Coarse-grained normal mode analysis in structural biology

The realization that experimentally observed functional motions of proteins can be predicted by coarse-grained normal mode analysis has renewed interest in applications to structural biology. Notable applications include the prediction of biologically relevant motions of proteins and supramolecular structures driven by their structure-encoded collective dynamics; the refinement of low-resolution structures, including those determined by cryo-electron microscopy; and the identification of conserved dynamic patterns and mechanically key regions within protein families. Additionally, hybrid methods that couple atomic simulations with deformations derived from coarse-grained normal mode analysis are able to sample collective motions beyond the range of conventional molecular dynamics simulations. Such applications have provided great insight into the underlying principles linking protein structures to their dynamics and their dynamics to their functions.     

基元模式分析在生物网络和途径分析中的应用

基元模式分析是应用最广泛的代谢途径分析方法。基元模式分析的研究对象从代谢网络发展到信号传导网络;研究尺度从细胞到生物反应器,甚至生态系统;数学描述从稳态分解到动态解析;研究领域从微生物代谢到人类疾病。以下综述了基元模式分析的算法和软件开发现状,以及其在代谢途径与鲁棒性、代谢通量分解、稳态代谢通量分析、动态模型与生物过程模拟、网络结构与调控、菌株设计和信号传导网络等方面的应用。开发新的算法解决组合爆炸问题,探索基元模式与代谢调控的关系以及提高菌株设计算法效率是今后基元模式的重要发展方向。     

缀块性和缀块动态:Ⅱ.描述与分析

在生态学中,“缀块”(patch)的概念早已在植被群落和海洋生态系统中浮游动植物空间分布研究中广泛应用。A.S.Watte早在1947年就强调缀块在植物群落结构分析中的重要性。实际上,缀块存在于地球的任何地方。森林可     

Predicting large-scale conformational changes in proteins using energy-weighted normal modes

We report the development of a method to improve the sampling of protein conformational space in molecular simulations. It is shown that a principal component analysis of energy-weighted normal modes in Cartesian coordinates can be used to extract vectors suitable for describing the dynamics of protein substructures. The method can operate with either atomistic or user-defined coarse-grained models of protein structure. An implicit reverse coarse-graining allows the dynamics of all-atoms to be recovered when a coarse-grained model is used. For an external test set of four proteins, it is shown that the new method is more successful than normal mode analysis in describing the large-scale conformational changes observed on ligand binding. The method has potential applications in protein-ligand and protein-protein docking and in biasing molecular dynamics simulations.     

Building-block approach for determining low-frequency normal modes of macromolecules

Normal mode analysis of proteins of various sizes, ranging from 46 (crambin) up to 858 residues (dimeric citrate synthase) were performed, by using standard approaches, as well as a recently proposed method that rests on the hypothesis that low-frequency normal modes of proteins can be described as pure rigid-body motions of blocks of consecutive amino-acid residues. Such a hypothesis is strongly supported by our results, because we show that the latter method, named RTB, yields very accurate approximations for the low-frequency normal modes of all proteins considered. Moreover, the quality of the normal modes thus obtained depends very little on the way the polypeptidic chain is split into blocks. Noteworthy, with six amino-acids per block, the normal modes are almost as accurate as with a single amino-acid per block. In this case, for a protein of n residues and N atoms, the RTB method requires the diagonalization of an n x n matrix, whereas standard procedures require the diagonalization of a 3N x 3N matrix. Being a fast method, our approach can be useful for normal mode analyses of large systems, paving the way for further developments and applications in contexts for which the normal modes are needed frequently, as for example during molecular dynamics calculations.     

Antifungal activity and mode of action of silver nano-particles on Candida albicans

In this study, the antifungal effects of silver nano-particles (nano-Ag) and their mode of action were investigated. Nano-Ag showed antifungal effects on fungi tested with low hemolytic effects against human erythrocytes. To elucidate the antifungal mode of action of nano-Ag, flow cytometry analysis, a glucose-release test, transmission electron microscopy (TEM) and the change in membrane dynamics using 1,6-diphenyl-1,3,5-hexatriene (DPH), as a plasma membrane probe, were performed with Candida albicans. The results suggest nano-Ag may exert an antifungal activity by disrupting the structure of the cell membrane and inhibiting the normal budding process due to the destruction of the membrane integrity. The present study indicates nano-Ag has considerable antifungal activity, deserving further investigation for clinical applications. K.-J. Kim and W. S. Sung contributed equally to this work and should be considered co-first authors.     

Single-molecule analysis of chromatin: changing the view of genomes one molecule at a time

Wrapping DNA into chromatin provides a wealth of regulatory mechanisms that ensure normal growth and development in eukaryotes. Our understanding of chromatin structure, including nucleosomes and non-histone protein-DNA interactions, has benefited immensely from nuclease and chemical digestion techniques. DNA-bound proteins, such as histones or site-specific factors, protect DNA against nuclease cleavage and generate large nucleosomal or small regulatory factor footprints. Chromatin subject to distinct modes of regulation often coincides with sites of nuclease hypersensitivity or nucleosome positioning. An inherent limitation of cleavage-based analyses has been the inability to reliably analyze regions of interest when levels of digestion depart from single-hit kinetics. Moreover, cleavage-based techniques provide views that are averaged over all the molecules in a sample population. Therefore, in cases of occupancy of multiple regulatory elements by factors, one cannot define whether the factors are bound to the same or different molecules in the population. The recent development of DNA methyltransferase-based, single-molecule MAP-IT technology overcomes limitations of ensemble approaches and has opened numerous new avenues in chromatin research. Here, we review the strengths, limitations, applications and future prospects of MAP-IT ranging from structural issues to mechanistic questions in eukaryotic chromatin regulation.     

生物医学数据分析中的深度学习方法应用

生物医学数据的积累速度史无前例,为生物医学研究带来机遇的同时,也让传统数据分析技术面临巨大挑战.本文综述了深度学习方法应用在生物医学数据分析中的最新研究进展.首先阐述了深度学习方法,列举深度学习方法的主要实现模型,随后总结了目前生物医学数据分析中的深度学习方法应用情况,分析了在数据处理、模型构建和训练方法等方面共有问题的解决方法,最后给出了深度学习方法应用于生物医学数据分析时可能存在的问题及建议.     

Genome-wide mRNA profiling: impact on compound evaluation and target identification in anti-bacterial research

Array-based mRNA profiling offers a variety of opportunities to address different issues relevant to anti-bacterial research. The technique can be used to investigate the mode of action of antibiotics, bacterial resistance mechanisms and virulence factors, and to identify novel targets. This review discusses recent developments of this highly innovative field of technology with respect to technical requirements and experimental design. Several applications are described in which bacterial mRNA profiling has already been successfully performed, illustrating how the generation of large numbers of diverse datasets can be used as a powerful tool for evaluating anti-bacterial compounds and consequent counteracting mechanisms in the cell.     

Assay of prostaglandin-like substances in faeces and their measurement in ulcerative colitis

A method is described for extracting and measuring prostaglandin-like substances from faeces. Bioassay has shown virtual absence of activity in stools from normal people (8 subjects) but raised levels in stools from patients with active ulcerative colitis (16 observations on 6 patients). The relevance of these observations to the mode of action of sulphasalazine is discussed and suggestions for possible applications of this method to other problems made.     

DNA structure and dynamics

This review primarily outlines the most recent atomic force microscopy (AFM) studies of DNA structure and dynamics. Sample preparation techniques allowing reliable and reproducible imaging of various DNA topologies are reviewed. Such important issues as imaging of supercoiled DNA conformations at different ionic conditions and detection of local alternative structures that are stabilized by negative DNA supercoiling are discussed in length in the article. The possibility of imaging DNA structural dynamics at different levels is another major focus of the article. Using time-lapse AFM imaging mode of nondried samples, such extensive DNA dynamic processes as transition of one local structure into another (H-DNA to B-form transition), the conformational transitions of DNA Holliday junctions and their branch migration were observed. Potential future applications of this single-molecule dynamics mode of AFM to analyses of various biochemical processes involving DNA are discussed.     

Evolutionary conservation of protein vibrational dynamics

The aim of the present work is to study the evolutionary divergence of vibrational protein dynamics. To this end, we used the Gaussian Network Model to perform a systematic analysis of normal mode conservation on a large dataset of proteins classified into homologous sets of family pairs and superfamily pairs. We found that the lowest most collective normal modes are the most conserved ones. More precisely, there is, on average, a linear correlation between normal mode conservation and mode collectivity. These results imply that the previously observed conservation of backbone flexibility (B-factor) profiles is due to the conservation of the most collective modes, which contribute the most to such profiles. We discuss the possible roles of normal mode robustness and natural selection in the determination of the observed behavior. Finally, we draw some practical implications for dynamics-based protein alignment and classification and discuss possible caveats of the present approach.     

Harmonic and anharmonic aspects in the dynamics of BPTI: a normal mode analysis and principal component analysis.

A comparison is made between a 200-ps molecular dynamics simulation in vacuum and a normal mode analysis on the protein bovine pancreatic trypsin inhibitor (BPTI) in order to elucidate the dual aspects of harmonicity and anharmonicity in the dynamics of proteins. The molecular dynamics trajectory is analyzed using principal component analysis, an effective harmonic analysis suited for comparison with the results from the normal mode analysis. The results suggest that the first principal component shows qualitatively different behavior from higher principal components and is associated with apparent barrier crossing events on an anharmonic conformational energy surface. The higher principal components appear to have probability distributions that are well approximated by Gaussians, indicating harmonicity. Eliminating the contribution from the first principal component reveals a great deal of correspondence between the 2 methods. This correspondence, however, involves a factor of 2, as the variances of the distribution of the higher principal components are, on average, roughly twice those found from the normal mode analysis. A model is proposed to reconcile these results with those from previous analyses.     

Electrospray-ionization mass spectrometry as a tool for fast screening of protein structural properties

Since the early 1990s, electrospray-ionization mass spectrometry (ESI-MS) has encountered growing interest as a complementary tool to established biochemical and biophysical methods for investigating protein structure and conformation. Nowadays, applications of ESI-MS to protein investigation span from the area of analytical biochemistry to that of structural biology. This review focuses on applications of this technique to the analysis of protein conformational properties and molecular interactions, underscoring their possible relevance for molecular biotechnology, although representing a still very young field. An introductive section presents the major issues related to theoretical and technical aspects of ESI-MS under non-denaturing conditions. Examples from our work and from the literature illustrate which kind of information can be obtained concerning key issues in biotechnology such as stability and aggregation of proteins under both near-native and challenging conditions, and interactions with other proteins, ligands and cofactors.     

The role of shape in determining molecular motions

We examined the role of molecular shape in determining the patterns of low-frequency deformational motions of biological macromolecules. The low-frequency subspace of eigenvectors in normal mode analysis was found to be robustly similar upon randomization of the Hessian matrix elements as long as the structure of the matrix is maintained, which indicates that the global shape of molecules plays a more dominant role in determining the highly anisotropic low-frequency motions than the absolute values of stiffness and directionality of local interactions. The results provided a quantitative foundation for the validity of elastic normal mode analysis.     

Web-based applications for building, managing and analysing kinetic models of biological systems

Mathematical modelling and computational analysis play an essentialrole in improving our capability to elucidate the functionsand characteristics of complex biological systems such as metabolic,regulatory and cell signalling pathways. The modelling and concomitantsimulation render it possible to predict the cellular behaviourof systems under various genetically and/or environmentallyperturbed conditions. This motivates systems biologists/bioengineers/bioinformaticiansto develop new tools and applications, allowing non-expertsto easily conduct such modelling and analysis. However, amonga multitude of systems biology tools developed to date, onlya handful of projects have adopted a web-based approach to kineticmodelling. In this report, we evaluate the capabilities andcharacteristics of current web-based tools in systems biologyand identify desirable features, limitations and bottlenecksfor further improvements in terms of usability and functionality.A short discussion on software architecture issues involvedin web-based applications and the approaches taken by existingtools is included for those interested in developing their ownsimulation applications.      

Data clustering in life sciences

Clustering has a wide range of applications in life sciences and over the years has been used in many areas ranging from the analysis of clinical information, phylogeny, genomics, and proteomics. The primary goal of this article is to provide an overview of the various issues involved in clustering large biological datasets, describe the merits and underlying assumptions of some of the commonly used clustering approaches, and provide insights on how to cluster datasets arising in various areas within life sciences. We also provide a brief introduction to Cluto, a general purpose toolkit for clustering various datasets, with an emphasis on its applications to problems and analysis requirements within life sciences.