花器官发育的分子机制研究进展

经典的ABC模型成功地解释了模式植物拟南芥和金鱼草因同源异型基因突变而引起的植物花器官的变异。随后,大量花器官特征基因和新突变体的研究不断完善和发展了ABC模型。该文综述了近年来花器官发育分子模型及花器官同源基因的调控机理等方面的最新研究成果,并对未来的研究方向进行了展望,以期为深入了解花发育的分子机理和遗传机制奠定基础。     

Analysis and quantification of a mixed exo-acting and endo-acting polysaccharide depolymerization system

A new mathematical model has been proposed based on a model presented by Suga, van Dedem, and Moo-Young.(10) The model requires a separate differential equation for each polymeric species (differentiated by degree of polymerization) in the reaction mixture. The main contribution of this model is the incorporation of experimental molecular weight distributions as the initial conditions. These molecular weight distributional as the initial conditions were obtained using modern analytical equipment previouly unknown for this application. The equipment, SEC/LALLS, measures relative concentrations of specific molecular weight species along with the corresponding molecular weights, thus yielding (through some mathematical manipulation) the absolute concentration of each molecular weight species. The concentration at each molecular weight can then be incorporated as the initial condition for that equation. Theoretically, the system of differential equations can be solved to give a more realistic time course of reaction.Synergism between endo-acting and exo-acting enzymes was examined theoretically using the mathematical model. Through model predictions, it was found that synergy is based on two fundamental parameters: (1) each enzyme's activity relative to the sum of enzyme activities and, (2) overall substrate concentration relative to the exo-acting enzyme's Michaeiis kinetic constant K(m). Theoretically, synergism increases as a function of reaction time. Intermediate endo fractions (ratio of endo-acting enzyme activity to the sum of endo-acting and exo-acting enzyme activity) from 0.3 to 0.7 exhibit the most synergism. Values of k[log(K(m, exo)/S(0))] above about zero also exhibits the most synergism.An examination of experimental data obtained both by SEC/LALLS and by reducing sugar measurements shows that the model is inadequate for successfully predicting quantities associated with the substrate during reaction. This is especially true for synergism predictions. At short reaction times, the model predicts the data fairly well, but at longer times the predictions are inconsistent with experimental data. These inconsistencies may be due to complicating phenomena such as enzyme inhibitions.     

Come FLY with us: toward understanding fragile X syndrome

The past few years have seen an increased number of articles using Drosophila as a model system to study fragile X syndrome. Phenotypic analyses have demonstrated an array of neuronal and behavioral defects similar to the phenotypes reported in mouse models as well as human patients. The availability of both cellular and molecular tools along with the power of genetics makes the tiny fruit fly a premiere model in elucidating the molecular basis of fragile X syndrome. Here, we summarize the advances made in recent years in the characterization of fragile X Drosophila models and the identification of new molecular partners in neural development.     

Biological networks 101: Computational modeling for molecular biologists

Computational modeling of biological networks permits the comprehensive analysis of cells and tissues to define molecular phenotypes and novel hypotheses. Although a large number of software tools have been developed, the versatility of these tools is limited by mathematical complexities that prevent their broad adoption and effective use by molecular biologists. This study clarifies the basic aspects of molecular modeling, how to convert data into useful input, as well as the number of time points and molecular parameters that should be considered for molecular regulatory models with both explanatory and predictive potential. We illustrate the necessary experimental preconditions for converting data into a computational model of network dynamics. This model requires neither a thorough background in mathematics nor precise data on intracellular concentrations, binding affinities or reaction kinetics. Finally, we show how an interactive model of crosstalk between signal transduction pathways in primary human articular chondrocytes allows insight into processes that regulate gene expression.     

Receptor independent and receptor dependent CoMSA modeling with IVE-PLS: application to CBG benchmark steroids and reductase activators

Comparative molecular surface analysis (CoMSA) with robust IVE-PLS variable elimination if tested for the benchmark CBG steroid series provides highly predictive RI 3D QSAR models, but failed however to model the activity of sulforaphane (SP) activators of quinone reductase. The application of the SP poses obtained from multipose molecular docking to model the RD IVE-PLS CoMSA resulted in a predictive form. This model indicated lipophilic potential as the activity determinant. The individual molecular surface areas of the highest contribution to the SP activity was identified and visualized by CoMSA contour plots.     

Resistance of Bacillus Endospores to Extreme Terrestrial and Extraterrestrial Environments

Endospores of Bacillus spp., especially Bacillus subtilis, have served as experimental models for exploring the molecular mechanisms underlying the incredible longevity of spores and their resistance to environmental insults. In this review we summarize the molecular laboratory model of spore resistance mechanisms and attempt to use the model as a basis for exploration of the resistance of spores to environmental extremes both on Earth and during postulated interplanetary transfer through space as a result of natural impact processes.     

The discovery of inhibitors of Fas-mediated cell death pathway using the combined computational method

In this study, pharmacophore and 3D-QSAR models were developed for analogues of 3-substituted-benzofuran-2-carboxylate as inhibitors of Fas-mediated cell death pathways. Our pharmacophore model has good correspondence with experimental results and can explain the variance in biological activities coherently with respect to the structure of the data set compounds. The predictive power for our synthesized compounds were 0.96 for the pharmacophore model, 0.58 for the comparative molecular field analysis (CoMFA) model, and 0.57 for the comparative molecular similarity analysis (CoMSIA) model.     

Mechanisms of controlled release from silk fibroin films

The controlled release of fluorescein-iso-thio-cyanate (FITC)-labeled dextrans from methanol-treated and untreated silk fibroin films was modeled to characterize the release kinetics and mechanisms. Silk films were prepared with FITC-dextrans of various molecular weights (4, 10, 20, 40 kDa). Methanol treatment was used to promote crystallinity. The release data were assessed with two different models, an empirical exponential equation commonly fit to release data and a mechanism-based semiempirical model derived from Fickian diffusion through a porous film. The FITC-dextran release kinetics were evaluated as a function of molecular weight and compared between the untreated- and methanol-treated films. For the empirical model, the estimated values of the model parameters decreased with the molecular weight of the analyte and showed no significant difference between untreated- and methanol-treated films. For the diffusion-based model, the estimated diffusion coefficient was smaller for the methanol-treated films than for the untreated films. Also, the diffusion coefficient was observed to decrease linearly with increasing molecular weight of the analyte. The percent of FITC-dextran loading entrapped and not released was less for the methanol-treated films than for untreated films and linearly increased with molecular weight. A linear regression was fit to the relationship between molecular weight and the percent of entrapped FITC-dextran particles. Using these defined linear relationships, we present an updated version of the diffusion model for simulating release of FITC-dextran of varied molecular weights from methanol-treated and untreated silk films.     

Resistance of Bacillus endospores to extreme terrestrial and extraterrestrial environments.

Endospores of Bacillus spp., especially Bacillus subtilis, have served as experimental models for exploring the molecular mechanisms underlying the incredible longevity of spores and their resistance to environmental insults. In this review we summarize the molecular laboratory model of spore resistance mechanisms and attempt to use the model as a basis for exploration of the resistance of spores to environmental extremes both on Earth and during postulated interplanetary transfer through space as a result of natural impact processes.     

Molecular modeling of the structures of human and rat pancreatic cholesterol esterases.

Structural models have been generated for rat and human cholesterol esterases by molecular modeling. For rat cholesterol esterase, three separate models were generated according to the following procedure: (1) the cholesterol esterase sequence was aligned with those of three template enzymes: Torpedo californica acetylcholinesterase, Geotrichum candidum lipase and Candida rugosa lipase; (2) the X-ray structure coordinates of the three template enzymes were used to construct cholesterol esterase models by amino acid replacements of matched sequence positions and by making sequence insertions and deletions as required; (3) bad contracts in each of the cholesterol esterase models were relaxed by molecular dynamics and mechanics; (4) the three cholesterol esterase models were merged into one by arithmetic averaging of atomic coordinates; (5) Ramachandran analysis indicated that the model generated from the AChE template possessed the best set of phi/psi angles. Therefore, this model was subjected to molecular dynamics, with harmonic constraints imposed on the C(alpha) coordinates to drive them toward the coordinates of the averaged model. (6) Subsequent relaxation by molecular mechanics produced the final rat cholesterol esterase model. A model for human cholesterol esterase was produced by repeating steps 1-3 above, albeit with the rat cholesterol esterase model as the template. Hydrophobic and electrostatic analyses of the rat and human cholesterol esterase models suggest the structural origins of molecular recognition of hydrophobic substrates and interfaces, of charged interfaces, and of bile salt activators.     

Improved hidden Markov models for molecular motors, part 1: basic theory

Hidden Markov models (HMMs) provide an excellent analysis of recordings with very poor signal/noise ratio made from systems such as ion channels which switch among a few states. This method has also recently been used for modeling the kinetic rate constants of molecular motors, where the observable variable—the position—steadily accumulates as a result of the motor's reaction cycle. We present a new HMM implementation for obtaining the chemical-kinetic model of a molecular motor's reaction cycle called the variable-stepsize HMM in which the quantized position variable is represented by a large number of states of the Markov model. Unlike previous methods, the model allows for arbitrary distributions of step sizes, and allows these distributions to be estimated. The result is a robust algorithm that requires little or no user input for characterizing the stepping kinetics of molecular motors as recorded by optical techniques.     

Molecular dynamics simulations of the interaction of phospholipid bilayers with polycaprolactone

The molecular interaction between common polymer chains and the cell membrane is unknown. Molecular dynamics simulations offer an emerging tool to characterise the nature of the interaction between common degradable polymer chains used in biomedical applications, such as polycaprolactone, and model cell membranes. Herein we characterise with all-atomistic and coarse-grained molecular dynamics simulations the interaction between single polycaprolactone chains of varying chain lengths with a phospholipid membrane. We find that the length of the polymer chain greatly affects the nature of interaction with the membrane, as well as the membrane properties. Furthermore, we next utilise advanced sampling techniques in molecular dynamics to characterise the two-dimensional free energy surface for the interaction of varying polymer chain lengths (short, intermediate, and long) with model cell membranes. We find that the free energy minimum shifts from the membrane-water interface to the hydrophobic core of the phospholipid membrane as a function of chain length. Finally, we perform coarse-grained molecular dynamics simulations of slightly larger membranes with polymers of the same length and characterise the results as compared with all-atomistic molecular dynamics simulations. These results can be used to design polymer chain lengths and chemistries to optimise their interaction with cell membranes at the molecular level.     

Hsp70 Reduces alpha-Synuclein Aggregation and Toxicity

Aggregation and cytotoxicity of misfolded alpha-synuclein is postulated to be crucial in the disease process of neurodegenerative disorders such as Parkinson's disease and DLB (dementia with Lewy bodies). In this study, we detected misfolded and aggregated alpha-synuclein in a Triton X-100 insoluble fraction as well as a high molecular weight product by gel electrophoresis of temporal neocortex from DLB patients but not from controls. We also found similar Triton X-100 insoluble forms of alpha-synuclein in an alpha-synuclein transgenic mouse model and in an in vitro model of alpha-synuclein aggregation. Introducing the molecular chaperone Hsp70 into the in vivo model by breeding alpha-synuclein transgenic mice with Hsp70-overexpressing mice led to a significant reduction in both the high molecular weight and detergent-insoluble alpha-synuclein species. Concomitantly, we found that Hsp70 overexpression in vitro similarly reduced detergent-insoluble alpha-synuclein species and protected cells from alpha-synuclein-induced cellular toxicity. Taken together, these data demonstrate that the molecular chaperone Hsp70 can reduce the amount of misfolded, aggregated alpha-synuclein species in vivo and in vitro and protect it from alpha-synuclein-dependent toxicity.     

Molecular Adsorption on Cold Gas-Phase Hydrogen-Bonded Clusters of Chiral Molecules

Origins of Life and Evolution of Biospheres - Gas-phase molecular adsorption was investigated as a model for molecular cloud formation. Molecular adsorption on cold gas-phase hydrogen-bonded...     

Evolution and development of model membranes for physicochemical and functional studies of the membrane lateral heterogeneity

One of the main questions in the membrane biology is the functional roles of membrane heterogeneity and molecular localization. Although segregation and local enrichment of protein/lipid components (rafts) have been extensively studied, the presence and functions of such membrane domains still remain elusive. Along with biochemical, cell observation, and simulation studies, model membranes are emerging as an important tool for understanding the biological membrane, providing quantitative information on the physicochemical properties of membrane proteins and lipids. Segregation of fluid lipid bilayer into liquid-ordered (Lo) and liquid-disordered (Ld) phases has been studied as a simplified model of raft in model membranes, including giant unilamellar vesicles (GUVs), giant plasma membrane vesicles (GPMVs), and supported lipid bilayers (SLB). Partition coefficients of membrane proteins between Lo and Ld phases were measured to gauze their affinities to lipid rafts (raftophilicity). One important development in model membrane is patterned SLB based on the microfabrication technology. Patterned Lo/Ld phases have been applied to study the partition and function of membrane-bound molecules. Quantitative information of individual molecular species attained by model membranes is critical for elucidating the molecular functions in the complex web of molecular interactions. The present review gives a short account of the model membranes developed for studying the lateral heterogeneity, especially focusing on patterned model membranes on solid substrates.     

Insights from molecular modeling and dynamics simulation of pathogen resistance (R) protein from brinjal

Resistance (R) protein recognizes molecular signature of pathogen infection and activates downstream hypersensitive response signalling in plants. R protein works as a molecular switch for pathogen defence signalling and represent one of the largest plant gene family. Hence, understanding molecular structure and function of R proteins has been of paramount importance for plant biologists. The present study is aimed at predicting structure of R proteins signalling domains (CC-NBS) by creating a homology model, refining and optimising the model by molecular dynamics simulation and comparing ADP and ATP binding. Based on sequence similarity with proteins of known structures, CC-NBS domains were initially modelled using CED- 4 (cell death abnormality protein) and APAF-1 (apoptotic protease activating factor) as multiple templates. The final CC-NBS structural model was built and optimized by molecular dynamic simulation for 5 nanoseconds (ns). Docking of ADP and ATP at active site shows that both ligand bind specifically with same residues and with minor difference (1 Kcal/mol) in binding energy. Sharing of binding site by ADP and ATP and low difference in their binding site makes CC-NBS suitable for working as molecular switch. Furthermore, structural superimposition elucidate that CC-NBS and CARD (caspase recruitment domains) domain of CED-4 have low RMSD value of 0.9 A° Availability of 3D structural model for both CC and NBS domains will . help in getting deeper insight in these pathogen defence genes.     

A gaussian model for substrates of entangled cross-linked poly(ethylene glycol) in biomedical applications

Cells usually spread on a synthetic substrate through bonds between receptors and chemical groups on the substrate (ligands). Therefore, it is valuable to study the effects of the average number density of these chemical groups and the average distance between them to model and predict the cell behavior. Poly(ethylene glycol) [PEG] modified with peptide groups has been used widely in biomedical applications as a substrate material. In this study, a coarse-grained model is proposed for PEG to predict the average number density of ligands and the average distance between them. Molecular information such as initial molecular weight distribution, average molecular weight between cross-links, and average molecular weight between entanglements is used as input parameters. Based on simulation results, it is concluded that both entanglement and cross-link densities are required to create a network structure. The results suggest that an average initial molecular weight 2-3 times the average molecular weight between entanglements and a moderate cross-link density are sufficient to create a closed network structure with a high ligand density and a small average distance between them.