Kinetic behavior of the general modifier mechanism of Botts and Morales with non-equilibrium binding

In this paper, we perform a complete analysis of the kinetic behavior of the general modifier mechanism of Botts and Morales in both equilibrium steady states and non-equilibrium steady states (NESS). Enlightened by the non-equilibrium theory of Markov chains, we introduce the net flux into discussion and acquire an expression of product rate in NESS, which has clear biophysical significance. Up till now, it is a general belief that being an activator or an inhibitor is an intrinsic property of the modifier. However, we reveal that this traditional point of view is based on the equilibrium assumption. A modifier may no longer be an overall activator or inhibitor when the reaction system is not in equilibrium. Based on the regulation of enzyme activity by the modifier concentration, we classify the kinetic behavior of the modifier into three categories, which are named hyperbolic behavior, bell-shaped behavior, and switching behavior, respectively. We show that the switching phenomenon, in which a modifier may convert between an activator and an inhibitor when the modifier concentration varies, occurs only in NESS. Effects of drugs on the Pgp ATPase activity, where drugs may convert from activators to inhibitors with the increase of the drug concentration, are taken as a typical example to demonstrate the occurrence of the switching phenomenon.Comment: 19 pages, 10 figure

Amyloidogenesis Abolished by Proline Substitutions but Enhanced by Lipid Binding

The influence of lipid molecules on the aggregation of a highly amyloidogenic segment of human islet amyloid polypeptide, hIAPP20–29, and the corresponding sequence from rat has been studied by all-atom replica exchange molecular dynamics (REMD) simulations with explicit solvent model. hIAPP20–29 fragments aggregate into partially ordered β-sheet oligomers and then undergo large conformational reorganization and convert into parallel/antiparallel β-sheet oligomers in mixed in-register and out-of-register patterns. The hydrophobic interaction between lipid tails and residues at positions 23–25 is found to stabilize the ordered β-sheet structure, indicating a catalysis role of lipid molecules in hIAPP20–29 self-assembly. The rat IAPP variants with three proline residues maintain unstructured micelle-like oligomers, which is consistent with non-amyloidogenic behavior observed in experimental studies. Our study provides the atomic resolution descriptions of the catalytic function of lipid molecules on the aggregation of IAPP peptides

Dynamic behavior of a vehicle with rear axle compliance steering

Rear axle compliance steering (RACS) is a technology of passive four-wheel steering, which is designed to improve the vehicle handling and stability at medium or high speed. This paper focuses on the dynamic behavior of the vehicle with RACS. Firstly, the compliance steering principle for different rear suspensions is illustrated. Then, the viscoelastic members with fractional order derivative properties are introduced into RACS, and the fractional order model of RACS is formulated. Next, the dynamic model of the vehicle with RACS is established, the adjusting rules for the compliance steering stiffness are derived, and the vehicle stability is investigated. Finally, numerical experiments are performed to illustrate the effects on the vehicle dynamic behavior caused by the compliance steering stiffness, the viscoelastic members and the vehicle longitudinal velocity. Research results show that, the vehicle with RACS has better dynamic characteristics than that without RACS at medium or high speed; and the compliance steering stiffness, the viscoelastic members and the vehicle longitudinal velocity have different impacts on the vehicle lateral dynamic behavior

How tyramine β-hydroxylase controls the production of octopamine, modulating the mobility of beetles

Biogenic amines perform many kinds of important physiological functions in the central nervous system (CNS) of insects, acting as neuromodulators, neurotransmitters, and neurohormones. The five most abundant types of biogenic amines in invertebrates are dopamine, histamine, serotonin, tyramine, and octopamine (OA). However, in beetles, an important group of model and pest insects, the role of tyramine beta-hydroxylase (T beta H) in the OA biosynthesis pathway and the regulation of behavior remains unknown so far. We therefore investigated the molecular characterization and spatiotemporal expression profiles of T beta H in red flour beetles (Triboliun castaneum). Most importantly, we detected the production of OA and measured the crawling speed of beetles after dsTcT beta H injection. We concluded that TcT beta H controls the biosynthesis amount of OA in the CNS, and this in turn modulates the mobility of the beetles. Our new results provided basic information about the key genes in the OA biosynthesis pathway of the beetles, and expanded our knowledge on the physiological functions of OA in insects

Optimizing and controlling functions of complex networks by manipulating rich-club connections

Traditionally, there is no evidence suggesting that there are strong ties between the rich-club property and the function of complex networks. In this study, we find that whether a very small portion of rich nodes connected to each other or not can strongly affect the frequency of occurrence of basic building blocks (motif) within networks, and therefore the function, of a heterogeneous network. Conversely whether a homogeneous network has a rich-club property or not generally has no significant effect on its structure and function. These findings open the possibility to optimize and control the function of complex networks by manipulating rich-club connections. Furthermore, based on the subgraph ratio profile, we develop a more rigorous approach to judge whether a network has a rich-club or not. The new method does not calculate how many links there are among rich nodes but depends on how the links among rich nodes can affect the overall structure as well as function of a given network. These results can also help us to understand the evolution of dynamical networks and design new models for characterizing real-world networks.Comment: 6 pages, 3 figure