, 50, 335]. Considering protein as a single spin unit, we map two states of a unit to the aggregation-prone (AP) and the fibril (F) states. This work shows that the model can successfully capture the nucleation-growth features of protein aggregation from experiments, which offers thermodynamic interpretations of aggregation properties, such as lag-time and fibril stability.

Protein aggregation is an important field of investigation because it is closely related to the problem of neurodegenerative diseases, to the development of biomaterials, and to the growth of cellular structures such as cyto-skeleton. Self-aggregation of protein amyloids, for example, is a complicated process involving many species and levels of structures. This complexity, however, can be dealt with using statistical mechanical tools, such as free energies, partition functions, and transfer matrices. In this article, we review general strategies for studying protein aggregation using statistical mechanical approaches and show that canonical and grand canonical ensembles can be used in such approaches. The grand canonical approach is particularly convenient since competing pathways of assembly and dis-assembly can be considered simultaneously. Another advantage of using statistical mechanics is that numerically exact solutions can be obtained for all of the thermodynamic properties of fibrils, such as the amount of fibrils formed, as a function of initial protein concentration. Furthermore, statistical mechanics models can be used to fit experimental data when they are available for comparison.

The b-hairpin is a building block in the -sheet structure. Understanding the formation of the -hairpin may provide insight into the formation of -sheet structures in, for example, protein amyloids. In this study, we performed molecular dynamics (MD) simulations to investigate the temperature-dependent transition behaviors of the GB1 -hairpin peptide. The simulated results are analysed in terms of distances between pairs of peptide bonds and site-dependent dihedral angles. Our results show that the properties of the hairpin can be site-dependent and that the dependency is primarily associated with the hairpin's geometrical shape and specific interactions, such as hydrophobic clustering. Thus our study provides a foundation for the interpretation of probe-dependent experimental results.