植物创伤诱导的挥发物及其信号功能

植物在受到动物或病原侵害时,会释放特异的挥发作作为信号,这些信号分子是植物防御系统的重要组成部分,文章对植物创伤诱导挥发物的种类,诱导因子及生理作用等的研究进展,以及这一领域的研究潜力和发展方向作了评述。     

缩醛磷脂的功能及信号传导机制研究进展

缩醛磷脂(plasmalogen)是甘油骨架C-1位置上含有烯醚键的磷脂,作为哺乳动物细胞质膜的结构成分广泛分布于生物电强的组织中。它可以调节质膜的流动,是多不饱和脂肪酸的储存库,并可作为内源抗氧化剂保护细胞氧化应激。同时,缩醛磷脂还与细胞信号传导有关。     

生长素信号转导途径及参与的生物学功能研究进展

生长素参与植物生长和发育诸多过程,调控众多生理反应,在植物整个生命周期中自始至终发挥着调节作用.研究生长素的作用机制,对深入认识植物生长发育的生理过程有着重要的意义.综述了与生长素信号转导途径相关的3类主要蛋白组分:生长素/吲哚乙酸蛋白(auxin/indoleacetic acids proteins,Aux/IAAs)、生长素响应因子(auxin response factors,ARFs)和SCF(SKP1-CDC53/CUL1-F-box)复合体,及相关的SGT1(suppressor of the G2 allele of skp1)基因,并对生长素相关基因表达的模式及其生物学功能进行了总结.     

植物中的MAPK及其在信号传导中的作用

促分裂原活化蛋白激酶(MAPKs)是一类存在于真核生物中的丝氨酸/苏氨酸蛋白激酶。同动物和酵母中MAPKs类似,植物中的MAPK级联途径也是由MAPKs、MAPKKs、MAPKKKs三种类型的激酶组成。植物细胞内受体接受外界刺激信号,然后依次磷酸化激活MAPKKKs、MAPKKs和MAPKs,并影响相关基因表达。目前已经从植物中分离到一些MAPKs、MAPKKs和MAPKKKs,它们参与了植物激素、生物胁迫及非生物胁迫等过程的信号传导。介绍了植物响应外界环境胁迫过程中,不同机制和因子对MAPKs级联途径的调控。     

Signal-LMS:一种局部序列匹配相似度预测信号肽的方法

信号肽预测是蛋白质功能预测中最重要的问题之一。为了避免使用滑动窗口造成的样本不平衡等问题,序列比对方法被有效地运用到了信号肽预测中。考虑到信号肽是蛋白质序列局部片段所体现的生物特性,本文提出一种局部序列匹配相似度的方法来预测信号肽,在采用氨基酸相对疏水性编码方案的基础上,搜索蛋白质局部匹配子序列,根据替换矩阵BLOSUM62来度量两个蛋白质的相似性,最后采用k最近邻思想进行分类。在目前广泛使用的SwissProt数据集上进行实验,结果表明该方法具有一定的高预测率。     

Parameterization for In-Silico Modeling of Ion Channel Interactions with Drugs

Since the first Hodgkin and Huxley ion channel model was described in the 1950s, there has been an explosion in mathematical models to describe ion channel function. As experimental data has become richer, models have concomitantly been improved to better represent ion channel kinetic processes, although these improvements have generally resulted in more model complexity and an increase in the number of parameters necessary to populate the models. Models have also been developed to explicitly model drug interactions with ion channels. Recent models of drug-channel interactions account for the discrete kinetics of drug interaction with distinct ion channel state conformations, as it has become clear that such interactions underlie complex emergent kinetics such as use-dependent block. Here, we describe an approach for developing a model for ion channel drug interactions. The method describes the process of extracting rate constants from experimental electrophysiological function data to use as initial conditions for the model parameters. We then describe implementation of a parameter optimization method to refine the model rate constants describing ion channel drug kinetics. The algorithm takes advantage of readily available parallel computing tools to speed up the optimization. Finally, we describe some potential applications of the platform including the potential for gaining fundamental mechanistic insights into ion channel function and applications to in silico drug screening and development.     

拟南芥AtMEKK1的结构特征和信号转导功能

促分裂原活化蛋白激酶（MAPK）级联途径是真核生物中高度保守的信号通路。MAPK级联途径由MAPKs、MAPKKs和MAPKKKs组成,通过MAPKKK→MAPKK→MAPK的逐级磷酸化传递细胞信号。AtMEKK1是拟南芥MAPKKK家族中的一员,是目前研究较为详细的MAPKKK。本文就AtMEKK1的结构特征、生理功能、信号转导中的＂交谈＂及其复杂性进行综述,旨在探讨植物MAPKKK的信号转导作用。     

Class I Myosins Have Overlapping and Specialized Functions in Left-Right Asymmetric Development in Drosophila

The class I myosin genes are conserved in diverse organisms, and their gene products are involved in actin dynamics, endocytosis, and signal transduction. Drosophila melanogaster has three class I myosin genes, Myosin 31DF (Myo31DF), Myosin 61F (Myo61F), and Myosin 95E (Myo95E). Myo31DF, Myo61F, and Myo95E belong to the Myosin ID, Myosin IC, and Myosin IB families, respectively. Previous loss-of-function analyses of Myo31DF and Myo61F revealed important roles in left–right (LR) asymmetric development and enterocyte maintenance, respectively. However, it was difficult to elucidate their roles in vivo, because of potential redundant activities. Here we generated class I myosin double and triple mutants to address this issue. We found that the triple mutant was viable and fertile, indicating that all three class I myosins were dispensable for survival. A loss-of-function analysis revealed further that Myo31DF and Myo61F, but not Myo95E, had redundant functions in promoting the dextral LR asymmetric development of the male genitalia. Myo61F overexpression is known to antagonize the dextral activity of Myo31DF in various Drosophila organs. Thus, the LR-reversing activity of overexpressed Myo61F may not reflect its physiological function. The endogenous activity of Myo61F in promoting dextral LR asymmetric development was observed in the male genitalia, but not the embryonic gut, another LR asymmetric organ. Thus, Myo61F and Myo31DF, but not Myo95E, play tissue-specific, redundant roles in LR asymmetric development. Our studies also revealed differential colocalization of the class I myosins with filamentous (F)-actin in the brush border of intestinal enterocytes.     

Parameterization and Application of an Implicit Solvent Model for Macromolecules

Abstract

As the field of theoretical biophysics begins to recognize systems of longer timescales and larger magnitude, rapid approaches for investigating these systems are required. One promising simplification of the typical system of a solute surrounded by water is the use of implicit solvation models. The generalized Born implicit solvent offers a rapid approach for computing the electrostatic effects of bulk solvent without the explicit representation of water molecules. This report describes the parameterization of a generalized Born (GB) model for protein and nucleic acid structures. As a demonstration of the usefulness of this approach, the GB model is applied toward the discrimination of misfolded and properly folded protein structures. This study attempts to illustrate the potential of the GB model for molecular dynamics simulations over longer timescales as well as for screening large structural databases.     

Transfer Functions for Protein Signal Transduction: Application to a Model of Striatal Neural Plasticity

We present a novel formulation for biochemical reaction networks in the context of protein signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of “source” species, which are interpreted as input signals. Signals are transmitted to all other species in the system (the “target” species) with a specific delay and with a specific transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and even recalled to build dynamical models on the basis of state changes. By separating the temporal and the magnitudinal domain we can greatly simplify the computational model, circumventing typical problems of complex dynamical systems. The transfer function transformation of biochemical reaction systems can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant novel insights while remaining a fully testable and executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modularizations that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. Remarkably, we found that overall interconnectedness depends on the magnitude of inputs, with higher connectivity at low input concentrations and significant modularization at moderate to high input concentrations. This general result, which directly follows from the properties of individual transfer functions, contradicts notions of ubiquitous complexity by showing input-dependent signal transmission inactivation.     

RedMDStream: Parameterization and Simulation Toolbox for Coarse-Grained Molecular Dynamics Models

Coarse-grained (CG) models in molecular dynamics (MD) are powerful tools to simulate the dynamics of large biomolecular systems on micro- to millisecond timescales. However, the CG model, potential energy terms, and parameters are typically not transferable between different molecules and problems. So parameterizing CG force fields, which is both tedious and time-consuming, is often necessary. We present RedMDStream, a software for developing, testing, and simulating biomolecules with CG MD models. Development includes an automatic procedure for the optimization of potential energy parameters based on metaheuristic methods. As an example we describe the parameterization of a simple CG MD model of an RNA hairpin.     

Agent-Based Model with Asymmetric Trading and Herding for Complex Financial Systems

Background

For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results.

Methods

To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors’ asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data.

Results

With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities.

Conclusions

We reveal that for the leverage and anti-leverage effects, both the investors’ asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors’ trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries.     

Microbial Resolution of 1-Phenoxy-2-propanol by Stereospecific Decomposition and Asymmetric Hydrolysis of 1-Phenoxy-2-propyl Acetate

We screened microorganisms for those that resolved a stereoisomer from rac-1-phenoxy-2-propyl acetate (PPAc). Several species of Nocardia and Rhodococcus hydrolyzed rac-PPAc to rac-1-phenoxy-2-propanol (PPol), and then selectively decomposed an isomer of PPol, leading to an accumulation of (R)-PPol. Several yeasts and bacteria hydrolyzed PPAc asymmetrically, affording (R)-PPol and the ester of (S)-PPol. An enzyme that catalyzed the asymmetric hydrolysis of PPAc was partially purified from Corynebacterium glutamicum ATCC 13059 and characterized. The enzymatic hydrolysis was highly specific for (R)-PPAc.     

Parameterization and optimization of the menthol force field for molecular dynamics simulations

Menthol’s various biological properties render it a useful component for medical and cosmetological applications, while its three centers of asymmetry mean that it can be used in a range of organic reactions. Menthol-substituted ionic liquids (ILs) have been found to exhibit promising antimicrobial and antielectrostatic properties, as well as being useful in organic catalysis and biochemical studies. However, so far, a force field designed and validated specifically for the menthol molecule has not been constructed. In the present work, the validation and optimization of force field parameters with regard to the ability to reproduce the macroscopic properties of menthol is presented. The set of optimized potentials for liquid simulations all atom (OPLS-AA) compatible parameters was tested and carefully tuned. The refinement of parameters included fitting of partial atomic charges, optimization of Lennard-Jones parameters, and recalculation of the dihedral angle parameters needed to reproduce quantum energy profiles. To validate the force field, a variety of physicochemical properties were calculated for liquid menthol. Both thermodynamic and kinetic properties were taken into account, including density, surface tension, enthalpy of vaporization, and shear viscosity. The obtained force field was proven to accurately reproduce the properties of the investigated compound while being fully compatible with the OPLS-AA force field.

     

Quantifying the Likelihood of Co-existence for Communities with Asymmetric Competition

Trade-offs in performance of different ecological functions within a species are commonly offered as an explanation for co-existence in natural communities. Single trade-offs between competitive ability and other life history traits have been shown to support a large number of species, as a result of strong competitive asymmetry. We consider a single competition-fecundity trade-off in a homogeneous environment, and examine the effect of the form of asymmetry on the likelihood of species co-existing. We find conditions that allow co-existence of two species for a general competition function, and show that (1)?two species can only co-exist if the competition function is sufficiently steep when the species are similar; (2)?when competition is determined by a linear function, no more than two species can co-exist; (3)?when the competition between two individuals is determined by a discontinuous step function, this single trade-off can support an arbitrarily large number of species. Further, we show analytically that as the degree of asymmetry in competition increases, the probability of a given number of species co-existing also increases, but note that even in the most favourable conditions, large numbers of species co-existing along a single trade-off is highly unlikely. On this basis, we suggest it is unlikely that single trade-offs are able to support high levels of bio-diversity without interacting other processes.     

A General Framework for Thermodynamically Consistent Parameterization and Efficient Sampling of Enzymatic Reactions

Kinetic models provide the means to understand and predict the dynamic behaviour of enzymes upon different perturbations. Despite their obvious advantages, classical parameterizations require large amounts of data to fit their parameters. Particularly, enzymes displaying complex reaction and regulatory (allosteric) mechanisms require a great number of parameters and are therefore often represented by approximate formulae, thereby facilitating the fitting but ignoring many real kinetic behaviours. Here, we show that full exploration of the plausible kinetic space for any enzyme can be achieved using sampling strategies provided a thermodynamically feasible parameterization is used. To this end, we developed a General Reaction Assembly and Sampling Platform (GRASP) capable of consistently parameterizing and sampling accurate kinetic models using minimal reference data. The former integrates the generalized MWC model and the elementary reaction formalism. By formulating the appropriate thermodynamic constraints, our framework enables parameterization of any oligomeric enzyme kinetics without sacrificing complexity or using simplifying assumptions. This thermodynamically safe parameterization relies on the definition of a reference state upon which feasible parameter sets can be efficiently sampled. Uniform sampling of the kinetics space enabled dissecting enzyme catalysis and revealing the impact of thermodynamics on reaction kinetics. Our analysis distinguished three reaction elasticity regions for common biochemical reactions: a steep linear region (0> ΔG_r >-2 kJ/mol), a transition region (-2> ΔG_r >-20 kJ/mol) and a constant elasticity region (ΔG_r <-20 kJ/mol). We also applied this framework to model more complex kinetic behaviours such as the monomeric cooperativity of the mammalian glucokinase and the ultrasensitive response of the phosphoenolpyruvate carboxylase of Escherichia coli. In both cases, our approach described appropriately not only the kinetic behaviour of these enzymes, but it also provided insights about the particular features underpinning the observed kinetics. Overall, this framework will enable systematic parameterization and sampling of enzymatic reactions.     

The Intramembrane Proteases Signal Peptide Peptidase-Like 2a and 2b Have Distinct Functions In Vivo

We reported recently that the presenilin homologue signal peptide peptidase-like 2a (SPPL2a) is essential for B cell development by cleaving the N-terminal fragment (NTF) of the invariant chain (li, CD74). Based on this, we suggested that pharmacological modulation of SPPL2a may represent a novel approach to deplete B cells in autoimmune disorders. With regard to reported overlapping substrate spectra of SPPL2a and its close homologue, SPPL2b, we investigated the role of SPPL2b in CD74 NTF proteolysis and its impact on B and dendritic cell homeostasis. In heterologous expression experiments, SPPL2b was found to cleave CD74 NTF with an efficiency simliar to that of SPPL2a. For in vivo analysis, SPPL2b single-deficient and SPPL2a/SPPL2b double-deficient mice were generated and examined for CD74 NTF turnover/accumulation, B cell maturation and functionality, and dendritic cell homeostasis. We demonstrate that in vivo SPPL2b does not exhibit a physiologically relevant contribution to CD74 proteolysis in B and dendritic cells. Furthermore, we reveal that both proteases exhibit divergent subcellular localizations in B cells and different expression profiles in murine tissues. These findings suggest distinct functions of SPPL2a and SPPL2b and, based on a high abundance of SPPL2b in brain, a physiological role of this protease in the central nervous system.