基于免疫进化算法（IEA）的鹤望兰(Strelitzia reginae)叶面积指数(LAI)模拟

免疫进化算法（IEA）是基于遗传算法（GA）的一种“加强局部搜索,兼顾全局搜索”的进化算法。利用免疫进化算法（IEA）对鹤望兰叶面积指数（IAI）进行模拟,平均相对误差为3．44％,取得满意的结果,对鹤望兰栽培管理有一定的实际意义。免疫进化算法用于鹤望兰叶面积指数模拟简便、易行,为鹤望兰叶面积指数模拟模型的建立及参数优化开辟了一条新途径。     

Confronting Uncertainty in Life Cycle Assessment Used for Decision Support

The aim of this article is to help confront uncertainty in life cycle assessments (LCAs) used for decision support. LCAs offer a quantitative approach to assess environmental effects of products, technologies, and services and are conducted by an LCA practitioner or analyst (AN) to support the decision maker (DM) in making the best possible choice for the environment. At present, some DMs do not trust the LCA to be a reliable decision‐support tool—often because DMs consider the uncertainty of an LCA to be too large. The standard evaluation of uncertainty in LCAs is an ex‐post approach that can be described as a variance simulation based on individual data points used in an LCA. This article develops and proposes a taxonomy for LCAs based on extensive research in the LCA, management, and economic literature. This taxonomy can be used ex ante to support planning and communication between an AN and DM regarding which type of LCA study to employ for the decision context at hand. This taxonomy enables the derivation of an LCA classification matrix to clearly identify and communicate the type of a given LCA. By relating the LCA classification matrix to statistical principles, we can also rank the different types of LCA on an expected inherent uncertainty scale that can be used to confront and address potential uncertainty. However, this article does not attempt to offer a quantitative approach for assessing uncertainty in LCAs used for decision support.     

Molecular dynamics simulations of peptides and proteins with a continuum electrostatic model based on screened Coulomb potentials

A continuum electrostatics approach for molecular dynamics (MD) simulations of macromolecules is presented and analyzed for its performance on a peptide and a globular protein. The approach incorporates the screened Coulomb potential (SCP) continuum model of electrostatics, which was reported earlier. The model was validated in a broad set of tests some of which were based on Monte Carlo simulations that included single amino acids, peptides, and proteins. The implementation for large-scale MD simulations presented in this article is based on a pairwise potential that makes the electrostatic model suitable for fast analytical calculation of forces. To assess the suitability of the approach, a preliminary validation is conducted, which consists of (i) a 3-ns MD simulation of the immunoglobulin-binding domain of streptococcal protein G, a 56-residue globular protein and (ii) a 3-ns simulation of Dynorphin, a biological peptide of 17 amino acids. In both cases, the results are compared with those obtained from MD simulations using explicit water (EW) molecules in an all-atom representation. The initial structure of Dynorphin was assumed to be an alpha-helix between residues 1 and 9 as suggested from NMR measurements in micelles. The results obtained in the MD simulations show that the helical structure collapses early in the simulation, a behavior observed in the EW simulation and consistent with spectroscopic data that suggest that the peptide may adopt mainly an extended conformation in water. The dynamics of protein G calculated with the SCP implicit solvent model (SCP-ISM) reveals a stable structure that conserves all the elements of secondary structure throughout the entire simulation time. The average structures calculated from the trajectories with the implicit and explicit solvent models had a cRMSD of 1.1 A, whereas each average structure had a cRMSD of about 0.8A with respect to the X-ray structure. The main conformational differences of the average structures with respect to the crystal structure occur in the loop involving residues 8-14. Despite the overall similarity of the simulated dynamics with EW and SCP models, fluctuations of side-chains are larger when the implicit solvent is used, especially in solvent exposed side-chains. The MD simulation of Dynorphin was extended to 40 ns to study its behavior in an aqueous environment. This long simulation showed that the peptide has a tendency to form an alpha-helical structure in water, but the stabilization free energy is too weak, resulting in frequent interconversions between random and helical conformations during the simulation time. The results reported here suggest that the SCP implicit solvent model is adequate to describe electrostatic effects in MD simulation of both peptides and proteins using the same set of parameters. It is suggested that the present approach could form the basis for the development of a reliable and general continuum approach for use in molecular biology, and directions are outlined for attaining this long-term goal.     

Models in researching cardiovascular morphogenesis

Several types of “models” are used in modern biological and biomedical research and teaching. This article attempts to provide a brief explanation of the termini model organism, theoretic and mathematic model, three‐dimensional (3D) model, and 4D model, and an overview about the generation and the fields of applications of these types of models. It will then focus on the application of theoretic and mathematic models, 3D models, 4D models, and simulation for researching cardiovascular morphogenesis. Birth Defects Research (Part C) 96:163–175, 2012. © 2012 Wiley Periodicals, Inc.     

NMMD: Efficient Cryo-EM Flexible Fitting Based on Simultaneous Normal Mode and Molecular Dynamics atomic displacements

Atomic models of cryo electron microscopy (cryo-EM) maps of biomolecular conformations are often obtained by flexible fitting of the maps with available atomic structures of other conformations (e.g., obtained by X-ray crystallography). This article presents a new flexible fitting method, NMMD, which combines normal mode analysis (NMA) and molecular dynamics simulation (MD). Given an atomic structure and a cryo-EM map to fit, NMMD simultaneously estimates global atomic displacements based on NMA and local displacements based on MD. NMMD was implemented by modifying EMfit, a flexible fitting method using MD only, in GENESIS 1.4. As EMfit, NMMD can be run with replica exchange umbrella sampling procedure. The new method was tested using a variety of EM maps (synthetic and experimental, with different noise levels and resolutions). The results of the tests show that adding normal modes to MD-based fitting makes the fitting faster (40% in average) and, in the majority of cases, more accurate.     

Bacterial classification with convolutional neural networks based on different data reduction layers

Abstract

For high accuracy classification of DNA sequences through Convolutional Neural Networks (CNNs), it is essential to use an efficient sequence representation that can accelerate similarity comparison between DNA sequences. In addition, CNN networks can be improved by avoiding the dimensionality problem associated with multi-layer CNN features. This paper presents a new approach for classification of bacterial DNA sequences based on a custom layer. A CNN is used with Frequency Chaos Game Representation (FCGR) of DNA. The FCGR is adopted as a sequence representation method with a suitable choice of the frequency k-lengthen words occurrence in DNA sequences. The DNA sequence is mapped using FCGR that produces an image of a gene sequence. This sequence displays both local and global patterns. A pre-trained CNN is built for image classification. First, the image is converted to feature maps through convolutional layers. This is sometimes followed by a down-sampling operation that reduces the spatial size of the feature map and removes redundant spatial information using the pooling layers. The Random Projection (RP) with an activation function, which carries data with a decent variety with some randomness, is suggested instead of the pooling layers. The feature reduction is achieved while keeping the high accuracy for classifying bacteria into taxonomic levels. The simulation results show that the proposed CNN based on RP has a trade-off between accuracy score and processing time.     

Viral structural transition mechanisms revealed by multiscale molecular dynamics/order parameter extrapolation simulation

On the basis of an all‐atom multiscale analysis theory of nanosystem dynamics, a multiscale molecular dynamics/order parameter extrapolation (MD/OPX) approach has recently been developed. It accelerates MD for long‐time simulation of large bionanosystems and addresses rapid atomistic fluctuations and slowly varying coherent dynamics simultaneously. In this study, MD/OPX is optimized and implemented to simulate viral capsid structural transitions. Specifically, 200 ns MD/OPX simulation of the swollen state of cowpea chlorotic mottle virus capsid reveals that it undergoes significant energy‐driven shrinkage in vacuum, which is a symmetry‐breaking process involving local initiation and front propagation. © 2009 Wiley Periodicals, Inc. Biopolymers 93: 61–73, 2010. This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com     

Extending the capabilities of targeted molecular dynamics: simulation of a large conformational transition in plasminogen activator inhibitor 1

Plasminogen activator inhibitor type 1 (PAI-1) is an inhibitor of plasminogen activators such as tissue-type plasminogen activator or urokinase-type plasminogen activator. For this molecule, different conformations are known. The inhibiting form that interacts with the proteinases is called the active form. The noninhibitory, noncleavable form is called the latent form. X-ray and modeling studies have revealed a large change in position of the reactive center loop (RCL), responsible for the interaction with the proteinases, that is inserted into a beta-sheet (s4A) in the latent form. The mechanism underlying this spontaneous conformational change (half-life = 2 h at 37 degrees C) is not known in detail. This investigation attempts to predict a transition path from the active to the latent structure at the atomic level, by using simulation techniques. Together with targeted molecular dynamics (TMD), a plausible assumption on a rigid body movement of the RCL was applied to define an initial guess for an intermediate. Different pathways were simulated, from the active to the intermediate, from the intermediate to the latent structure and vice versa under different conditions. Equilibrium simulations at different steps of the path also were performed. The results show that a continuous pathway from the active to the latent structure can be modeled. This study also shows that this approach may be applied in general to model large conformational changes in any kind of protein for which the initial and final three-dimensional structure is known.     

胰高血糖素样肽1与干细胞定向分化

糖尿病已经成为21世纪严重威胁人类健康的疾病之一。胰岛移植被认为是治疗Ⅰ型和部分Ⅱ型糖尿病的最有效方法。然而,供体组织来源的匮乏限制了其应用。随着细胞移植和组织工程的日益发展,干细胞研究为新型胰岛的来源开辟了新的途径。干细胞定向诱导分化的关键是筛选合适的诱导剂以及优化诱导微环境,使干细胞培养微环境尽可能接近体内正常细胞发育分化的微环境,从而有利于干细胞适宜生长及定向分化。最近研究证实,胰高血糖素样肽1（Glucagon- Like PeptideⅠ,GLP-1）在干细胞向胰岛样细胞诱导分化中具有显著作用。因此,为了更好地应用GLP-1在干细胞定向分化中的潜能、促进应用干细胞治疗糖尿病新疗法研究的进程及干细胞定向分化技术逐渐成熟,本文就胰高血糖素样肽-1及它诱导干细胞定向分化胰岛样细胞的研究进展作一阐述。     

Electrostatic interactions determine entrance/release order of substrates in the catalytic cycle of adenylate kinase

Adenylate kinase is a monomeric phosphotransferase with important biological function in regulating concentration of adenosine triphosphate (ATP) in cells, by transferring the terminal phosphate group from ATP to adenosine monophosphate (AMP) and forming two adenosine diphosphate (ADP) molecules. During this reaction, the kinase may undergo a large conformational transition, forming different states with its substrates. Although many structures of the protein are available, atomic details of the whole process remain unclear. In this article, we use both conventional molecular dynamics (MD) simulation and an enhanced sampling technique called parallel cascade selection MD simulation to explore different conformational states of the Escherichia coli adenylate kinase. Based on the simulation results, we propose a possible entrance/release order of substrates during the catalytic cycle. The substrate-free protein prefers an open conformation, but changes to a closed state once ATP·Mg enters into its binding pocket first and then AMP does. After the reaction of ATP transferring the terminal phosphate group to AMP, ADP·Mg and ADP are released sequentially, and finally the whole catalyze cycle is completed. Detailed contact and distance analysis reveals that the entrance/release order of substrates may be largely controlled by electrostatic interactions between the protein and the substrates.     

TomoFlow: Analysis of Continuous Conformational Variability of Macromolecules in Cryogenic Subtomograms based on 3D Dense Optical Flow

Cryogenic Electron Tomography (cryo-ET) allows structural and dynamics studies of macromolecules in situ. Averaging different copies of imaged macromolecules is commonly used to obtain their structure at higher resolution and discrete classification to analyze their dynamics. Instrumental and data processing developments are progressively equipping cryo-ET studies with the ability to escape the trap of classification into a complete continuous conformational variability analysis. In this work, we propose TomoFlow, a method for analyzing macromolecular continuous conformational variability in cryo-ET subtomograms based on a three-dimensional dense optical flow (OF) approach. The resultant lower-dimensional conformational space allows generating movies of macromolecular motion and obtaining subtomogram averages by grouping conformationally similar subtomograms. The animations and the subtomogram group averages reveal accurate trajectories of macromolecular motion based on a novel mathematical model that makes use of OF properties. This paper describes TomoFlow with tests on simulated datasets generated using different techniques, namely Normal Mode Analysis and Molecular Dynamics Simulation. It also shows an application of TomoFlow on a dataset of nucleosomes in situ, which provided promising results coherent with previous findings using the same dataset but without imposing any prior knowledge on the analysis of the conformational variability. The method is discussed with its potential uses and limitations.     

Generalized correlation for biomolecular dynamics

Correlated motions in biomolecules are often essential for their function, e.g., allosteric signal transduction or mechanical/thermodynamic energy transport. Because correlated motions in biomolecules remain difficult to access experimentally, molecular dynamics (MD) simulations are particular useful for their analysis. The established method to quantify correlations from MD simulations via calculation of the covariance matrix, however, is restricted to linear correlations and therefore misses part of the correlations in the atomic fluctuations. Herein, we propose a general statistical mechanics approach to detect and quantify any correlated motion from MD trajectories. This generalized correlation measure is contrasted with correlations obtained from covariance matrices for the B1 domain of protein G and T4 lysozyme. The new method successfully quantifies correlations and provides a valuable global overview over the functionally relevant collective motions of lysozyme. In particular, correlated motions of helix 1 together with the two main lobes of lysozyme are detected, which are not seen by the conventional covariance matrix. Overall, the established method misses more than 50% of the correlation. This failure is attributed to both, an interfering and unnecessary dependence on mutual orientations of the atomic fluctuations and, to a lesser extent, attributed to nonlinear correlations. Our generalized correlation measure overcomes these problems and, moreover, allows for an improved understanding of the conformational dynamics by separating linear and nonlinear contributions of the correlation.     

Enhanced sampling of peptide and protein conformations using replica exchange simulations with a peptide backbone biasing-potential

During replica exchange molecular dynamics (RexMD) simulations, several replicas of a system are simulated at different temperatures in parallel allowing for exchange between replicas at frequent intervals. This technique allows significantly improved sampling of conformational space and is increasingly being used for structure prediction of peptides and proteins. A drawback of the standard temperature RexMD is the rapid increase of the replica number with increasing system size to cover a desired temperature range. In an effort to limit the number of replicas, a new Hamiltonian-RexMD method has been developed that is specifically designed to enhance the sampling of peptide and protein conformations by applying various levels of a backbone biasing potential for each replica run. The biasing potential lowers the barrier for backbone dihedral transitions and promotes enhanced peptide backbone transitions along the replica coordinate. The application on several peptide cases including in all cases explicit solvent indicates significantly improved conformational sampling when compared with standard MD simulations. This was achieved with a very modest number of 5-7 replicas for each simulation system making it ideally suited for peptide and protein folding simulations as well as refinement of protein model structures in the presence of explicit solvent.     

Molecular dynamics simulations reveal structural insights into inhibitor binding modes and mechanism of casein kinase II inhibitors

Casein kinase-II, a member of protein kinase family, plays significant role in different cellular processes such as cell growth, differentiation, proliferation, gene expression, and embryogenesis. Being a potent suppressor of apoptosis, it serves as a significant link for its association with various types of malignancies such as colorectal and breast cancer. To overcome its pathological role in various cancerous diseases, CK-II procures great consideration as a therapeutic target. This study aimed at understanding the binding mechanism and structural properties of benzimidazole derivatives by utilizing various computational tools including docking simulation, three-dimensional quantitative structure activity relationships and molecular dynamic simulation. Structure-based 3D-QSAR techniques such as CoMFA and CoMSIA models, were established from the conformations gained by protein–ligand docking approach. The attained models have showed a good extrapolative power for internal as well as external validation. Moreover, MD simulation was carried out to explain the detailed binding mechanism and the comparison of inhibitor’s binding mode with diverse biological activities. A good correlation was observed among docking studies, MD results, and contour map analysis. Interestingly new molecules were designed using detail structural information from MD simulation, showed higher potency of inhibition (pIC₅₀ 7.6–7.7) compare to the most active compound of the series.     

Barriers to Industrial Symbiosis: Insights from the Use of a Maturity Grid

The concept of industrial symbiosis (IS) over the last 20 years has become a well‐recognized approach for environmental improvements at the regional level. Many technical solutions for waste and by‐product material, water, and energy reuse between neighboring industries (so‐called synergies) have been discovered and applied in the IS examples from all over the world. However, the potential for uptake of new synergies in the regions is often limited by a range of nontechnical barriers. These barriers include environmental regulation, lack of cooperation and trust between industries in the area, economic barriers, and lack of information sharing. Although several approaches to help identify and overcome some of the nontechnical barriers were examined, no methodology was found that systematically assessed and tracked the barriers to guide the progress of IS development. This article presents a new tool—IS maturity grid—to tackle this issue in the regional IS studies. The tool helps monitor and assess the level of regional industrial collaboration and also indicates a potential path for further improvements and development in an industrial region, depending on where that region currently lies in the grid. The application of the developed tool to the Gladstone industrial region of Queensland, Australia, is presented in the article. It showed that Gladstone is at the third (active) stage of five stages of maturity, with cooperation and trust among industries the strongest characteristic and information barriers the characteristic for greatest improvement.     

Molecular dynamics simulations of alanine rich beta-sheet oligomers: Insight into amyloid formation

The aggregation observed in protein conformational diseases is the outcome of significant new beta-sheet structure not present in the native state. Peptide model systems have been useful in studies of fibril aggregate formation. Experimentally, it was found that a short peptide AGAAAAGA is one of the most highly amyloidogenic peptides. This peptide corresponds to the Syrian hamster prion protein (ShPrP) residues 113-120. The peptide was observed to be conserved in all species for which the PrP sequence has been determined. We have simulated the stabilities of oligomeric AGAAAAGA and AAAAAAAA (A8) by molecular dynamic simulations. Oligomers of both AGAAAAGA and AAAAAAAA were found to be stable when the size is 6 to 8 (hexamer to octamer). Subsequent simulation of an additional alpha-helical AAAAAAAA placed on the A8-octamer surface has revealed molecular events related to conformational change and oligomer growth. Our study addresses both the minimal oligomeric size of an aggregate seed and the mechanism of seed growth. Our simulations of the prion-derived 8-residue amyloidogenic peptide and its variant have indicated that an octamer is stable enough to be a seed and that the driving force for stabilization is the hydrophobic effect.     

Bodily selves in relation: embodied simulation as second-person perspective on intersubjectivity

This article addresses basic aspects of social cognition focusing on the pivotal role played by the lived body in the constitution of our experience of others. It is suggested that before studying intersubjectivity we should better qualify the notion of the self. A minimal notion of the self, the bodily self, defined in terms of its motor potentialities, is proposed. The discovery of mirror mechanisms for action, emotions and sensations led to the proposal of an embodied approach to intersubjectivity—embodied simulation (ES) theory. ES and the related notion of neural reuse provide a new empirically based perspective on intersubjectivity, viewed first and foremost as intercorporeality. ES challenges the notion that folk psychology is the sole account of interpersonal understanding. ES is discussed within a second-person perspective on mindreading.     

Current state and prospects of biotechnology in Central and Eastern European countries. Part I: Visegrad countries (CZ,H, PL,SK)

Innovation is a key determinant of sustainable growth. Biotechnology (BT) is one such industry that has witnessed a revolution in innovative ideas leading to the founding of many new companies based on providing products, solutions and services, stretching from the food industry to environmental remediation, and new medicines. BT holds much promise for the development of national and local economies, however, this requires a strategic approach involving actors within government, industry, and academia working in concert to maximize this potential. This first article reviews the current “state of play” in the field of BT within the Central Eastern European (CEE) countries. For the purposes of this article, CEE refers to the countries of Czech Republic, Hungary, Poland, and Slovakia (the so-called Visegrad – V4 countries). We examine the components that support the creation and development of a BT sector in CEE and also highlight the barriers to these objectives. Clearly setting priorities for the countries’ policy agenda, as well as the alignment of Smart Specialization Strategy will help to focus efforts. Recent investments in R&D infrastructure within CEE have been substantial, but conditions will need to be optimized to harness these largely European investments for effective use towards SME high-tech development.     

Biochemical simulations: stochastic, approximate stochastic and hybrid approaches

Computer simulations have become an invaluable tool to studythe sometimes counterintuitive temporal dynamics of (bio-)chemicalsystems. In particular, stochastic simulation methods have attractedincreasing interest recently. In contrast to the well-knowndeterministic approach based on ordinary differential equations,they can capture effects that occur due to the underlying discretenessof the systems and random fluctuations in molecular numbers.Numerous stochastic, approximate stochastic and hybrid simulationmethods have been proposed in the literature. In this article,they are systematically reviewed in order to guide the researcherand help her find the appropriate method for a specific problem.