Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

PubMed Central

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

Application of Nuclear Magnetic Resonance and Hybrid Methods to Structure Determination of Complex Systems.

PubMed

Prischi, Filippo; Pastore, Annalisa

2016-01-01

The current main challenge of Structural Biology is to undertake the structure determination of increasingly complex systems in the attempt to better understand their biological function. As systems become more challenging, however, there is an increasing demand for the parallel use of more than one independent technique to allow pushing the frontiers of structure determination and, at the same time, obtaining independent structural validation. The combination of different Structural Biology methods has been named hybrid approaches. The aim of this review is to critically discuss the most recent examples and new developments that have allowed structure determination or experimentally-based modelling of various molecular complexes selecting them among those that combine the use of nuclear magnetic resonance and small angle scattering techniques. We provide a selective but focused account of some of the most exciting recent approaches and discuss their possible further developments.

Advances in Structural Biology and the Application to Biological Filament Systems.

PubMed

Popp, David; Koh, Fujiet; Scipion, Clement P M; Ghoshdastider, Umesh; Narita, Akihiro; Holmes, Kenneth C; Robinson, Robert C

2018-04-01

Structural biology has experienced several transformative technological advances in recent years. These include: development of extremely bright X-ray sources (microfocus synchrotron beamlines and free electron lasers) and the use of electrons to extend protein crystallography to ever decreasing crystal sizes; and an increase in the resolution attainable by cryo-electron microscopy. Here we discuss the use of these techniques in general terms and highlight their application for biological filament systems, an area that is severely underrepresented in atomic resolution structures. We assemble a model of a capped tropomyosin-actin minifilament to demonstrate the utility of combining structures determined by different techniques. Finally, we survey the methods that attempt to transform high resolution structural biology into more physiological environments, such as the cell. Together these techniques promise a compelling decade for structural biology and, more importantly, they will provide exciting discoveries in understanding the designs and purposes of biological machines. © 2018 The Authors. BioEssays Published by WILEY Periodicals, Inc.

Clustering of 3D-Structure Similarity Based Network of Secondary Metabolites Reveals Their Relationships with Biological Activities.

PubMed

Ohtana, Yuki; Abdullah, Azian Azamimi; Altaf-Ul-Amin, Md; Huang, Ming; Ono, Naoaki; Sato, Tetsuo; Sugiura, Tadao; Horai, Hisayuki; Nakamura, Yukiko; Morita Hirai, Aki; Lange, Klaus W; Kibinge, Nelson K; Katsuragi, Tetsuo; Shirai, Tsuyoshi; Kanaya, Shigehiko

2014-12-01

Developing database systems connecting diverse species based on omics is the most important theme in big data biology. To attain this purpose, we have developed KNApSAcK Family Databases, which are utilized in a number of researches in metabolomics. In the present study, we have developed a network-based approach to analyze relationships between 3D structure and biological activity of metabolites consisting of four steps as follows: construction of a network of metabolites based on structural similarity (Step 1), classification of metabolites into structure groups (Step 2), assessment of statistically significant relations between structure groups and biological activities (Step 3), and 2-dimensional clustering of the constructed data matrix based on statistically significant relations between structure groups and biological activities (Step 4). Applying this method to a data set consisting of 2072 secondary metabolites and 140 biological activities reported in KNApSAcK Metabolite Activity DB, we obtained 983 statistically significant structure group-biological activity pairs. As a whole, we systematically analyzed the relationship between 3D-chemical structures of metabolites and biological activities. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

X-rays in the Cryo-EM Era: Structural Biology’s Dynamic Future

PubMed Central

Shoemaker, Susannah C.; Ando, Nozomi

2018-01-01

Over the past several years, single-particle cryo-electron microscopy (cryo-EM) has emerged as a leading method for elucidating macromolecular structures at near-atomic resolution, rivaling even the established technique of X-ray crystallography. Cryo-EM is now able to probe proteins as small as hemoglobin (64 kDa), while avoiding the crystallization bottleneck entirely. The remarkable success of cryo-EM has called into question the continuing relevance of X-ray methods, particularly crystallography. To say that the future of structural biology is either cryo-EM or crystallography, however, would be misguided. Crystallography remains better suited to yield precise atomic coordinates of macromolecules under a few hundred kDa in size, while the ability to probe larger, potentially more disordered assemblies is a distinct advantage of cryo-EM. Likewise, crystallography is better equipped to provide high-resolution dynamic information as a function of time, temperature, pressure, and other perturbations, whereas cryo-EM offers increasing insight into conformational and energy landscapes, particularly as algorithms to deconvolute conformational heterogeneity become more advanced. Ultimately, the future of both techniques depends on how their individual strengths are utilized to tackle questions on the frontiers of structural biology. Structure determination is just one piece of a much larger puzzle: a central challenge of modern structural biology is to relate structural information to biological function. In this perspective, we share insight from several leaders in the field and examine the unique and complementary ways in which X-ray methods and cryo-EM can shape the future of structural biology. PMID:29227642

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

Informatic innovations in glycobiology: relevance to drug discovery.

PubMed

Mamitsuka, Hiroshi

2008-02-01

The recent development and applications of tree-based informatics on glycans have accelerated the biological analysis on glycans, particularly from structural viewpoints. We review three major aspects of recent informatics innovations on glycan structures: maturity of well-organized databases on glycan structures linking with other biological information, implementation of glycan structure matching algorithms and extensive development of methods for mining frequent patterns from glycan structures.

[Physical methods and molecular biology].

PubMed

Serdiuk, I N

2009-01-01

The review is devoted to the description of the current state of physical and chemical methods used for studying the structural and functional bases of living processes. Special attention is focused on the physical methods that have opened a new page in the research of the structure of biological macromolecules. They include primarily the methods of detecting and manipulating single molecules using optical and magnetic traps. New physical methods, such as two-dimensional infrared spectroscopy, fluorescence correlation spectroscopy and magnetic resonance microscopy are also analyzed briefly in the review. The path that physics and biology have passed for the latest 55 years shows that there is no single method providing all necessary information on macromolecules and their interactions. Each method provides its space-time view of the system. All physical methods are complementary. It is just complementarity that is the fundamental idea justifying the existence in practice of all physical methods, whose description is the aim of the review.

Cryo-EM visualization of the protein machine that replicates the chromosome

NASA Astrophysics Data System (ADS)

Li, Huilin

Structural knowledge is key to understanding biological functions. Cryo-EM is a physical method that uses transmission electron microscopy to visualize biological molecules that are frozen in vitreous ice. Due to recent advances in direct electron detector and image processing algorithm, cryo-EM has become a high-resolution technique. Cryo-EM field is undergoing a rapid expansion and vast majority research institutions and research universities around the world are setting up cryo-EM research. Indeed, the method is revolutionizing structural and molecular biology. We have been using cryo-EM to study the structure and mechanism of eukaryotic chromosome replication. Despite an abundance of cartoon drawings found in review articles and biology textbooks, the structure of the eukaryotic helicase that unwinds the double stranded DNA has been unknown. It has also been unknown how the helicase works with DNA polymerases to accomplish the feat of duplicating the genome. In my presentation, I will show how we have used cryo-EM to derive at structures of the eukaryotic chromosome replication machinery and describe mechanistic insights we have gleaned from the structures.

The Androgen Receptor and Its Use in Biological Assays: Looking Toward Effect-Based Testing and Its Applications

PubMed Central

Cadwallader, Amy B.; Lim, Carol S.; Rollins, Douglas E.; Botrè, Francesco

2015-01-01

Steroid abuse is a growing problem among amateur and professional athletes. Because of an inundation of newly and illegally synthesized steroids with minor structural modifications and other designer steroid receptor modulators, there is a need to develop new methods of detection which do not require prior knowledge of the abused steroid structure. The number of designer steroids currently being abused is unknown because detection methods in general are only identifying substances with a known structure. The detection of doping is moving away from merely checking for exposure to prohibited substance toward detecting an effect of prohibited substances, as biological assays can do. Cell-based biological assays are the next generation of assays which should be utilized by antidoping laboratories; they can detect androgenic anabolic steroid and other human androgen receptor (hAR) ligand presence without knowledge of their structure and assess the relative biological activity of these compounds. This review summarizes the hAR and its action and discusses its relevance to sports doping and its use in biological assays. PMID:22080898

Structure-seq2: sensitive and accurate genome-wide profiling of RNA structure in vivo

PubMed Central

Ritchey, Laura E.; Su, Zhao; Tang, Yin; Tack, David C.

2017-01-01

Abstract RNA serves many functions in biology such as splicing, temperature sensing, and innate immunity. These functions are often determined by the structure of RNA. There is thus a pressing need to understand RNA structure and how it changes during diverse biological processes both in vivo and genome-wide. Here, we present Structure-seq2, which provides nucleotide-resolution RNA structural information in vivo and genome-wide. This optimized version of our original Structure-seq method increases sensitivity by at least 4-fold and improves data quality by minimizing formation of a deleterious by-product, reducing ligation bias, and improving read coverage. We also present a variation of Structure-seq2 in which a biotinylated nucleotide is incorporated during reverse transcription, which greatly facilitates the protocol by eliminating two PAGE purification steps. We benchmark Structure-seq2 on both mRNA and rRNA structure in rice (Oryza sativa). We demonstrate that Structure-seq2 can lead to new biological insights. Our Structure-seq2 datasets uncover hidden breaks in chloroplast rRNA and identify a previously unreported N1-methyladenosine (m1A) in a nuclear-encoded Oryza sativa rRNA. Overall, Structure-seq2 is a rapid, sensitive, and unbiased method to probe RNA in vivo and genome-wide that facilitates new insights into RNA biology. PMID:28637286

Determining Biology Student Teachers' Cognitive Structure on the Concept of "Diffusion" through the Free Word-Association Test and the Drawing-Writing Technique

ERIC Educational Resources Information Center

Kurt, Hakan; Ekici, Gülay; Aktas, Murat; Aksu, Özlem

2013-01-01

The aim of the current study is to investigate student biology teachers' cognitive structures related to "diffusion" through the free word-association test and the drawing-writing technique. As the research design of the study, the qualitative research method was applied. The data were collected from 44 student biology teachers. The free…

Building blocks for automated elucidation of metabolites: machine learning methods for NMR prediction.

PubMed

Kuhn, Stefan; Egert, Björn; Neumann, Steffen; Steinbeck, Christoph

2008-09-25

Current efforts in Metabolomics, such as the Human Metabolome Project, collect structures of biological metabolites as well as data for their characterisation, such as spectra for identification of substances and measurements of their concentration. Still, only a fraction of existing metabolites and their spectral fingerprints are known. Computer-Assisted Structure Elucidation (CASE) of biological metabolites will be an important tool to leverage this lack of knowledge. Indispensable for CASE are modules to predict spectra for hypothetical structures. This paper evaluates different statistical and machine learning methods to perform predictions of proton NMR spectra based on data from our open database NMRShiftDB. A mean absolute error of 0.18 ppm was achieved for the prediction of proton NMR shifts ranging from 0 to 11 ppm. Random forest, J48 decision tree and support vector machines achieved similar overall errors. HOSE codes being a notably simple method achieved a comparatively good result of 0.17 ppm mean absolute error. NMR prediction methods applied in the course of this work delivered precise predictions which can serve as a building block for Computer-Assisted Structure Elucidation for biological metabolites.

A novel knowledge-based potential for RNA 3D structure evaluation

NASA Astrophysics Data System (ADS)

Yang, Yi; Gu, Qi; Zhang, Ben-Gong; Shi, Ya-Zhou; Shao, Zhi-Gang

2018-03-01

Ribonucleic acids (RNAs) play a vital role in biology, and knowledge of their three-dimensional (3D) structure is required to understand their biological functions. Recently structural prediction methods have been developed to address this issue, but a series of RNA 3D structures are generally predicted by most existing methods. Therefore, the evaluation of the predicted structures is generally indispensable. Although several methods have been proposed to assess RNA 3D structures, the existing methods are not precise enough. In this work, a new all-atom knowledge-based potential is developed for more accurately evaluating RNA 3D structures. The potential not only includes local and nonlocal interactions but also fully considers the specificity of each RNA by introducing a retraining mechanism. Based on extensive test sets generated from independent methods, the proposed potential correctly distinguished the native state and ranked near-native conformations to effectively select the best. Furthermore, the proposed potential precisely captured RNA structural features such as base-stacking and base-pairing. Comparisons with existing potential methods show that the proposed potential is very reliable and accurate in RNA 3D structure evaluation. Project supported by the National Science Foundation of China (Grants Nos. 11605125, 11105054, 11274124, and 11401448).

Navigating 3D electron microscopy maps with EM-SURFER.

PubMed

Esquivel-Rodríguez, Juan; Xiong, Yi; Han, Xusi; Guang, Shuomeng; Christoffer, Charles; Kihara, Daisuke

2015-05-30

The Electron Microscopy DataBank (EMDB) is growing rapidly, accumulating biological structural data obtained mainly by electron microscopy and tomography, which are emerging techniques for determining large biomolecular complex and subcellular structures. Together with the Protein Data Bank (PDB), EMDB is becoming a fundamental resource of the tertiary structures of biological macromolecules. To take full advantage of this indispensable resource, the ability to search the database by structural similarity is essential. However, unlike high-resolution structures stored in PDB, methods for comparing low-resolution electron microscopy (EM) density maps in EMDB are not well established. We developed a computational method for efficiently searching low-resolution EM maps. The method uses a compact fingerprint representation of EM maps based on the 3D Zernike descriptor, which is derived from a mathematical series expansion for EM maps that are considered as 3D functions. The method is implemented in a web server named EM-SURFER, which allows users to search against the entire EMDB in real-time. EM-SURFER compares the global shapes of EM maps. Examples of search results from different types of query structures are discussed. We developed EM-SURFER, which retrieves structurally relevant matches for query EM maps from EMDB within seconds. The unique capability of EM-SURFER to detect 3D shape similarity of low-resolution EM maps should prove invaluable in structural biology.

Quantification of the impact of PSI:Biology according to the annotations of the determined structures.

PubMed

DePietro, Paul J; Julfayev, Elchin S; McLaughlin, William A

2013-10-21

Protein Structure Initiative:Biology (PSI:Biology) is the third phase of PSI where protein structures are determined in high-throughput to characterize their biological functions. The transition to the third phase entailed the formation of PSI:Biology Partnerships which are composed of structural genomics centers and biomedical science laboratories. We present a method to examine the impact of protein structures determined under the auspices of PSI:Biology by measuring their rates of annotations. The mean numbers of annotations per structure and per residue are examined. These are designed to provide measures of the amount of structure to function connections that can be leveraged from each structure. One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI. A second result is that the subset of PSI:Biology structures determined through PSI:Biology Partnerships have a higher rate of annotations than those determined exclusive of those partnerships. Both results hold when the annotation rates are examined either at the level of the entire protein or for annotations that are known to fall at specific residues within the portion of the protein that has a determined structure. We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations. For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology. We interpret the added value to mean that team-based structural biology projects that utilize the expertise and technologies of structural genomics centers together with biological laboratories in the community are conducted in a synergistic manner. We show that the annotation rates can be used in conjunction with established metrics, i.e. the numbers of structures and impact of publication records, to monitor the progress of PSI:Biology towards its goals of examining structure to function connections of high biomedical relevance. The metric provides an objective means to quantify the overall impact of PSI:Biology as it uses biomedical annotations from external sources.

Quantification of the impact of PSI:Biology according to the annotations of the determined structures

PubMed Central

2013-01-01

Background Protein Structure Initiative:Biology (PSI:Biology) is the third phase of PSI where protein structures are determined in high-throughput to characterize their biological functions. The transition to the third phase entailed the formation of PSI:Biology Partnerships which are composed of structural genomics centers and biomedical science laboratories. We present a method to examine the impact of protein structures determined under the auspices of PSI:Biology by measuring their rates of annotations. The mean numbers of annotations per structure and per residue are examined. These are designed to provide measures of the amount of structure to function connections that can be leveraged from each structure. Results One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI. A second result is that the subset of PSI:Biology structures determined through PSI:Biology Partnerships have a higher rate of annotations than those determined exclusive of those partnerships. Both results hold when the annotation rates are examined either at the level of the entire protein or for annotations that are known to fall at specific residues within the portion of the protein that has a determined structure. Conclusions We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations. For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology. We interpret the added value to mean that team-based structural biology projects that utilize the expertise and technologies of structural genomics centers together with biological laboratories in the community are conducted in a synergistic manner. We show that the annotation rates can be used in conjunction with established metrics, i.e. the numbers of structures and impact of publication records, to monitor the progress of PSI:Biology towards its goals of examining structure to function connections of high biomedical relevance. The metric provides an objective means to quantify the overall impact of PSI:Biology as it uses biomedical annotations from external sources. PMID:24139526

bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System.

PubMed

Alexander, Nathan; Woetzel, Nils; Meiler, Jens

2011-02-01

Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.

G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design.

PubMed

Lee, Hui Sun; Im, Wonpil

2016-04-01

Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. © 2016 The Protein Society.

Personal Constructions of Biological Concepts--The Repertory Grid Approach

ERIC Educational Resources Information Center

McCloughlin, Thomas J. J.; Matthews, Philip S. C.

2017-01-01

This work discusses repertory grid analysis as a tool for investigating the structures of students' representations of biological concepts. Repertory grid analysis provides the researcher with a variety of techniques that are not associated with standard methods of concept mapping for investigating conceptual structures. It can provide valuable…

Impact of environmental inputs on reverse-engineering approach to network structures.

PubMed

Wu, Jianhua; Sinfield, James L; Buchanan-Wollaston, Vicky; Feng, Jianfeng

2009-12-04

Uncovering complex network structures from a biological system is one of the main topic in system biology. The network structures can be inferred by the dynamical Bayesian network or Granger causality, but neither techniques have seriously taken into account the impact of environmental inputs. With considerations of natural rhythmic dynamics of biological data, we propose a system biology approach to reveal the impact of environmental inputs on network structures. We first represent the environmental inputs by a harmonic oscillator and combine them with Granger causality to identify environmental inputs and then uncover the causal network structures. We also generalize it to multiple harmonic oscillators to represent various exogenous influences. This system approach is extensively tested with toy models and successfully applied to a real biological network of microarray data of the flowering genes of the model plant Arabidopsis Thaliana. The aim is to identify those genes that are directly affected by the presence of the sunlight and uncover the interactive network structures associating with flowering metabolism. We demonstrate that environmental inputs are crucial for correctly inferring network structures. Harmonic causal method is proved to be a powerful technique to detect environment inputs and uncover network structures, especially when the biological data exhibit periodic oscillations.

Methods for the synthesis of aza(deaza)xanthines as a basis of biologically active compounds

NASA Astrophysics Data System (ADS)

Babkov, D. A.; Geisman, A. N.; Khandazhinskaya, A. L.; Novikov, M. S.

2016-03-01

The review covers methods for the synthesis of aza(deaza)xanthines, i.e., fused pyrrolo-, pyrazolo- and triazolopyrimidine heterocyclic systems, which are common core structures of various biologically active compounds. The extensive range of modern synthetic approaches is organized according to target structures and starting building blocks. The presented material is intended to benefit broad audience of specialists in the fields of organic, medicinal and pharmaceutical chemistry. The bibliography includes 195 references.

High-refractive index of acrylate embedding resin clarifies mouse brain tissue

NASA Astrophysics Data System (ADS)

Zhou, Hongfu; Xiong, Yumiao; Wang, Yu; Wang, Xiaojun; Li, Pei; Gang, Yadong; Liu, Xiuli; Zeng, Shaoqun

2017-11-01

Biological tissue transparency combined with light-sheet fluorescence microscopy is a useful method for studying the neural structure of biological tissues. The development of light-sheet fluorescence microscopy also promotes progress in biological tissue clearing methods. The current clarifying methods mostly use liquid reagent to denature protein or remove lipids first, to eliminate or reduce the scattering index or refractive index of the biological tissue. However, denaturing protein and removing lipids require complex procedures or an extended time period. Therefore, here we have developed acrylate resin with a high refractive index, which causes clearing of biological tissue directly after polymerization. This method can improve endogenous fluorescence retention by adjusting the pH value of the resin monomer.

Synthetic analogs of bacterial quorum sensors

DOEpatents

Iyer, Rashi [Los Alamos, NM; Ganguly, Kumkum [Los Alamos, NM; Silks, Louis A [Los Alamos, NM

2011-12-06

Bacterial quorum-sensing molecule analogs having the following structures: ##STR00001## and methods of reducing bacterial pathogenicity, comprising providing a biological system comprising pathogenic bacteria which produce natural quorum-sensing molecule; providing a synthetic bacterial quorum-sensing molecule having the above structures and introducing the synthetic quorum-sensing molecule into the biological system comprising pathogenic bacteria. Further is provided a method of targeted delivery of an antibiotic, comprising providing a synthetic quorum-sensing molecule; chemically linking the synthetic quorum-sensing molecule to an antibiotic to produce a quorum-sensing molecule-antibiotic conjugate; and introducing the conjugate into a biological system comprising pathogenic bacteria susceptible to the antibiotic.

Synthetic analogs of bacterial quorum sensors

DOEpatents

Iyer, Rashi S.; Ganguly, Kumkum; Silks, Louis A.

2013-01-08

Bacterial quorum-sensing molecule analogs having the following structures: ##STR00001## and methods of reducing bacterial pathogenicity, comprising providing a biological system comprising pathogenic bacteria which produce natural quorum-sensing molecule; providing a synthetic bacterial quorum-sensing molecule having the above structures and introducing the synthetic quorum-sensing molecule into the biological system comprising pathogenic bacteria. Further is provided a method of targeted delivery of an antibiotic, comprising providing a synthetic quorum-sensing molecule; chemically linking the synthetic quorum-sensing molecule to an antibiotic to produce a quorum-sensing molecule-antibiotic conjugate; and introducing the conjugate into a biological system comprising pathogenic bacteria susceptible to the antibiotic.

Detecting and evaluating communities in complex human and biological networks

NASA Astrophysics Data System (ADS)

Morrison, Greg; Mahadevan, L.

2012-02-01

We develop a simple method for detecting the community structure in a network can by utilizing a measure of closeness between nodes. This approach readily leads to a method of coarse graining the network, which allows the detection of the natural hierarchy (or hierarchies) of community structure without appealing to an unknown resolution parameter. The closeness measure can also be used to evaluate the robustness of an individual node's assignment to its community (rather than evaluating only the quality of the global structure). Each of these methods in community detection and evaluation are illustrated using a variety of real world networks of either biological or sociological importance and illustrate the power and flexibility of the approach.

Biologic restoration: a treatment option for reconstruction of anterior teeth.

PubMed

Babaji, Prashant; Khanna, Priyanka; S, Shankar; Chaurasia, Vishwajit Rampratap; Masamatti, Vinaykumar S

2014-11-01

Several procedures are advised to manage fractured anterior tooth structure using acrylic resin, composite restoration, ceramic or metal crown with ceramic facing. Biologic restoration is a procedure to restore fractured tooth structure with natural tooth material. In this in vitro case we have made an attempt for aesthetic rehabilitation of maxillary central incisor with similar biologic crown taken form extracted maxillary central incisor. It was observed that biologic restoration is an aesthetic, economical, fast and functional procedure which can be used as an alternative method to restore fractured primary or permanent anteriors.

Prediction of phenotypes of missense mutations in human proteins from biological assemblies.

PubMed

Wei, Qiong; Xu, Qifang; Dunbrack, Roland L

2013-02-01

Single nucleotide polymorphisms (SNPs) are the most frequent variation in the human genome. Nonsynonymous SNPs that lead to missense mutations can be neutral or deleterious, and several computational methods have been presented that predict the phenotype of human missense mutations. These methods use sequence-based and structure-based features in various combinations, relying on different statistical distributions of these features for deleterious and neutral mutations. One structure-based feature that has not been studied significantly is the accessible surface area within biologically relevant oligomeric assemblies. These assemblies are different from the crystallographic asymmetric unit for more than half of X-ray crystal structures. We find that mutations in the core of proteins or in the interfaces in biological assemblies are significantly more likely to be disease-associated than those on the surface of the biological assemblies. For structures with more than one protein in the biological assembly (whether the same sequence or different), we find the accessible surface area from biological assemblies provides a statistically significant improvement in prediction over the accessible surface area of monomers from protein crystal structures (P = 6e-5). When adding this information to sequence-based features such as the difference between wildtype and mutant position-specific profile scores, the improvement from biological assemblies is statistically significant but much smaller (P = 0.018). Combining this information with sequence-based features in a support vector machine leads to 82% accuracy on a balanced dataset of 50% disease-associated mutations from SwissVar and 50% neutral mutations from human/primate sequence differences in orthologous proteins. Copyright © 2012 Wiley Periodicals, Inc.

Student Structured Learning in Biology.

ERIC Educational Resources Information Center

Penick, John E.; And Others

Described is a highly individualized and open teaching situation, Student-Structured Learning in Biology (SSLB), used with a randomly selected group of 9th-, 10th-, and 11th-grade students at the Florida State University Developmental Research School. Students chose their own content and method of learning and were free to pursue, or not pursue,…

A guide to large-scale RNA sample preparation.

PubMed

Baronti, Lorenzo; Karlsson, Hampus; Marušič, Maja; Petzold, Katja

2018-05-01

RNA is becoming more important as an increasing number of functions, both regulatory and enzymatic, are being discovered on a daily basis. As the RNA boom has just begun, most techniques are still in development and changes occur frequently. To understand RNA functions, revealing the structure of RNA is of utmost importance, which requires sample preparation. We review the latest methods to produce and purify a variation of RNA molecules for different purposes with the main focus on structural biology and biophysics. We present a guide aimed at identifying the most suitable method for your RNA and your biological question and highlighting the advantages of different methods. Graphical abstract In this review we present different methods for large-scale production and purification of RNAs for structural and biophysical studies.

Neuro-symbolic representation learning on biological knowledge graphs.

PubMed

Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert

2017-09-01

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action.

PubMed

Papamokos, George; Silins, Ilona

2016-01-01

There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens.

Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action

PubMed Central

Papamokos, George; Silins, Ilona

2016-01-01

There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens. PMID:27625608

The diverse and expanding role of mass spectrometry in structural and molecular biology.

PubMed

Lössl, Philip; van de Waterbeemd, Michiel; Heck, Albert Jr

2016-12-15

The emergence of proteomics has led to major technological advances in mass spectrometry (MS). These advancements not only benefitted MS-based high-throughput proteomics but also increased the impact of mass spectrometry on the field of structural and molecular biology. Here, we review how state-of-the-art MS methods, including native MS, top-down protein sequencing, cross-linking-MS, and hydrogen-deuterium exchange-MS, nowadays enable the characterization of biomolecular structures, functions, and interactions. In particular, we focus on the role of mass spectrometry in integrated structural and molecular biology investigations of biological macromolecular complexes and cellular machineries, highlighting work on CRISPR-Cas systems and eukaryotic transcription complexes. © 2016 The Authors. Published under the terms of the CC BY NC ND 4.0 license.

Structural identifiability of cyclic graphical models of biological networks with latent variables.

PubMed

Wang, Yulin; Lu, Na; Miao, Hongyu

2016-06-13

Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and is thus of higher resolution in comparison with many existing approaches. Overall, this study provides a basis for systematic examination and refinement of graphical models of biological networks from the identifiability point of view, and it has a significant potential to be extended to more complex network structures or high-dimensional systems.

Synthesis, spectroscopic, crystal structure, biological activities and theoretical studies of 2-[(2E)-2-(2-chloro-6-fluorobenzylidene)hydrazinyl]pyridine

NASA Astrophysics Data System (ADS)

Dilek Özçelik, Nefise; Tunç, Tuncay; Çatak Çelik, Raziye; Erzengin, Mahmut; Özışık, Hacı

2017-05-01

We report in this paper the synthesis, spectroscopic, crystal structure, biological activities and theoretical results of the title compound. The crystal structure was defined by the X-ray diffraction (XRD) method. In addition, this newly synthesized hydrazone derivative was also subjected to its possible antioxidant activity with free radical scavenging ability of 2,2-diphenyl-1-picrylhydrazyl (DPPH) radicals using butylated hydroxytoluene (BHT) as standard antioxidant. The structural calculations were performed by the density functional theory using the B3LYP method with 6-311++G(2d,2p) basis set. The calculated values were compared with experimental results.

Incorporating biological information in sparse principal component analysis with application to genomic data.

PubMed

Li, Ziyi; Safo, Sandra E; Long, Qi

2017-07-11

Sparse principal component analysis (PCA) is a popular tool for dimensionality reduction, pattern recognition, and visualization of high dimensional data. It has been recognized that complex biological mechanisms occur through concerted relationships of multiple genes working in networks that are often represented by graphs. Recent work has shown that incorporating such biological information improves feature selection and prediction performance in regression analysis, but there has been limited work on extending this approach to PCA. In this article, we propose two new sparse PCA methods called Fused and Grouped sparse PCA that enable incorporation of prior biological information in variable selection. Our simulation studies suggest that, compared to existing sparse PCA methods, the proposed methods achieve higher sensitivity and specificity when the graph structure is correctly specified, and are fairly robust to misspecified graph structures. Application to a glioblastoma gene expression dataset identified pathways that are suggested in the literature to be related with glioblastoma. The proposed sparse PCA methods Fused and Grouped sparse PCA can effectively incorporate prior biological information in variable selection, leading to improved feature selection and more interpretable principal component loadings and potentially providing insights on molecular underpinnings of complex diseases.

G‐LoSA: An efficient computational tool for local structure‐centric biological studies and drug design

PubMed Central

2016-01-01

Abstract Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G‐LoSA. G‐LoSA aligns protein local structures in a sequence order independent way and provides a GA‐score, a chemical feature‐based and size‐independent structure similarity score. Our benchmark validation shows the robust performance of G‐LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure‐centric comparative biology studies. In particular, G‐LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G‐LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer‐aided drug design. We hope that G‐LoSA can be a useful computational method for exploring interesting biological problems through large‐scale comparison of protein local structures and facilitating drug discovery research and development. G‐LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. PMID:26813336

Uncovering three-dimensional gradients in fibrillar orientation in an impact-resistant biological armour.

PubMed

Zhang, Y; Paris, O; Terrill, N J; Gupta, H S

2016-05-23

The complex hierarchical structure in biological and synthetic fibrous nanocomposites entails considerable difficulties in the interpretation of the crystallographic texture from diffraction data. Here, we present a novel reconstruction method to obtain the 3D distribution of fibres in such systems. An analytical expression is derived for the diffraction intensity from fibres, explaining the azimuthal intensity distribution in terms of the angles of the three dimensional fibre orientation distributions. The telson of stomatopod (mantis shrimp) serves as an example of natural biological armour whose high impact resistance property is believed to arise from the hierarchical organization of alpha chitin nanofibrils into fibres and twisted plywood (Bouligand) structures at the sub-micron and micron scale. Synchrotron microfocus scanning X-ray diffraction data on stomatopod telson were used as a test case to map the 3D fibre orientation across the entire tissue section. The method is applicable to a range of biological and biomimetic structures with graded 3D fibre texture at the sub-micron and micron length scales.

Uncovering three-dimensional gradients in fibrillar orientation in an impact-resistant biological armour

NASA Astrophysics Data System (ADS)

Zhang, Y.; Paris, O.; Terrill, N. J.; Gupta, H. S.

2016-05-01

The complex hierarchical structure in biological and synthetic fibrous nanocomposites entails considerable difficulties in the interpretation of the crystallographic texture from diffraction data. Here, we present a novel reconstruction method to obtain the 3D distribution of fibres in such systems. An analytical expression is derived for the diffraction intensity from fibres, explaining the azimuthal intensity distribution in terms of the angles of the three dimensional fibre orientation distributions. The telson of stomatopod (mantis shrimp) serves as an example of natural biological armour whose high impact resistance property is believed to arise from the hierarchical organization of alpha chitin nanofibrils into fibres and twisted plywood (Bouligand) structures at the sub-micron and micron scale. Synchrotron microfocus scanning X-ray diffraction data on stomatopod telson were used as a test case to map the 3D fibre orientation across the entire tissue section. The method is applicable to a range of biological and biomimetic structures with graded 3D fibre texture at the sub-micron and micron length scales.

Uncovering three-dimensional gradients in fibrillar orientation in an impact-resistant biological armour

PubMed Central

Zhang, Y.; Paris, O.; Terrill, N. J.; Gupta, H. S.

2016-01-01

The complex hierarchical structure in biological and synthetic fibrous nanocomposites entails considerable difficulties in the interpretation of the crystallographic texture from diffraction data. Here, we present a novel reconstruction method to obtain the 3D distribution of fibres in such systems. An analytical expression is derived for the diffraction intensity from fibres, explaining the azimuthal intensity distribution in terms of the angles of the three dimensional fibre orientation distributions. The telson of stomatopod (mantis shrimp) serves as an example of natural biological armour whose high impact resistance property is believed to arise from the hierarchical organization of alpha chitin nanofibrils into fibres and twisted plywood (Bouligand) structures at the sub-micron and micron scale. Synchrotron microfocus scanning X-ray diffraction data on stomatopod telson were used as a test case to map the 3D fibre orientation across the entire tissue section. The method is applicable to a range of biological and biomimetic structures with graded 3D fibre texture at the sub-micron and micron length scales. PMID:27211574

Structural biology data archiving - where we are and what lies ahead.

PubMed

Kleywegt, Gerard J; Velankar, Sameer; Patwardhan, Ardan

2018-05-10

For almost 50 years, structural biology has endeavoured to conserve and share its experimental data and their interpretations (usually, atomistic models) through global public archives such as the Protein Data Bank, Electron Microscopy Data Bank and Biological Magnetic Resonance Data Bank (BMRB). These archives are treasure troves of freely accessible data that document our quest for molecular or atomic understanding of biological function and processes in health and disease. They have prepared the field to tackle new archiving challenges as more and more (combinations of) techniques are being utilized to elucidate structure at ever increasing length scales. Furthermore, the field has made substantial efforts to develop validation methods that help users to assess the reliability of structures and to identify the most appropriate data for their needs. In this Review, we present an overview of public data archives in structural biology and discuss the importance of validation for users and producers of structural data. Finally, we sketch our efforts to integrate structural data with bioimaging data and with other sources of biological data. This will make relevant structural information available and more easily discoverable for a wide range of scientists. © 2018 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

Evolutionary optimization with data collocation for reverse engineering of biological networks.

PubMed

Tsai, Kuan-Yao; Wang, Feng-Sheng

2005-04-01

Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very efficient computational method to identify the model structure and parameters. Numerical integration for differential equations and finding global parameter values are still two major challenges in this field of the parameter estimation of nonlinear dynamic biological systems. We compare three techniques of parameter estimation for nonlinear dynamic biological systems. In the proposed scheme, the modified collocation method is applied to convert the differential equations to the system of algebraic equations. The observed time-course data are then substituted into the algebraic system equations to decouple system interactions in order to obtain the approximate model profiles. Hybrid differential evolution (HDE) with population size of five is able to find a global solution. The method is not only suited for parameter estimation but also can be applied for structure identification. The solution obtained by HDE is then used as the starting point for a local search method to yield the refined estimates.

RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

ERIC Educational Resources Information Center

Ellington, Roni; Wachira, James; Nkwanta, Asamoah

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses…

High-refractive index of acrylate embedding resin clarifies mouse brain tissue.

PubMed

Zhou, Hongfu; Xiong, Yumiao; Wang, Yu; Wang, Xiaojun; Li, Pei; Gang, Yadong; Liu, Xiuli; Zeng, Shaoqun

2017-11-01

Biological tissue transparency combined with light-sheet fluorescence microscopy is a useful method for studying the neural structure of biological tissues. The development of light-sheet fluorescence microscopy also promotes progress in biological tissue clearing methods. The current clarifying methods mostly use liquid reagent to denature protein or remove lipids first, to eliminate or reduce the scattering index or refractive index of the biological tissue. However, denaturing protein and removing lipids require complex procedures or an extended time period. Therefore, here we have developed acrylate resin with a high refractive index, which causes clearing of biological tissue directly after polymerization. This method can improve endogenous fluorescence retention by adjusting the pH value of the resin monomer. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Orientation determination of interfacial beta-sheet structures in situ.

PubMed

Nguyen, Khoi Tan; King, John Thomas; Chen, Zhan

2010-07-01

Structural information such as orientations of interfacial proteins and peptides is important for understanding properties and functions of such biological molecules, which play crucial roles in biological applications and processes such as antimicrobial selectivity, membrane protein activity, biocompatibility, and biosensing performance. The alpha-helical and beta-sheet structures are the most widely encountered secondary structures in peptides and proteins. In this paper, for the first time, a method to quantify the orientation of the interfacial beta-sheet structure using a combined attenuated total reflectance Fourier transformation infrared spectroscopic (ATR-FTIR) and sum frequency generation (SFG) vibrational spectroscopic study was developed. As an illustration of the methodology, the orientation of tachyplesin I, a 17 amino acid peptide with an antiparallel beta-sheet, adsorbed to polymer surfaces as well as associated with a lipid bilayer was determined using the regular and chiral SFG spectra, together with polarized ATR-FTIR amide I signals. Both the tilt angle (theta) and the twist angle (psi) of the beta-sheet at interfaces are determined. The developed method in this paper can be used to obtain in situ structural information of beta-sheet components in complex molecules. The combination of this method and the existing methodology that is currently used to investigate alpha-helical structures will greatly broaden the application of optical spectroscopy in physical chemistry, biochemistry, biophysics, and structural biology.

Computational challenges of structure-based approaches applied to HIV.

PubMed

Forli, Stefano; Olson, Arthur J

2015-01-01

Here, we review some of the opportunities and challenges that we face in computational modeling of HIV therapeutic targets and structural biology, both in terms of methodology development and structure-based drug design (SBDD). Computational methods have provided fundamental support to HIV research since the initial structural studies, helping to unravel details of HIV biology. Computational models have proved to be a powerful tool to analyze and understand the impact of mutations and to overcome their structural and functional influence in drug resistance. With the availability of structural data, in silico experiments have been instrumental in exploiting and improving interactions between drugs and viral targets, such as HIV protease, reverse transcriptase, and integrase. Issues such as viral target dynamics and mutational variability, as well as the role of water and estimates of binding free energy in characterizing ligand interactions, are areas of active computational research. Ever-increasing computational resources and theoretical and algorithmic advances have played a significant role in progress to date, and we envision a continually expanding role for computational methods in our understanding of HIV biology and SBDD in the future.

QSAR Methods.

PubMed

Gini, Giuseppina

2016-01-01

In this chapter, we introduce the basis of computational chemistry and discuss how computational methods have been extended to some biological properties and toxicology, in particular. Since about 20 years, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Then we see how animal experiments, aimed at providing a standardized result about a biological property, can be mimicked by new in silico methods. Our emphasis here is on toxicology and on predicting properties through chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (Quantitative Structure Activity Relationships), and models that find relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. We discuss how the experimental practice in biological science is moving more and more toward modeling and simulation. Such virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals.

Recent progress in structural biology: lessons from our research history.

PubMed

Nitta, Ryo; Imasaki, Tsuyoshi; Nitta, Eriko

2018-05-16

The recent 'resolution revolution' in structural analyses of cryo-electron microscopy (cryo-EM) has drastically changed the research strategy for structural biology. In addition to X-ray crystallography and nuclear magnetic resonance spectroscopy, cryo-EM has achieved the structural analysis of biological molecules at near-atomic resolution, resulting in the Nobel Prize in Chemistry 2017. The effect of this revolution has spread within the biology and medical science fields affecting everything from basic research to pharmaceutical development by visualizing atomic structure. As we have used cryo-EM as well as X-ray crystallography since 2000 to elucidate the molecular mechanisms of the fundamental phenomena in the cell, here we review our research history and summarize our findings. In the first half of the review, we describe the structural mechanisms of microtubule-based motility of molecular motor kinesin by using a joint cryo-EM and X-ray crystallography method. In the latter half, we summarize our structural studies on transcriptional regulation by X-ray crystallography of in vitro reconstitution of a multi-protein complex.

RSRE: RNA structural robustness evaluator

PubMed Central

Shu, Wenjie; Zheng, Zhiqiang; Wang, Shengqi

2007-01-01

Biological robustness, defined as the ability to maintain stable functioning in the face of various perturbations, is an important and fundamental topic in current biology, and has become a focus of numerous studies in recent years. Although structural robustness has been explored in several types of RNA molecules, the origins of robustness are still controversial. Computational analysis results are needed to make up for the lack of evidence of robustness in natural biological systems. The RNA structural robustness evaluator (RSRE) web server presented here provides a freely available online tool to quantitatively evaluate the structural robustness of RNA based on the widely accepted definition of neutrality. Several classical structure comparison methods are employed; five randomization methods are implemented to generate control sequences; sub-optimal predicted structures can be optionally utilized to mitigate the uncertainty of secondary structure prediction. With a user-friendly interface, the web application is easy to use. Intuitive illustrations are provided along with the original computational results to facilitate analysis. The RSRE will be helpful in the wide exploration of RNA structural robustness and will catalyze our understanding of RNA evolution. The RSRE web server is freely available at http://biosrv1.bmi.ac.cn/RSRE/ or http://biotech.bmi.ac.cn/RSRE/. PMID:17567615

Cross-Linking and Mass Spectrometry Methodologies to Facilitate Structural Biology: Finding a Path through the Maze

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merkley, Eric D.; Cort, John R.; Adkins, Joshua N.

2013-09-01

Multiprotein complexes, rather than individual proteins, make up a large part of the biological macromolecular machinery of a cell. Understanding the structure and organization of these complexes is critical to understanding cellular function. Chemical cross-linking coupled with mass spectrometry is emerging as a complementary technique to traditional structural biology methods and can provide low-resolution structural information for a multitude of purposes, such as distance constraints in computational modeling of protein complexes. In this review, we discuss the experimental considerations for successful application of chemical cross-linking-mass spectrometry in biological studies and highlight three examples of such studies from the recent literature.more » These examples (as well as many others) illustrate the utility of a chemical cross-linking-mass spectrometry approach in facilitating structural analysis of large and challenging complexes.« less

In Silico Analysis for the Study of Botulinum Toxin Structure

NASA Astrophysics Data System (ADS)

Suzuki, Tomonori; Miyazaki, Satoru

2010-01-01

Protein-protein interactions play many important roles in biological function. Knowledge of protein-protein complex structure is required for understanding the function. The determination of protein-protein complex structure by experimental studies remains difficult, therefore computational prediction of protein structures by structure modeling and docking studies is valuable method. In addition, MD simulation is also one of the most popular methods for protein structure modeling and characteristics. Here, we attempt to predict protein-protein complex structure and property using some of bioinformatic methods, and we focus botulinum toxin complex as target structure.

Image processing for cryogenic transmission electron microscopy of symmetry-mismatched complexes.

PubMed

Huiskonen, Juha T

2018-02-08

Cryogenic transmission electron microscopy (cryo-TEM) is a high-resolution biological imaging method, whereby biological samples, such as purified proteins, macromolecular complexes, viral particles, organelles and cells, are embedded in vitreous ice preserving their native structures. Due to sensitivity of biological materials to the electron beam of the microscope, only relatively low electron doses can be applied during imaging. As a result, the signal arising from the structure of interest is overpowered by noise in the images. To increase the signal-to-noise ratio, different image processing-based strategies that aim at coherent averaging of signal have been devised. In such strategies, images are generally assumed to arise from multiple identical copies of the structure. Prior to averaging, the images must be grouped according to the view of the structure they represent and images representing the same view must be simultaneously aligned relatively to each other. For computational reconstruction of the three-dimensional structure, images must contain different views of the original structure. Structures with multiple symmetry-related substructures are advantageous in averaging approaches because each image provides multiple views of the substructures. However, the symmetry assumption may be valid for only parts of the structure, leading to incoherent averaging of the other parts. Several image processing approaches have been adapted to tackle symmetry-mismatched substructures with increasing success. Such structures are ubiquitous in nature and further computational method development is needed to understanding their biological functions. ©2018 The Author(s).

Joining Forces: Integrating Proteomics and Cross-linking with the Mass Spectrometry of Intact Complexes*

PubMed Central

Stengel, Florian; Aebersold, Ruedi; Robinson, Carol V.

2012-01-01

Protein assemblies are critical for cellular function and understanding their physical organization is the key aim of structural biology. However, applying conventional structural biology approaches is challenging for transient, dynamic, or polydisperse assemblies. There is therefore a growing demand for hybrid technologies that are able to complement classical structural biology methods and thereby broaden our arsenal for the study of these important complexes. Exciting new developments in the field of mass spectrometry and proteomics have added a new dimension to the study of protein-protein interactions and protein complex architecture. In this review, we focus on how complementary mass spectrometry-based techniques can greatly facilitate structural understanding of protein assemblies. PMID:22180098

Network science of biological systems at different scales: A review

NASA Astrophysics Data System (ADS)

Gosak, Marko; Markovič, Rene; Dolenšek, Jurij; Slak Rupnik, Marjan; Marhl, Marko; Stožer, Andraž; Perc, Matjaž

2018-03-01

Network science is today established as a backbone for description of structure and function of various physical, chemical, biological, technological, and social systems. Here we review recent advances in the study of complex biological systems that were inspired and enabled by methods of network science. First, we present

OpenStructure: a flexible software framework for computational structural biology.

PubMed

Biasini, Marco; Mariani, Valerio; Haas, Jürgen; Scheuber, Stefan; Schenk, Andreas D; Schwede, Torsten; Philippsen, Ansgar

2010-10-15

Developers of new methods in computational structural biology are often hampered in their research by incompatible software tools and non-standardized data formats. To address this problem, we have developed OpenStructure as a modular open source platform to provide a powerful, yet flexible general working environment for structural bioinformatics. OpenStructure consists primarily of a set of libraries written in C++ with a cleanly designed application programmer interface. All functionality can be accessed directly in C++ or in a Python layer, meeting both the requirements for high efficiency and ease of use. Powerful selection queries and the notion of entity views to represent these selections greatly facilitate the development and implementation of algorithms on structural data. The modular integration of computational core methods with powerful visualization tools makes OpenStructure an ideal working and development environment. Several applications, such as the latest versions of IPLT and QMean, have been implemented based on OpenStructure-demonstrating its value for the development of next-generation structural biology algorithms. Source code licensed under the GNU lesser general public license and binaries for MacOS X, Linux and Windows are available for download at http://www.openstructure.org. torsten.schwede@unibas.ch Supplementary data are available at Bioinformatics online.

A Bright Future for Serial Femtosecond Crystallography with XFELs.

PubMed

Johansson, Linda C; Stauch, Benjamin; Ishchenko, Andrii; Cherezov, Vadim

2017-09-01

X-ray free electron lasers (XFELs) have the potential to revolutionize macromolecular structural biology due to the unique combination of spatial coherence, extreme peak brilliance, and short duration of X-ray pulses. A recently emerged serial femtosecond (fs) crystallography (SFX) approach using XFEL radiation overcomes some of the biggest hurdles of traditional crystallography related to radiation damage through the diffraction-before-destruction principle. Intense fs XFEL pulses enable high-resolution room-temperature structure determination of difficult-to-crystallize biological macromolecules, while simultaneously opening a new era of time-resolved structural studies. Here, we review the latest developments in instrumentation, sample delivery, data analysis, crystallization methods, and applications of SFX to important biological questions, and conclude with brief insights into the bright future of structural biology using XFELs. Copyright © 2017 Elsevier Ltd. All rights reserved.

GOSA, a simulated annealing-based program for global optimization of nonlinear problems, also reveals transyears

PubMed Central

Czaplicki, Jerzy; Cornélissen, Germaine; Halberg, Franz

2009-01-01

Summary Transyears in biology have been documented thus far by the extended cosinor approach, including linear-nonlinear rhythmometry. We here confirm the existence of transyears by simulated annealing, a method originally developed for a much broader use, but described and introduced herein for validating its application to time series. The method is illustrated both on an artificial test case with known components and on biological data. We provide a table comparing results by the two methods and trust that the procedure will serve the budding sciences of chronobiology (the study of mechanisms underlying biological time structure), chronomics (the mapping of time structures in and around us), and chronobioethics, using the foregoing disciplines to add to concern for illnesses of individuals, and to budding focus on diseases of nations and civilizations. PMID:20414480

A general method for targeted quantitative cross-linking mass spectrometry

USDA-ARS?s Scientific Manuscript database

Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NM...

The Most Important Concept of Transport and Circulatory Systems: Turkish Biology Student Teachers' Cognitive Structure

ERIC Educational Resources Information Center

Kurt, Hakan; Ekici, Gulay; Aksu, Ozlem; Aktas, Murat

2013-01-01

The purpose of this study is to determine biology student teachers' cognitive structure with regard to "Blood". Qualitative research method has been used. The free word association test and the draw-write technique have been used in collection of data. The data obtained have been evaluated and divided into categories based on content…

Using novel descriptor accounting for ligand-receptor interactions to define and visually explore biologically relevant chemical space.

PubMed

Rabal, Obdulia; Oyarzabal, Julen

2012-05-25

The definition and pragmatic implementation of biologically relevant chemical space is critical in addressing navigation strategies in the overlapping regions where chemistry and therapeutically relevant targets reside and, therefore, also key to performing an efficient drug discovery project. Here, we describe the development and implementation of a simple and robust method for representing biologically relevant chemical space as a general reference according to current knowledge, independently of any reference space, and analyzing chemical structures accordingly. Underlying our method is the generation of a novel descriptor (LiRIf) that converts structural information into a one-dimensional string accounting for the plausible ligand-receptor interactions as well as for topological information. Capitalizing on ligand-receptor interactions as a descriptor enables the clustering, profiling, and comparison of libraries of compounds from a chemical biology and medicinal chemistry perspective. In addition, as a case study, R-groups analysis is performed to identify the most populated ligand-receptor interactions according to different target families (GPCR, kinases, etc.), as well as to evaluate the coverage of biologically relevant chemical space by structures annotated in different databases (ChEMBL, Glida, etc.).

Biological life-support systems

NASA Technical Reports Server (NTRS)

Shepelev, Y. Y.

1975-01-01

The establishment of human living environments by biologic methods, utilizing the appropriate functions of autotrophic and heterotrophic organisms is examined. Natural biologic systems discussed in terms of modeling biologic life support systems (BLSS), the structure of biologic life support systems, and the development of individual functional links in biologic life support systems are among the factors considered. Experimental modeling of BLSS in order to determine functional characteristics, mechanisms by which stability is maintained, and principles underlying control and regulation is also discussed.

RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

PubMed Central

Ellington, Roni; Wachira, James

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems. PMID:20810968

RNA secondary structure prediction by using discrete mathematics: an interdisciplinary research experience for undergraduate students.

PubMed

Ellington, Roni; Wachira, James; Nkwanta, Asamoah

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems.

Understanding pre-mRNA splicing through crystallography.

PubMed

Espinosa, Sara; Zhang, Lingdi; Li, Xueni; Zhao, Rui

2017-08-01

Crystallography is a powerful tool to determine the atomic structures of proteins and RNAs. X-ray crystallography has been used to determine the structure of many splicing related proteins and RNAs, making major contributions to our understanding of the molecular mechanism and regulation of pre-mRNA splicing. Compared to other structural methods, crystallography has its own advantage in the high-resolution structural information it can provide and the unique biological questions it can answer. In addition, two new crystallographic methods - the serial femtosecond crystallography and 3D electron crystallography - were developed to overcome some of the limitations of traditional X-ray crystallography and broaden the range of biological problems that crystallography can solve. This review discusses the theoretical basis, instrument requirements, troubleshooting, and exciting potential of these crystallographic methods to further our understanding of pre-mRNA splicing, a critical event in gene expression of all eukaryotes. Copyright © 2017 Elsevier Inc. All rights reserved.

Aspects of Theme in the Method and Discussion Sections of Biology Journal Articles in English.

ERIC Educational Resources Information Center

Martinez, Iliana A.

2003-01-01

Analyzes the thematic structure of the method and Discussion section of biology research articles. A corpus of 30 journal articles was analyzed using the categories of systematic functional linguistics and a semantic categorization for unmarked themes realized by subject. Revealed differences in the semantic construction of the sections. (VWL)

Models Role within Active Learning in Biology. A Case Study

ERIC Educational Resources Information Center

Pop-Pacurar, Irina; Tirla, Felicia-Doina

2009-01-01

In order to integrate ideas and information creatively, to motivate students and activate their thinking, we have used in Biology classes a series of active methods, among which the methods of critical thinking, which had very good results. Still, in the case of some intuitive, abstract, more difficult topics, such as the cell structure,…

Systems Biology as an Integrated Platform for Bioinformatics, Systems Synthetic Biology, and Systems Metabolic Engineering

PubMed Central

Chen, Bor-Sen; Wu, Chia-Chou

2013-01-01

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering. PMID:24709875

Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

PubMed

Chen, Bor-Sen; Wu, Chia-Chou

2013-10-11

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

The Widespread Prevalence and Functional Significance of Silk-Like Structural Proteins in Metazoan Biological Materials

PubMed Central

McDougall, Carmel; Woodcroft, Ben J.

2016-01-01

In nature, numerous mechanisms have evolved by which organisms fabricate biological structures with an impressive array of physical characteristics. Some examples of metazoan biological materials include the highly elastic byssal threads by which bivalves attach themselves to rocks, biomineralized structures that form the skeletons of various animals, and spider silks that are renowned for their exceptional strength and elasticity. The remarkable properties of silks, which are perhaps the best studied biological materials, are the result of the highly repetitive, modular, and biased amino acid composition of the proteins that compose them. Interestingly, similar levels of modularity/repetitiveness and similar bias in amino acid compositions have been reported in proteins that are components of structural materials in other organisms, however the exact nature and extent of this similarity, and its functional and evolutionary relevance, is unknown. Here, we investigate this similarity and use sequence features common to silks and other known structural proteins to develop a bioinformatics-based method to identify similar proteins from large-scale transcriptome and whole-genome datasets. We show that a large number of proteins identified using this method have roles in biological material formation throughout the animal kingdom. Despite the similarity in sequence characteristics, most of the silk-like structural proteins (SLSPs) identified in this study appear to have evolved independently and are restricted to a particular animal lineage. Although the exact function of many of these SLSPs is unknown, the apparent independent evolution of proteins with similar sequence characteristics in divergent lineages suggests that these features are important for the assembly of biological materials. The identification of these characteristics enable the generation of testable hypotheses regarding the mechanisms by which these proteins assemble and direct the construction of biological materials with diverse morphologies. The SilkSlider predictor software developed here is available at https://github.com/wwood/SilkSlider. PMID:27415783

Interactive and coordinated visualization approaches for biological data analysis.

PubMed

Cruz, António; Arrais, Joel P; Machado, Penousal

2018-03-26

The field of computational biology has become largely dependent on data visualization tools to analyze the increasing quantities of data gathered through the use of new and growing technologies. Aside from the volume, which often results in large amounts of noise and complex relationships with no clear structure, the visualization of biological data sets is hindered by their heterogeneity, as data are obtained from different sources and contain a wide variety of attributes, including spatial and temporal information. This requires visualization approaches that are able to not only represent various data structures simultaneously but also provide exploratory methods that allow the identification of meaningful relationships that would not be perceptible through data analysis algorithms alone. In this article, we present a survey of visualization approaches applied to the analysis of biological data. We focus on graph-based visualizations and tools that use coordinated multiple views to represent high-dimensional multivariate data, in particular time series gene expression, protein-protein interaction networks and biological pathways. We then discuss how these methods can be used to help solve the current challenges surrounding the visualization of complex biological data sets.

Integrative Approaches for Predicting in vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-term Biological Assays

PubMed Central

Low, Yen S.; Sedykh, Alexander; Rusyn, Ivan; Tropsha, Alexander

2017-01-01

Cheminformatics approaches such as Quantitative Structure Activity Relationship (QSAR) modeling have been used traditionally for predicting chemical toxicity. In recent years, high throughput biological assays have been increasingly employed to elucidate mechanisms of chemical toxicity and predict toxic effects of chemicals in vivo. The data generated in such assays can be considered as biological descriptors of chemicals that can be combined with molecular descriptors and employed in QSAR modeling to improve the accuracy of toxicity prediction. In this review, we discuss several approaches for integrating chemical and biological data for predicting biological effects of chemicals in vivo and compare their performance across several data sets. We conclude that while no method consistently shows superior performance, the integrative approaches rank consistently among the best yet offer enriched interpretation of models over those built with either chemical or biological data alone. We discuss the outlook for such interdisciplinary methods and offer recommendations to further improve the accuracy and interpretability of computational models that predict chemical toxicity. PMID:24805064

Loading and conjugating cavity biostructures

DOEpatents

Hainfeld, J.F.

1997-11-25

Methods for the preparation and use of a biological delivery system are disclosed. The method of preparation includes the loading of a non-biological material into a biostructure having a load-bearing structure. The method also includes the removal of some of the biostructure`s contents and the loading of a non-biological material into the biostructure. The biostructure is biologically compatible with the host, and preferably is derived from the host, the host`s species or a related species. The loaded biostructure is used directly, or it can be targeted to specific cells, tissues and/or organs within a host. The targeted biostructure can be used to deliver the non-biological material to a specified tissue, organ or cell within a host for diagnostic, therapeutic or other purposes. 11 figs.

Loading and conjugating cavity biostructures

DOEpatents

Hainfeld, J.F.

1995-08-22

Methods for the preparation and use of a biological delivery system are disclosed. The method of preparation includes the loading of a non-biological material into a biostructure having a load-bearing structure. The method also includes the removal of some of the biostructure`s contents and the loading of a non-biological material into the biostructure. The biostructure is biologically compatible with the host, and preferably is derived from the host, the host`s species or a related species. The loaded biostructure is used directly, or it can be targeted to specific cells, tissues and/or organs within a host. The targeted biostructure can be used to deliver the non-biological material to a specified tissue, organ or cell within a host for diagnostic, therapeutic or other purposes. 11 figs.

Permeating disciplines: Overcoming barriers between molecular simulations and classical structure-function approaches in biological ion transport.

PubMed

Howard, Rebecca J; Carnevale, Vincenzo; Delemotte, Lucie; Hellmich, Ute A; Rothberg, Brad S

2018-04-01

Ion translocation across biological barriers is a fundamental requirement for life. In many cases, controlling this process-for example with neuroactive drugs-demands an understanding of rapid and reversible structural changes in membrane-embedded proteins, including ion channels and transporters. Classical approaches to electrophysiology and structural biology have provided valuable insights into several such proteins over macroscopic, often discontinuous scales of space and time. Integrating these observations into meaningful mechanistic models now relies increasingly on computational methods, particularly molecular dynamics simulations, while surfacing important challenges in data management and conceptual alignment. Here, we seek to provide contemporary context, concrete examples, and a look to the future for bridging disciplinary gaps in biological ion transport. This article is part of a Special Issue entitled: Beyond the Structure-Function Horizon of Membrane Proteins edited by Ute Hellmich, Rupak Doshi and Benjamin McIlwain. Copyright © 2017 Elsevier B.V. All rights reserved.

2010 Diffraction Methods in Structural Biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dr. Ana Gonzalez

2011-03-10

Advances in basic methodologies have played a major role in the dramatic progress in macromolecular crystallography over the past decade, both in terms of overall productivity and in the increasing complexity of the systems being successfully tackled. The 2010 Gordon Research Conference on Diffraction Methods in Structural Biology will, as in the past, focus on the most recent developments in methodology, covering all aspects of the process from crystallization to model building and refinement, complemented by examples of structural highlights and complementary methods. Extensive discussion will be encouraged and it is hoped that all attendees will participate by giving oralmore » or poster presentations, the latter using the excellent poster display area available at Bates College. The relatively small size and informal atmosphere of the meeting provides an excellent opportunity for all participants, especially younger scientists, to meet and exchange ideas with leading methods developers.« less

Computer support for physiological cell modelling using an ontology on cell physiology.

PubMed

Takao, Shimayoshi; Kazuhiro, Komurasaki; Akira, Amano; Takeshi, Iwashita; Masanori, Kanazawa; Tetsuya, Matsuda

2006-01-01

The development of electrophysiological whole cell models to support the understanding of biological mechanisms is increasing rapidly. Due to the complexity of biological systems, comprehensive cell models, which are composed of many imported sub-models of functional elements, can get quite complicated as well, making computer modification difficult. Here, we propose a computer support to enhance structural changes of cell models, employing the markup languages CellML and our original PMSML (physiological model structure markup language), in addition to a new ontology for cell physiological modelling. In particular, a method to make references from CellML files to the ontology and a method to assist manipulation of model structures using markup languages together with the ontology are reported. Using these methods three software utilities, including a graphical model editor, are implemented. Experimental results proved that these methods are effective for the modification of electrophysiological models.

First-principles modeling of biological systems and structure-based drug-design.

PubMed

Sgrignani, Jacopo; Magistrato, Alessandra

2013-03-01

Molecular modeling techniques play a relevant role in drug design providing detailed information at atomistic level on the structural, dynamical, mechanistic and electronic properties of biological systems involved in diseases' onset, integrating and supporting commonly used experimental approaches. These information are often not accessible to the experimental techniques taken singularly, but are of crucial importance for drug design. Due to the enormous increase of the computer power in the last decades, quantum mechanical (QM) or first-principles-based methods have become often used to address biological issues of pharmaceutical relevance, providing relevant information for drug design. Due to their complexity and their size, biological systems are often investigated by means of a mixed quantum-classical (QM/MM) approach, which treats at an accurate QM level a limited chemically relevant portion of the system and at the molecular mechanics (MM) level the remaining of the biomolecule and its environment. This method provides a good compromise between computational cost and accuracy, allowing to characterize the properties of the biological system and the (free) energy landscape of the process in study with the accuracy of a QM description. In this review, after a brief introduction of QM and QM/MM methods, we will discuss few representative examples, taken from our work, of the application of these methods in the study of metallo-enzymes of pharmaceutical interest, of metal-containing anticancer drugs targeting the DNA as well as of neurodegenerative diseases. The information obtained from these studies may provide the basis for a rationale structure-based drug design of new and more efficient inhibitors or drugs.

Three-dimensional refractive index and fluorescence tomography using structured illumination (Conference Presentation)

NASA Astrophysics Data System (ADS)

Park, GwangSik; Shin, SeungWoo; Kim, Kyoohyun; Park, YongKeun

2017-02-01

Optical diffraction tomography (ODT) has been an emerging optical technique for label-free imaging of three-dimensional (3-D) refractive index (RI) distribution of biological samples. ODT employs interferometric microscopy for measuring multiple holograms of samples with various incident angles, from which the Fourier diffraction theorem reconstructs the 3-D RI distribution of samples from retrieved complex optical fields. Since the RI value is linearly proportional to the protein concentration of biological samples where the proportional coefficient is called as refractive index increment (RII), reconstructed 3-D RI tomograms provide precise structural and biochemical information of individual biological samples. Because most proteins have similar RII value, however, ODT has limited molecular specificity, especially for imaging eukaryotic cells having various types of proteins and subcellular organelles. Here, we present an ODT system combined with structured illumination microscopy which can measure the 3-D RI distribution of biological samples as well as 3-D super-resolution fluorescent images in the same optical setup. A digital micromirror device (DMD) controls the incident angle of the illumination beam for tomogram reconstruction, and the same DMD modulates the structured illumination pattern of the excitation beam for super-resolution fluorescent imaging. We first validate the proposed method for simultaneous optical diffraction tomographic imaging and super-resolution fluorescent imaging of fluorescent beads. The proposed method is also exploited for various biological samples.

Structural and chemical aspects of HPMA copolymers as drug carriers.

PubMed

Ulbrich, Karel; Subr, Vladimír

2010-02-17

Synthetic strategies and chemical and structural aspects of the synthesis of HPMA copolymer conjugates with various drugs and other biologically active molecules are described and discussed in this chapter. The discussion is held from the viewpoint of design and structure of the polymer backbone and biodegradable spacer between a polymer and drug, structure and methods of attachment of the employed drugs to the carrier and structure and methods of conjugation with targeting moieties. Physicochemical properties of the water-soluble polymer-drug conjugates and polymer micelles including mechanisms of drug release are also discussed. Detailed description of biological behavior of the polymer-drug conjugates as well as application of the copolymers for surface modification and targeting of gene delivery vectors are not included, they are presented and discussed in separate chapters of this issue. Copyright 2009 Elsevier B.V. All rights reserved.

THE PRACTICE OF STRUCTURE ACTIVITY RELATIONSHIPS (SAR) IN TOXICOLOGY

EPA Science Inventory

Both qualitative and quantitative modeling methods relating chemical structure to biological activity, called structure-activity relationship analyses or SAR, are applied to the prediction and characterization of chemical toxicity. This minireview will discuss some generic issue...

Super-Resolution Microscopy Techniques and Their Potential for Applications in Radiation Biophysics.

PubMed

Eberle, Jan Philipp; Rapp, Alexander; Krufczik, Matthias; Eryilmaz, Marion; Gunkel, Manuel; Erfle, Holger; Hausmann, Michael

2017-01-01

Fluorescence microscopy is an essential tool for imaging tagged biological structures. Due to the wave nature of light, the resolution of a conventional fluorescence microscope is limited laterally to about 200 nm and axially to about 600 nm, which is often referred to as the Abbe limit. This hampers the observation of important biological structures and dynamics in the nano-scaled range ~10 nm to ~100 nm. Consequentially, various methods have been developed circumventing this limit of resolution. Super-resolution microscopy comprises several of those methods employing physical and/or chemical properties, such as optical/instrumental modifications and specific labeling of samples. In this article, we will give a brief insight into a variety of selected optical microscopy methods reaching super-resolution beyond the Abbe limit. We will survey three different concepts in connection to biological applications in radiation research without making a claim to be complete.

Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets

PubMed Central

McKinney, Bill; Meyer, Peter A.; Crosas, Mercè; Sliz, Piotr

2016-01-01

Access to experimental X-ray diffraction image data is important for validation and reproduction of macromolecular models and indispensable for the development of structural biology processing methods. In response to the evolving needs of the structural biology community, we recently established a diffraction data publication system, the Structural Biology Data Grid (SBDG, data.sbgrid.org), to preserve primary experimental datasets supporting scientific publications. All datasets published through the SBDG are freely available to the research community under a public domain dedication license, with metadata compliant with the DataCite Schema (schema.datacite.org). A proof-of-concept study demonstrated community interest and utility. Publication of large datasets is a challenge shared by several fields, and the SBDG has begun collaborating with the Institute for Quantitative Social Science at Harvard University to extend the Dataverse (dataverse.org) open-source data repository system to structural biology datasets. Several extensions are necessary to support the size and metadata requirements for structural biology datasets. In this paper, we describe one such extension—functionality supporting preservation of filesystem structure within Dataverse—which is essential for both in-place computation and supporting non-http data transfers. PMID:27862010

New Synthetic Methods for Hypericum Natural Products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeon, Insik

Organic chemistry has served as a solid foundation for interdisciplinary research areas, such as molecular biology and medicinal chemistry. An understanding of the biological activities and structural elucidations of natural products can lead to the development of clinically valuable therapeutic options. The advancements of modern synthetic methodologies allow for more elaborate and concise natural product syntheses. The theme of this study centers on the synthesis of natural products with particularly challenging structures and interesting biological activities. The synthetic expertise developed here will be applicable to analog syntheses and to other research problems.

Color mapping of one specific velocity of a biological fluid flows with complex geometry using optical coherence tomography

NASA Astrophysics Data System (ADS)

Potlov, A. Yu.; Frolov, S. V.; Proskurin, S. G.

2018-04-01

The method of Doppler color mapping of one specific (previously chosen) velocity in a turbulent flow inside biological tissues using optical coherence tomography is described. The key features of the presented method are: the raw data are separated into three parts, corresponding to the unmoving biological tissue, the positively and negatively directed biological fluid flows; the further independent signal processing procedure yields the structure image and two images of the chosen velocity, which are then normalised, encoded and joined. The described method can be used to obtain in real time the anatomical maps of the chosen velocities in normal and pathological states. The described method can be applied not only in optical coherence tomography, but also in endoscopic and Doppler ultrasonic medical imaging systems.

Evolving cell models for systems and synthetic biology.

PubMed

Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio

2010-03-01

This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.

A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization

PubMed Central

2012-01-01

Background Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. Methods We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. Results The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. Conclusions By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications. PMID:22448851

Introduction to electron crystallography.

PubMed

Kühlbrandt, Werner

2013-01-01

From the earliest work on regular arrays in negative stain, electron crystallography has contributed greatly to our understanding of the structure and function of biological macromolecules. The development of electron cryo-microscopy (cryo-EM) then lead to the first groundbreaking atomic models of the membrane proteins bacteriorhodopsin and light harvesting complex II within lipid bilayers. Key contributions towards cryo-EM and electron crystallography methods included specimen preparation and vitrification, liquid-helium cooling, data collection, and image processing. These methods are now applied almost routinely to both membrane and soluble proteins. Here we outline the advances and the breakthroughs that paved the way towards high-resolution structures by electron crystallography, both in terms of methods development and biological milestones.

Harnessing glycomics technologies: integrating structure with function for glycan characterization

PubMed Central

Robinson, Luke N.; Artpradit, Charlermchai; Raman, Rahul; Shriver, Zachary H.; Ruchirawat, Mathuros; Sasisekharan, Ram

2013-01-01

Glycans, or complex carbohydrates, are a ubiquitous class of biological molecules which impinge on a variety of physiological processes ranging from signal transduction to tissue development and microbial pathogenesis. In comparison to DNA and proteins, glycans present unique challenges to the study of their structure and function owing to their complex and heterogeneous structures and the dominant role played by multivalency in their sequence-specific biological interactions. Arising from these challenges, there is a need to integrate information from multiple complementary methods to decode structure-function relationships. Focusing on acidic glycans, we describe here key glycomics technologies for characterizing their structural attributes, including linkage, modifications, and topology, as well as for elucidating their role in biological processes. Two cases studies, one involving sialylated branched glycans and the other sulfated glycosaminoglycans, are used to highlight how integration of orthogonal information from diverse datasets enables rapid convergence of glycan characterization for development of robust structure-function relationships. PMID:22522536

Biopolymers for sample collection, protection, and preservation.

PubMed

Sorokulova, Iryna; Olsen, Eric; Vodyanoy, Vitaly

2015-07-01

One of the principal challenges in the collection of biological samples from air, water, and soil matrices is that the target agents are not stable enough to be transferred from the collection point to the laboratory of choice without experiencing significant degradation and loss of viability. At present, there is no method to transport biological samples over considerable distances safely, efficiently, and cost-effectively without the use of ice or refrigeration. Current techniques of protection and preservation of biological materials have serious drawbacks. Many known techniques of preservation cause structural damages, so that biological materials lose their structural integrity and viability. We review applications of a novel bacterial preservation process, which is nontoxic and water soluble and allows for the storage of samples without refrigeration. The method is capable of protecting the biological sample from the effects of environment for extended periods of time and then allows for the easy release of these collected biological materials from the protective medium without structural or DNA damage. Strategies for sample collection, preservation, and shipment of bacterial, viral samples are described. The water-soluble polymer is used to immobilize the biological material by replacing the water molecules within the sample with molecules of the biopolymer. The cured polymer results in a solid protective film that is stable to many organic solvents, but quickly removed by the application of the water-based solution. The process of immobilization does not require the use of any additives, accelerators, or plastifiers and does not involve high temperature or radiation to promote polymerization.

[Computational chemistry in structure-based drug design].

PubMed

Cao, Ran; Li, Wei; Sun, Han-Zi; Zhou, Yu; Huang, Niu

2013-07-01

Today, the understanding of the sequence and structure of biologically relevant targets is growing rapidly and researchers from many disciplines, physics and computational science in particular, are making significant contributions to modern biology and drug discovery. However, it remains challenging to rationally design small molecular ligands with desired biological characteristics based on the structural information of the drug targets, which demands more accurate calculation of ligand binding free-energy. With the rapid advances in computer power and extensive efforts in algorithm development, physics-based computational chemistry approaches have played more important roles in structure-based drug design. Here we reviewed the newly developed computational chemistry methods in structure-based drug design as well as the elegant applications, including binding-site druggability assessment, large scale virtual screening of chemical database, and lead compound optimization. Importantly, here we address the current bottlenecks and propose practical solutions.

Comprehensive inventory of protein complexes in the Protein Data Bank from consistent classification of interfaces.

PubMed

Bordner, Andrew J; Gorin, Andrey A

2008-05-12

Protein-protein interactions are ubiquitous and essential for all cellular processes. High-resolution X-ray crystallographic structures of protein complexes can reveal the details of their function and provide a basis for many computational and experimental approaches. Differentiation between biological and non-biological contacts and reconstruction of the intact complex is a challenging computational problem. A successful solution can provide additional insights into the fundamental principles of biological recognition and reduce errors in many algorithms and databases utilizing interaction information extracted from the Protein Data Bank (PDB). We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1) comprehensively collecting all protein-protein interfaces; (2) clustering similar protein-protein interfaces together; (3) estimating the probability that each cluster is relevant based on a diverse set of properties; and (4) combining these scores for each PDB entry in order to predict the complex structure. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions. These interfaces, as well as the predicted protein complexes, are available from the Protein Interface Server (PInS) website (see Availability and requirements section). Our method demonstrates an almost two-fold reduction of the annotation error rate as evaluated on a large benchmark set of complexes validated from the literature. We also estimate relative contributions of each interface property to the accurate discrimination of biologically relevant interfaces and discuss possible directions for further improving the prediction method.

Three novel approaches to structural identifiability analysis in mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not possible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

3D molecular models of whole HIV-1 virions generated with cellPACK

PubMed Central

Goodsell, David S.; Autin, Ludovic; Forli, Stefano; Sanner, Michel F.; Olson, Arthur J.

2014-01-01

As knowledge of individual biological processes grows, it becomes increasingly useful to frame new findings within their larger biological contexts in order to generate new systems-scale hypotheses. This report highlights two major iterations of a whole virus model of HIV-1, generated with the cellPACK software. cellPACK integrates structural and systems biology data with packing algorithms to assemble comprehensive 3D models of cell-scale structures in molecular detail. This report describes the biological data, modeling parameters and cellPACK methods used to specify and construct editable models for HIV-1. Anticipating that cellPACK interfaces under development will enable researchers from diverse backgrounds to critique and improve the biological models, we discuss how cellPACK can be used as a framework to unify different types of data across all scales of biology. PMID:25253262

Acoustic fine structure may encode biologically relevant information for zebra finches.

PubMed

Prior, Nora H; Smith, Edward; Lawson, Shelby; Ball, Gregory F; Dooling, Robert J

2018-04-18

The ability to discriminate changes in the fine structure of complex sounds is well developed in birds. However, the precise limit of this discrimination ability and how it is used in the context of natural communication remains unclear. Here we describe natural variability in acoustic fine structure of male and female zebra finch calls. Results from psychoacoustic experiments demonstrate that zebra finches are able to discriminate extremely small differences in fine structure, which are on the order of the variation in acoustic fine structure that is present in their vocal signals. Results from signal analysis methods also suggest that acoustic fine structure may carry information that distinguishes between biologically relevant categories including sex, call type and individual identity. Combined, our results are consistent with the hypothesis that zebra finches can encode biologically relevant information within the fine structure of their calls. This study provides a foundation for our understanding of how acoustic fine structure may be involved in animal communication.

Model structure identification for wastewater treatment simulation based on computational fluid dynamics.

PubMed

Alex, J; Kolisch, G; Krause, K

2002-01-01

The objective of this presented project is to use the results of an CFD simulation to automatically, systematically and reliably generate an appropriate model structure for simulation of the biological processes using CSTR activated sludge compartments. Models and dynamic simulation have become important tools for research but also increasingly for the design and optimisation of wastewater treatment plants. Besides the biological models several cases are reported about the application of computational fluid dynamics ICFD) to wastewater treatment plants. One aim of the presented method to derive model structures from CFD results is to exclude the influence of empirical structure selection to the result of dynamic simulations studies of WWTPs. The second application of the approach developed is the analysis of badly performing treatment plants where the suspicion arises that bad flow behaviour such as short cut flows is part of the problem. The method suggested requires as the first step the calculation of fluid dynamics of the biological treatment step at different loading situations by use of 3-dimensional CFD simulation. The result of this information is used to generate a suitable model structure for conventional dynamic simulation of the treatment plant by use of a number of CSTR modules with a pattern of exchange flows between the tanks automatically. The method is explained in detail and the application to the WWTP Wuppertal Buchenhofen is presented.

Polarization visualization of changes of anisotropic meat structure

NASA Astrophysics Data System (ADS)

Blokhina, Anastasia A.; Ryzhova, Victoria A.; Kleshchenok, Maksim A.; Lobanova, Anastasiya Y.

2017-06-01

The main aspect in developing methods for optical diagnostics and visualization of biological tissues using polarized radiation is the transformation analysis of the state of light polarization when it is scattered by the medium. The polarization characteristic spatial distributions of the detected scattered radiation, in particular the degree of depolarization, have a pronounced anisotropy. The presence of optical anisotropy can provide valuable additional information on the structural features of the biological object and its physiological status. Analysis of the polarization characteristics of the scattered radiation of biological tissues in some cases provides a qualitatively new results in the study of biological samples. These results can be used in medicine and food industry.

The system spatial-frequency filtering of birefringence images of human blood layers

NASA Astrophysics Data System (ADS)

Ushenko, A. G.; Boychuk, T. M.; Mincer, O. P.; Angelsky, P. O.; Bodnar, N. B.; Oleinichenko, B. P.; Bizer, L. I.

2013-09-01

Among various opticophysical methods [1 - 3] of diagnosing the structure and properties of the optical anisotropic component of various biological objects a specific trend has been singled out - multidimensional laser polarimetry of microscopic images of the biological tissues with the following statistic, correlative and fractal analysis of the coordinate distributions of the azimuths and ellipticity of polarization in approximating of linear birefringence polycrystalline protein networks [4 - 10]. At the same time, in most cases, experimental obtaining of tissue sample is a traumatic biopsy operation. In addition, the mechanisms of transformation of the state of polarization of laser radiation by means of the opticoanisotropic biological structures are more varied (optical dichroism, circular birefringence). Hereat, real polycrystalline networks can be formed by different types, both in size and optical properties of biological crystals. Finally, much more accessible for an experimental investigation are biological fluids such as blood, bile, urine, and others. Thus, further progress of laser polarimetry can be associated with the development of new methods of analysis and processing (selection) of polarization- heterogeneous images of biological tissues and fluids, taking into account a wider set of mechanisms anisotropic mechanisms. Our research is aimed at developing experimental method of the Fourier polarimetry and a spatialfrequency selection for distributions of the azimuth and the ellipticity polarization of blood plasma laser images with a view of diagnosing prostate cancer.

Method and apparatus for sustaining viability of biological cells on a substrate

DOEpatents

McKnight, Timothy E.; Melechko, Anatoli V.; Simpson, Michael L.

2013-01-01

A method for the transient transformation of a living biological cell having an intact cell membrane defining an intracellular domain, and an apparatus for the transient transformation of biological cells. The method and apparatus include introducing a compartmentalized extracellular component fixedly attached to a cellular penetrant structure to the intracellular domain of the cell, wherein the cell is fixed in a predetermined location and wherein the component is expressed within in the cell while being retained within the compartment and wherein the compartment restricts the mobility and interactions of the component within the cell and prevents transference of the component to the cell.

Method and apparatus for sustaining viability of biological cells on a substrate

DOEpatents

McKnight, Timothy E [Greenback, TN; Melechko, Anatoli V [Oak Ridge, TN; Simpson, Michael L [Knoxville, TN

2011-12-13

A method for the transient transformation of a living biological cell having an intact cell membrane defining an intracellular domain, and an apparatus for the transient transformation of biological cells. The method and apparatus include introducing a compartmentalized extracellular component fixedly attached to a cellular penetrant structure to the intracellular domain of the cell, wherein the cell is fixed in a predetermined location and wherein the component is expressed within in the cell while being retained within the compartment and wherein the compartment restricts the mobility and interactions of the component within the cell and prevents transference of the component to the cell.

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

PubMed

duVerle, David A; Yotsukura, Sohiya; Nomura, Seitaro; Aburatani, Hiroyuki; Tsuda, Koji

2016-09-13

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths. Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights. With cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/ .

A laser-engraved glass duplicating the structure, mechanics and performance of natural nacre.

PubMed

Valashani, Seyed Mohammad Mirkhalaf; Barthelat, Francois

2015-03-30

Highly mineralized biological materials such as nacre (mother of pearl), tooth enamel or conch shell boast unique and attractive combinations of stiffness, strength and toughness. The structures of these biological materials and their associated mechanisms are now inspiring new types of advanced structural materials. However, despite significant efforts, no bottom up fabrication method could so far match biological materials in terms of microstructural organization and mechanical performance. Here we present a new 'top down' strategy to tackling this fabrication problem, which consists in carving weak interfaces within a brittle material using a laser engraving technique. We demonstrate the method by fabricating and testing borosilicate glasses containing nacre-like microstructures infiltrated with polyurethane. When deformed, these materials properly duplicate the mechanisms of natural nacre: combination of controlled sliding of the tablets, accompanied with geometric hardening, strain hardening and strain rate hardening. The nacre-like glass is composed of 93 volume % (vol%) glass, yet 700 times tougher and breaks at strains as high as 20%.

Recombinant protein expression for structural biology in HEK 293F suspension cells: a novel and accessible approach.

PubMed

Portolano, Nicola; Watson, Peter J; Fairall, Louise; Millard, Christopher J; Milano, Charles P; Song, Yun; Cowley, Shaun M; Schwabe, John W R

2014-10-16

The expression and purification of large amounts of recombinant protein complexes is an essential requirement for structural biology studies. For over two decades, prokaryotic expression systems such as E. coli have dominated the scientific literature over costly and less efficient eukaryotic cell lines. Despite the clear advantage in terms of yields and costs of expressing recombinant proteins in bacteria, the absence of specific co-factors, chaperones and post-translational modifications may cause loss of function, mis-folding and can disrupt protein-protein interactions of certain eukaryotic multi-subunit complexes, surface receptors and secreted proteins. The use of mammalian cell expression systems can address these drawbacks since they provide a eukaryotic expression environment. However, low protein yields and high costs of such methods have until recently limited their use for structural biology. Here we describe a simple and accessible method for expressing and purifying milligram quantities of protein by performing transient transfections of suspension grown HEK (Human Embryonic Kidney) 293 F cells.

Bioinspired Design: Magnetic Freeze Casting

NASA Astrophysics Data System (ADS)

Porter, Michael Martin

Nature is the ultimate experimental scientist, having billions of years of evolution to design, test, and adapt a variety of multifunctional systems for a plethora of diverse applications. Next-generation materials that draw inspiration from the structure-property-function relationships of natural biological materials have led to many high-performance structural materials with hybrid, hierarchical architectures that fit form to function. In this dissertation, a novel materials processing method, magnetic freeze casting, is introduced to develop porous scaffolds and hybrid composites with micro-architectures that emulate bone, abalone nacre, and other hard biological materials. This method uses ice as a template to form ceramic-based materials with continuously, interconnected microstructures and magnetic fields to control the alignment of these structures in multiple directions. The resulting materials have anisotropic properties with enhanced mechanical performance that have potential applications as bone implants or lightweight structural composites, among others.

SFG analysis of surface bound proteins: a route towards structure determination.

PubMed

Weidner, Tobias; Castner, David G

2013-08-14

The surface of a material is rapidly covered with proteins once that material is placed in a biological environment. The structure and function of these bound proteins play a key role in the interactions and communications of the material with the biological environment. Thus, it is crucial to gain a molecular level understanding of surface bound protein structure. While X-ray diffraction and solution phase NMR methods are well established for determining the structure of proteins in the crystalline or solution phase, there is not a corresponding single technique that can provide the same level of structural detail about proteins at surfaces or interfaces. However, recent advances in sum frequency generation (SFG) vibrational spectroscopy have significantly increased our ability to obtain structural information about surface bound proteins and peptides. A multi-technique approach of combining SFG with (1) protein engineering methods to selectively introduce mutations and isotopic labels, (2) other experimental methods such as time-of-flight secondary ion mass spectrometry (ToF-SIMS) and near edge X-ray absorption fine structure (NEXAFS) to provide complementary information, and (3) molecular dynamic (MD) simulations to extend the molecular level experimental results is a particularly promising route for structural characterization of surface bound proteins and peptides. By using model peptides and small proteins with well-defined structures, methods have been developed to determine the orientation of both backbone and side chains to the surface.

SFG analysis of surface bound proteins: A route towards structure determination

PubMed Central

Weidner, Tobias; Castner, David G.

2013-01-01

The surface of a material is rapidly covered with proteins once that material is placed in a biological environment. The structure and function of these bound proteins play a key role in the interactions and communications of the material with the biological environment. Thus, it is crucial to gain a molecular level understanding of surface bound protein structure. While X-ray diffraction and solution phase NMR methods are well established for determining the structure of proteins in the crystalline or solution phase, there is not a corresponding single technique that can provide the same level of structural detail about proteins at surfaces or interfaces. However, recent advances in sum frequency generation (SFG) vibrational spectroscopy have significantly increased our ability to obtain structural information about surface bound proteins and peptides. A multi-technique approach of combining SFG with (1) protein engineering methods to selectively introduce mutations and isotopic labels, (2) other experimental methods such as time-of-flight secondary ion mass spectrometry (ToF-SIMS) and near edge x-ray absorption fine structure (NEXAFS) to provide complementary information, and (3) molecular dynamic (MD) simulations to extend the molecular level experimental results is a particularly promising route for structural characterization of surface bound proteins and peptides. By using model peptides and small proteins with well-defined structures, methods have been developed to determine the orientation of both backbone and side chains to the surface. PMID:23727992

[Structural Study in the Platform for Drug Discovery, Informatics, and Structural Life Science].

PubMed

Senda, Toshiya

2016-01-01

The Platform for Drug Discovery, Informatics, and Structural Life Science (PDIS), which has been launched since FY2012, is a national project in the field of structural biology. The PDIS consists of three cores - structural analysis, control, and informatics - and aims to support life science researchers who are not familiar with structural biology. The PDIS project is able to provide full-scale support for structural biology research. The support provided by the PDIS project includes protein purification with various expression systems, large scale protein crystallization, crystal structure determination, small angle scattering (SAXS), NMR, electron microscopy, bioinformatics, etc. In order to utilize these methods of support, PDIS users need to submit an application form to the one-stop service office. Submitted applications will be reviewed by three referees. It is strongly encouraged that PDIS users have sufficient discussion with researchers in the PDIS project before submitting the application. This discussion is very useful in the process of project design, particularly for beginners in structural biology. In addition to this user support, the PDIS project has conducted R&D, which includes the development of synchrotron beamlines. In the PDIS project, PF and SPring-8 have developed beamlines for micro-crystallography, high-throughput data collection, supramolecular assembly, and native single anomalous dispersion (SAD) phasing. The newly developed beamlines have been open to all users, and have accelerated structural biology research. Beamlines for SAXS have also been developed, which has dramatically increased bio-SAXS users.

Marine Antifreeze Proteins: Structure, Function, and Application to Cryopreservation as a Potential Cryoprotectant

PubMed Central

Kim, Hak Jun; Lee, Jun Hyuck; Hur, Young Baek; Lee, Chang Woo; Park, Sun-Ha; Koo, Bon-Won

2017-01-01

Antifreeze proteins (AFPs) are biological antifreezes with unique properties, including thermal hysteresis (TH), ice recrystallization inhibition (IRI), and interaction with membranes and/or membrane proteins. These properties have been utilized in the preservation of biological samples at low temperatures. Here, we review the structure and function of marine-derived AFPs, including moderately active fish AFPs and hyperactive polar AFPs. We also survey previous and current reports of cryopreservation using AFPs. Cryopreserved biological samples are relatively diverse ranging from diatoms and reproductive cells to embryos and organs. Cryopreserved biological samples mainly originate from mammals. Most cryopreservation trials using marine-derived AFPs have demonstrated that addition of AFPs can improve post-thaw viability regardless of freezing method (slow-freezing or vitrification), storage temperature, and types of biological sample type. PMID:28134801

Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets.

PubMed

McKinney, Bill; Meyer, Peter A; Crosas, Mercè; Sliz, Piotr

2017-01-01

Access to experimental X-ray diffraction image data is important for validation and reproduction of macromolecular models and indispensable for the development of structural biology processing methods. In response to the evolving needs of the structural biology community, we recently established a diffraction data publication system, the Structural Biology Data Grid (SBDG, data.sbgrid.org), to preserve primary experimental datasets supporting scientific publications. All datasets published through the SBDG are freely available to the research community under a public domain dedication license, with metadata compliant with the DataCite Schema (schema.datacite.org). A proof-of-concept study demonstrated community interest and utility. Publication of large datasets is a challenge shared by several fields, and the SBDG has begun collaborating with the Institute for Quantitative Social Science at Harvard University to extend the Dataverse (dataverse.org) open-source data repository system to structural biology datasets. Several extensions are necessary to support the size and metadata requirements for structural biology datasets. In this paper, we describe one such extension-functionality supporting preservation of file system structure within Dataverse-which is essential for both in-place computation and supporting non-HTTP data transfers. © 2016 New York Academy of Sciences.

The ins and outs of lncRNA structure: How, why and what comes next?

PubMed

Blythe, Amanda J; Fox, Archa H; Bond, Charles S

2016-01-01

The field of structural biology has the unique advantage of being able to provide a comprehensive picture of biological mechanisms at the molecular and atomic level. Long noncoding RNAs (lncRNAs) represent the new frontier in the molecular biology of complex organisms yet remain the least characterised of all the classes of RNA. Thousands of new lncRNAs are being reported each year yet very little structural data exists for this rapidly expanding field. The length of lncRNAs ranges from 200 nt to over 100 kb in length and they generally exhibit low cellular abundance. Therefore, obtaining sufficient quantities of lncRNA to use for structural analysis is challenging. However, as technologies develop structures of lncRNAs are starting to emerge providing important information regarding their mechanism of action. Here we review the current methods used to determine the structure of lncRNA and lncRNA:protein complexes and describe the significant contribution structural biology has and will make to the field of lncRNA research. This article is part of a Special Issue entitled: Clues to long noncoding RNA taxonomy1, edited by Dr. Tetsuro Hirose and Dr. Shinichi Nakagawa. Copyright © 2015 Elsevier B.V. All rights reserved.

Lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry and its application to complex biological samples

PubMed Central

Triebl, Alexander; Trötzmüller, Martin; Hartler, Jürgen; Stojakovic, Tatjana; Köfeler, Harald C

2018-01-01

An improved approach for selective and sensitive identification and quantitation of lipid molecular species using reversed phase chromatography coupled to high resolution mass spectrometry was developed. The method is applicable to a wide variety of biological matrices using a simple liquid-liquid extraction procedure. Together, this approach combines three selectivity criteria: Reversed phase chromatography separates lipids according to their acyl chain length and degree of unsaturation and is capable of resolving positional isomers of lysophospholipids, as well as structural isomers of diacyl phospholipids and glycerolipids. Orbitrap mass spectrometry delivers the elemental composition of both positive and negative ions with high mass accuracy. Finally, automatically generated tandem mass spectra provide structural insight into numerous glycerolipids, phospholipids, and sphingolipids within a single run. Method validation resulted in a linearity range of more than four orders of magnitude, good values for accuracy and precision at biologically relevant concentration levels, and limits of quantitation of a few femtomoles on column. Hundreds of lipid molecular species were detected and quantified in three different biological matrices, which cover well the wide variety and complexity of various model organisms in lipidomic research. Together with a reliable software package, this method is a prime choice for global lipidomic analysis of even the most complex biological samples. PMID:28415015

Methods for the Study of Gonadal Development.

PubMed

Piprek, Rafal P

2016-01-01

Current knowledge on gonadal development and sex determination is the product of many decades of research involving a variety of scientific methods from different biological disciplines such as histology, genetics, biochemistry, and molecular biology. The earliest embryological investigations, followed by the invention of microscopy and staining methods, were based on histological examinations. The most robust development of histological staining techniques occurred in the second half of the nineteenth century and resulted in structural descriptions of gonadogenesis. These first studies on gonadal development were conducted on domesticated animals; however, currently the mouse is the most extensively studied species. The next key point in the study of gonadogenesis was the advancement of methods allowing for the in vitro culture of fetal gonads. For instance, this led to the description of the origin of cell lines forming the gonads. Protein detection using antibodies and immunolabeling methods and the use of reporter genes were also invaluable for developmental studies, enabling the visualization of the formation of gonadal structure. Recently, genetic and molecular biology techniques, especially gene expression analysis, have revolutionized studies on gonadogenesis and have provided insight into the molecular mechanisms that govern this process. The successive invention of new methods is reflected in the progress of research on gonadal development.

Ranking Enzyme Structures in the PDB by Bound Ligand Similarity to Biological Substrates.

PubMed

Tyzack, Jonathan D; Fernando, Laurent; Ribeiro, Antonio J M; Borkakoti, Neera; Thornton, Janet M

2018-04-03

There are numerous applications that use the structures of protein-ligand complexes from the PDB, such as 3D pharmacophore identification, virtual screening, and fragment-based drug design. The structures underlying these applications are potentially much more informative if they contain biologically relevant bound ligands, with high similarity to the cognate ligands. We present a study of ligand-enzyme complexes that compares the similarity of bound and cognate ligands, enabling the best matches to be identified. We calculate the molecular similarity scores using a method called PARITY (proportion of atoms residing in identical topology), which can conveniently be combined to give a similarity score for all cognate reactants or products in the reaction. Thus, we generate a rank-ordered list of related PDB structures, according to the biological similarity of the ligands bound in the structures. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Molecular Precision at Micrometer Length Scales: Hierarchical Assembly of DNA-Protein Nanostructures.

PubMed

Schiffels, Daniel; Szalai, Veronika A; Liddle, J Alexander

2017-07-25

Robust self-assembly across length scales is a ubiquitous feature of biological systems but remains challenging for synthetic structures. Taking a cue from biology-where disparate molecules work together to produce large, functional assemblies-we demonstrate how to engineer microscale structures with nanoscale features: Our self-assembly approach begins by using DNA polymerase to controllably create double-stranded DNA (dsDNA) sections on a single-stranded template. The single-stranded DNA (ssDNA) sections are then folded into a mechanically flexible skeleton by the origami method. This process simultaneously shapes the structure at the nanoscale and directs the large-scale geometry. The DNA skeleton guides the assembly of RecA protein filaments, which provides rigidity at the micrometer scale. We use our modular design strategy to assemble tetrahedral, rectangular, and linear shapes of defined dimensions. This method enables the robust construction of complex assemblies, greatly extending the range of DNA-based self-assembly methods.

Physical Theory in Biology: An Interdisciplinary Course.

ERIC Educational Resources Information Center

Lumsden, Charles J.; And Others

1979-01-01

Describes an interdisciplinary course which explores the relationships between physics and biology in terms of their conceptual structures and mathematical frameworks. Highlights the course content, its system of cross-disciplinary literature resources, and several innovative aspects of the method used for evaluating students. (Author/GA)

PDB-wide identification of biological assemblies from conserved quaternary structure geometry.

PubMed

Dey, Sucharita; Ritchie, David W; Levy, Emmanuel D

2018-01-01

Protein structures are key to understanding biomolecular mechanisms and diseases, yet their interpretation is hampered by limited knowledge of their biologically relevant quaternary structure (QS). A critical challenge in inferring QS information from crystallographic data is distinguishing biological interfaces from fortuitous crystal-packing contacts. Here, we tackled this problem by developing strategies for aligning and comparing QS states across both homologs and data repositories. QS conservation across homologs proved remarkably strong at predicting biological relevance and is implemented in two methods, QSalign and anti-QSalign, for annotating homo-oligomers and monomers, respectively. QS conservation across repositories is implemented in QSbio (http://www.QSbio.org), which approaches the accuracy of manual curation and allowed us to predict >100,000 QS states across the Protein Data Bank. Based on this high-quality data set, we analyzed pairs of structurally conserved interfaces, and this analysis revealed a striking plasticity whereby evolutionary distant interfaces maintain similar interaction geometries through widely divergent chemical properties.

Anomalous Diffraction in Crystallographic Phase Evaluation

PubMed Central

Hendrickson, Wayne A.

2014-01-01

X-ray diffraction patterns from crystals of biological macromolecules contain sufficient information to define atomic structures, but atomic positions are inextricable without having electron-density images. Diffraction measurements provide amplitudes, but the computation of electron density also requires phases for the diffracted waves. The resonance phenomenon known as anomalous scattering offers a powerful solution to this phase problem. Exploiting scattering resonances from diverse elements, the methods of multiwavelength anomalous diffraction (MAD) and single-wavelength anomalous diffraction (SAD) now predominate for de novo determinations of atomic-level biological structures. This review describes the physical underpinnings of anomalous diffraction methods, the evolution of these methods to their current maturity, the elements, procedures and instrumentation used for effective implementation, and the realm of applications. PMID:24726017

Future directions of electron crystallography.

PubMed

Fujiyoshi, Yoshinori

2013-01-01

In biological science, there are still many interesting and fundamental yet difficult questions, such as those in neuroscience, remaining to be answered. Structural and functional studies of membrane proteins, which are key molecules of signal transduction in neural and other cells, are essential for understanding the molecular mechanisms of many fundamental biological processes. Technological and instrumental advancements of electron microscopy have facilitated comprehension of structural studies of biological components, such as membrane proteins. While X-ray crystallography has been the main method of structure analysis of proteins including membrane proteins, electron crystallography is now an established technique to analyze structures of membrane proteins in the lipid bilayer, which is close to their natural biological environment. By utilizing cryo-electron microscopes with helium-cooled specimen stages, structures of membrane proteins were analyzed at a resolution better than 3 Å. Such high-resolution structural analysis of membrane proteins by electron crystallography opens up the new research field of structural physiology. Considering the fact that the structures of integral membrane proteins in their native membrane environment without artifacts from crystal contacts are critical in understanding their physiological functions, electron crystallography will continue to be an important technology for structural analysis. In this chapter, I will present several examples to highlight important advantages and to suggest future directions of this technique.

Microbial-enzymatic-hybrid biological fuel cell with optimized growth conditions for Shewanella oneidensis DSP-10.

PubMed

Roy, Jared N; Luckarift, Heather R; Sizemore, Susan R; Farrington, Karen E; Lau, Carolin; Johnson, Glenn R; Atanassov, Plamen

2013-07-10

In this work we present a biological fuel cell fabricated by combining a Shewanella oneidensis microbial anode and a laccase-modified air-breathing cathode. This concept is devised as an extension to traditional biochemical methods by incorporating diverse biological catalysts with the aim of powering small devices. In preparing the biological fuel cell anode, novel hierarchical-structured architectures and biofilm configurations were investigated. A method for creating an artificial biofilm based on encapsulating microorganisms in a porous, thin film of silica was compared with S. oneidensis biofilms that were allowed to colonize naturally. Results indicate comparable current and power densities for artificial and natural biofilm formations, based on growth characteristics. As a result, this work describes methods for creating controllable and reproducible bio-anodes and demonstrates the versatility of hybrid biological fuel cells. Copyright © 2013 Elsevier Inc. All rights reserved.

Developing JSequitur to Study the Hierarchical Structure of Biological Sequences in a Grammatical Inference Framework of String Compression Algorithms.

PubMed

Galbadrakh, Bulgan; Lee, Kyung-Eun; Park, Hyun-Seok

2012-12-01

Grammatical inference methods are expected to find grammatical structures hidden in biological sequences. One hopes that studies of grammar serve as an appropriate tool for theory formation. Thus, we have developed JSequitur for automatically generating the grammatical structure of biological sequences in an inference framework of string compression algorithms. Our original motivation was to find any grammatical traits of several cancer genes that can be detected by string compression algorithms. Through this research, we could not find any meaningful unique traits of the cancer genes yet, but we could observe some interesting traits in regards to the relationship among gene length, similarity of sequences, the patterns of the generated grammar, and compression rate.

Coupled Analysis of In Vitro and Histology Tissue Samples to Quantify Structure-Function Relationship

PubMed Central

Acar, Evrim; Plopper, George E.; Yener, Bülent

2012-01-01

The structure/function relationship is fundamental to our understanding of biological systems at all levels, and drives most, if not all, techniques for detecting, diagnosing, and treating disease. However, at the tissue level of biological complexity we encounter a gap in the structure/function relationship: having accumulated an extraordinary amount of detailed information about biological tissues at the cellular and subcellular level, we cannot assemble it in a way that explains the correspondingly complex biological functions these structures perform. To help close this information gap we define here several quantitative temperospatial features that link tissue structure to its corresponding biological function. Both histological images of human tissue samples and fluorescence images of three-dimensional cultures of human cells are used to compare the accuracy of in vitro culture models with their corresponding human tissues. To the best of our knowledge, there is no prior work on a quantitative comparison of histology and in vitro samples. Features are calculated from graph theoretical representations of tissue structures and the data are analyzed in the form of matrices and higher-order tensors using matrix and tensor factorization methods, with a goal of differentiating between cancerous and healthy states of brain, breast, and bone tissues. We also show that our techniques can differentiate between the structural organization of native tissues and their corresponding in vitro engineered cell culture models. PMID:22479315

Integrative, Dynamic Structural Biology at Atomic Resolution—It’s About Time

PubMed Central

van den Bedem, Henry; Fraser, James S.

2015-01-01

Biomolecules adopt a dynamic ensemble of conformations, each with the potential to interact with binding partners or perform the chemical reactions required for a multitude of cellular functions. Recent advances in X-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy, and other techniques are helping us realize the dream of seeing—in atomic detail—how different parts of biomolecules exchange between functional sub-states using concerted motions. Integrative structural biology has advanced our understanding of the formation of large macromolecular complexes and how their components interact in assemblies by leveraging data from many low-resolution methods. Here, we review the growing opportunities for integrative, dynamic structural biology at the atomic scale, contending there is increasing synergistic potential between X-ray crystallography, NMR, and computer simulations to reveal a structural basis for protein conformational dynamics at high resolution. PMID:25825836

Leveraging unsupervised training sets for multi-scale compartmentalization in renal pathology

NASA Astrophysics Data System (ADS)

Lutnick, Brendon; Tomaszewski, John E.; Sarder, Pinaki

2017-03-01

Clinical pathology relies on manual compartmentalization and quantification of biological structures, which is time consuming and often error-prone. Application of computer vision segmentation algorithms to histopathological image analysis, in contrast, can offer fast, reproducible, and accurate quantitative analysis to aid pathologists. Algorithms tunable to different biologically relevant structures can allow accurate, precise, and reproducible estimates of disease states. In this direction, we have developed a fast, unsupervised computational method for simultaneously separating all biologically relevant structures from histopathological images in multi-scale. Segmentation is achieved by solving an energy optimization problem. Representing the image as a graph, nodes (pixels) are grouped by minimizing a Potts model Hamiltonian, adopted from theoretical physics, modeling interacting electron spins. Pixel relationships (modeled as edges) are used to update the energy of the partitioned graph. By iteratively improving the clustering, the optimal number of segments is revealed. To reduce computational time, the graph is simplified using a Cantor pairing function to intelligently reduce the number of included nodes. The classified nodes are then used to train a multiclass support vector machine to apply the segmentation over the full image. Accurate segmentations of images with as many as 106 pixels can be completed only in 5 sec, allowing for attainable multi-scale visualization. To establish clinical potential, we employed our method in renal biopsies to quantitatively visualize for the first time scale variant compartments of heterogeneous intra- and extraglomerular structures simultaneously. Implications of the utility of our method extend to fields such as oncology, genomics, and non-biological problems.

Accounting for noise when clustering biological data.

PubMed

Sloutsky, Roman; Jimenez, Nicolas; Swamidass, S Joshua; Naegle, Kristen M

2013-07-01

Clustering is a powerful and commonly used technique that organizes and elucidates the structure of biological data. Clustering data from gene expression, metabolomics and proteomics experiments has proven to be useful at deriving a variety of insights, such as the shared regulation or function of biochemical components within networks. However, experimental measurements of biological processes are subject to substantial noise-stemming from both technical and biological variability-and most clustering algorithms are sensitive to this noise. In this article, we explore several methods of accounting for noise when analyzing biological data sets through clustering. Using a toy data set and two different case studies-gene expression and protein phosphorylation-we demonstrate the sensitivity of clustering algorithms to noise. Several methods of accounting for this noise can be used to establish when clustering results can be trusted. These methods span a range of assumptions about the statistical properties of the noise and can therefore be applied to virtually any biological data source.

The Use of Bayesian Methods for Uncertainty Analysis and Evaluation of Biological Hypotheses in PBPK Models

EPA Science Inventory

Physiologically based pharmacokinetic (PBPK) models are compartmental models that describe the uptake and distribution of drugs and chemicals throughout the body. They can be structured so that model parameters (i.e., physiological and chemical-specific) reflect biological charac...

Biology for the Visually Impaired Student.

ERIC Educational Resources Information Center

Cooperman, Susan

1980-01-01

This is a description of a beginning college biology course for visually impaired students. Equipment for instruction is discussed and methods for using the materials are included. Topics included in the course are chemical bonding, diffusion and osmosis, cell structure, meiosis and mitosis, reproduction, behavior, nutrition, and circulation. (SA)

A discrete structure of the brain waves.

NASA Astrophysics Data System (ADS)

Dabaghian, Yuri; Perotti, Luca; oscillons in biological rhythms Collaboration; physics of biological rhythms Team

A physiological interpretation of the biological rhythms, e.g., of the local field potentials (LFP) depends on the mathematical approaches used for the analysis. Most existing mathematical methods are based on decomposing the signal into a set of ``primitives,'' e.g., sinusoidal harmonics, and correlating them with different cognitive and behavioral phenomena. A common feature of all these methods is that the decomposition semantics is presumed from the onset, and the goal of the subsequent analysis reduces merely to identifying the combination that best reproduces the original signal. We propose a fundamentally new method in which the decomposition components are discovered empirically, and demonstrate that it is more flexible and more sensitive to the signal's structure than the standard Fourier method. Applying this method to the rodent LFP signals reveals a fundamentally new structure of these ``brain waves.'' In particular, our results suggest that the LFP oscillations consist of a superposition of a small, discrete set of frequency modulated oscillatory processes, which we call ``oscillons''. Since these structures are discovered empirically, we hypothesize that they may capture the signal's actual physical structure, i.e., the pattern of synchronous activity in neuronal ensembles. Proving this hypothesis will help to advance our principal understanding of the neuronal synchronization mechanisms and reveal new structure within the LFPs and other biological oscillations. NSF 1422438 Grant, Houston Bioinformatics Endowment Fund.

Mimicking/extracting structure and functions of natural products: synthetic approaches that address unexplored needs in chemical biology.

PubMed

Hirai, Go

2015-04-01

Natural products are often attractive and challenging targets for synthetic chemists, and many have interesting biological activities. However, synthetic chemists need to be more than simply suppliers of compounds to biologists. Therefore, we have been seeking ways to actively apply organic synthetic methods to chemical biology studies of natural products and their activities. In this personal review, I would like to introduce our work on the development of new biologically active compounds inspired by, or extracted from, the structures of natural products, focusing on enhancement of functional activity and specificity and overcoming various drawbacks of the parent natural products. Copyright © 2014 The Chemical Society of Japan and Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A historical perspective on protein crystallization from 1840 to the present day.

PubMed

Giegé, Richard

2013-12-01

Protein crystallization has been known since 1840 and can prove to be straightforward but, in most cases, it constitutes a real bottleneck. This stimulated the birth of the biocrystallogenesis field with both 'practical' and 'basic' science aims. In the early years of biochemistry, crystallization was a tool for the preparation of biological substances. Today, biocrystallogenesis aims to provide efficient methods for crystal fabrication and a means to optimize crystal quality for X-ray crystallography. The historical development of crystallization methods for structural biology occurred first in conjunction with that of biochemical and genetic methods for macromolecule production, then with the development of structure determination methodologies and, recently, with routine access to synchrotron X-ray sources. Previously, the identification of conditions that sustain crystal growth occurred mostly empirically but, in recent decades, this has moved progressively towards more rationality as a result of a deeper understanding of the physical chemistry of protein crystal growth and the use of idea-driven screening and high-throughput procedures. Protein and nucleic acid engineering procedures to facilitate crystallization, as well as crystallization methods in gelled-media or by counter-diffusion, represent recent important achievements, although the underlying concepts are old. The new nanotechnologies have brought a significant improvement in the practice of protein crystallization. Today, the increasing number of crystal structures deposited in the Protein Data Bank could mean that crystallization is no longer a bottleneck. This is not the case, however, because structural biology projects always become more challenging and thereby require adapted methods to enable the growth of the appropriate crystals, notably macromolecular assemblages. © 2013 FEBS.

Outcome of the First wwPDB Hybrid/Integrative Methods Task Force Workshop

PubMed Central

Sali, Andrej; Berman, Helen M.; Schwede, Torsten; Trewhella, Jill; Kleywegt, Gerard; Burley, Stephen K.; Markley, John; Nakamura, Haruki; Adams, Paul; Bonvin, Alexandre M.J.J.; Chiu, Wah; Dal Peraro, Matteo; Di Maio, Frank; Ferrin, Thomas E.; Grünewald, Kay; Gutmanas, Aleksandras; Henderson, Richard; Hummer, Gerhard; Iwasaki, Kenji; Johnson, Graham; Lawson, Catherine L.; Meiler, Jens; Marti-Renom, Marc A.; Montelione, Gaetano T.; Nilges, Michael; Nussinov, Ruth; Patwardhan, Ardan; Rappsilber, Juri; Read, Randy J.; Saibil, Helen; Schröder, Gunnar F.; Schwieters, Charles D.; Seidel, Claus A. M.; Svergun, Dmitri; Topf, Maya; Ulrich, Eldon L.; Velankar, Sameer; Westbrook, John D.

2016-01-01

Summary Structures of biomolecular systems are increasingly computed by integrative modeling that relies on varied types of experimental data and theoretical information. We describe here the proceedings and conclusions from the first wwPDB Hybrid/Integrative Methods Task Force Workshop held at the European Bioinformatics Institute in Hinxton, UK, October 6 and 7, 2014. At the workshop, experts in various experimental fields of structural biology, experts in integrative modeling and visualization, and experts in data archiving addressed a series of questions central to the future of structural biology. How should integrative models be represented? How should the data and integrative models be validated? What data should be archived? How should the data and models be archived? What information should accompany the publication of integrative models? PMID:26095030

Virtual Reconstruction and Three-Dimensional Printing of Blood Cells as a Tool in Cell Biology Education.

PubMed

Augusto, Ingrid; Monteiro, Douglas; Girard-Dias, Wendell; Dos Santos, Thaisa Oliveira; Rosa Belmonte, Simone Letícia; Pinto de Oliveira, Jairo; Mauad, Helder; da Silva Pacheco, Marcos; Lenz, Dominik; Stefanon Bittencourt, Athelson; Valentim Nogueira, Breno; Lopes Dos Santos, Jorge Roberto; Miranda, Kildare; Guimarães, Marco Cesar Cunegundes

2016-01-01

The cell biology discipline constitutes a highly dynamic field whose concepts take a long time to be incorporated into the educational system, especially in developing countries. Amongst the main obstacles to the introduction of new cell biology concepts to students is their general lack of identification with most teaching methods. The introduction of elaborated figures, movies and animations to textbooks has given a tremendous contribution to the learning process and the search for novel teaching methods has been a central goal in cell biology education. Some specialized tools, however, are usually only available in advanced research centers or in institutions that are traditionally involved with the development of novel teaching/learning processes, and are far from becoming reality in the majority of life sciences schools. When combined with the known declining interest in science among young people, a critical scenario may result. This is especially important in the field of electron microscopy and associated techniques, methods that have greatly contributed to the current knowledge on the structure and function of different cell biology models but are rarely made accessible to most students. In this work, we propose a strategy to increase the engagement of students into the world of cell and structural biology by combining 3D electron microscopy techniques and 3D prototyping technology (3D printing) to generate 3D physical models that accurately and realistically reproduce a close-to-the native structure of the cell and serve as a tool for students and teachers outside the main centers. We introduce three strategies for 3D imaging, modeling and prototyping of cells and propose the establishment of a virtual platform where different digital models can be deposited by EM groups and subsequently downloaded and printed in different schools, universities, research centers and museums, thereby modernizing teaching of cell biology and increasing the accessibility to modern approaches in basic science.

Virtual Reconstruction and Three-Dimensional Printing of Blood Cells as a Tool in Cell Biology Education

PubMed Central

Girard-Dias, Wendell; dos Santos, Thaisa Oliveira; Rosa Belmonte, Simone Letícia; Pinto de Oliveira, Jairo; Mauad, Helder; da Silva Pacheco, Marcos; Lenz, Dominik; Stefanon Bittencourt, Athelson; Valentim Nogueira, Breno; Lopes dos Santos, Jorge Roberto; Miranda, Kildare; Guimarães, Marco Cesar Cunegundes

2016-01-01

The cell biology discipline constitutes a highly dynamic field whose concepts take a long time to be incorporated into the educational system, especially in developing countries. Amongst the main obstacles to the introduction of new cell biology concepts to students is their general lack of identification with most teaching methods. The introduction of elaborated figures, movies and animations to textbooks has given a tremendous contribution to the learning process and the search for novel teaching methods has been a central goal in cell biology education. Some specialized tools, however, are usually only available in advanced research centers or in institutions that are traditionally involved with the development of novel teaching/learning processes, and are far from becoming reality in the majority of life sciences schools. When combined with the known declining interest in science among young people, a critical scenario may result. This is especially important in the field of electron microscopy and associated techniques, methods that have greatly contributed to the current knowledge on the structure and function of different cell biology models but are rarely made accessible to most students. In this work, we propose a strategy to increase the engagement of students into the world of cell and structural biology by combining 3D electron microscopy techniques and 3D prototyping technology (3D printing) to generate 3D physical models that accurately and realistically reproduce a close-to-the native structure of the cell and serve as a tool for students and teachers outside the main centers. We introduce three strategies for 3D imaging, modeling and prototyping of cells and propose the establishment of a virtual platform where different digital models can be deposited by EM groups and subsequently downloaded and printed in different schools, universities, research centers and museums, thereby modernizing teaching of cell biology and increasing the accessibility to modern approaches in basic science. PMID:27526196

On the interplay between mathematics and biology. Hallmarks toward a new systems biology

NASA Astrophysics Data System (ADS)

Bellomo, Nicola; Elaiw, Ahmed; Althiabi, Abdullah M.; Alghamdi, Mohammed Ali

2015-03-01

This paper proposes a critical analysis of the existing literature on mathematical tools developed toward systems biology approaches and, out of this overview, develops a new approach whose main features can be briefly summarized as follows: derivation of mathematical structures suitable to capture the complexity of biological, hence living, systems, modeling, by appropriate mathematical tools, Darwinian type dynamics, namely mutations followed by selection and evolution. Moreover, multiscale methods to move from genes to cells, and from cells to tissue are analyzed in view of a new systems biology approach.

The road not taken: Applications of fluorescence spectroscopy and electronic structure theory to systems of materials and biological relevance

NASA Astrophysics Data System (ADS)

Carlson, Philip Joseph

Applications of Fluorescence Spectroscopy and Electronic Structure Theory to Systems of Materials and Biological Relevance. The photophysics of curcumin was studied in micelles and the solvation dynamics were probed. The high-energy ionic liquid HEATN was also studied using the fragment molecular orbital method. The solvation dynamics of the HEATN system were determined. This marks the first study of the solvation dynamics in a triazolium ionic liquid system.

An Introduction to Biological NMR Spectroscopy*

PubMed Central

Marion, Dominique

2013-01-01

NMR spectroscopy is a powerful tool for biologists interested in the structure, dynamics, and interactions of biological macromolecules. This review aims at presenting in an accessible manner the requirements and limitations of this technique. As an introduction, the history of NMR will highlight how the method evolved from physics to chemistry and finally to biology over several decades. We then introduce the NMR spectral parameters used in structural biology, namely the chemical shift, the J-coupling, nuclear Overhauser effects, and residual dipolar couplings. Resonance assignment, the required step for any further NMR study, bears a resemblance to jigsaw puzzle strategy. The NMR spectral parameters are then converted into angle and distances and used as input using restrained molecular dynamics to compute a bundle of structures. When interpreting a NMR-derived structure, the biologist has to judge its quality on the basis of the statistics provided. When the 3D structure is a priori known by other means, the molecular interaction with a partner can be mapped by NMR: information on the binding interface as well as on kinetic and thermodynamic constants can be gathered. NMR is suitable to monitor, over a wide range of frequencies, protein fluctuations that play a crucial role in their biological function. In the last section of this review, intrinsically disordered proteins, which have escaped the attention of classical structural biology, are discussed in the perspective of NMR, one of the rare available techniques able to describe structural ensembles. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 16 MCP). PMID:23831612

Challenges in the Development of Functional Assays of Membrane Proteins

PubMed Central

Tiefenauer, Louis; Demarche, Sophie

2012-01-01

Lipid bilayers are natural barriers of biological cells and cellular compartments. Membrane proteins integrated in biological membranes enable vital cell functions such as signal transduction and the transport of ions or small molecules. In order to determine the activity of a protein of interest at defined conditions, the membrane protein has to be integrated into artificial lipid bilayers immobilized on a surface. For the fabrication of such biosensors expertise is required in material science, surface and analytical chemistry, molecular biology and biotechnology. Specifically, techniques are needed for structuring surfaces in the micro- and nanometer scale, chemical modification and analysis, lipid bilayer formation, protein expression, purification and solubilization, and most importantly, protein integration into engineered lipid bilayers. Electrochemical and optical methods are suitable to detect membrane activity-related signals. The importance of structural knowledge to understand membrane protein function is obvious. Presently only a few structures of membrane proteins are solved at atomic resolution. Functional assays together with known structures of individual membrane proteins will contribute to a better understanding of vital biological processes occurring at biological membranes. Such assays will be utilized in the discovery of drugs, since membrane proteins are major drug targets.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de; Schreiber, Falk; Martin-Luther-University Halle-Wittenberg, Halle

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the contextmore » of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.« less

Integrating structure-based and ligand-based approaches for computational drug design.

PubMed

Wilson, Gregory L; Lill, Markus A

2011-04-01

Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.

Research progress of microbial corrosion of reinforced concrete structure

NASA Astrophysics Data System (ADS)

Li, Shengli; Li, Dawang; Jiang, Nan; Wang, Dongwei

2011-04-01

Microbial corrosion of reinforce concrete structure is a new branch of learning. This branch deals with civil engineering , environment engineering, biology, chemistry, materials science and so on and is a interdisciplinary area. Research progress of the causes, research methods and contents of microbial corrosion of reinforced concrete structure is described. The research in the field is just beginning and concerted effort is needed to go further into the mechanism of reinforce concrete structure and assess the security and natural life of reinforce concrete structure under the special condition and put forward the protective methods.

Review: Serial Femtosecond Crystallography: A Revolution in Structural Biology

PubMed Central

Martin-Garcia, Jose M.; Conrad, Chelsie E.; Coe, Jesse; Roy-Chowdhury, Shatabdi; Fromme, Petra

2016-01-01

Macromolecular crystallography at synchrotron sources has proven to be the most influential method within structural biology, producing thousands of structures since its inception. While its utility has been instrumental in progressing our knowledge of structures of molecules, it suffers from limitations such as the need for large, well-diffracting crystals, and radiation damage that can hamper native structural determination. The recent advent of X-ray free electron lasers (XFELs) and their implementation in the emerging field of serial femtosecond crystallography (SFX) has given rise to a remarkable expansion upon existing crystallographic constraints, allowing structural biologists access to previously restricted scientific territory. SFX relies on exceptionally brilliant, micro-focused X-ray pulses, which are femtoseconds in duration, to probe nano/micrometer sized crystals in a serial fashion. This results in data sets comprised of individual snapshots, each capturing Bragg diffraction of single crystals in random orientations prior to their subsequent destruction. Thus structural elucidation while avoiding radiation damage, even at room temperature, can now be achieved. This emerging field has cultivated new methods for nanocrystallogenesis, sample delivery, and data processing. Opportunities and challenges within SFX are reviewed herein. PMID:27143509

Serial femtosecond crystallography: A revolution in structural biology.

PubMed

Martin-Garcia, Jose M; Conrad, Chelsie E; Coe, Jesse; Roy-Chowdhury, Shatabdi; Fromme, Petra

2016-07-15

Macromolecular crystallography at synchrotron sources has proven to be the most influential method within structural biology, producing thousands of structures since its inception. While its utility has been instrumental in progressing our knowledge of structures of molecules, it suffers from limitations such as the need for large, well-diffracting crystals, and radiation damage that can hamper native structural determination. The recent advent of X-ray free electron lasers (XFELs) and their implementation in the emerging field of serial femtosecond crystallography (SFX) has given rise to a remarkable expansion upon existing crystallographic constraints, allowing structural biologists access to previously restricted scientific territory. SFX relies on exceptionally brilliant, micro-focused X-ray pulses, which are femtoseconds in duration, to probe nano/micrometer sized crystals in a serial fashion. This results in data sets comprised of individual snapshots, each capturing Bragg diffraction of single crystals in random orientations prior to their subsequent destruction. Thus structural elucidation while avoiding radiation damage, even at room temperature, can now be achieved. This emerging field has cultivated new methods for nanocrystallogenesis, sample delivery, and data processing. Opportunities and challenges within SFX are reviewed herein. Published by Elsevier Inc.

An Overview of Biological Macromolecule Crystallization

PubMed Central

Krauss, Irene Russo; Merlino, Antonello; Vergara, Alessandro; Sica, Filomena

2013-01-01

The elucidation of the three dimensional structure of biological macromolecules has provided an important contribution to our current understanding of many basic mechanisms involved in life processes. This enormous impact largely results from the ability of X-ray crystallography to provide accurate structural details at atomic resolution that are a prerequisite for a deeper insight on the way in which bio-macromolecules interact with each other to build up supramolecular nano-machines capable of performing specialized biological functions. With the advent of high-energy synchrotron sources and the development of sophisticated software to solve X-ray and neutron crystal structures of large molecules, the crystallization step has become even more the bottleneck of a successful structure determination. This review introduces the general aspects of protein crystallization, summarizes conventional and innovative crystallization methods and focuses on the new strategies utilized to improve the success rate of experiments and increase crystal diffraction quality. PMID:23727935

What Combined Measurements From Structures and Imaging Tell Us About DNA Damage Responses

PubMed Central

Brosey, Chris A.; Ahmed, Zamal; Lees-Miller, Susan P.; Tainer, John A.

2017-01-01

DNA damage outcomes depend upon the efficiency and fidelity of DNA damage responses (DDRs) for different cells and damage. As such, DDRs represent tightly regulated prototypical systems for linking nanoscale biomolecular structure and assembly to the biology of genomic regulation and cell signaling. However, the dynamic and multifunctional nature of DDR assemblies can render elusive the correlation between the structures of DDR factors and specific biological disruptions to the DDR when these structures are altered. In this chapter, we discuss concepts and strategies for combining structural, biophysical, and imaging techniques to investigate DDR recognition and regulation, and thus bridge sequence-level structural biochemistry to quantitative biological outcomes visualized in cells. We focus on representative DDR responses from PARP/PARG/AIF damage signaling in DNA single-strand break repair and nonhomologous end joining complexes in double-strand break repair. Methods with exemplary experimental results are considered with a focus on strategies for probing flexibility, conformational changes, and assembly processes that shape a predictive understanding of DDR mechanisms in a cellular context. Integration of structural and imaging measurements promises to provide foundational knowledge to rationally control and optimize DNA damage outcomes for synthetic lethality and for immune activation with resulting insights for biology and cancer interventions. PMID:28668129

The Prediction of Botulinum Toxin Structure Based on in Silico and in Vitro Analysis

NASA Astrophysics Data System (ADS)

Suzuki, Tomonori; Miyazaki, Satoru

2011-01-01

Many of biological system mediated through protein-protein interactions. Knowledge of protein-protein complex structure is required for understanding the function. The determination of huge size and flexible protein-protein complex structure by experimental studies remains difficult, costly and five-consuming, therefore computational prediction of protein structures by homolog modeling and docking studies is valuable method. In addition, MD simulation is also one of the most powerful methods allowing to see the real dynamics of proteins. Here, we predict protein-protein complex structure of botulinum toxin to analyze its property. These bioinformatics methods are useful to report the relation between the flexibility of backbone structure and the activity.

Use of EPR to Solve Biochemical Problems

PubMed Central

Sahu, Indra D.; McCarrick, Robert M.; Lorigan, Gary A.

2013-01-01

EPR spectroscopy is a very powerful biophysical tool that can provide valuable structural and dynamic information on a wide variety of biological systems. The intent of this review is to provide a general overview for biochemists and biological researchers on the most commonly used EPR methods and how these techniques can be used to answer important biological questions. The topics discussed could easily fill one or more textbooks; thus, we present a brief background on several important biological EPR techniques and an overview of several interesting studies that have successfully used EPR to solve pertinent biological problems. The review consists of the following sections: an introduction to EPR techniques, spin labeling methods, and studies of naturally occurring organic radicals and EPR active transition metal systems which are presented as a series of case studies in which EPR spectroscopy has been used to greatly further our understanding of several important biological systems. PMID:23961941

Bayesian parameter estimation for nonlinear modelling of biological pathways.

PubMed

Ghasemi, Omid; Lindsey, Merry L; Yang, Tianyi; Nguyen, Nguyen; Huang, Yufei; Jin, Yu-Fang

2011-01-01

The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC) method. We applied this approach to the biological pathways involved in the left ventricle (LV) response to myocardial infarction (MI) and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly parameterized dynamic systems. Our proposed Bayesian algorithm successfully estimated parameters in nonlinear mathematical models for biological pathways. This method can be further extended to high order systems and thus provides a useful tool to analyze biological dynamics and extract information using temporal data.

Pushing the size limit of de novo structure ensemble prediction guided by sparse SDSL-EPR restraints to 200 residues: The monomeric and homodimeric forms of BAX

PubMed Central

Fischer, Axel W.; Bordignon, Enrica; Bleicken, Stephanie; García-Sáez, Ana J.; Jeschke, Gunnar; Meiler, Jens

2016-01-01

Structure determination remains a challenge for many biologically important proteins. In particular, proteins that adopt multiple conformations often evade crystallization in all biologically relevant states. Although computational de novo protein folding approaches often sample biologically relevant conformations, the selection of the most accurate model for different functional states remains a formidable challenge, in particular, for proteins with more than about 150 residues. Electron paramagnetic resonance (EPR) spectroscopy can obtain limited structural information for proteins in well-defined biological states and thereby assist in selecting biologically relevant conformations. The present study demonstrates that de novo folding methods are able to accurately sample the folds of 192-residue long soluble monomeric Bcl-2-associated X protein (BAX). The tertiary structures of the monomeric and homodimeric forms of BAX were predicted using the primary structure as well as 25 and 11 EPR distance restraints, respectively. The predicted models were subsequently compared to respective NMR/X-ray structures of BAX. EPR restraints improve the protein-size normalized root-mean-square-deviation (RMSD100) of the most accurate models with respect to the NMR/crystal structure from 5.9 Å to 3.9 Å and from 5.7 Å to 3.3 Å, respectively. Additionally, the model discrimination is improved, which is demonstrated by an improvement of the enrichment from 5% to 15% and from 13% to 21%, respectively. PMID:27129417

Resolving biomolecular motion and interactions by R2 and R1ρ relaxation dispersion NMR.

PubMed

Walinda, Erik; Morimoto, Daichi; Sugase, Kenji

2018-04-26

Among the tools of structural biology, NMR spectroscopy is unique in that it not only derives a static three-dimensional structure, but also provides an atomic-level description of the local fluctuations and global dynamics around this static structure. A battery of NMR experiments is now available to probe the motions of proteins and nucleic acids over the whole biologically relevant timescale from picoseconds to hours. Here we focus on one of these methods, relaxation dispersion, which resolves dynamics on the micro- to millisecond timescale. Key biological processes that occur on this timescale include enzymatic catalysis, ligand binding, and local folding. In other words, relaxation-dispersion-resolved dynamics are often closely related to the function of the molecule and therefore highly interesting to the structural biochemist. With an astounding sensitivity of ∼0.5%, the method detects low-population excited states that are invisible to any other biophysical method. The kinetics of the exchange between the ground state and excited states are quantified in the form of the underlying exchange rate, while structural information about the invisible excited state is obtained in the form of its chemical shift. Lastly, the population of the excited state can be derived. This diversity in the information that can be obtained makes relaxation dispersion an excellent method to study the detailed mechanisms of conformational transitions and molecular interactions. Here we describe the two branches of relaxation dispersion, R 2 and R 1ρ , discussing their applicability, similarities, and differences, as well as recent developments in pulse sequence design and data processing. Copyright © 2018 Elsevier Inc. All rights reserved.

Bridging quantum mechanics and structure-based drug design.

PubMed

De Vivo, Marco

2011-01-01

The last decade has seen great advances in the use of quantum mechanics (QM) to solve biological problems of pharmaceutical relevance. For instance, enzymatic catalysis is often investigated by means of the so-called QM/MM approach, which uses QM and molecular mechanics (MM) methods to determine the (free) energy landscape of the enzymatic reaction mechanism. Here, I will discuss a few representative examples of QM and QM/MM studies of important metalloenzymes of pharmaceutical interest (i.e. metallophosphatases and metallo-beta-lactamases). This review article aims to show how QM-based methods can be used to elucidate ligand-receptor interactions. The challenge is then to exploit this knowledge for the structure-based design of new and potent inhibitors, such as transition state (TS) analogues that resemble the structure and physicochemical properties of the enzymatic TS. Given the results and potential expressed to date by QM-based methods in studying biological problems, the application of QM in structure-based drug design will likely increase, making of these once-prohibitive computations a routinely used tool for drug design.

An immersed-boundary method for flow–structure interaction in biological systems with application to phonation

PubMed Central

Luo, Haoxiang; Mittal, Rajat; Zheng, Xudong; Bielamowicz, Steven A.; Walsh, Raymond J.; Hahn, James K.

2008-01-01

A new numerical approach for modeling a class of flow–structure interaction problems typically encountered in biological systems is presented. In this approach, a previously developed, sharp-interface, immersed-boundary method for incompressible flows is used to model the fluid flow and a new, sharp-interface Cartesian grid, immersed boundary method is devised to solve the equations of linear viscoelasticity that governs the solid. The two solvers are coupled to model flow–structure interaction. This coupled solver has the advantage of simple grid generation and efficient computation on simple, single-block structured grids. The accuracy of the solid-mechanics solver is examined by applying it to a canonical problem. The solution methodology is then applied to the problem of laryngeal aerodynamics and vocal fold vibration during human phonation. This includes a three-dimensional eigen analysis for a multi-layered vocal fold prototype as well as two-dimensional, flow-induced vocal fold vibration in a modeled larynx. Several salient features of the aerodynamics as well as vocal-fold dynamics are presented. PMID:19936017

Biomineralization of unicellular organisms: an unusual membrane biochemistry for the production of inorganic nano- and microstructures.

PubMed

Bäuerlein, Edmund

2003-02-10

With evolution, Nature has ingeniously succeeded in giving rise to an impressive variety of inorganic structures. Every organism that synthesizes biogenic minerals does so in a form that is unique to that species. This biomineralization is apparently biologically controlled. It is thus expected that both the synthesis and the form of every specific biogenic mineral is genetically determined and controlled. An investigation of the mechanism of biomineralization has only become possible with the development of modern methods in molecular biology. Unicellular organisms such as magnetic bacteria, calcareous algae, and diatoms, all of which are amongst the simplest forms of life, are particularly suited to be investigated by these methods. Crystals and composites of proteins and amorphous inorganic polymers are formed as complex structures within these organisms; these structures are not known in conventional inorganic chemistry.

Outcome of the First wwPDB Hybrid/Integrative Methods Task Force Workshop.

PubMed

Sali, Andrej; Berman, Helen M; Schwede, Torsten; Trewhella, Jill; Kleywegt, Gerard; Burley, Stephen K; Markley, John; Nakamura, Haruki; Adams, Paul; Bonvin, Alexandre M J J; Chiu, Wah; Peraro, Matteo Dal; Di Maio, Frank; Ferrin, Thomas E; Grünewald, Kay; Gutmanas, Aleksandras; Henderson, Richard; Hummer, Gerhard; Iwasaki, Kenji; Johnson, Graham; Lawson, Catherine L; Meiler, Jens; Marti-Renom, Marc A; Montelione, Gaetano T; Nilges, Michael; Nussinov, Ruth; Patwardhan, Ardan; Rappsilber, Juri; Read, Randy J; Saibil, Helen; Schröder, Gunnar F; Schwieters, Charles D; Seidel, Claus A M; Svergun, Dmitri; Topf, Maya; Ulrich, Eldon L; Velankar, Sameer; Westbrook, John D

2015-07-07

Structures of biomolecular systems are increasingly computed by integrative modeling that relies on varied types of experimental data and theoretical information. We describe here the proceedings and conclusions from the first wwPDB Hybrid/Integrative Methods Task Force Workshop held at the European Bioinformatics Institute in Hinxton, UK, on October 6 and 7, 2014. At the workshop, experts in various experimental fields of structural biology, experts in integrative modeling and visualization, and experts in data archiving addressed a series of questions central to the future of structural biology. How should integrative models be represented? How should the data and integrative models be validated? What data should be archived? How should the data and models be archived? What information should accompany the publication of integrative models? Copyright © 2015 Elsevier Ltd. All rights reserved.

The impact of structural biology in medicine illustrated with four case studies.

PubMed

Hu, Tiancen; Sprague, Elizabeth R; Fodor, Michelle; Stams, Travis; Clark, Kirk L; Cowan-Jacob, Sandra W

2018-01-01

The contributions of structural biology to drug discovery have expanded over the last 20 years from structure-based ligand optimization to a broad range of clinically relevant topics including the understanding of disease, target discovery, screening for new types of ligands, discovery of new modes of action, addressing clinical challenges such as side effects or resistance, and providing data to support drug registration. This expansion of scope is due to breakthroughs in the technology, which allow structural information to be obtained rapidly and for more complex molecular systems, but also due to the combination of different technologies such as X-ray, NMR, and other biophysical methods, which allows one to get a more complete molecular understanding of disease and ways to treat it. In this review, we provide examples of the types of impact molecular structure information can have in the clinic for both low molecular weight and biologic drug discovery and describe several case studies from our own work to illustrate some of these contributions.

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.

PubMed

Ligon, Thomas S; Fröhlich, Fabian; Chis, Oana T; Banga, Julio R; Balsa-Canto, Eva; Hasenauer, Jan

2018-04-15

Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models. GenSSI 2.0 is an open-source MATLAB toolbox and available at https://github.com/genssi-developer/GenSSI. thomas.ligon@physik.uni-muenchen.de or jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

Transmission electron microscopy in molecular structural biology: A historical survey.

PubMed

Harris, J Robin

2015-09-01

In this personal, historic account of macromolecular transmission electron microscopy (TEM), published data from the 1940s through to recent times is surveyed, within the context of the remarkable progress that has been achieved during this time period. The evolution of present day molecular structural biology is described in relation to the associated biological disciplines. The contribution of numerous electron microscope pioneers to the development of the subject is discussed. The principal techniques for TEM specimen preparation, thin sectioning, metal shadowing, negative staining and plunge-freezing (vitrification) of thin aqueous samples are described, with a selection of published images to emphasise the virtues of each method. The development of digital image analysis and 3D reconstruction is described in detail as applied to electron crystallography and reconstructions from helical structures, 2D membrane crystals as well as single particle 3D reconstruction of icosahedral viruses and macromolecules. The on-going development of new software, algorithms and approaches is highlighted before specific examples of the historical progress of the structural biology of proteins and viruses are presented. Copyright © 2014 Elsevier Inc. All rights reserved.

3D freeform printing of silk fibroin.

PubMed

Rodriguez, Maria J; Dixon, Thomas A; Cohen, Eliad; Huang, Wenwen; Omenetto, Fiorenzo G; Kaplan, David L

2018-04-15

Freeform fabrication has emerged as a key direction in printing biologically-relevant materials and structures. With this emerging technology, complex structures with microscale resolution can be created in arbitrary geometries and without the limitations found in traditional bottom-up or top-down additive manufacturing methods. Recent advances in freeform printing have used the physical properties of microparticle-based granular gels as a medium for the submerged extrusion of bioinks. However, most of these techniques require post-processing or crosslinking for the removal of the printed structures (Miller et al., 2015; Jin et al., 2016) [1,2]. In this communication, we introduce a novel method for the one-step gelation of silk fibroin within a suspension of synthetic nanoclay (Laponite) and polyethylene glycol (PEG). Silk fibroin has been used as a biopolymer for bioprinting in several contexts, but chemical or enzymatic additives or bulking agents are needed to stabilize 3D structures. Our method requires no post-processing of printed structures and allows for in situ physical crosslinking of pure aqueous silk fibroin into arbitrary geometries produced through freeform 3D printing. 3D bioprinting has emerged as a technology that can produce biologically relevant structures in defined geometries with microscale resolution. Techniques for fabrication of free-standing structures by printing into granular gel media has been demonstrated previously, however, these methods require crosslinking agents and post-processing steps on printed structures. Our method utilizes one-step gelation of silk fibroin within a suspension of synthetic nanoclay (Laponite), with no need for additional crosslinking compounds or post processing of the material. This new method allows for in situ physical crosslinking of pure aqueous silk fibroin into defined geometries produced through freeform 3D printing. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Biological Remediation of Petroleum Contaminants

NASA Astrophysics Data System (ADS)

Kuhad, Ramesh Chander; Gupta, Rishi

Large volumes of hazardous wastes are generated in the form of oily sludges and contaminated soils during crude oil transportation and processing. Although many physical, chemical and biological treatment technologies are available for petroleum contaminants petroleum contaminants in soil, biological methods have been considered the most cost-effective. Practical biological remediation methods typically involve direct use of the microbes naturally occurring in the contaminated environment and/or cultured indigenous or modified microorganisms. Environmental and nutritional factors, including the properties of the soil, the chemical structure of the hydrocarbon(s), oxygen, water, nutrient availability, pH, temperature, and contaminant bioavailability, can significantly affect the rate and the extent of hydrocarbon biodegradation hydrocarbon biodegradation by microorganisms in contaminated soils. This chapter concisely discusses the major aspects of bioremediation of petroleum contaminants.

Ultrafast and Wide Range Analysis of DNA Molecules Using Rigid Network Structure of Solid Nanowires

PubMed Central

Rahong, Sakon; Yasui, Takao; Yanagida, Takeshi; Nagashima, Kazuki; Kanai, Masaki; Klamchuen, Annop; Meng, Gang; He, Yong; Zhuge, Fuwei; Kaji, Noritada; Kawai, Tomoji; Baba, Yoshinobu

2014-01-01

Analyzing sizes of DNA via electrophoresis using a gel has played an important role in the recent, rapid progress of biology and biotechnology. Although analyzing DNA over a wide range of sizes in a short time is desired, no existing electrophoresis methods have been able to fully satisfy these two requirements. Here we propose a novel method using a rigid 3D network structure composed of solid nanowires within a microchannel. This rigid network structure enables analysis of DNA under applied DC electric fields for a large DNA size range (100 bp–166 kbp) within 13 s, which are much wider and faster conditions than those of any existing methods. The network density is readily varied for the targeted DNA size range by tailoring the number of cycles of the nanowire growth only at the desired spatial position within the microchannel. The rigid dense 3D network structure with spatial density control plays an important role in determining the capability for analyzing DNA. Since the present method allows the spatial location and density of the nanostructure within the microchannels to be defined, this unique controllability offers a new strategy to develop an analytical method not only for DNA but also for other biological molecules. PMID:24918865

Ultrafast and Wide Range Analysis of DNA Molecules Using Rigid Network Structure of Solid Nanowires

NASA Astrophysics Data System (ADS)

Rahong, Sakon; Yasui, Takao; Yanagida, Takeshi; Nagashima, Kazuki; Kanai, Masaki; Klamchuen, Annop; Meng, Gang; He, Yong; Zhuge, Fuwei; Kaji, Noritada; Kawai, Tomoji; Baba, Yoshinobu

2014-06-01

Analyzing sizes of DNA via electrophoresis using a gel has played an important role in the recent, rapid progress of biology and biotechnology. Although analyzing DNA over a wide range of sizes in a short time is desired, no existing electrophoresis methods have been able to fully satisfy these two requirements. Here we propose a novel method using a rigid 3D network structure composed of solid nanowires within a microchannel. This rigid network structure enables analysis of DNA under applied DC electric fields for a large DNA size range (100 bp-166 kbp) within 13 s, which are much wider and faster conditions than those of any existing methods. The network density is readily varied for the targeted DNA size range by tailoring the number of cycles of the nanowire growth only at the desired spatial position within the microchannel. The rigid dense 3D network structure with spatial density control plays an important role in determining the capability for analyzing DNA. Since the present method allows the spatial location and density of the nanostructure within the microchannels to be defined, this unique controllability offers a new strategy to develop an analytical method not only for DNA but also for other biological molecules.

J D Bernal and the genesis of structural biology

NASA Astrophysics Data System (ADS)

Caffrey, Martin

2007-02-01

I was invited to participate in this Symposium a month or so before the event. At that time however, I knew little about J D Bernal. I vaguely remembered a brief conversation on the topic over a decade ago with Professor Vittorio Luzzati as we ambled around the gardens at the Palace of Varsailles. Vittorio likely knew Bernal through his friend Rosalind Franklin who worked with Bernal at Birbeck College. But beyond that I knew nothing about the man or his science. And so it was most fortunate that Andrew Brown's book J D Bernal: The Sage of Science appeared in 2005 and I was able to call on it. Indeed, much of the material included in this chapter is based on that source and on Dorothy Hodgkin's biographic memoir of J D Bernal, her postgraduate supervisor. Given that this chapter is to be published in a Physics journal I thought it appropriate to provide some background to the theme of my presentation, structural biology. Accordingly, I will begin with an introduction to proteins, one of structural biology's central characters, and to which Bernal devoted much energy and attention. How the molecular structure of a protein determines its activity and function will then be described. Bernal's major contribution in this area was to X-ray crystallography, the primary method by which a protein's structure is determined. The method, and aspects of its development, will be described. I will also make reference to some of Bernal's additional contributions in related fields. Finally, Vincent Casey, the symposium organizer, asked that I comment on how structural biology might impact on society. I will attempt to address that at the close of my presentation.

Supercritical fluid extraction and ultra performance liquid chromatography of respiratory quinones for microbial community analysis in environmental and biological samples.

PubMed

Hanif, Muhammad; Atsuta, Yoichi; Fujie, Koichi; Daimon, Hiroyuki

2012-03-05

Microbial community structure plays a significant role in environmental assessment and animal health management. The development of a superior analytical strategy for the characterization of microbial community structure is an ongoing challenge. In this study, we developed an effective supercritical fluid extraction (SFE) and ultra performance liquid chromatography (UPLC) method for the analysis of bacterial respiratory quinones (RQ) in environmental and biological samples. RQ profile analysis is one of the most widely used culture-independent tools for characterizing microbial community structure. A UPLC equipped with a photo diode array (PDA) detector was successfully applied to the simultaneous determination of ubiquinones (UQ) and menaquinones (MK) without tedious pretreatment. Supercritical carbon dioxide (scCO(2)) extraction with the solid-phase cartridge trap proved to be a more effective and rapid method for extracting respiratory quinones, compared to a conventional organic solvent extraction method. This methodology leads to a successful analytical procedure that involves a significant reduction in the complexity and sample preparation time. Application of the optimized methodology to characterize microbial communities based on the RQ profile was demonstrated for a variety of environmental samples (activated sludge, digested sludge, and compost) and biological samples (swine and Japanese quail feces).

Enhancing biological relevance of a weighted gene co-expression network for functional module identification.

PubMed

Prom-On, Santitham; Chanthaphan, Atthawut; Chan, Jonathan Hoyin; Meechai, Asawin

2011-02-01

Relationships among gene expression levels may be associated with the mechanisms of the disease. While identifying a direct association such as a difference in expression levels between case and control groups links genes to disease mechanisms, uncovering an indirect association in the form of a network structure may help reveal the underlying functional module associated with the disease under scrutiny. This paper presents a method to improve the biological relevance in functional module identification from the gene expression microarray data by enhancing the structure of a weighted gene co-expression network using minimum spanning tree. The enhanced network, which is called a backbone network, contains only the essential structural information to represent the gene co-expression network. The entire backbone network is decoupled into a number of coherent sub-networks, and then the functional modules are reconstructed from these sub-networks to ensure minimum redundancy. The method was tested with a simulated gene expression dataset and case-control expression datasets of autism spectrum disorder and colorectal cancer studies. The results indicate that the proposed method can accurately identify clusters in the simulated dataset, and the functional modules of the backbone network are more biologically relevant than those obtained from the original approach.

On the interplay between mathematics and biology: hallmarks toward a new systems biology.

PubMed

Bellomo, Nicola; Elaiw, Ahmed; Althiabi, Abdullah M; Alghamdi, Mohammed Ali

2015-03-01

This paper proposes a critical analysis of the existing literature on mathematical tools developed toward systems biology approaches and, out of this overview, develops a new approach whose main features can be briefly summarized as follows: derivation of mathematical structures suitable to capture the complexity of biological, hence living, systems, modeling, by appropriate mathematical tools, Darwinian type dynamics, namely mutations followed by selection and evolution. Moreover, multiscale methods to move from genes to cells, and from cells to tissue are analyzed in view of a new systems biology approach. Copyright © 2014 Elsevier B.V. All rights reserved.

Chemical imaging analysis of the brain with X-ray methods

NASA Astrophysics Data System (ADS)

Collingwood, Joanna F.; Adams, Freddy

2017-04-01

Cells employ various metal and metalloid ions to augment the structure and the function of proteins and to assist with vital biological processes. In the brain they mediate biochemical processes, and disrupted metabolism of metals may be a contributing factor in neurodegenerative disorders. In this tutorial review we will discuss the particular role of X-ray methods for elemental imaging analysis of accumulated metal species and metal-containing compounds in biological materials, in the context of post-mortem brain tissue. X-rays have the advantage that they have a short wavelength and can penetrate through a thick biological sample. Many of the X-ray microscopy techniques that provide the greatest sensitivity and specificity for trace metal concentrations in biological materials are emerging at synchrotron X-ray facilities. Here, the extremely high flux available across a wide range of soft and hard X-rays, combined with state-of-the-art focusing techniques and ultra-sensitive detectors, makes it viable to undertake direct imaging of a number of elements in brain tissue. The different methods for synchrotron imaging of metals in brain tissues at regional, cellular, and sub-cellular spatial resolution are discussed. Methods covered include X-ray fluorescence for elemental imaging, X-ray absorption spectrometry for speciation imaging, X-ray diffraction for structural imaging, phase contrast for enhanced contrast imaging and scanning transmission X-ray microscopy for spectromicroscopy. Two- and three-dimensional (confocal and tomographic) imaging methods are considered as well as the correlation of X-ray microscopy with other imaging tools.

Hemojuvelin-hepcidin axis modeled and analyzed using Petri nets.

PubMed

Formanowicz, Dorota; Kozak, Adam; Głowacki, Tomasz; Radom, Marcin; Formanowicz, Piotr

2013-12-01

Systems biology approach to investigate biological phenomena seems to be very promising because it is capable to capture one of the fundamental properties of living organisms, i.e. their inherent complexity. It allows for analysis biological entities as complex systems of interacting objects. The first and necessary step of such an analysis is building a precise model of the studied biological system. This model is expressed in the language of some branch of mathematics, as for example, differential equations. During the last two decades the theory of Petri nets has appeared to be very well suited for building models of biological systems. The structure of these nets reflects the structure of interacting biological molecules and processes. Moreover, on one hand, Petri nets have intuitive graphical representation being very helpful in understanding the structure of the system and on the other hand, there is a lot of mathematical methods and software tools supporting an analysis of the properties of the nets. In this paper a Petri net based model of the hemojuvelin-hepcidin axis involved in the maintenance of the human body iron homeostasis is presented. The analysis based mainly on T-invariants of the model properties has been made and some biological conclusions have been drawn. Copyright © 2013 Elsevier Inc. All rights reserved.

Surface-Tension Replica-Exchange Molecular Dynamics Method for Enhanced Sampling of Biological Membrane Systems.

PubMed

Mori, Takaharu; Jung, Jaewoon; Sugita, Yuji

2013-12-10

Conformational sampling is fundamentally important for simulating complex biomolecular systems. The generalized-ensemble algorithm, especially the temperature replica-exchange molecular dynamics method (T-REMD), is one of the most powerful methods to explore structures of biomolecules such as proteins, nucleic acids, carbohydrates, and also of lipid membranes. T-REMD simulations have focused on soluble proteins rather than membrane proteins or lipid bilayers, because explicit membranes do not keep their structural integrity at high temperature. Here, we propose a new generalized-ensemble algorithm for membrane systems, which we call the surface-tension REMD method. Each replica is simulated in the NPγT ensemble, and surface tensions in a pair of replicas are exchanged at certain intervals to enhance conformational sampling of the target membrane system. We test the method on two biological membrane systems: a fully hydrated DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine) lipid bilayer and a WALP23-POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) membrane system. During these simulations, a random walk in surface tension space is realized. Large-scale lateral deformation (shrinking and stretching) of the membranes takes place in all of the replicas without collapse of the lipid bilayer structure. There is accelerated lateral diffusion of DPPC lipid molecules compared with conventional MD simulation, and a much wider range of tilt angle of the WALP23 peptide is sampled due to large deformation of the POPC lipid bilayer and through peptide-lipid interactions. Our method could be applicable to a wide variety of biological membrane systems.

Multi-energy method of digital radiography for imaging of biological objects

NASA Astrophysics Data System (ADS)

Ryzhikov, V. D.; Naydenov, S. V.; Opolonin, O. D.; Volkov, V. G.; Smith, C. F.

2016-03-01

This work has been dedicated to the search for a new possibility to use multi-energy digital radiography (MER) for medical applications. Our work has included both theoretical and experimental investigations of 2-energy (2E) and 3- energy (3D) radiography for imaging the structure of biological objects. Using special simulation methods and digital analysis based on the X-ray interaction energy dependence for each element of importance to medical applications in the X-ray range of energy up to 150 keV, we have implemented a quasi-linear approximation for the energy dependence of the X-ray linear mass absorption coefficient μm (E) that permits us to determine the intrinsic structure of the biological objects. Our measurements utilize multiple X-ray tube voltages (50, 100, and 150 kV) with Al and Cu filters of different thicknesses to achieve 3-energy X-ray examination of objects. By doing so, we are able to achieve significantly improved imaging quality of the structure of the subject biological objects. To reconstruct and visualize the final images, we use both two-dimensional (2D) and three-dimensional (3D) palettes of identification. The result is a 2E and/or 3E representation of the object with color coding of each pixel according to the data outputs. Following the experimental measurements and post-processing, we produce a 3D image of the biological object - in the case of our trials, fragments or parts of chicken and turkey.

Variational formulation of open-ended coaxial line in contact with layered biological medium.

PubMed

Alanen, E; Lahtinen, T; Nuutinen, J

1998-10-01

An open-ended coaxial probe designed to measure layered biological media is analyzed with a new method. The probe is considered as an electrostatic circuit element whose capacitance is solved using a stationary functional. The fundamental transverse electric and magnetic field (TEM)-mode and the series of evanescent wavemodes in the coaxial cable are used as basis functions. The field outside the probe is solved using a Hankel transform. The capacitance is calculated for homogeneous materials and two-layer structures and the results are compared with values measured with a phantom model. The method can be easily extended for structures with an arbitrary number of layers. A practical approximation for two-layer cases, originally developed to take into account the effect of subcutaneous fat in skin measurements, is presented and its validity for different combinations of dielectric constants and the thickness of the first layer is demonstrated. The static approximation limits the frequency range, but it covers biological measurements up to 500 MHz. The developed method is accurate and easy to adopt in practice.

Protein interface classification by evolutionary analysis

PubMed Central

2012-01-01

Background Distinguishing biologically relevant interfaces from lattice contacts in protein crystals is a fundamental problem in structural biology. Despite efforts towards the computational prediction of interface character, many issues are still unresolved. Results We present here a protein-protein interface classifier that relies on evolutionary data to detect the biological character of interfaces. The classifier uses a simple geometric measure, number of core residues, and two evolutionary indicators based on the sequence entropy of homolog sequences. Both aim at detecting differential selection pressure between interface core and rim or rest of surface. The core residues, defined as fully buried residues (>95% burial), appear to be fundamental determinants of biological interfaces: their number is in itself a powerful discriminator of interface character and together with the evolutionary measures it is able to clearly distinguish evolved biological contacts from crystal ones. We demonstrate that this definition of core residues leads to distinctively better results than earlier definitions from the literature. The stringent selection and quality filtering of structural and sequence data was key to the success of the method. Most importantly we demonstrate that a more conservative selection of homolog sequences - with relatively high sequence identities to the query - is able to produce a clearer signal than previous attempts. Conclusions An evolutionary approach like the one presented here is key to the advancement of the field, which so far was missing an effective method exploiting the evolutionary character of protein interfaces. Its coverage and performance will only improve over time thanks to the incessant growth of sequence databases. Currently our method reaches an accuracy of 89% in classifying interfaces of the Ponstingl 2003 datasets and it lends itself to a variety of useful applications in structural biology and bioinformatics. We made the corresponding software implementation available to the community as an easy-to-use graphical web interface at http://www.eppic-web.org. PMID:23259833

Structure-Based Virtual Screening of Protein Tyrosine Phosphatase Inhibitors: Significance, Challenges, and Solutions.

PubMed

Reddy, Rallabandi Harikrishna; Kim, Hackyoung; Cha, Seungbin; Lee, Bongsoo; Kim, Young Jun

2017-05-28

Phosphorylation, a critical mechanism in biological systems, is estimated to be indispensable for about 30% of key biological activities, such as cell cycle progression, migration, and division. It is synergistically balanced by kinases and phosphatases, and any deviation from this balance leads to disease conditions. Pathway or biological activity-based abnormalities in phosphorylation and the type of involved phosphatase influence the outcome, and cause diverse diseases ranging from diabetes, rheumatoid arthritis, and numerous cancers. Protein tyrosine phosphatases (PTPs) are of prime importance in the process of dephosphorylation and catalyze several biological functions. Abnormal PTP activities are reported to result in several human diseases. Consequently, there is an increased demand for potential PTP inhibitory small molecules. Several strategies in structure-based drug designing techniques for potential inhibitory small molecules of PTPs have been explored along with traditional drug designing methods in order to overcome the hurdles in PTP inhibitor discovery. In this review, we discuss druggable PTPs and structure-based virtual screening efforts for successful PTP inhibitor design.

Synthetic fossilization of soft biological tissues and their shape-preserving transformation into silica or electron-conductive replicas

DOE PAGES

Townson, Jason L.; Lin, Yu-Shen; Chou, Stanley S.; ...

2014-12-08

Structural preservation of complex biological systems from the subcellular to whole organism level in robust forms, enabling dissection and imaging while preserving 3D context, represents an enduring grand challenge in biology. Here we report a simple immersion method for structurally preserving intact organisms via conformal stabilization within silica. This self-limiting process, which we refer to as silica bioreplication, occurs by condensation of water-soluble silicic acid proximally to biomolecular interfaces throughout the organism. Conformal nanoscopic silicification of all biomolecular features imparts structural rigidity enabling the preservation of shape and nano-to-macroscale dimensional features upon drying to form a biocomposite and further highmore » temperature oxidative calcination to form silica replicas or reductive pyrolysis to form electrically conductive carbon replicas of complete organisms. Ultimately, the simplicity and generalizability of this approach should facilitate efforts in biological preservation and analysis and could enable the development of new classes of biomimetic composite materials.« less

Ontology based molecular signatures for immune cell types via gene expression analysis

PubMed Central

2013-01-01

Background New technologies are focusing on characterizing cell types to better understand their heterogeneity. With large volumes of cellular data being generated, innovative methods are needed to structure the resulting data analyses. Here, we describe an ‘Ontologically BAsed Molecular Signature’ (OBAMS) method that identifies novel cellular biomarkers and infers biological functions as characteristics of particular cell types. This method finds molecular signatures for immune cell types based on mapping biological samples to the Cell Ontology (CL) and navigating the space of all possible pairwise comparisons between cell types to find genes whose expression is core to a particular cell type’s identity. Results We illustrate this ontological approach by evaluating expression data available from the Immunological Genome project (IGP) to identify unique biomarkers of mature B cell subtypes. We find that using OBAMS, candidate biomarkers can be identified at every strata of cellular identity from broad classifications to very granular. Furthermore, we show that Gene Ontology can be used to cluster cell types by shared biological processes in order to find candidate genes responsible for somatic hypermutation in germinal center B cells. Moreover, through in silico experiments based on this approach, we have identified genes sets that represent genes overexpressed in germinal center B cells and identify genes uniquely expressed in these B cells compared to other B cell types. Conclusions This work demonstrates the utility of incorporating structured ontological knowledge into biological data analysis – providing a new method for defining novel biomarkers and providing an opportunity for new biological insights. PMID:24004649

Statistical and fractal analysis of autofluorescent myocardium images in posthumous diagnostics of acute coronary insufficiency

NASA Astrophysics Data System (ADS)

Boichuk, T. M.; Bachinskiy, V. T.; Vanchuliak, O. Ya.; Minzer, O. P.; Garazdiuk, M.; Motrich, A. V.

2014-08-01

This research presents the results of investigation of laser polarization fluorescence of biological layers (histological sections of the myocardium). The polarized structure of autofluorescence imaging layers of biological tissues was detected and investigated. Proposed the model of describing the formation of polarization inhomogeneous of autofluorescence imaging biological optically anisotropic layers. On this basis, analytically and experimentally tested to justify the method of laser polarimetry autofluorescent. Analyzed the effectiveness of this method in the postmortem diagnosis of infarction. The objective criteria (statistical moments) of differentiation of autofluorescent images of histological sections myocardium were defined. The operational characteristics (sensitivity, specificity, accuracy) of these technique were determined.

Perspective: next generation isotope-aided methods for protein NMR spectroscopy.

PubMed

Kainosho, Masatsune; Miyanoiri, Yohei; Terauchi, Tsutomu; Takeda, Mitsuhiro

2018-06-22

In this perspective, we describe our efforts to innovate the current isotope-aided NMR methodology to investigate biologically important large proteins and protein complexes, for which only limited structural information could be obtained by conventional NMR approaches. At the present time, it is widely believed that only backbone amide and methyl signals are amenable for investigating such difficult targets. Therefore, our primary mission is to disseminate our novel knowledge within the biological NMR community; specifically, that any type of NMR signals other than methyl and amide groups can be obtained, even for quite large proteins, by optimizing the transverse relaxation properties by isotope labeling methods. The idea of "TROSY by isotope labeling" has been cultivated through our endeavors aiming to improve the original stereo-array isotope labeling (SAIL) method (Kainosho et al., Nature 440:52-57, 2006). The SAIL TROSY methods subsequently culminated in the successful observations of individual NMR signals for the side-chain aliphatic and aromatic 13 CH groups in large proteins, as exemplified by the 82 kDa single domain protein, malate synthase G. Meanwhile, the expected role of NMR spectroscopy in the emerging integrative structural biology has been rapidly shifting, from structure determination to the acquisition of biologically relevant structural dynamics, which are poorly accessible by X-ray crystallography or cryo-electron microscopy. Therefore, the newly accessible NMR probes, in addition to the methyl and amide signals, will open up a new horizon for investigating difficult protein targets, such as membrane proteins and supramolecular complexes, by NMR spectroscopy. We briefly introduce our latest results, showing that the protons attached to 12 C-atoms give profoundly narrow 1 H-NMR signals even for large proteins, by isolating them from the other protons using the selective deuteration. The direct 1 H observation methods exhibit the highest sensitivities, as compared to heteronuclear multidimensional spectroscopy, in which the 1 H-signals are acquired via the spin-coupled 13 C- and/or 15 N-nuclei. Although the selective deuteration method was launched a half century ago, as the first milestone in the following prosperous history of isotope-aided NMR methods, our results strongly imply that the low-dimensional 1 H-direct observation NMR methods should be revitalized in the coming era, featuring ultrahigh-field spectrometers beyond 1 GHz.

Analysing hierarchy in the organization of biological and physical systems.

PubMed

Jagers op Akkerhuis, Gerard A J M

2008-02-01

A structured approach is discussed for analysing hierarchy in the organization of biological and physical systems. The need for a structured approach follows from the observation that many hierarchies in the literature apply conflicting hierarchy rules and include ill-defined systems. As an alternative, we suggest a framework that is based on the following analytical steps: determination of the succession stage of the universe, identification of a specific system as part of the universe, specification of external influences on a system's creation and analysis of a system's internal organization. At the end, the paper discusses practical implications of the proposed method for the analysis of system organization and hierarchy in biology, ecology and physics.

An integrative approach to inferring biologically meaningful gene modules.

PubMed

Cho, Ji-Hoon; Wang, Kai; Galas, David J

2011-07-26

The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.

Universal nucleic acids sample preparation method for cells, spores and their mixture

DOEpatents

Bavykin, Sergei [Darien, IL

2011-01-18

The present invention relates to a method for extracting nucleic acids from biological samples. More specifically the invention relates to a universal method for extracting nucleic acids from unidentified biological samples. An advantage of the presently invented method is its ability to effectively and efficiently extract nucleic acids from a variety of different cell types including but not limited to prokaryotic or eukaryotic cells and/or recalcitrant organisms (i.e. spores). Unlike prior art methods which are focused on extracting nucleic acids from vegetative cell or spores, the present invention effectively extracts nucleic acids from spores, multiple cell types or mixtures thereof using a single method. Important that the invented method has demonstrated an ability to extract nucleic acids from spores and vegetative bacterial cells with similar levels effectiveness. The invented method employs a multi-step protocol which erodes the cell structure of the biological sample, isolates, labels, fragments nucleic acids and purifies labeled samples from the excess of dye.

Diffraction Techniques in Structural Biology

PubMed Central

Egli, Martin

2016-01-01

A detailed understanding of chemical and biological function and the mechanisms underlying the molecular activities ultimately requires atomic-resolution structural data. Diffraction-based techniques such as single-crystal X-ray crystallography, electron microscopy, and neutron diffraction are well established and they have paved the road to the stunning successes of modern-day structural biology. The major advances achieved in the last 20 years in all aspects of structural research, including sample preparation, crystallization, the construction of synchrotron and spallation sources, phasing approaches, and high-speed computing and visualization, now provide specialists and nonspecialists alike with a steady flow of molecular images of unprecedented detail. The present unit combines a general overview of diffraction methods with a detailed description of the process of a single-crystal X-ray structure determination experiment, from chemical synthesis or expression to phasing and refinement, analysis, and quality control. For novices it may serve as a stepping-stone to more in-depth treatises of the individual topics. Readers relying on structural information for interpreting functional data may find it a useful consumer guide. PMID:27248784

Diffraction Techniques in Structural Biology

PubMed Central

Egli, Martin

2010-01-01

A detailed understanding of chemical and biological function and the mechanisms underlying the activities ultimately requires atomic-resolution structural data. Diffraction-based techniques such as single-crystal X-ray crystallography, electron microscopy and neutron diffraction are well established and have paved the road to the stunning successes of modern-day structural biology. The major advances achieved in the last 20 years in all aspects of structural research, including sample preparation, crystallization, the construction of synchrotron and spallation sources, phasing approaches and high-speed computing and visualization, now provide specialists and non-specialists alike with a steady flow of molecular images of unprecedented detail. The present chapter combines a general overview of diffraction methods with a step-by-step description of the process of a single-crystal X-ray structure determination experiment, from chemical synthesis or expression to phasing and refinement, analysis and quality control. For novices it may serve as a stepping-stone to more in-depth treatises of the individual topics. Readers relying on structural information for interpreting functional data may find it a useful consumer guide. PMID:20517991

Diffraction Techniques in Structural Biology.

PubMed

Egli, Martin

2016-06-01

A detailed understanding of chemical and biological function and the mechanisms underlying the molecular activities ultimately requires atomic-resolution structural data. Diffraction-based techniques such as single-crystal X-ray crystallography, electron microscopy, and neutron diffraction are well established and they have paved the road to the stunning successes of modern-day structural biology. The major advances achieved in the last twenty years in all aspects of structural research, including sample preparation, crystallization, the construction of synchrotron and spallation sources, phasing approaches, and high-speed computing and visualization, now provide specialists and nonspecialists alike with a steady flow of molecular images of unprecedented detail. The present unit combines a general overview of diffraction methods with a detailed description of the process of a single-crystal X-ray structure determination experiment, from chemical synthesis or expression to phasing and refinement, analysis, and quality control. For novices it may serve as a stepping-stone to more in-depth treatises of the individual topics. Readers relying on structural information for interpreting functional data may find it a useful consumer guide. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Online quantitative analysis of multispectral images of human body tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.

2013-08-01

A method is developed for online monitoring of structural and morphological parameters of biological tissues (haemoglobin concentration, degree of blood oxygenation, average diameter of capillaries and the parameter characterising the average size of tissue scatterers), which involves multispectral tissue imaging, image normalisation to one of its spectral layers and determination of unknown parameters based on their stable regression relation with the spectral characteristics of the normalised image. Regression is obtained by simulating numerically the diffuse reflectance spectrum of the tissue by the Monte Carlo method at a wide variation of model parameters. The correctness of the model calculations is confirmed by the good agreement with the experimental data. The error of the method is estimated under conditions of general variability of structural and morphological parameters of the tissue. The method developed is compared with the traditional methods of interpretation of multispectral images of biological tissues, based on the solution of the inverse problem for each pixel of the image in the approximation of different analytical models.

Three-Dimensional Geometry of Collagenous Tissues by Second Harmonic Polarimetry.

PubMed

Reiser, Karen; Stoller, Patrick; Knoesen, André

2017-06-01

Collagen is a biological macromolecule capable of second harmonic generation, allowing label-free detection in tissues; in addition, molecular orientation can be determined from the polarization dependence of the second harmonic signal. Previously we reported that in-plane orientation of collagen fibrils could be determined by modulating the polarization angle of the laser during scanning. We have now extended this method so that out-of-plane orientation angles can be determined at the same time, allowing visualization of the 3-dimensional structure of collagenous tissues. This approach offers advantages compared with other methods for determining out-of-plane orientation. First, the orientation angles are directly calculated from the polarimetry data obtained in a single scan, while other reported methods require data from multiple scans, use of iterative optimization methods, application of fitting algorithms, or extensive post-optical processing. Second, our method does not require highly specialized instrumentation, and thus can be adapted for use in almost any nonlinear optical microscopy setup. It is suitable for both basic and clinical applications. We present three-dimensional images of structurally complex collagenous tissues that illustrate the power of such 3-dimensional analyses to reveal the architecture of biological structures.

Three-Dimensional Geometry of Collagenous Tissues by Second Harmonic Polarimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reiser, Karen; Stoller, Patrick; Knoesen, André

Collagen is a biological macromolecule capable of second harmonic generation, allowing label-free detection in tissues; in addition, molecular orientation can be determined from the polarization dependence of the second harmonic signal. Previously we reported that in-plane orientation of collagen fibrils could be determined by modulating the polarization angle of the laser during scanning. We have now extended this method so that out-of-plane orientation angles can be determined at the same time, allowing visualization of the 3-dimensional structure of collagenous tissues. This approach offers advantages compared with other methods for determining out-of-plane orientation. First, the orientation angles are directly calculated frommore » the polarimetry data obtained in a single scan, while other reported methods require data from multiple scans, use of iterative optimization methods, application of fitting algorithms, or extensive post-optical processing. Second, our method does not require highly specialized instrumentation, and thus can be adapted for use in almost any nonlinear optical microscopy setup. It is suitable for both basic and clinical applications. We present three-dimensional images of structurally complex collagenous tissues that illustrate the power of such 3-dimensional analyses to reveal the architecture of biological structures.« less

Three-Dimensional Geometry of Collagenous Tissues by Second Harmonic Polarimetry

DOE PAGES

Reiser, Karen; Stoller, Patrick; Knoesen, André

2017-06-01

Collagen is a biological macromolecule capable of second harmonic generation, allowing label-free detection in tissues; in addition, molecular orientation can be determined from the polarization dependence of the second harmonic signal. Previously we reported that in-plane orientation of collagen fibrils could be determined by modulating the polarization angle of the laser during scanning. We have now extended this method so that out-of-plane orientation angles can be determined at the same time, allowing visualization of the 3-dimensional structure of collagenous tissues. This approach offers advantages compared with other methods for determining out-of-plane orientation. First, the orientation angles are directly calculated frommore » the polarimetry data obtained in a single scan, while other reported methods require data from multiple scans, use of iterative optimization methods, application of fitting algorithms, or extensive post-optical processing. Second, our method does not require highly specialized instrumentation, and thus can be adapted for use in almost any nonlinear optical microscopy setup. It is suitable for both basic and clinical applications. We present three-dimensional images of structurally complex collagenous tissues that illustrate the power of such 3-dimensional analyses to reveal the architecture of biological structures.« less

The conservation and function of RNA secondary structure in plants

PubMed Central

Vandivier, Lee E.; Anderson, Stephen J.; Foley, Shawn W.; Gregory, Brian D.

2016-01-01

RNA transcripts fold into secondary structures via intricate patterns of base pairing. These secondary structures impart catalytic, ligand binding, and scaffolding functions to a wide array of RNAs, forming a critical node of biological regulation. Among their many functions, RNA structural elements modulate epigenetic marks, alter mRNA stability and translation, regulate alternative splicing, transduce signals, and scaffold large macromolecular complexes. Thus, the study of RNA secondary structure is critical to understanding the function and regulation of RNA transcripts. Here, we review the origins, form, and function of RNA secondary structure, focusing on plants. We then provide an overview of methods for probing secondary structure, from physical methods such as X-ray crystallography and nuclear magnetic resonance imaging (NMR) to chemical and nuclease probing methods. Marriage with high-throughput sequencing has enabled these latter methods to scale across whole transcriptomes, yielding tremendous new insights into the form and function of RNA secondary structure. PMID:26865341

Structural Identifiability of Dynamic Systems Biology Models

PubMed Central

Villaverde, Alejandro F.

2016-01-01

A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas. PMID:27792726

Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

PubMed

Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

2016-08-01

The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

From Sequence and Forces to Structure, Function and Evolution of Intrinsically Disordered Proteins

PubMed Central

Forman-Kay, Julie D.; Mittag, Tanja

2015-01-01

Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales and compactness is shaping a unified understanding of structure-dynamics-disorder/function relationships. On the 20th anniversary of this journal, Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional and evolutionary properties. PMID:24010708

From sequence and forces to structure, function, and evolution of intrinsically disordered proteins.

PubMed

Forman-Kay, Julie D; Mittag, Tanja

2013-09-03

Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics, and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales, and compactness are shaping a unified understanding of structure-dynamics-disorder/function relationships. In the 20(th) anniversary of Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional, and evolutionary properties. Copyright © 2013 Elsevier Ltd. All rights reserved.

Quantitative Characterization of Tissue Microstructure with Temporal Diffusion Spectroscopy

PubMed Central

Xu, Junzhong; Does, Mark D.; Gore, John C.

2009-01-01

The signals recorded by diffusion-weighted magnetic resonance imaging (DWI) are dependent on the micro-structural properties of biological tissues, so it is possible to obtain quantitative structural information non-invasively from such measurements. Oscillating gradient spin echo (OGSE) methods have the ability to probe the behavior of water diffusion over different time scales and the potential to detect variations in intracellular structure. To assist in the interpretation of OGSE data, analytical expressions have been derived for diffusion-weighted signals with OGSE methods for restricted diffusion in some typical structures, including parallel planes, cylinders and spheres, using the theory of temporal diffusion spectroscopy. These analytical predictions have been confirmed with computer simulations. These expressions suggest how OGSE signals from biological tissues should be analyzed to characterize tissue microstructure, including how to estimate cell nuclear sizes. This approach provides a model to interpret diffusion data obtained from OGSE measurements that can be used for applications such as monitoring tumor response to treatment in vivo. PMID:19616979

The phantom leaf effect: a replication, part 1.

PubMed

Hubacher, John

2015-02-01

To replicate the phantom leaf effect and demonstrate a possible means to directly observe properties of the biological field. Thirty percent to 60% of plant leaves were amputated, and the remaining leaf sections were photographed with corona discharge imaging. All leaves were cut before placement on film. A total of 137 leaves were used. Plant leaves of 14 different species. Ninety-six phantom leaf specimens were successfully obtained; 41 specimens did not yield the phantom leaf effect. A normally undetected phantom "structure," possibly evidence of the biological field, can persist in the area of an amputated leaf section, and corona discharge can occur from this invisible structure. This protocol may suggest a testable method to study properties of conductivity and other parameters through direct observation of the complete biological field in plant leaves, with broad implications for biology and physics.

EMDataBank unified data resource for 3DEM.

PubMed

Lawson, Catherine L; Patwardhan, Ardan; Baker, Matthew L; Hryc, Corey; Garcia, Eduardo Sanz; Hudson, Brian P; Lagerstedt, Ingvar; Ludtke, Steven J; Pintilie, Grigore; Sala, Raul; Westbrook, John D; Berman, Helen M; Kleywegt, Gerard J; Chiu, Wah

2016-01-04

Three-dimensional Electron Microscopy (3DEM) has become a key experimental method in structural biology for a broad spectrum of biological specimens from molecules to cells. The EMDataBank project provides a unified portal for deposition, retrieval and analysis of 3DEM density maps, atomic models and associated metadata (emdatabank.org). We provide here an overview of the rapidly growing 3DEM structural data archives, which include maps in EM Data Bank and map-derived models in the Protein Data Bank. In addition, we describe progress and approaches toward development of validation protocols and methods, working with the scientific community, in order to create a validation pipeline for 3DEM data. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

SAC-CI methodology applied to molecular spectroscopy and photo-biology

NASA Astrophysics Data System (ADS)

Hasegawa, J.; Miyahara, T.; Nakashima, H.; Nakatsuji, H.

2012-06-01

The SAC-CI method was applied to the spectroscopy of radical cations and anions of various organic molecules. It was also applied to photo-biology, in particular, to elucidate the bio-molecular color-tuning mechanism of human visions and to the circular dichroism spectroscopy that is used to understand the helical structures of DNA and RNA.

Bioturbo similarity searching: combining chemical and biological similarity to discover structurally diverse bioactive molecules.

PubMed

Wassermann, Anne Mai; Lounkine, Eugen; Glick, Meir

2013-03-25

Virtual screening using bioactivity profiles has become an integral part of currently applied hit finding methods in pharmaceutical industry. However, a significant drawback of this approach is that it is only applicable to compounds that have been biologically tested in the past and have sufficient activity annotations for meaningful profile comparisons. Although bioactivity data generated in pharmaceutical institutions are growing on an unprecedented scale, the number of biologically annotated compounds still covers only a minuscule fraction of chemical space. For a newly synthesized compound or an isolated natural product to be biologically characterized across multiple assays, it may take a considerable amount of time. Consequently, this chemical matter will not be included in virtual screening campaigns based on bioactivity profiles. To overcome this problem, we herein introduce bioturbo similarity searching that uses chemical similarity to map molecules without biological annotations into bioactivity space and then searches for biologically similar compounds in this reference system. In benchmark calculations on primary screening data, we demonstrate that our approach generally achieves higher hit rates and identifies structurally more diverse compounds than approaches using chemical information only. Furthermore, our method is able to discover hits with novel modes of inhibition that traditional 2D and 3D similarity approaches are unlikely to discover. Test calculations on a set of natural products reveal the practical utility of the approach for identifying novel and synthetically more accessible chemical matter.

System among the corticosteroids: specificity and molecular dynamics

PubMed Central

Brookes, Jennifer C.; Galigniana, Mario D.; Harker, Anthony H.; Stoneham, A. Marshall; Vinson, Gavin P.

2012-01-01

Understanding how structural features determine specific biological activities has often proved elusive. With over 161 000 steroid structures described, an algorithm able to predict activity from structural attributes would provide manifest benefits. Molecular simulations of a range of 35 corticosteroids show striking correlations between conformational mobility and biological specificity. Thus steroid ring A is important for glucocorticoid action, and is rigid in the most specific (and potent) examples, such as dexamethasone. By contrast, ring C conformation is important for the mineralocorticoids, and is rigid in aldosterone. Other steroids that are less specific, or have mixed functions, or none at all, are more flexible. One unexpected example is 11-deoxycorticosterone, which the methods predict (and our activity studies confirm) is not only a specific mineralocorticoid, but also has significant glucocorticoid activity. These methods may guide the design of new corticosteroid agonists and antagonists. They will also have application in other examples of ligand–receptor interactions. PMID:21613285

Prediction of enzymatic pathways by integrative pathway mapping

PubMed Central

Wichelecki, Daniel J; San Francisco, Brian; Zhao, Suwen; Rodionov, Dmitry A; Vetting, Matthew W; Al-Obaidi, Nawar F; Lin, Henry; O'Meara, Matthew J; Scott, David A; Morris, John H; Russel, Daniel; Almo, Steven C; Osterman, Andrei L

2018-01-01

The functions of most proteins are yet to be determined. The function of an enzyme is often defined by its interacting partners, including its substrate and product, and its role in larger metabolic networks. Here, we describe a computational method that predicts the functions of orphan enzymes by organizing them into a linear metabolic pathway. Given candidate enzyme and metabolite pathway members, this aim is achieved by finding those pathways that satisfy structural and network restraints implied by varied input information, including that from virtual screening, chemoinformatics, genomic context analysis, and ligand -binding experiments. We demonstrate this integrative pathway mapping method by predicting the L-gulonate catabolic pathway in Haemophilus influenzae Rd KW20. The prediction was subsequently validated experimentally by enzymology, crystallography, and metabolomics. Integrative pathway mapping by satisfaction of structural and network restraints is extensible to molecular networks in general and thus formally bridges the gap between structural biology and systems biology. PMID:29377793

Expression of recombinant glycoproteins in mammalian cells: towards an integrative approach to structural biology.

PubMed

Aricescu, A Radu; Owens, Raymond J

2013-06-01

Mammalian cells are rapidly becoming the system of choice for the production of recombinant glycoproteins for structural biology applications. Their use has enabled the structural investigation of a whole new set of targets including large, multi-domain and highly glycosylated eukaryotic cell surface receptors and their supra-molecular assemblies. We summarize the technical advances that have been made in mammalian expression technology and highlight some of the structural insights that have been obtained using these methods. Looking forward, it is clear that mammalian cell expression will provide exciting and unique opportunities for an integrative approach to the structural study of proteins, especially of human origin and medically relevant, by bridging the gap between the purified state and the cellular context. Copyright © 2013 Elsevier Ltd. All rights reserved.

Nanostructures Enabled by On-Wire Lithography (OWL)

PubMed Central

Braunschweig, Adam B.; Schmucker, Abrin L.; Wei, Wei David; Mirkin, Chad A.

2010-01-01

Nanostructures fabricated by a novel technique, termed On-Wire-Lithography (OWL), can be combined with organic and biological molecules to create systems with emergent and highly functional properties. OWL is a template-based, electrochemical process for forming gapped cylindrical structures on a solid support, with feature sizes (both gap and segment length) that can be controlled on the sub-100 nm length scale. Structures prepared by this method have provided valuable insight into the plasmonic properties of noble metal nanomaterials and have formed the basis for novel molecular electronic, encoding, and biological detection devices. PMID:20396668

Biological materials: a materials science approach.

PubMed

Meyers, Marc A; Chen, Po-Yu; Lopez, Maria I; Seki, Yasuaki; Lin, Albert Y M

2011-07-01

The approach used by Materials Science and Engineering is revealing new aspects in the structure and properties of biological materials. The integration of advanced characterization, mechanical testing, and modeling methods can rationalize heretofore unexplained aspects of these structures. As an illustration of the power of this methodology, we apply it to biomineralized shells, avian beaks and feathers, and fish scales. We also present a few selected bioinspired applications: Velcro, an Al2O3-PMMA composite inspired by the abalone shell, and synthetic attachment devices inspired by gecko. Copyright © 2010 Elsevier Ltd. All rights reserved.

Lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry and its application to complex biological samples.

PubMed

Triebl, Alexander; Trötzmüller, Martin; Hartler, Jürgen; Stojakovic, Tatjana; Köfeler, Harald C

2017-05-15

An improved approach for selective and sensitive identification and quantitation of lipid molecular species using reversed phase chromatography coupled to high resolution mass spectrometry was developed. The method is applicable to a wide variety of biological matrices using a simple liquid-liquid extraction procedure. Together, this approach combines multiple selectivity criteria: Reversed phase chromatography separates lipids according to their acyl chain length and degree of unsaturation and is capable of resolving positional isomers of lysophospholipids, as well as structural isomers of diacyl phospholipids and glycerolipids. Orbitrap mass spectrometry delivers the elemental composition of both positive and negative ions with high mass accuracy. Finally, automatically generated tandem mass spectra provide structural insight into numerous glycerolipids, phospholipids, and sphingolipids within a single run. Calibration showed linearity ranges of more than four orders of magnitude, good values for accuracy and precision at biologically relevant concentration levels, and limits of quantitation of a few femtomoles on column. Hundreds of lipid molecular species were detected and quantified in three different biological matrices, which cover well the wide variety and complexity of various model organisms in lipidomic research. Together with a software package, this method is a prime choice for global lipidomic analysis of even the most complex biological samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Structures and physical properties of gaseous metal cationized biological ions.

PubMed

Burt, Michael B; Fridgen, Travis D

2012-01-01

Metal chelation can alter the activity of free biomolecules by modifying their structures or stabilizing higher energy tautomers. In recent years, mass spectrometric techniques have been used to investigate the effects of metal complexation with proteins, nucleobases and nucleotides, where small conformational changes can have significant physiological consequences. In particular, infrared multiple photon dissociation spectroscopy has emerged as an important tool for determining the structure and reactivity of gas-phase ions. Unlike other mass spectrometric approaches, this method is able to directly resolve structural isomers using characteristic vibrational signatures. Other activation and dissociation methods, such as blackbody infrared radiative dissociation or collision-induced dissociation can also reveal information about the thermochemistry and dissociative pathways of these biological ions. This information can then be used to provide information about the structures of the ionic complexes under study. In this article, we review the use of gas-phase techniques in characterizing metal-bound biomolecules. Particular attention will be given to our own contributions, which detail the ability of metal cations to disrupt nucleobase pairs, direct the self-assembly of nucleobase clusters and stabilize non-canonical isomers of amino acids.

An Evolution-Based Approach to De Novo Protein Design and Case Study on Mycobacterium tuberculosis

PubMed Central

Brender, Jeffrey R.; Czajka, Jeff; Marsh, David; Gray, Felicia; Cierpicki, Tomasz; Zhang, Yang

2013-01-01

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality. PMID:24204234

Searching molecular structure databases with tandem mass spectra using CSI:FingerID

PubMed Central

Dührkop, Kai; Shen, Huibin; Meusel, Marvin; Rousu, Juho; Böcker, Sebastian

2015-01-01

Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. We present a method for searching molecular structure databases using tandem MS data of small molecules. Our method computes a fragmentation tree that best explains the fragmentation spectrum of an unknown molecule. We use the fragmentation tree to predict the molecular structure fingerprint of the unknown compound using machine learning. This fingerprint is then used to search a molecular structure database such as PubChem. Our method is shown to improve on the competing methods for computational metabolite identification by a considerable margin. PMID:26392543

The program structure does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem.

PubMed

Puechmaille, Sebastien J

2016-05-01

Inferences of population structure and more precisely the identification of genetically homogeneous groups of individuals are essential to the fields of ecology, evolutionary biology and conservation biology. Such population structure inferences are routinely investigated via the program structure implementing a Bayesian algorithm to identify groups of individuals at Hardy-Weinberg and linkage equilibrium. While the method is performing relatively well under various population models with even sampling between subpopulations, the robustness of the method to uneven sample size between subpopulations and/or hierarchical levels of population structure has not yet been tested despite being commonly encountered in empirical data sets. In this study, I used simulated and empirical microsatellite data sets to investigate the impact of uneven sample size between subpopulations and/or hierarchical levels of population structure on the detected population structure. The results demonstrated that uneven sampling often leads to wrong inferences on hierarchical structure and downward-biased estimates of the true number of subpopulations. Distinct subpopulations with reduced sampling tended to be merged together, while at the same time, individuals from extensively sampled subpopulations were generally split, despite belonging to the same panmictic population. Four new supervised methods to detect the number of clusters were developed and tested as part of this study and were found to outperform the existing methods using both evenly and unevenly sampled data sets. Additionally, a subsampling strategy aiming to reduce sampling unevenness between subpopulations is presented and tested. These results altogether demonstrate that when sampling evenness is accounted for, the detection of the correct population structure is greatly improved. © 2016 John Wiley & Sons Ltd.

Holographic femtosecond laser processing and its application to biological materials (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hayasaki, Yoshio

2017-02-01

Femtosecond laser processing is a promising tool for fabricating novel and useful structures on the surfaces of and inside materials. An enormous number of pulse irradiation points will be required for fabricating actual structures with millimeter scale, and therefore, the throughput of femtosecond laser processing must be improved for practical adoption of this technique. One promising method to improve throughput is parallel pulse generation based on a computer-generated hologram (CGH) displayed on a spatial light modulator (SLM), a technique called holographic femtosecond laser processing. The holographic method has the advantages such as high throughput, high light use efficiency, and variable, instantaneous, and 3D patterning. Furthermore, the use of an SLM gives an ability to correct unknown imperfections of the optical system and inhomogeneity in a sample using in-system optimization of the CGH. Furthermore, the CGH can adaptively compensate in response to dynamic unpredictable mechanical movements, air and liquid disturbances, a shape variation and deformation of the target sample, as well as adaptive wavefront control for environmental changes. Therefore, it is a powerful tool for the fabrication of biological cells and tissues, because they have free form, variable, and deformable structures. In this paper, we present the principle and the experimental setup of holographic femtosecond laser processing, and the effective way for processing the biological sample. We demonstrate the femtosecond laser processing of biological materials and the processing properties.

A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization.

PubMed

Tuikkala, Johannes; Vähämaa, Heidi; Salmela, Pekka; Nevalainen, Olli S; Aittokallio, Tero

2012-03-26

Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications.

Data publication with the structural biology data grid supports live analysis

DOE PAGES

Meyer, Peter A.; Socias, Stephanie; Key, Jason; ...

2016-03-07

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of themore » original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. In conclusion, it is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis.« less

Data publication with the structural biology data grid supports live analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meyer, Peter A.; Socias, Stephanie; Key, Jason

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of themore » original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. In conclusion, it is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis.« less

Data publication with the structural biology data grid supports live analysis.

PubMed

Meyer, Peter A; Socias, Stephanie; Key, Jason; Ransey, Elizabeth; Tjon, Emily C; Buschiazzo, Alejandro; Lei, Ming; Botka, Chris; Withrow, James; Neau, David; Rajashankar, Kanagalaghatta; Anderson, Karen S; Baxter, Richard H; Blacklow, Stephen C; Boggon, Titus J; Bonvin, Alexandre M J J; Borek, Dominika; Brett, Tom J; Caflisch, Amedeo; Chang, Chung-I; Chazin, Walter J; Corbett, Kevin D; Cosgrove, Michael S; Crosson, Sean; Dhe-Paganon, Sirano; Di Cera, Enrico; Drennan, Catherine L; Eck, Michael J; Eichman, Brandt F; Fan, Qing R; Ferré-D'Amaré, Adrian R; Fromme, J Christopher; Garcia, K Christopher; Gaudet, Rachelle; Gong, Peng; Harrison, Stephen C; Heldwein, Ekaterina E; Jia, Zongchao; Keenan, Robert J; Kruse, Andrew C; Kvansakul, Marc; McLellan, Jason S; Modis, Yorgo; Nam, Yunsun; Otwinowski, Zbyszek; Pai, Emil F; Pereira, Pedro José Barbosa; Petosa, Carlo; Raman, C S; Rapoport, Tom A; Roll-Mecak, Antonina; Rosen, Michael K; Rudenko, Gabby; Schlessinger, Joseph; Schwartz, Thomas U; Shamoo, Yousif; Sondermann, Holger; Tao, Yizhi J; Tolia, Niraj H; Tsodikov, Oleg V; Westover, Kenneth D; Wu, Hao; Foster, Ian; Fraser, James S; Maia, Filipe R N C; Gonen, Tamir; Kirchhausen, Tom; Diederichs, Kay; Crosas, Mercè; Sliz, Piotr

2016-03-07

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis.

Data publication with the structural biology data grid supports live analysis

PubMed Central

Meyer, Peter A.; Socias, Stephanie; Key, Jason; Ransey, Elizabeth; Tjon, Emily C.; Buschiazzo, Alejandro; Lei, Ming; Botka, Chris; Withrow, James; Neau, David; Rajashankar, Kanagalaghatta; Anderson, Karen S.; Baxter, Richard H.; Blacklow, Stephen C.; Boggon, Titus J.; Bonvin, Alexandre M. J. J.; Borek, Dominika; Brett, Tom J.; Caflisch, Amedeo; Chang, Chung-I; Chazin, Walter J.; Corbett, Kevin D.; Cosgrove, Michael S.; Crosson, Sean; Dhe-Paganon, Sirano; Di Cera, Enrico; Drennan, Catherine L.; Eck, Michael J.; Eichman, Brandt F.; Fan, Qing R.; Ferré-D'Amaré, Adrian R.; Christopher Fromme, J.; Garcia, K. Christopher; Gaudet, Rachelle; Gong, Peng; Harrison, Stephen C.; Heldwein, Ekaterina E.; Jia, Zongchao; Keenan, Robert J.; Kruse, Andrew C.; Kvansakul, Marc; McLellan, Jason S.; Modis, Yorgo; Nam, Yunsun; Otwinowski, Zbyszek; Pai, Emil F.; Pereira, Pedro José Barbosa; Petosa, Carlo; Raman, C. S.; Rapoport, Tom A.; Roll-Mecak, Antonina; Rosen, Michael K.; Rudenko, Gabby; Schlessinger, Joseph; Schwartz, Thomas U.; Shamoo, Yousif; Sondermann, Holger; Tao, Yizhi J.; Tolia, Niraj H.; Tsodikov, Oleg V.; Westover, Kenneth D.; Wu, Hao; Foster, Ian; Fraser, James S.; Maia, Filipe R. N C.; Gonen, Tamir; Kirchhausen, Tom; Diederichs, Kay; Crosas, Mercè; Sliz, Piotr

2016-01-01

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis. PMID:26947396

Combined X-ray and neutron fibre diffraction studies of biological and synthetic polymers

NASA Astrophysics Data System (ADS)

Parrot, I. M.; Urban, V.; Gardner, K. H.; Forsyth, V. T.

2005-08-01

The fibrous state is a natural one for polymer molecules which tend to assume regular helical conformations rather than the globular structures characteristic of many proteins. Fibre diffraction therefore has broad application to the study of a wide range of biological and synthetic polymers. The purpose of this paper is to illustrate the general scope of the method and in particular to demonstrate the impact of a combined approach involving both X-ray and neutron diffraction methods. While the flux of modern X-ray synchrotron radiation sources allows high quality datasets to be recorded with good resolution within a very short space of time, neutron studies can provide unique information through the ability to locate hydrogen or deuterium atoms that are often difficult or impossible to locate using X-ray methods. Furthermore, neutron fibre diffraction methods can, through the ability to selectively label specific parts of a structure, be used to highlight novel aspects of polymer structure that can not be studied using X-rays. Two examples are given. The first describes X-ray and neutron diffraction studies of conformational transitions in DNA. The second describes structural studies of the synthetic high-performance polymer poly(p-phenylene terephthalamide) (PPTA), known commercially as Kevlar® or Twaron®.

Integrative analysis of transcriptomic and metabolomic data via sparse canonical correlation analysis with incorporation of biological information.

PubMed

Safo, Sandra E; Li, Shuzhao; Long, Qi

2018-03-01

Integrative analysis of high dimensional omics data is becoming increasingly popular. At the same time, incorporating known functional relationships among variables in analysis of omics data has been shown to help elucidate underlying mechanisms for complex diseases. In this article, our goal is to assess association between transcriptomic and metabolomic data from a Predictive Health Institute (PHI) study that includes healthy adults at a high risk of developing cardiovascular diseases. Adopting a strategy that is both data-driven and knowledge-based, we develop statistical methods for sparse canonical correlation analysis (CCA) with incorporation of known biological information. Our proposed methods use prior network structural information among genes and among metabolites to guide selection of relevant genes and metabolites in sparse CCA, providing insight on the molecular underpinning of cardiovascular disease. Our simulations demonstrate that the structured sparse CCA methods outperform several existing sparse CCA methods in selecting relevant genes and metabolites when structural information is informative and are robust to mis-specified structural information. Our analysis of the PHI study reveals that a number of gene and metabolic pathways including some known to be associated with cardiovascular diseases are enriched in the set of genes and metabolites selected by our proposed approach. © 2017, The International Biometric Society.

From lows to highs: using low-resolution models to phase X-ray data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stuart, David I.; Diamond Light Source Ltd, Diamond House, Harwell Science and Innovation Campus, Didcot; Abrescia, Nicola G. A., E-mail: nabrescia@cicbiogune.es

2013-11-01

An unusual example of how virus structure determination pushes the limits of the molecular replacement method is presented. The study of virus structures has contributed to methodological advances in structural biology that are generally applicable (molecular replacement and noncrystallographic symmetry are just two of the best known examples). Moreover, structural virology has been instrumental in forging the more general concept of exploiting phase information derived from multiple structural techniques. This hybridization of structural methods, primarily electron microscopy (EM) and X-ray crystallography, but also small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy, is central to integrative structural biology. Here,more » the interplay of X-ray crystallography and EM is illustrated through the example of the structural determination of the marine lipid-containing bacteriophage PM2. Molecular replacement starting from an ∼13 Å cryo-EM reconstruction, followed by cycling density averaging, phase extension and solvent flattening, gave the X-ray structure of the intact virus at 7 Å resolution This in turn served as a bridge to phase, to 2.5 Å resolution, data from twinned crystals of the major coat protein (P2), ultimately yielding a quasi-atomic model of the particle, which provided significant insights into virus evolution and viral membrane biogenesis.« less

Anti-infectious drug repurposing using an integrated chemical genomics and structural systems biology approach.

PubMed

Ng, Clara; Hauptman, Ruth; Zhang, Yinliang; Bourne, Philip E; Xie, Lei

2014-01-01

The emergence of multi-drug and extensive drug resistance of microbes to antibiotics poses a great threat to human health. Although drug repurposing is a promising solution for accelerating the drug development process, its application to anti-infectious drug discovery is limited by the scope of existing phenotype-, ligand-, or target-based methods. In this paper we introduce a new computational strategy to determine the genome-wide molecular targets of bioactive compounds in both human and bacterial genomes. Our method is based on the use of a novel algorithm, ligand Enrichment of Network Topological Similarity (ligENTS), to map the chemical universe to its global pharmacological space. ligENTS outperforms the state-of-the-art algorithms in identifying novel drug-target relationships. Furthermore, we integrate ligENTS with our structural systems biology platform to identify drug repurposing opportunities via target similarity profiling. Using this integrated strategy, we have identified novel P. falciparum targets of drug-like active compounds from the Malaria Box, and suggest that a number of approved drugs may be active against malaria. This study demonstrates the potential of an integrative chemical genomics and structural systems biology approach to drug repurposing.

Chemistry and Pharmacology of Thioflavones.

PubMed

Dong, Jinyun; Zhang, Qijing; Meng, Qingqing; Wang, Zengtao; Li, Shaoshun; Cui, Jiahua

2018-05-15

Thioflavone derivatives are the thio analogs of the core constituent of the natural product class of flavones. Based on the position and oxidation level of sulfur, they can be divided into three major categories: 4-thioflavones, 1-thioflavones and 1-thioflavones 1,1-dioxide. In recent years, great efforts have been made to develop an approach to thioflavones, especially 1-thioflavones with high functional group compatibility, high yields, low toxicity as well as proceeding under a mild condition, and a variety of synthetic protocols have been developed, the method of choice being dependent on the nature of substrates. As isosteric analogs of biologically active flavones, likewise thioflavones exhibit various pharmaceutical properties, such as antimicrobial, anticancer and neuroprotective activities. Replacement of the oxygen atom on flavone skeleton by a sulfur atom resulted in modified biological effects due in most part to the change of structural properties. However, these varying effects depend on the substituents present and the test species. To provide a comprehensive vision of this class of compounds, this review primarily focuses on the structure, synthetic methods, biological properties as well as structure-activity relationships of thioflavones. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Structural Analysis of PTM Hotspots (SAPH-ire)--A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families.

PubMed

Dewhurst, Henry M; Choudhury, Shilpa; Torres, Matthew P

2015-08-01

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)--a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits--conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit-N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

A novel and rapid method for obtaining high titre intact prion strains from mammalian brain.

PubMed

Wenborn, Adam; Terry, Cassandra; Gros, Nathalie; Joiner, Susan; D'Castro, Laura; Panico, Silvia; Sells, Jessica; Cronier, Sabrina; Linehan, Jacqueline M; Brandner, Sebastian; Saibil, Helen R; Collinge, John; Wadsworth, Jonathan D F

2015-05-07

Mammalian prions exist as multiple strains which produce characteristic and highly reproducible phenotypes in defined hosts. How this strain diversity is encoded by a protein-only agent remains one of the most interesting and challenging questions in biology with wide relevance to understanding other diseases involving the aggregation or polymerisation of misfolded host proteins. Progress in understanding mammalian prion strains has however been severely limited by the complexity and variability of the methods used for their isolation from infected tissue and no high resolution structures have yet been reported. Using high-throughput cell-based prion bioassay to re-examine prion purification from first principles we now report the isolation of prion strains to exceptional levels of purity from small quantities of infected brain and demonstrate faithful retention of biological and biochemical strain properties. The method's effectiveness and simplicity should facilitate its wide application and expedite structural studies of prions.

Topic modeling for cluster analysis of large biological and medical datasets

PubMed Central

2014-01-01

Background The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. Results In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Conclusion Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets. PMID:25350106

Topic modeling for cluster analysis of large biological and medical datasets.

PubMed

Zhao, Weizhong; Zou, Wen; Chen, James J

2014-01-01

The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets.

Toward a structure determination method for biomineral-associated protein using combined solid- state NMR and computational structure prediction.

PubMed

Masica, David L; Ash, Jason T; Ndao, Moise; Drobny, Gary P; Gray, Jeffrey J

2010-12-08

Protein-biomineral interactions are paramount to materials production in biology, including the mineral phase of hard tissue. Unfortunately, the structure of biomineral-associated proteins cannot be determined by X-ray crystallography or solution nuclear magnetic resonance (NMR). Here we report a method for determining the structure of biomineral-associated proteins. The method combines solid-state NMR (ssNMR) and ssNMR-biased computational structure prediction. In addition, the algorithm is able to identify lattice geometries most compatible with ssNMR constraints, representing a quantitative, novel method for investigating crystal-face binding specificity. We use this method to determine most of the structure of human salivary statherin interacting with the mineral phase of tooth enamel. Computation and experiment converge on an ensemble of related structures and identify preferential binding at three crystal surfaces. The work represents a significant advance toward determining structure of biomineral-adsorbed protein using experimentally biased structure prediction. This method is generally applicable to proteins that can be chemically synthesized. Copyright © 2010 Elsevier Ltd. All rights reserved.

Nonlinear optical methods for the analysis of protein nanocrystals and biological tissues

NASA Astrophysics Data System (ADS)

Dow, Ximeng You

Structural biology underpins rational drug design and fundamental understanding of protein function. X-ray diffraction (XRD) has been the golden standard for solving for high-resolution protein structure. Second harmonic generation (SHG) microscopy has been developed by the Simpson lab as a sensitive, crystal-specific detection method for the identification of protein crystal and help optimize the crystallization condition. Protein nanocrystals has been widely used for structure determination of membrane proteins in serial femtosecond nanocrystallography. In this thesis work, novel nonlinear optical methods were developed to address the challenges associated with the detection and characterization of protein nanocrystals. SHG-correlation spectroscopy (SHG-CS) was developed to take advantage of the diffusing motion and retrieve the size distribution and crystal quality of the nanocrystals. Polarization-dependent SHG imaging technique was developed to measure the relative orientation as well as the internal structure of the sample. Two photon- excited fluorescence has been used in the Simpson lab as a complementary measurement besides the inherent SHG signal from the crystals. A novel instrumentation development was also introduced in this thesis work to greatly improve the speed of fluorescence lifetime imaging (FLIM).

A history of neutrons in biology: the development of neutron protein crystallography at BNL and LANL.

PubMed

Schoenborn, Benno P

2010-11-01

The first neutron diffraction data were collected from crystals of myoglobin almost 42 years ago using a step-scan diffractometer with a single detector. Since then, major advances have been made in neutron sources, instrumentation and data collection and analysis, and in biochemistry. Fundamental discoveries about enzyme mechanisms, biological complex structures, protein hydration and H-atom positions have been and continue to be made using neutron diffraction. The promise of neutrons has not changed since the first crystal diffraction data were collected. Today, with the developments of beamlines at spallation neutron sources and the use of the Laue method for data collection, the field of neutrons in structural biology has renewed vitality.

Bioinspired Functional Materials

DOE PAGES

Zheng, Yongmei; Wang, Jingxia; Hou, Yongping; ...

2014-11-25

This special issue is focused on the nanoscale or micro-/nanoscale structures similar to the biological features in multilevels or hierarchy and so on. Research by mimicking biological systems has shown more impact on many applications due to the well-designed micro-/nanostructures inspired from the biological surfaces or interfaces; therefore, the materials may achieve the fascinating functionality. In conclusion, the bioinspired functional materials may be fabricated by developing novel technology or methods such as synthesis, self-assembly, and soft lithography at micro- or nanolevel or multilevels and, in addition, the multidisciplinary procedures of physical or chemical methods and nanotechnology to mimic the biologicalmore » multiscale micro-/nanostructures onto one-/two-dimensional surface materials.« less

Teaching structure: student use of software tools for understanding macromolecular structure in an undergraduate biochemistry course.

PubMed

Jaswal, Sheila S; O'Hara, Patricia B; Williamson, Patrick L; Springer, Amy L

2013-01-01

Because understanding the structure of biological macromolecules is critical to understanding their function, students of biochemistry should become familiar not only with viewing, but also with generating and manipulating structural representations. We report a strategy from a one-semester undergraduate biochemistry course to integrate use of structural representation tools into both laboratory and homework activities. First, early in the course we introduce the use of readily available open-source software for visualizing protein structure, coincident with modules on amino acid and peptide bond properties. Second, we use these same software tools in lectures and incorporate images and other structure representations in homework tasks. Third, we require a capstone project in which teams of students examine a protein-nucleic acid complex and then use the software tools to illustrate for their classmates the salient features of the structure, relating how the structure helps explain biological function. To ensure engagement with a range of software and database features, we generated a detailed template file that can be used to explore any structure, and that guides students through specific applications of many of the software tools. In presentations, students demonstrate that they are successfully interpreting structural information, and using representations to illustrate particular points relevant to function. Thus, over the semester students integrate information about structural features of biological macromolecules into the larger discussion of the chemical basis of function. Together these assignments provide an accessible introduction to structural representation tools, allowing students to add these methods to their biochemical toolboxes early in their scientific development. © 2013 by The International Union of Biochemistry and Molecular Biology.

Hierarchical thinking in network biology: the unbiased modularization of biochemical networks.

PubMed

Papin, Jason A; Reed, Jennifer L; Palsson, Bernhard O

2004-12-01

As reconstructed biochemical reaction networks continue to grow in size and scope, there is a growing need to describe the functional modules within them. Such modules facilitate the study of biological processes by deconstructing complex biological networks into conceptually simple entities. The definition of network modules is often based on intuitive reasoning. As an alternative, methods are being developed for defining biochemical network modules in an unbiased fashion. These unbiased network modules are mathematically derived from the structure of the whole network under consideration.

Structural Elucidation and Biological Activity of a Highly Regular Fucosylated Glycosaminoglycan from the Edible Sea Cucumber Stichopus herrmanni.

PubMed

Li, Xiaomei; Luo, Lan; Cai, Ying; Yang, Wenjiao; Lin, Lisha; Li, Zi; Gao, Na; Purcell, Steven W; Wu, Mingyi; Zhao, Jinhua

2017-10-25

Edible sea cucumbers are widely used as a health food and medicine. A fucosylated glycosaminoglycan (FG) was purified from the high-value sea cucumber Stichopus herrmanni. Its physicochemical properties and structure were analyzed and characterized by chemical and instrumental methods. Chemical analysis indicated that this FG with a molecular weight of ∼64 kDa is composed of N-acetyl-d-galactosamine, d-glucuronic acid (GlcA), and l-fucose. Structural analysis clarified that the FG contains the chondroitin sulfate E-like backbone, with mostly 2,4-di-O-sulfated (85%) and some 3,4-di-O-sulfated (10%) and 4-O-sulfated (5%) fucose side chains that link to the C3 position of GlcA. This FG is structurally highly regular and homogeneous, differing from the FGs of other sea cucumbers, for its sulfation patterns are simpler. Biological activity assays indicated that it is a strong anticoagulant, inhibiting thrombin and intrinsic factor Xase. Our results expand the knowledge on structural types of FG and illustrate its biological activity as a functional food material.

Structural Studies of Silver Nanoparticles Obtained Through Single-Step Green Synthesis

NASA Astrophysics Data System (ADS)

Prasad Peddi, Siva; Abdallah Sadeh, Bilal

2015-10-01

Green synthesis of silver Nanoparticles (AGNP's) has been the most prominent among the metallic nanoparticles for research for over a decade and half now due to both the simplicity of preparation and the applicability of biological species with extensive applications in medicine and biotechnology to reduce and trap the particles. The current article uses Eclipta Prostrata leaf extract as the biological species to cap the AGNP's through a single step process. The characterization data obtained was used for the analysis of the sample structure. The article emphasizes the disquisition of their shape and size of the lattice parameters and proposes a general scheme and a mathematical model for the analysis of their dependence. The data of the synthesized AGNP's has been used to advantage through the introduction of a structural shape factor for the crystalline nanoparticles. The properties of the structure of the AGNP's proposed and evaluated through a theoretical model was undeviating with the experimental consequences. This modus operandi gives scope for the structural studies of ultrafine particles prepared using biological methods.

An optimal transportation approach for nuclear structure-based pathology.

PubMed

Wang, Wei; Ozolek, John A; Slepčev, Dejan; Lee, Ann B; Chen, Cheng; Rohde, Gustavo K

2011-03-01

Nuclear morphology and structure as visualized from histopathology microscopy images can yield important diagnostic clues in some benign and malignant tissue lesions. Precise quantitative information about nuclear structure and morphology, however, is currently not available for many diagnostic challenges. This is due, in part, to the lack of methods to quantify these differences from image data. We describe a method to characterize and contrast the distribution of nuclear structure in different tissue classes (normal, benign, cancer, etc.). The approach is based on quantifying chromatin morphology in different groups of cells using the optimal transportation (Kantorovich-Wasserstein) metric in combination with the Fisher discriminant analysis and multidimensional scaling techniques. We show that the optimal transportation metric is able to measure relevant biological information as it enables automatic determination of the class (e.g., normal versus cancer) of a set of nuclei. We show that the classification accuracies obtained using this metric are, on average, as good or better than those obtained utilizing a set of previously described numerical features. We apply our methods to two diagnostic challenges for surgical pathology: one in the liver and one in the thyroid. Results automatically computed using this technique show potentially biologically relevant differences in nuclear structure in liver and thyroid cancers.

An optimal transportation approach for nuclear structure-based pathology

PubMed Central

Wang, Wei; Ozolek, John A.; Slepčev, Dejan; Lee, Ann B.; Chen, Cheng; Rohde, Gustavo K.

2012-01-01

Nuclear morphology and structure as visualized from histopathology microscopy images can yield important diagnostic clues in some benign and malignant tissue lesions. Precise quantitative information about nuclear structure and morphology, however, is currently not available for many diagnostic challenges. This is due, in part, to the lack of methods to quantify these differences from image data. We describe a method to characterize and contrast the distribution of nuclear structure in different tissue classes (normal, benign, cancer, etc.). The approach is based on quantifying chromatin morphology in different groups of cells using the optimal transportation (Kantorovich-Wasserstein) metric in combination with the Fisher discriminant analysis and multidimensional scaling techniques. We show that the optimal transportation metric is able to measure relevant biological information as it enables automatic determination of the class (e.g. normal vs. cancer) of a set of nuclei. We show that the classification accuracies obtained using this metric are, on average, as good or better than those obtained utilizing a set of previously described numerical features. We apply our methods to two diagnostic challenges for surgical pathology: one in the liver and one in the thyroid. Results automatically computed using this technique show potentially biologically relevant differences in nuclear structure in liver and thyroid cancers. PMID:20977984

Virtual screening applications: a study of ligand-based methods and different structure representations in four different scenarios.

PubMed

Hristozov, Dimitar P; Oprea, Tudor I; Gasteiger, Johann

2007-01-01

Four different ligand-based virtual screening scenarios are studied: (1) prioritizing compounds for subsequent high-throughput screening (HTS); (2) selecting a predefined (small) number of potentially active compounds from a large chemical database; (3) assessing the probability that a given structure will exhibit a given activity; (4) selecting the most active structure(s) for a biological assay. Each of the four scenarios is exemplified by performing retrospective ligand-based virtual screening for eight different biological targets using two large databases--MDDR and WOMBAT. A comparison between the chemical spaces covered by these two databases is presented. The performance of two techniques for ligand--based virtual screening--similarity search with subsequent data fusion (SSDF) and novelty detection with Self-Organizing Maps (ndSOM) is investigated. Three different structure representations--2,048-dimensional Daylight fingerprints, topological autocorrelation weighted by atomic physicochemical properties (sigma electronegativity, polarizability, partial charge, and identity) and radial distribution functions weighted by the same atomic physicochemical properties--are compared. Both methods were found applicable in scenario one. The similarity search was found to perform slightly better in scenario two while the SOM novelty detection is preferred in scenario three. No method/descriptor combination achieved significant success in scenario four.

An integrative approach to inferring biologically meaningful gene modules

PubMed Central

2011-01-01

Background The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. Results We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. Conclusions The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level. PMID:21791051

News and views in Histochemistry and Cell Biology.

PubMed

Asan, Esther; Drenckhahn, Detlev

2004-12-01

Advances in histochemical methodology and ingenious applications of novel and improved methods continue to confirm the standing of morphological means and approaches in research efforts, and contribute significantly to increasing our knowledge about structures and functions in all areas of the life sciences from cell biology to pathology. Reports published during recent months documenting this progress are summarized in the present review.

Bio-inspired fabrication of stimuli-responsive photonic crystals with hierarchical structures and their applications

NASA Astrophysics Data System (ADS)

Lu, Tao; Peng, Wenhong; Zhu, Shenmin; Zhang, Di

2016-03-01

When the constitutive materials of photonic crystals (PCs) are stimuli-responsive, the resultant PCs exhibit optical properties that can be tuned by the stimuli. This can be exploited for promising applications in colour displays, biological and chemical sensors, inks and paints, and many optically active components. However, the preparation of the required photonic structures is the first issue to be solved. In the past two decades, approaches such as microfabrication and self-assembly have been developed to incorporate stimuli-responsive materials into existing periodic structures for the fabrication of PCs, either as the initial building blocks or as the surrounding matrix. Generally, the materials that respond to thermal, pH, chemical, optical, electrical, or magnetic stimuli are either soft or aggregate, which is why the manufacture of three-dimensional hierarchical photonic structures with responsive properties is a great challenge. Recently, inspired by biological PCs in nature which exhibit both flexible and responsive properties, researchers have developed various methods to synthesize metals and metal oxides with hierarchical structures by using a biological PC as the template. This review will focus on the recent developments in this field. In particular, PCs with biological hierarchical structures that can be tuned by external stimuli have recently been successfully fabricated. These findings offer innovative insights into the design of responsive PCs and should be of great importance for future applications of these materials.

A brief introduction to mixed effects modelling and multi-model inference in ecology

PubMed Central

Donaldson, Lynda; Correa-Cano, Maria Eugenia; Goodwin, Cecily E.D.

2018-01-01

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions. PMID:29844961

A brief introduction to mixed effects modelling and multi-model inference in ecology.

PubMed

Harrison, Xavier A; Donaldson, Lynda; Correa-Cano, Maria Eugenia; Evans, Julian; Fisher, David N; Goodwin, Cecily E D; Robinson, Beth S; Hodgson, David J; Inger, Richard

2018-01-01

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.

Revealing biological information using data structuring and automated learning.

PubMed

Mohorianu, Irina; Moulton, Vincent

2010-11-01

The intermediary steps between a biological hypothesis, concretized in the input data, and meaningful results, validated using biological experiments, commonly employ bioinformatics tools. Starting with storage of the data and ending with a statistical analysis of the significance of the results, every step in a bioinformatics analysis has been intensively studied and the resulting methods and models patented. This review summarizes the bioinformatics patents that have been developed mainly for the study of genes, and points out the universal applicability of bioinformatics methods to other related studies such as RNA interference. More specifically, we overview the steps undertaken in the majority of bioinformatics analyses, highlighting, for each, various approaches that have been developed to reveal details from different perspectives. First we consider data warehousing, the first task that has to be performed efficiently, optimizing the structure of the database, in order to facilitate both the subsequent steps and the retrieval of information. Next, we review data mining, which occupies the central part of most bioinformatics analyses, presenting patents concerning differential expression, unsupervised and supervised learning. Last, we discuss how networks of interactions of genes or other players in the cell may be created, which help draw biological conclusions and have been described in several patents.

Hamiltonian dynamics for complex food webs

NASA Astrophysics Data System (ADS)

Kozlov, Vladimir; Vakulenko, Sergey; Wennergren, Uno

2016-03-01

We investigate stability and dynamics of large ecological networks by introducing classical methods of dynamical system theory from physics, including Hamiltonian and averaging methods. Our analysis exploits the topological structure of the network, namely the existence of strongly connected nodes (hubs) in the networks. We reveal new relations between topology, interaction structure, and network dynamics. We describe mechanisms of catastrophic phenomena leading to sharp changes of dynamics and hence completely altering the ecosystem. We also show how these phenomena depend on the structure of interaction between species. We can conclude that a Hamiltonian structure of biological interactions leads to stability and large biodiversity.

ICON: 3D reconstruction with 'missing-information' restoration in biological electron tomography.

PubMed

Deng, Yuchen; Chen, Yu; Zhang, Yan; Wang, Shengliu; Zhang, Fa; Sun, Fei

2016-07-01

Electron tomography (ET) plays an important role in revealing biological structures, ranging from macromolecular to subcellular scale. Due to limited tilt angles, ET reconstruction always suffers from the 'missing wedge' artifacts, thus severely weakens the further biological interpretation. In this work, we developed an algorithm called Iterative Compressed-sensing Optimized Non-uniform fast Fourier transform reconstruction (ICON) based on the theory of compressed-sensing and the assumption of sparsity of biological specimens. ICON can significantly restore the missing information in comparison with other reconstruction algorithms. More importantly, we used the leave-one-out method to verify the validity of restored information for both simulated and experimental data. The significant improvement in sub-tomogram averaging by ICON indicates its great potential in the future application of high-resolution structural determination of macromolecules in situ. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Report of the Interagency biological methods workshop

USGS Publications Warehouse

Gurtz, Martin E.; Muir, Thomas A.

1994-01-01

The U.S. Geological Survey hosted the Interagency Biological Methods Workshop in Reston, Virginia, during June 22-23, 1993. The purposes of the workshop were to (1) promote better communication among Federal agencies that are using or developing biological methods in water-quality assessment programs for streams and rivers, and (2) facilitate the sharing of data and interagency collaboration. The workshop was attended by 45 biologists representing numerous Federal agencies and programs, and a few regional and State programs that were selected to provide additional perspectives. The focus of the workshop was community assessment methods for fish, invertebrates, and algae; physical habitat characterization; and chemical analyses of biological tissues. Charts comparing program objectives, design features, and sampling methods were compiled from materials that were provided by participating agencies prior to the workshop and formed the basis for small workgroup discussions. Participants noted that differences in methods among programs were often necessitated by differences in program objectives. However, participants agreed that where programs have identified similar data needs, the use of common methods is beneficial. Opportunities discussed for improving data compatibility and information sharing included (1) modifying existing methods, (2) adding parameters, (3) improving access to data through shared databases (potentially with common database structures), and (4) future collaborative efforts that range from research on selected protocol questions to followup meetings and continued discussions.

Preparation and Observation of Thick Biological Samples by Scanning Transmission Electron Tomography.

PubMed

Trépout, Sylvain; Bastin, Philippe; Marco, Sergio

2017-03-12

This report describes a protocol for preparing thick biological specimens for further observation using a scanning transmission electron microscope. It also describes an imaging method for studying the 3D structure of thick biological specimens by scanning transmission electron tomography. The sample preparation protocol is based on conventional methods in which the sample is fixed using chemical agents, treated with a heavy atom salt contrasting agent, dehydrated in a series of ethanol baths, and embedded in resin. The specific imaging conditions for observing thick samples by scanning transmission electron microscopy are then described. Sections of the sample are observed using a through-focus method involving the collection of several images at various focal planes. This enables the recovery of in-focus information at various heights throughout the sample. This particular collection pattern is performed at each tilt angle during tomography data collection. A single image is then generated, merging the in-focus information from all the different focal planes. A classic tilt-series dataset is then generated. The advantage of the method is that the tilt-series alignment and reconstruction can be performed using standard tools. The collection of through-focal images allows the reconstruction of a 3D volume that contains all of the structural details of the sample in focus.

Clustering and visualizing similarity networks of membrane proteins.

PubMed

Hu, Geng-Ming; Mai, Te-Lun; Chen, Chi-Ming

2015-08-01

We proposed a fast and unsupervised clustering method, minimum span clustering (MSC), for analyzing the sequence-structure-function relationship of biological networks, and demonstrated its validity in clustering the sequence/structure similarity networks (SSN) of 682 membrane protein (MP) chains. The MSC clustering of MPs based on their sequence information was found to be consistent with their tertiary structures and functions. For the largest seven clusters predicted by MSC, the consistency in chain function within the same cluster is found to be 100%. From analyzing the edge distribution of SSN for MPs, we found a characteristic threshold distance for the boundary between clusters, over which SSN of MPs could be properly clustered by an unsupervised sparsification of the network distance matrix. The clustering results of MPs from both MSC and the unsupervised sparsification methods are consistent with each other, and have high intracluster similarity and low intercluster similarity in sequence, structure, and function. Our study showed a strong sequence-structure-function relationship of MPs. We discussed evidence of convergent evolution of MPs and suggested applications in finding structural similarities and predicting biological functions of MP chains based on their sequence information. © 2015 Wiley Periodicals, Inc.

Parasites as biological tags to assess host population structure: Guidelines, recent genetic advances and comments on a holistic approach☆

PubMed Central

Catalano, Sarah R.; Whittington, Ian D.; Donnellan, Stephen C.; Gillanders, Bronwyn M.

2013-01-01

We review the use of parasites as biological tags of marine fishes and cephalopods in host population structure studies. The majority of the work published has focused on marine fish and either single parasite species or more recently, whole parasite assemblages, as biological tags. There is representation of host organisms and parasites from a diverse range of taxonomic groups, although focus has primarily been on host species of commercial importance. In contrast, few studies have used parasites as tags to assess cephalopod population structure, even though records of parasites infecting cephalopods are well-documented. Squid species are the only cephalopod hosts for which parasites as biological tags have been applied, with anisakid nematode larvae and metacestodes being the parasite taxa most frequently used. Following a brief insight into the importance of accurate parasite identification, the population studies that have used parasites as biological tags for marine fishes and cephalopods are reviewed, including comments on the dicyemid mesozoans. The advancement of molecular genetic techniques is discussed in regards to the new ways parasite genetic data can be incorporated into population structure studies, alongside host population genetic analyses, followed by an update on the guidelines for selecting a parasite species as a reliable tag candidate. As multiple techniques and methods can be used to assess the population structure of marine organisms (e.g. artificial tags, phenotypic characters, biometrics, life history, genetics, otolith microchemistry and parasitological data), we conclude by commenting on a holistic approach to allow for a deeper insight into population structuring. PMID:25197624

Connecting synthetic chemistry decisions to cell and genome biology using small-molecule phenotypic profiling

PubMed Central

Wagner, Bridget K.; Clemons, Paul A.

2009-01-01

Discovering small-molecule modulators for thousands of gene products requires multiple stages of biological testing, specificity evaluation, and chemical optimization. Many cellular profiling methods, including cellular sensitivity, gene-expression, and cellular imaging, have emerged as methods to assess the functional consequences of biological perturbations. Cellular profiling methods applied to small-molecule science provide opportunities to use complex phenotypic information to prioritize and optimize small-molecule structures simultaneously against multiple biological endpoints. As throughput increases and cost decreases for such technologies, we see an emerging paradigm of using more information earlier in probe- and drug-discovery efforts. Moreover, increasing access to public datasets makes possible the construction of “virtual” profiles of small-molecule performance, even when multiplexed measurements were not performed or when multidimensional profiling was not the original intent. We review some key conceptual advances in small-molecule phenotypic profiling, emphasizing connections to other information, such as protein-binding measurements, genetic perturbations, and cell states. We argue that to maximally leverage these measurements in probe and drug discovery requires a fundamental connection to synthetic chemistry, allowing the consequences of synthetic decisions to be described in terms of changes in small-molecule profiles. Mining such data in the context of chemical structure and synthesis strategies can inform decisions about chemistry procurement and library development, leading to optimal small-molecule screening collections. PMID:19825513

Systematic methods for defining coarse-grained maps in large biomolecules.

PubMed

Zhang, Zhiyong

2015-01-01

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

Computer-Aided Drug Design Methods.

PubMed

Yu, Wenbo; MacKerell, Alexander D

2017-01-01

Computational approaches are useful tools to interpret and guide experiments to expedite the antibiotic drug design process. Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two general types of computer-aided drug design (CADD) approaches in existence. SBDD methods analyze macromolecular target 3-dimensional structural information, typically of proteins or RNA, to identify key sites and interactions that are important for their respective biological functions. Such information can then be utilized to design antibiotic drugs that can compete with essential interactions involving the target and thus interrupt the biological pathways essential for survival of the microorganism(s). LBDD methods focus on known antibiotic ligands for a target to establish a relationship between their physiochemical properties and antibiotic activities, referred to as a structure-activity relationship (SAR), information that can be used for optimization of known drugs or guide the design of new drugs with improved activity. In this chapter, standard CADD protocols for both SBDD and LBDD will be presented with a special focus on methodologies and targets routinely studied in our laboratory for antibiotic drug discoveries.

Asymmetric Methods for the Synthesis of Flavanones, Chromanones, and Azaflavanones

PubMed Central

Nibbs, Antoinette E.

2012-01-01

Flavanones, chromanones, and related structures are privileged natural products that display a wide variety of biological activities. Although flavanoids are abundant in nature, there are a limited number of available general and efficient synthetic methods for accessing molecules of this class in a stereoselective manner. Their structurally simple architectures belie the difficulties involved in installation and maintenance of the stereogenic configuration at the C2 position, which can be sensitive and can undergo epimerization under mildly acidic, basic, and thermal reaction conditions. This review presents the methods currently used to access these related structures. The synthetic methods include manipulation of the flavone/flavanone core, carbon-carbon bond formation, and carbon–heteroatom bond formation. PMID:22876166

Chemical cross-linking and native mass spectrometry: A fruitful combination for structural biology

PubMed Central

Sinz, Andrea; Arlt, Christian; Chorev, Dror; Sharon, Michal

2015-01-01

Mass spectrometry (MS) is becoming increasingly popular in the field of structural biology for analyzing protein three-dimensional-structures and for mapping protein–protein interactions. In this review, the specific contributions of chemical crosslinking and native MS are outlined to reveal the structural features of proteins and protein assemblies. Both strategies are illustrated based on the examples of the tetrameric tumor suppressor protein p53 and multisubunit vinculin-Arp2/3 hybrid complexes. We describe the distinct advantages and limitations of each technique and highlight synergistic effects when both techniques are combined. Integrating both methods is especially useful for characterizing large protein assemblies and for capturing transient interactions. We also point out the future directions we foresee for a combination of in vivo crosslinking and native MS for structural investigation of intact protein assemblies. PMID:25970732

Using NMR chemical shifts to calculate the propensity for structural order and disorder in proteins.

PubMed

Tamiola, Kamil; Mulder, Frans A A

2012-10-01

NMR spectroscopy offers the unique possibility to relate the structural propensities of disordered proteins and loop segments of folded peptides to biological function and aggregation behaviour. Backbone chemical shifts are ideally suited for this task, provided that appropriate reference data are available and idiosyncratic sensitivity of backbone chemical shifts to structural information is treated in a sensible manner. In the present paper, we describe methods to detect structural protein changes from chemical shifts, and present an online tool [ncSPC (neighbour-corrected Structural Propensity Calculator)], which unites aspects of several current approaches. Examples of structural propensity calculations are given for two well-characterized systems, namely the binding of α-synuclein to micelles and light activation of photoactive yellow protein. These examples spotlight the great power of NMR chemical shift analysis for the quantitative assessment of protein disorder at the atomic level, and further our understanding of biologically important problems.

Mix-and-match nanobiosensor design: Logical and spatial programming of biosensors using self-assembled DNA nanostructures.

PubMed

Liu, Ying; Kumar, Sriram; Taylor, Rebecca E

2018-04-06

The evergrowing need to understand and engineer biological and biochemical mechanisms has led to the emergence of the field of nanobiosensing. Structural DNA nanotechnology, encompassing methods such as DNA origami and single-stranded tiles, involves the base pairing-driven knitting of DNA into discrete one-, two-, and three-dimensional shapes at nanoscale. Such nanostructures enable a versatile design and fabrication of nanobiosensors. These systems benefit from DNA's programmability, inherent biocompatibility, and the ability to incorporate and organize functional materials such as proteins and metallic nanoparticles. In this review, we present a mix-and-match taxonomy and approach to designing nanobiosensors in which the choices of bioanalyte and transduction mechanism are fully independent of each other. We also highlight opportunities for greater complexity and programmability of these systems that are built using structural DNA nanotechnology. This article is categorized under: Implantable Materials and Surgical Technologies > Nanomaterials and Implants Diagnostic Tools > Biosensing Biology-Inspired Nanomaterials > Nucleic Acid-Based Structures Nanotechnology Approaches to Biology > Nanoscale Systems in Biology. © 2018 Wiley Periodicals, Inc.

Learning Microbial Community Structures with Supervised and Unsupervised Non-negative Matrix Factorization.

PubMed

Cai, Yun; Gu, Hong; Kenney, Toby

2017-08-31

Learning the structure of microbial communities is critical in understanding the different community structures and functions of microbes in distinct individuals. We view microbial communities as consisting of many subcommunities which are formed by certain groups of microbes functionally dependent on each other. The focus of this paper is on methods for extracting the subcommunities from the data, in particular Non-Negative Matrix Factorization (NMF). Our methods can be applied to both OTU data and functional metagenomic data. We apply the existing unsupervised NMF method and also develop a new supervised NMF method for extracting interpretable information from classification problems. The relevance of the subcommunities identified by NMF is demonstrated by their excellent performance for classification. Through three data examples, we demonstrate how to interpret the features identified by NMF to draw meaningful biological conclusions and discover hitherto unidentified patterns in the data. Comparing whole metagenomes of various mammals, (Muegge et al., Science 332:970-974, 2011), the biosynthesis of macrolides pathway is found in hindgut-fermenting herbivores, but not carnivores. This is consistent with results in veterinary science that macrolides should not be given to non-ruminant herbivores. For time series microbiome data from various body sites (Caporaso et al., Genome Biol 12:50, 2011), a shift in the microbial communities is identified for one individual. The shift occurs at around the same time in the tongue and gut microbiomes, indicating that the shift is a genuine biological trait, rather than an artefact of the method. For whole metagenome data from IBD patients and healthy controls (Qin et al., Nature 464:59-65, 2010), we identify differences in a number of pathways (some known, others new). NMF is a powerful tool for identifying the key features of microbial communities. These identified features can not only be used to perform difficult classification problems with a high degree of accuracy, they are also very interpretable and can lead to important biological insights into the structure of the communities. In addition, NMF is a dimension-reduction method (similar to PCA) in that it reduces the extremely complex microbial data into a low-dimensional representation, allowing a number of analyses to be performed more easily-for example, searching for temporal patterns in the microbiome. When we are interested in the differences between the structures of two groups of communities, supervised NMF provides a better way to do this, while retaining all the advantages of NMF-e.g. interpretability and a simple biological intuition.

Truss Optimization for a Manned Nuclear Electric Space Vehicle using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Benford, Andrew; Tinker, Michael L.

2004-01-01

The purpose of this paper is to utilize the genetic algorithm (GA) optimization method for structural design of a nuclear propulsion vehicle. Genetic algorithms provide a guided, random search technique that mirrors biological adaptation. To verify the GA capabilities, other traditional optimization methods were used to generate results for comparison to the GA results, first for simple two-dimensional structures, and then for full-scale three-dimensional truss designs.

Super-resolution biomolecular crystallography with low-resolution data.

PubMed

Schröder, Gunnar F; Levitt, Michael; Brunger, Axel T

2010-04-22

X-ray diffraction plays a pivotal role in the understanding of biological systems by revealing atomic structures of proteins, nucleic acids and their complexes, with much recent interest in very large assemblies like the ribosome. As crystals of such large assemblies often diffract weakly (resolution worse than 4 A), we need methods that work at such low resolution. In macromolecular assemblies, some of the components may be known at high resolution, whereas others are unknown: current refinement methods fail as they require a high-resolution starting structure for the entire complex. Determining the structure of such complexes, which are often of key biological importance, should be possible in principle as the number of independent diffraction intensities at a resolution better than 5 A generally exceeds the number of degrees of freedom. Here we introduce a method that adds specific information from known homologous structures but allows global and local deformations of these homology models. Our approach uses the observation that local protein structure tends to be conserved as sequence and function evolve. Cross-validation with R(free) (the free R-factor) determines the optimum deformation and influence of the homology model. For test cases at 3.5-5 A resolution with known structures at high resolution, our method gives significant improvements over conventional refinement in the model as monitored by coordinate accuracy, the definition of secondary structure and the quality of electron density maps. For re-refinements of a representative set of 19 low-resolution crystal structures from the Protein Data Bank, we find similar improvements. Thus, a structure derived from low-resolution diffraction data can have quality similar to a high-resolution structure. Our method is applicable to the study of weakly diffracting crystals using X-ray micro-diffraction as well as data from new X-ray light sources. Use of homology information is not restricted to X-ray crystallography and cryo-electron microscopy: as optical imaging advances to subnanometre resolution, it can use similar tools.

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

PubMed

Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

2011-10-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

Mathematical methods for protein science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.; Istrail, S.; Atkins, J.

1997-12-31

Understanding the structure and function of proteins is a fundamental endeavor in molecular biology. Currently, over 100,000 protein sequences have been determined by experimental methods. The three dimensional structure of the protein determines its function, but there are currently less than 4,000 structures known to atomic resolution. Accordingly, techniques to predict protein structure from sequence have an important role in aiding the understanding of the Genome and the effects of mutations in genetic disease. The authors describe current efforts at Sandia to better understand the structure of proteins through rigorous mathematical analyses of simple lattice models. The efforts have focusedmore » on two aspects of protein science: mathematical structure prediction, and inverse protein folding.« less

A sensor network based virtual beam-like structure method for fault diagnosis and monitoring of complex structures with Improved Bacterial Optimization

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-02-01

This paper proposes a novel method for the fault diagnosis of complex structures based on an optimized virtual beam-like structure approach. A complex structure can be regarded as a combination of numerous virtual beam-like structures considering the vibration transmission path from vibration sources to each sensor. The structural 'virtual beam' consists of a sensor chain automatically obtained by an Improved Bacterial Optimization Algorithm (IBOA). The biologically inspired optimization method (i.e. IBOA) is proposed for solving the discrete optimization problem associated with the selection of the optimal virtual beam for fault diagnosis. This novel virtual beam-like-structure approach needs less or little prior knowledge. Neither does it require stationary response data, nor is it confined to a specific structure design. It is easy to implement within a sensor network attached to the monitored structure. The proposed fault diagnosis method has been tested on the detection of loosening screws located at varying positions in a real satellite-like model. Compared with empirical methods, the proposed virtual beam-like structure method has proved to be very effective and more reliable for fault localization.

Tomographic reconstruction of melanin structures of optical coherence tomography via the finite-difference time-domain simulation

NASA Astrophysics Data System (ADS)

Huang, Shi-Hao; Wang, Shiang-Jiu; Tseng, Snow H.

2015-03-01

Optical coherence tomography (OCT) provides high resolution, cross-sectional image of internal microstructure of biological tissue. We use the Finite-Difference Time-Domain method (FDTD) to analyze the data acquired by OCT, which can help us reconstruct the refractive index of the biological tissue. We calculate the refractive index tomography and try to match the simulation with the data acquired by OCT. Specifically, we try to reconstruct the structure of melanin, which has complex refractive indices and is the key component of human pigment system. The results indicate that better reconstruction can be achieved for homogenous sample, whereas the reconstruction is degraded for samples with fine structure or with complex interface. Simulation reconstruction shows structures of the Melanin that may be useful for biomedical optics applications.

Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry: Mechanistic Studies and Methods for Improving the Structural Identification of Carbohydrates

PubMed Central

Lai, Yin-Hung; Wang, Yi-Sheng

2017-01-01

Although matrix-assisted laser desorption/ionization (MALDI) mass spectrometry is one of the most widely used soft ionization methods for biomolecules, the lack of detailed understanding of ionization mechanisms restricts its application in the analysis of carbohydrates. Structural identification of carbohydrates achieved by MALDI mass spectrometry helps us to gain insights into biological functions and pathogenesis of disease. In this review, we highlight mechanistic details of MALDI, including both ionization and desorption. Strategies to improve the ion yield of carbohydrates are also reviewed. Furthermore, commonly used fragmentation methods to identify the structure are discussed. PMID:28959517

Breath Figure Method for Construction of Honeycomb Films

PubMed Central

Dou, Yingying; Jin, Mingliang; Zhou, Guofu; Shui, Lingling

2015-01-01

Honeycomb films with various building units, showing potential applications in biological, medical, physicochemical, photoelectric, and many other areas, could be prepared by the breath figure method. The ordered hexagonal structures formed by the breath figure process are related to the building units, solvents, substrates, temperature, humidity, air flow, and other factors. Therefore, by adjusting these factors, the honeycomb structures could be tuned properly. In this review, we summarized the development of the breath figure method of fabricating honeycomb films and the factors of adjusting honeycomb structures. The organic-inorganic hybrid was taken as the example building unit to discuss the preparation, mechanism, properties, and applications of the honeycomb films. PMID:26343734

Novel nuclear magnetic resonance techniques for studying biological molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Laws, David Douglas

2000-06-01

Over the fifty-five year history of Nuclear Magnetic Resonance (NMR), considerable progress has been made in the development of techniques for studying the structure, function, and dynamics of biological molecules. The majority of this research has involved the development of multi-dimensional NMR experiments for studying molecules in solution, although in recent years a number of groups have begun to explore NMR methods for studying biological systems in the solid-state. Despite this new effort, a need still exists for the development of techniques that improve sensitivity, maximize information, and take advantage of all the NMR interactions available in biological molecules. Inmore » this dissertation, a variety of novel NMR techniques for studying biomolecules are discussed. A method for determining backbone (Φ/Ψ) dihedral angles by comparing experimentally determined 13C a, chemical-shift anisotropies with theoretical calculations is presented, along with a brief description of the theory behind chemical-shift computation in proteins and peptides. The utility of the Spin-Polarization Induced Nuclear Overhauser Effect (SPINOE) to selectively enhance NMR signals in solution is examined in a variety of systems, as are methods for extracting structural information from cross-relaxation rates that can be measured in SPINOE experiments. Techniques for the production of supercritical and liquid laser-polarized xenon are discussed, as well as the prospects for using optically pumped xenon as a polarizing solvent. In addition, a detailed study of the structure of PrP 89-143 is presented. PrP 89-143 is a 54 residue fragment of the prion proteins which, upon mutation and aggregation, can induce prion diseases in transgenic mice. Whereas the structure of the wild-type PrP 89-143 is a generally unstructured mixture of α-helical and β-sheet conformers in the solid state, the aggregates formed from the PrP 89-143 mutants appear to be mostly β-sheet.« less

Preparation and characterization of new biologically active polyurethane foams.

PubMed

Savelyev, Yuri; Veselov, Vitali; Markovskaya, Ludmila; Savelyeva, Olga; Akhranovich, Elena; Galatenko, Natalya; Robota, Ludmila; Travinskaya, Tamara

2014-12-01

Biologically active polyurethane foams are the fast-developed alternative to many applications of biomedical materials. Due to the polyurethane structure features and foam technology it is possible to incorporate into their structure the biologically active compounds of target purpose via structural-chemical modification of macromolecule. A series of new biologically active polyurethane foams (PUFs) was synthesized with polyethers (MM 2500-5000), polyesters MM (500-2200), 2,4(2,6) toluene diisocyanate, water as a foaming agent, catalysts, foam stabilizers and functional compounds. Different functional compounds: 1,4-di-N-oxy-2,3-bis-(oxymethyl)-quinoxaline (DOMQ), partial sodium salt of poly(acrylic acid) and 2,6-dimethyl-N,N-diethyl aminoacetatanilide hydrochloride were incorporated into the polymer structure/composition due to the chemical and/or physical bonding. Structural peculiarities of PUFs were studied by FTIR spectroscopy and X-ray scattering. Self-adhesion properties of PUFs were estimated by measuring of tensile strength at break of adhesive junction. The optical microscopy method was performed for the PUF morphology studies. Toxicological estimation of the PUFs was carried out in vitro and in vivo. The antibacterial action towards the Gram-positive and Gram-negative bacteria (Escherichia coli ATC 25922, E. coli ATC 2150, Klebsiella pneumoniae 6447, Staphylococcus aureus 180, Pseudomonas aeruginosa 8180, Proteus mirabilis F 403, P. mirabilis 6054, and Proteus vulgaris 8718) was studied by the disc method on the solid nutrient. Physic-chemical properties of the PUFs (density, tensile strength and elongation at break, water absorption and vapor permeability) showed that all studied PUFs are within the operational requirements for such materials and represent fine-cellular foams. Spectral studies confirmed the incorporation of DOMQ into the PUF's macrochain. PUFs are characterized by microheterogeneous structure. They are antibacterially active, non-toxic materials with high affinity to the tissue body, self-adhesive properties and local anesthetic effect. Copyright © 2014 Elsevier B.V. All rights reserved.

Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

PubMed

Roche, Daniel Barry; Brackenridge, Danielle Allison; McGuffin, Liam James

2015-12-15

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein-ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein-ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein-ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

A versatile and efficient high-throughput cloning tool for structural biology.

PubMed

Geertsma, Eric R; Dutzler, Raimund

2011-04-19

Methods for the cloning of large numbers of open reading frames into expression vectors are of critical importance for challenging structural biology projects. Here we describe a system termed fragment exchange (FX) cloning that facilitates the high-throughput generation of expression constructs. The method is based on a class IIS restriction enzyme and negative selection markers. FX cloning combines attractive features of established recombination- and ligation-independent cloning methods: It allows the straightforward transfer of an open reading frame into a variety of expression vectors and is highly efficient and very economic in its use. In addition, FX cloning avoids the common but undesirable feature of significantly extending target open reading frames with cloning related sequences, as it leaves a minimal seam of only a single extra amino acid to either side of the protein. The method has proven to be very robust and suitable for all common pro- and eukaryotic expression systems. It considerably speeds up the generation of expression constructs compared to traditional methods and thus facilitates a broader expression screening.

Carbocyclic nucleoside analogues: classification, target enzymes, mechanisms of action and synthesis

NASA Astrophysics Data System (ADS)

Matyugina, E. S.; Khandazhinskaya, A. P.; Kochetkov, Sergei N.

2012-08-01

Key biological targets (S-adenosyl-L-homocysteine hydrolase, telomerase, human immunodeficiency virus reverse transcriptase, herpes virus DNA polymerase and hepatitis B virus DNA polymerase) and the mechanisms of action of carbocyclic nucleoside analogues are considered. Structural types of analogues are discussed. Methods of synthesis for the most promising compounds and the spectrum of their biological activities are described. The bibliography includes 126 references.

3D structure of individual nanocrystals in solution by electron microscopy

NASA Astrophysics Data System (ADS)

Park, Jungwon; Elmlund, Hans; Ercius, Peter; Yuk, Jong Min; Limmer, David T.; Chen, Qian; Kim, Kwanpyo; Han, Sang Hoon; Weitz, David A.; Zettl, A.; Alivisatos, A. Paul

2015-07-01

Knowledge about the synthesis, growth mechanisms, and physical properties of colloidal nanoparticles has been limited by technical impediments. We introduce a method for determining three-dimensional (3D) structures of individual nanoparticles in solution. We combine a graphene liquid cell, high-resolution transmission electron microscopy, a direct electron detector, and an algorithm for single-particle 3D reconstruction originally developed for analysis of biological molecules. This method yielded two 3D structures of individual platinum nanocrystals at near-atomic resolution. Because our method derives the 3D structure from images of individual nanoparticles rotating freely in solution, it enables the analysis of heterogeneous populations of potentially unordered nanoparticles that are synthesized in solution, thereby providing a means to understand the structure and stability of defects at the nanoscale.

Rclick: a web server for comparison of RNA 3D structures.

PubMed

Nguyen, Minh N; Verma, Chandra

2015-03-15

RNA molecules play important roles in key biological processes in the cell and are becoming attractive for developing therapeutic applications. Since the function of RNA depends on its structure and dynamics, comparing and classifying the RNA 3D structures is of crucial importance to molecular biology. In this study, we have developed Rclick, a web server that is capable of superimposing RNA 3D structures by using clique matching and 3D least-squares fitting. Our server Rclick has been benchmarked and compared with other popular servers and methods for RNA structural alignments. In most cases, Rclick alignments were better in terms of structure overlap. Our server also recognizes conformational changes between structures. For this purpose, the server produces complementary alignments to maximize the extent of detectable similarity. Various examples showcase the utility of our web server for comparison of RNA, RNA-protein complexes and RNA-ligand structures. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

New Era of Studying RNA Secondary Structure and Its Influence on Gene Regulation in Plants.

PubMed

Yang, Xiaofei; Yang, Minglei; Deng, Hongjing; Ding, Yiliang

2018-01-01

The dynamic structure of RNA plays a central role in post-transcriptional regulation of gene expression such as RNA maturation, degradation, and translation. With the rise of next-generation sequencing, the study of RNA structure has been transformed from in vitro low-throughput RNA structure probing methods to in vivo high-throughput RNA structure profiling. The development of these methods enables incremental studies on the function of RNA structure to be performed, revealing new insights of novel regulatory mechanisms of RNA structure in plants. Genome-wide scale RNA structure profiling allows us to investigate general RNA structural features over 10s of 1000s of mRNAs and to compare RNA structuromes between plant species. Here, we provide a comprehensive and up-to-date overview of: (i) RNA structure probing methods; (ii) the biological functions of RNA structure; (iii) genome-wide RNA structural features corresponding to their regulatory mechanisms; and (iv) RNA structurome evolution in plants.

Structural Analysis of PTM Hotspots (SAPH-ire) – A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families*

PubMed Central

Dewhurst, Henry M.; Choudhury, Shilpa; Torres, Matthew P.

2015-01-01

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)—a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits—conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit–N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data. PMID:26070665

Receptor Surface Models in the Classroom: Introducing Molecular Modeling to Students in a 3-D World

ERIC Educational Resources Information Center

Geldenhuys, Werner J.; Hayes, Michael; Van der Schyf, Cornelis J.; Allen, David D.; Malan, Sarel F.

2007-01-01

A simple, novel and generally applicable method to demonstrate structure-activity associations of a group of biologically interesting compounds in relation to receptor binding is described. This method is useful for undergraduates and graduate students in medicinal chemistry and computer modeling programs.

METHODS OF EXPLORING METABOLIC STRUCTURE AND TAXONOMIC DIVERSITY RELATIONSHIPS BETWEEN BACTERIOPLANKTON AND PHYTOPLANKTON IN SALT MARSH TIDAL CREEKS

EPA Science Inventory

Bacterial metabolic diversity and phytoplankton community diversity were examined in eight shallow tidal creeks over a two-year period (1997-1998) within North Inlet estuary, South Carolina. The BIOLOG 96-well microplate method was used to assess metabolic diversity of bacteria, ...

Preparation, characterization, and silanization of 3D microporous PDMS structure with properly sized pores for endothelial cell culture.

PubMed

Zargar, Reyhaneh; Nourmohammadi, Jhamak; Amoabediny, Ghassem

2016-01-01

Nowadays, application of porous polydimethylsiloxane (PDMS) structure in biomedical is becoming widespread, and many methods have been established to create such structure. Although the pores created through these methods are mostly developed on the outer surface of PDMS membrane, this study offers a simple and cost-efficient technique for creating three-dimensional (3D) microporous PDMS structure with appropriate pore size for endothelial cell culture. In this study, combination of gas foaming and particulate leaching methods, with NaHCO3 as effervescent salt and NaCl as progen are used to form a 3D PDMS sponge. The in situ chemical reaction between NaHCO3 and HCl resulted in the formation of small pores and channels. Moreover, soaking the samples in HCl solution temporarily improved the hydrophilicity of PDMS, which then facilitated the penetration of water for further leaching of NaCl. The surface chemical modification process was performed by (3-aminopropyl)triethoxysilane to culture endothelial cells on porous PDMS matrix. The results are an indication of positive response of endothelial cells to the fabricated PDMS sponge. Because of simplicity and practicality of this method for preparing PDMS sponge with appropriate pore size and biological properties, the fabricated matrix can perfectly be applied to future studies in blood-contacting devices. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

The Reconstruction and Analysis of Gene Regulatory Networks.

PubMed

Zheng, Guangyong; Huang, Tao

2018-01-01

In post-genomic era, an important task is to explore the function of individual biological molecules (i.e., gene, noncoding RNA, protein, metabolite) and their organization in living cells. For this end, gene regulatory networks (GRNs) are constructed to show relationship between biological molecules, in which the vertices of network denote biological molecules and the edges of network present connection between nodes (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). Biologists can understand not only the function of biological molecules but also the organization of components of living cells through interpreting the GRNs, since a gene regulatory network is a comprehensively physiological map of living cells and reflects influence of genetic and epigenetic factors (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). In this paper, we will review the inference methods of GRN reconstruction and analysis approaches of network structure. As a powerful tool for studying complex diseases and biological processes, the applications of the network method in pathway analysis and disease gene identification will be introduced.

Biological sequence compression algorithms.

PubMed

Matsumoto, T; Sadakane, K; Imai, H

2000-01-01

Today, more and more DNA sequences are becoming available. The information about DNA sequences are stored in molecular biology databases. The size and importance of these databases will be bigger and bigger in the future, therefore this information must be stored or communicated efficiently. Furthermore, sequence compression can be used to define similarities between biological sequences. The standard compression algorithms such as gzip or compress cannot compress DNA sequences, but only expand them in size. On the other hand, CTW (Context Tree Weighting Method) can compress DNA sequences less than two bits per symbol. These algorithms do not use special structures of biological sequences. Two characteristic structures of DNA sequences are known. One is called palindromes or reverse complements and the other structure is approximate repeats. Several specific algorithms for DNA sequences that use these structures can compress them less than two bits per symbol. In this paper, we improve the CTW so that characteristic structures of DNA sequences are available. Before encoding the next symbol, the algorithm searches an approximate repeat and palindrome using hash and dynamic programming. If there is a palindrome or an approximate repeat with enough length then our algorithm represents it with length and distance. By using this preprocessing, a new program achieves a little higher compression ratio than that of existing DNA-oriented compression algorithms. We also describe new compression algorithm for protein sequences.

The method of intraoperative analysis of structural and metabolic changes in the area of tumor resection

NASA Astrophysics Data System (ADS)

Savelieva, Tatiana A.; Loshchenov, Victor B.; Volkov, Vladimir V.; Linkov, Kirill G.; Goryainov, Sergey A.; Potapov, Alexander A.

2014-05-01

The method of intraoperative analysis of tumor markers such as structural changes, concentrations of 5- ALA induced protoporphyrin IX and hemoglobin in the area of tissue resection was developed. A device for performing this method is a neurosurgical aspiration cannulae coupled with the fiber optic probe. The configuration of fibers at the end of cannulae was developed according to the results of numerical modeling of light distribution in biological tissues. The optimal distance between the illuminating and receiving fiber was found for biologically relevant interval of optical properties. On this particular distance the detected diffuse reflectance depends on scattering coefficient almost linearly. Array of optical phantoms containing hemoglobin, protoporphyrin IX and fat emulsion (as scattering media) in various concentrations was prepared to verify the method. The recovery of hemoglobin and protoporphyrin IX concentrations in the scattering media with an error less than 10% has been demonstrated. The fat emulsion concentration estimation accuracy was less than 12%. The first clinical test was carried out during glioblastoma multiforme resection in Burdenko Neurosurgery Institute and confirmed that sensitivity of this method is enough to detect investigated tumor markers in vivo. This method will allow intraoperative analysis of the structural and metabolical tumor markers directly in the zone of destruction of tumor tissue, thereby increasing the degree of radical removal and preservation of healthy tissue.

Characterization of Isomeric Glycans by Reversed Phase Liquid Chromatography-Electronic Excitation Dissociation Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Tang, Yang; Wei, Juan; Costello, Catherine E.; Lin, Cheng

2018-04-01

The occurrence of numerous structural isomers in glycans from biological sources presents a severe challenge for structural glycomics. The subtle differences among isomeric structures demand analytical methods that can provide structural details while working efficiently with on-line glycan separation methods. Although liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a powerful tool for mixture analysis, the commonly utilized collision-induced dissociation (CID) method often does not generate a sufficient number of fragments at the MS2 level for comprehensive structural characterization. Here, we studied the electronic excitation dissociation (EED) behaviors of metal-adducted, permethylated glycans, and identified key spectral features that could facilitate both topology and linkage determinations. We developed an EED-based, nanoscale, reversed phase (RP)LC-MS/MS platform, and demonstrated its ability to achieve complete structural elucidation of up to five structural isomers in a single LC-MS/MS analysis. [Figure not available: see fulltext.

Effects of imputation on correlation: implications for analysis of mass spectrometry data from multiple biological matrices.

PubMed

Taylor, Sandra L; Ruhaak, L Renee; Kelly, Karen; Weiss, Robert H; Kim, Kyoungmi

2017-03-01

With expanded access to, and decreased costs of, mass spectrometry, investigators are collecting and analyzing multiple biological matrices from the same subject such as serum, plasma, tissue and urine to enhance biomarker discoveries, understanding of disease processes and identification of therapeutic targets. Commonly, each biological matrix is analyzed separately, but multivariate methods such as MANOVAs that combine information from multiple biological matrices are potentially more powerful. However, mass spectrometric data typically contain large amounts of missing values, and imputation is often used to create complete data sets for analysis. The effects of imputation on multiple biological matrix analyses have not been studied. We investigated the effects of seven imputation methods (half minimum substitution, mean substitution, k-nearest neighbors, local least squares regression, Bayesian principal components analysis, singular value decomposition and random forest), on the within-subject correlation of compounds between biological matrices and its consequences on MANOVA results. Through analysis of three real omics data sets and simulation studies, we found the amount of missing data and imputation method to substantially change the between-matrix correlation structure. The magnitude of the correlations was generally reduced in imputed data sets, and this effect increased with the amount of missing data. Significant results from MANOVA testing also were substantially affected. In particular, the number of false positives increased with the level of missing data for all imputation methods. No one imputation method was universally the best, but the simple substitution methods (Half Minimum and Mean) consistently performed poorly. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

[The identification investigation of the material evidence of biological origin after multifactorial exposure].

PubMed

Iakovlev, D Iu; Solodun, Iu V; Proskurin, V N

1999-01-01

The possibility of investigating pieces of material evidence of biological origin after exposure to various factors is evaluated. The possibility of detecting proteins of liquid media of human organism by electrophoresis in polyacrylamide denatured gel is investigated. The method is intended for identification of biological material in a state of grave destruction. Methodology of such studies is proposed. The data indicate that the structural integrity and qualitative composition of the spectrum of main serum proteins are retained after combined exposure to damaging factors and complete destruction of blood cells.

Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease.

PubMed

Torres, Matthew P; Dewhurst, Henry; Sundararaman, Niveda

2016-11-01

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable body of potential regulatory elements that impact hundreds of different biological processes important in eukaryotic biology and human health. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

3D bioprinting of structural proteins.

PubMed

Włodarczyk-Biegun, Małgorzata K; Del Campo, Aránzazu

2017-07-01

3D bioprinting is a booming method to obtain scaffolds of different materials with predesigned and customized morphologies and geometries. In this review we focus on the experimental strategies and recent achievements in the bioprinting of major structural proteins (collagen, silk, fibrin), as a particularly interesting technology to reconstruct the biochemical and biophysical composition and hierarchical morphology of natural scaffolds. The flexibility in molecular design offered by structural proteins, combined with the flexibility in mixing, deposition, and mechanical processing inherent to bioprinting technologies, enables the fabrication of highly functional scaffolds and tissue mimics with a degree of complexity and organization which has only just started to be explored. Here we describe the printing parameters and physical (mechanical) properties of bioinks based on structural proteins, including the biological function of the printed scaffolds. We describe applied printing techniques and cross-linking methods, highlighting the modifications implemented to improve scaffold properties. The used cell types, cell viability, and possible construct applications are also reported. We envision that the application of printing technologies to structural proteins will enable unprecedented control over their supramolecular organization, conferring printed scaffolds biological properties and functions close to natural systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

A spectral method to detect community structure based on distance modularity matrix

NASA Astrophysics Data System (ADS)

Yang, Jin-Xuan; Zhang, Xiao-Dong

2017-08-01

There are many community organizations in social and biological networks. How to identify these community structure in complex networks has become a hot issue. In this paper, an algorithm to detect community structure of networks is proposed by using spectra of distance modularity matrix. The proposed algorithm focuses on the distance of vertices within communities, rather than the most weakly connected vertex pairs or number of edges between communities. The experimental results show that our method achieves better effectiveness to identify community structure for a variety of real-world networks and computer generated networks with a little more time-consumption.

Advances in imaging secondary ion mass spectrometry for biological samples

DOE PAGES

Boxer, Steven G.; Kraft, Mary L.; Weber, Peter K.

2008-12-16

Imaging mass spectrometry combines the power of mass spectrometry to identify complex molecules based on mass with sample imaging. Recent advances in secondary ion mass spectrometry have improved sensitivity and spatial resolution, so that these methods have the potential to bridge between high-resolution structures obtained by X-ray crystallography and cyro-electron microscopy and ultrastructure visualized by conventional light microscopy. Following background information on the method and instrumentation, we address the key issue of sample preparation. Because mass spectrometry is performed in high vacuum, it is essential to preserve the lateral organization of the sample while removing bulk water, and this hasmore » been a major barrier for applications to biological systems. Furthermore, recent applications of imaging mass spectrometry to cell biology, microbial communities, and biosynthetic pathways are summarized briefly, and studies of biological membrane organization are described in greater depth.« less

Metabolic cancer biology: structural-based analysis of cancer as a metabolic disease, new sights and opportunities for disease treatment.

PubMed

Masoudi-Nejad, Ali; Asgari, Yazdan

2015-02-01

The cancer cell metabolism or the Warburg effect discovery goes back to 1924 when, for the first time Otto Warburg observed, in contrast to the normal cells, cancer cells have different metabolism. With the initiation of high throughput technologies and computational systems biology, cancer cell metabolism renaissances and many attempts were performed to revise the Warburg effect. The development of experimental and analytical tools which generate high-throughput biological data including lots of information could lead to application of computational models in biological discovery and clinical medicine especially for cancer. Due to the recent availability of tissue-specific reconstructed models, new opportunities in studying metabolic alteration in various kinds of cancers open up. Structural approaches at genome-scale levels seem to be suitable for developing diagnostic and prognostic molecular signatures, as well as in identifying new drug targets. In this review, we have considered these recent advances in structural-based analysis of cancer as a metabolic disease view. Two different structural approaches have been described here: topological and constraint-based methods. The ultimate goal of this type of systems analysis is not only the discovery of novel drug targets but also the development of new systems-based therapy strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Insulated Conducting Cantilevered Nanotips and Two-Chamber Recording System for High Resolution Ion Sensing AFM

PubMed Central

Meckes, Brian; Arce, Fernando Teran; Connelly, Laura S.; Lal, Ratnesh

2014-01-01

Biological membranes contain ion channels, which are nanoscale pores allowing controlled ionic transport and mediating key biological functions underlying normal/abnormal living. Synthetic membranes with defined pores are being developed to control various processes, including filtration of pollutants, charge transport for energy storage, and separation of fluids and molecules. Although ionic transport (currents) can be measured with single channel resolution, imaging their structure and ionic currents simultaneously is difficult. Atomic force microscopy enables high resolution imaging of nanoscale structures and can be modified to measure ionic currents simultaneously. Moreover, the ionic currents can also be used to image structures. A simple method for fabricating conducting AFM cantilevers to image pore structures at high resolution is reported. Tungsten microwires with nanoscale tips are insulated except at the apex. This allows simultaneous imaging via cantilever deflections in normal AFM force feedback mode as well as measuring localized ionic currents. These novel probes measure ionic currents as small as picoampere while providing nanoscale spatial resolution surface topography and is suitable for measuring ionic currents and conductance of biological ion channels. PMID:24663394

Spectroscopic characteristic (FT-IR, FT-Raman, UV, 1H and 13C NMR), theoretical calculations and biological activity of alkali metal homovanillates

NASA Astrophysics Data System (ADS)

Samsonowicz, M.; Kowczyk-Sadowy, M.; Piekut, J.; Regulska, E.; Lewandowski, W.

2016-04-01

The structural and vibrational properties of lithium, sodium, potassium, rubidium and cesium homovanillates were investigated in this paper. Supplementary molecular spectroscopic methods such as: FT-IR, FT-Raman in the solid phase, UV and NMR were applied. The geometrical parameters and energies were obtained from density functional theory (DFT) B3LYP method with 6-311++G** basis set calculations. The geometry of the molecule was fully optimized, vibrational spectra were calculated and fundamental vibrations were assigned. Geometric and magnetic aromaticity indices, atomic charges, dipole moments, HOMO and LUMO energies were also calculated. The microbial activity of investigated compounds was tested against Bacillus subtilis (BS), Pseudomonas aeruginosa (PA), Escherichia coli (EC), Staphylococcus aureus (SA) and Candida albicans (CA). The relationship between the molecular structure of tested compounds and their antimicrobial activity was studied. The principal component analysis (PCA) was applied in order to attempt to distinguish the biological activities of these compounds according to selected band wavenumbers. Obtained data show that the FT-IR spectra can be a rapid and reliable analytical tool and a good source of information for the quantitative analysis of the relationship between the molecular structure of the compound and its biological activity.

Quantitative nanoscale imaging of orientational order in biological filaments by polarized superresolution microscopy

PubMed Central

Valades Cruz, Cesar Augusto; Shaban, Haitham Ahmed; Kress, Alla; Bertaux, Nicolas; Monneret, Serge; Mavrakis, Manos; Savatier, Julien; Brasselet, Sophie

2016-01-01

Essential cellular functions as diverse as genome maintenance and tissue morphogenesis rely on the dynamic organization of filamentous assemblies. For example, the precise structural organization of DNA filaments has profound consequences on all DNA-mediated processes including gene expression, whereas control over the precise spatial arrangement of cytoskeletal protein filaments is key for mechanical force generation driving animal tissue morphogenesis. Polarized fluorescence is currently used to extract structural organization of fluorescently labeled biological filaments by determining the orientation of fluorescent labels, however with a strong drawback: polarized fluorescence imaging is indeed spatially limited by optical diffraction, and is thus unable to discriminate between the intrinsic orientational mobility of the fluorophore labels and the real structural disorder of the labeled biomolecules. Here, we demonstrate that quantitative single-molecule polarized detection in biological filament assemblies allows not only to correct for the rotational flexibility of the label but also to image orientational order of filaments at the nanoscale using superresolution capabilities. The method is based on polarized direct stochastic optical reconstruction microscopy, using dedicated optical scheme and image analysis to determine both molecular localization and orientation with high precision. We apply this method to double-stranded DNA in vitro and microtubules and actin stress fibers in whole cells. PMID:26831082

Coupling Flash LC with MS for enrichment and isolation of milk oligosaccharides for functional studies

PubMed Central

Strum, John S.; Aldredge, Danielle; Barile, Daniela; Lebrilla, Carlito B.

2013-01-01

Mass spectrometry has been coupled with flash liquid chromatography to yield new capabilities for isolating non-chromophoric material from complicated biological mixtures. A flash LC/MS/MS method enabled fraction collection of milk oligosaccharides from biological mixtures based on composition and structure. The method is compatible with traditional gas-pressure driven flow flash chromatography, widely employed in organic chemistry laboratories. The on-line mass detector enabled real-time optimization of chromatographic parameters to favor separation of oligosaccharides that would otherwise be indistinguishable from co-eluting components with a non-specific detector. Unlike previously described preparative LC/MS techniques, we have employed a dynamic flow connection that permits any flow rate from the flash system to be delivered from 1–200 mL/min without affecting the ionization conditions of the mass spectrometer. A new way of packing large amounts of graphitized carbon allowed the enrichment and separation of milligram quantities of structurally heterogeneous mixtures of human milk oligosaccharides (HMOs) and bovine milk oligosaccharides (BMOs). Abundant saccharide components in milk, such as lactose and lacto-N-tetraose, were separated from the rarer and less abundant oligosaccharides that have greater structural diversity and biological functionality. Neutral and acidic HMOs and BMOs were largely separated and enriched with a dual binary solvent system. PMID:22370281

Spectroscopic study of biologically active glasses

NASA Astrophysics Data System (ADS)

Szumera, M.; Wacławska, I.; Mozgawa, W.; Sitarz, M.

2005-06-01

It is known that the chemical activity phenomenon is characteristic for some inorganic glasses and they are able to participate in biological processes of living organisms (plants, animals and human bodies). An example here is the selective removal of silicate-phosphate glass components under the influence of biological solutions, which has been applied in designing glasses acting as ecological fertilizers of controlled release rate of the nutrients for plants. The structure of model silicate-phosphate glasses containing the different amounts of the glass network formers, i.e. Ca 2+ and Mg 2+, as a binding components were studied. These elements besides other are indispensable of the normal growth of plants. In order to establish the function and position occupied by the particular components in the glass structure, the glasses were examined by FTIR spectroscopy (with spectra decomposition) and XRD methods. It has been found that the increasing amount of MgO in the structure of silicate-phosphate glasses causes the formation of domains the structure of which changes systematically from a structure of the cristobalite type to a structure corresponding to forsterite type. Whilst the increasing content of CaO in the structure of silicate-phosphate glasses causes the formation of domains the structure of which changes from a structure typical for cristobalite through one similar to the structure of calcium orthophosphate, to a structure corresponding to calcium silicates. The changing character of domains structure is the reason of different chemical activity of glasses.

The Dynamics of DNA Sequencing.

ERIC Educational Resources Information Center

Morvillo, Nancy

1997-01-01

Describes a paper-and-pencil activity that helps students understand DNA sequencing and expands student understanding of DNA structure, replication, and gel electrophoresis. Appropriate for advanced biology students who are familiar with the Sanger method. (DDR)

Advances in three-dimensional rapid prototyping of microfluidic devices for biological applications

PubMed Central

O'Neill, P. F.; Ben Azouz, A.; Vázquez, M.; Liu, J.; Marczak, S.; Slouka, Z.; Chang, H. C.; Diamond, D.; Brabazon, D.

2014-01-01

The capability of 3D printing technologies for direct production of complex 3D structures in a single step has recently attracted an ever increasing interest within the field of microfluidics. Recently, ultrafast lasers have also allowed developing new methods for production of internal microfluidic channels within the bulk of glass and polymer materials by direct internal 3D laser writing. This review critically summarizes the latest advances in the production of microfluidic 3D structures by using 3D printing technologies and direct internal 3D laser writing fabrication methods. Current applications of these rapid prototyped microfluidic platforms in biology will be also discussed. These include imaging of cells and living organisms, electrochemical detection of viruses and neurotransmitters, and studies in drug transport and induced-release of adenosine triphosphate from erythrocytes. PMID:25538804

The radiation biology of the thyroid.

PubMed

Malone, J F

1975-10-01

The structure and function of the thyroid gland are described. A detailed analysis of population kinetics in the gland suggests a method of measuring cell survival after irradiation that has many features in common with methods used in other mammalian cell systems. This method is used to obtain survival curves for thyroid cells afer irradiation. The effects on survival of splitting the radiation dose into two or multiple fractions, radiation type, and radioprotective agents are also examined. In the light of these data the tolerance of thyroid tissue to radiation exposure under various conditions is discussed. The dosimetry and biological effects of 125I and 131I are described in detail, and compared with X-rays. Radioiodine treatment of thyrotoxicosis is presented in relation to the known biological effects of the isotopes on the gland. Carcinogenic action of ionizing radiations in the thyroid are reviewed with particular reference to the clinical consequences of observations in this field.

Biologically Plausible, Human-Scale Knowledge Representation.

PubMed

Crawford, Eric; Gingerich, Matthew; Eliasmith, Chris

2016-05-01

Several approaches to implementing symbol-like representations in neurally plausible models have been proposed. These approaches include binding through synchrony (Shastri & Ajjanagadde, ), "mesh" binding (van der Velde & de Kamps, ), and conjunctive binding (Smolensky, ). Recent theoretical work has suggested that most of these methods will not scale well, that is, that they cannot encode structured representations using any of the tens of thousands of terms in the adult lexicon without making implausible resource assumptions. Here, we empirically demonstrate that the biologically plausible structured representations employed in the Semantic Pointer Architecture (SPA) approach to modeling cognition (Eliasmith, ) do scale appropriately. Specifically, we construct a spiking neural network of about 2.5 million neurons that employs semantic pointers to successfully encode and decode the main lexical relations in WordNet, which has over 100,000 terms. In addition, we show that the same representations can be employed to construct recursively structured sentences consisting of arbitrary WordNet concepts, while preserving the original lexical structure. We argue that these results suggest that semantic pointers are uniquely well-suited to providing a biologically plausible account of the structured representations that underwrite human cognition. Copyright © 2015 Cognitive Science Society, Inc.

Reductive chemical release of N-glycans as 1-amino-alditols and subsequent 9-fluorenylmethyloxycarbonyl labeling for MS and LC/MS analysis.

PubMed

Wang, Chengjian; Qiang, Shan; Jin, Wanjun; Song, Xuezheng; Zhang, Ying; Huang, Linjuan; Wang, Zhongfu

2018-06-06

Glycoproteins play pivotal roles in a series of biological processes and their glycosylation patterns need to be structurally and functionally characterized. However, the lack of versatile methods to release N-glycans as functionalized forms has been undermining glycomics studies. Here a novel method is developed for dissociation of N-linked glycans from glycoproteins for analysis by MS and online LC/MS. This new method employs aqueous ammonia solution containing NaBH 3 CN as the reaction medium to release glycans from glycoproteins as 1-amino-alditol forms. The released glycans are conveniently labeled with 9-fluorenylmethyloxycarbonyl (Fmoc) and analyzed by ESI-MS and online LC/MS. Using the method, the neutral and acidic N-glycans were successfully released without peeling degradation of the core α-1,3-fucosylated structure or detectable de-N-acetylation, revealing its general applicability to various types of N-glycans. The Fmoc-derivatized N-glycans derived from chicken ovalbumin, Fagopyrum esculentum Moench Pollen and FBS were successfully analyzed by online LC/MS to distinguish isomers. The 1-amino-alditols were also permethylated to form quaternary ammonium cations at the reducing end, which enhance the MS sensitivity and are compatible with sequential multi-stage mass spectrometry (MS n ) fragmentation for glycan sequencing. The Fmoc-labeled N-glycans were further permethylated to produce methylated carbamates for determination of branches and linkages by sequential MS n fragmentation. N-Glycosylation represents one of the most common post-translational modification forms and plays pivotal roles in the structural and functional regulation of proteins in various biological activities, relating closely to human health and diseases. As a type of informational molecule, the N-glycans of glycoproteins participate directly in the molecular interactions between glycan epitopes and their corresponding protein receptors. Detailed structural and functional characterization of different types of N-glycans is essential for understanding the functional mechanisms of many biological activities and the pathologies of many diseases. Here we describe a simple, versatile method to indistinguishably release all types of N-glycans as functionalized forms without remarkable side reactions, enabling convenient, rapid analysis and preparation of released N-glycans from various complex biological samples. It is very valuable for studies on the complicated structure-function relationship of N-glycans, as well as for the search of N-glycan biomarkers of some major diseases and N-glycan related targets of some drugs. Copyright © 2018. Published by Elsevier B.V.

From molecular chaperones to membrane motors: through the lens of a mass spectrometrist.

PubMed

Robinson, Carol V

2017-02-08

Twenty-five years ago, we obtained our first mass spectra of molecular chaperones in complex with protein ligands and entered a new field of gas-phase structural biology. It is perhaps now time to pause and reflect, and to ask how many of our initial structure predictions and models derived from mass spectrometry (MS) datasets were correct. With recent advances in structure determination, many of the most challenging complexes that we studied over the years have become tractable by other structural biology approaches enabling such comparisons to be made. Moreover, in the light of powerful new electron microscopy methods, what role is there now for MS? In considering these questions, I will give my personal view on progress and problems as well as my predictions for future directions. © 2017 The Author(s).

Adaptive optical fluorescence microscopy.

PubMed

Ji, Na

2017-03-31

The past quarter century has witnessed rapid developments of fluorescence microscopy techniques that enable structural and functional imaging of biological specimens at unprecedented depth and resolution. The performance of these methods in multicellular organisms, however, is degraded by sample-induced optical aberrations. Here I review recent work on incorporating adaptive optics, a technology originally applied in astronomical telescopes to combat atmospheric aberrations, to improve image quality of fluorescence microscopy for biological imaging.

Investigating biological activity spectrum for novel quinoline analogues 2: hydroxyquinolinecarboxamides with photosynthesis-inhibiting activity.

PubMed

Musiol, Robert; Tabak, Dominik; Niedbala, Halina; Podeszwa, Barbara; Jampilek, Josef; Kralova, Katarina; Dohnal, Jiri; Finster, Jacek; Mencel, Agnieszka; Polanski, Jaroslaw

2008-04-15

Two series of amides based on quinoline scaffold were designed and synthesized in search of photosynthesis inhibitors. The compounds were tested for their photosynthesis-inhibiting activity against Spinacia oleracea L. and Chlorella vulgaris Beij. The compounds lipophilicity was determined by the RP-HPLC method. Several compounds showed biological activity similar or even higher than that of the standard (DCMU). The structure-activity relationships are discussed.

Design and integration of a problem-based biofabrication course into an undergraduate biomedical engineering curriculum.

PubMed

Raman, Ritu; Mitchell, Marlon; Perez-Pinera, Pablo; Bashir, Rashid; DeStefano, Lizanne

2016-01-01

The rapidly evolving discipline of biological and biomedical engineering requires adaptive instructional approaches that teach students to target and solve multi-pronged and ill-structured problems at the cutting edge of scientific research. Here we present a modular approach to designing a lab-based course in the emerging field of biofabrication and biological design, leading to a final capstone design project that requires students to formulate and test a hypothesis using the scientific method. Students were assessed on a range of metrics designed to evaluate the format of the course, the efficacy of the format for teaching new topics and concepts, and the depth of the contribution this course made to students training for biological engineering careers. The evaluation showed that the problem-based format of the course was well suited to teaching students how to use the scientific method to investigate and uncover the fundamental biological design rules that govern the field of biofabrication. We show that this approach is an efficient and effective method of translating emergent scientific principles from the lab bench to the classroom and training the next generation of biological and biomedical engineers for careers as researchers and industry practicians.

Scanning superlens microscopy for non-invasive large field-of-view visible light nanoscale imaging

NASA Astrophysics Data System (ADS)

Wang, Feifei; Liu, Lianqing; Yu, Haibo; Wen, Yangdong; Yu, Peng; Liu, Zhu; Wang, Yuechao; Li, Wen Jung

2016-12-01

Nanoscale correlation of structural information acquisition with specific-molecule identification provides new insight for studying rare subcellular events. To achieve this correlation, scanning electron microscopy has been combined with super-resolution fluorescent microscopy, despite its destructivity when acquiring biological structure information. Here we propose time-efficient non-invasive microsphere-based scanning superlens microscopy that enables the large-area observation of live-cell morphology or sub-membrane structures with sub-diffraction-limited resolution and is demonstrated by observing biological and non-biological objects. This microscopy operates in both non-invasive and contact modes with ~200 times the acquisition efficiency of atomic force microscopy, which is achieved by replacing the point of an atomic force microscope tip with an imaging area of microspheres and stitching the areas recorded during scanning, enabling sub-diffraction-limited resolution. Our method marks a possible path to non-invasive cell imaging and simultaneous tracking of specific molecules with nanoscale resolution, facilitating the study of subcellular events over a total cell period.

New strategy for protein interactions and application to structure-based drug design

NASA Astrophysics Data System (ADS)

Zou, Xiaoqin

One of the greatest challenges in computational biophysics is to predict interactions between biological molecules, which play critical roles in biological processes and rational design of therapeutic drugs. Biomolecular interactions involve delicate interplay between multiple interactions, including electrostatic interactions, van der Waals interactions, solvent effect, and conformational entropic effect. Accurate determination of these complex and subtle interactions is challenging. Moreover, a biological molecule such as a protein usually consists of thousands of atoms, and thus occupies a huge conformational space. The large degrees of freedom pose further challenges for accurate prediction of biomolecular interactions. Here, I will present our development of physics-based theory and computational modeling on protein interactions with other molecules. The major strategy is to extract microscopic energetics from the information embedded in the experimentally-determined structures of protein complexes. I will also present applications of the methods to structure-based therapeutic design. Supported by NSF CAREER Award DBI-0953839, NIH R01GM109980, and the American Heart Association (Midwest Affiliate) [13GRNT16990076].

Effects of Humic Acids Isolated from Peat of Various Origin on in Vitro Production of Nitric Oxide: a Screening Study.

PubMed

Trofimova, E S; Zykova, M V; Ligacheva, A A; Sherstoboev, E Yu; Zhdanov, V V; Belousov, M V; Yusubov, M S; Krivoshchekov, S V; Danilets, M G; Dygai, A M

2016-09-01

A screening study of biological activity of native humic acids isolated from peat was performed; several physical and chemical parameters of their structures were studied by UV- and infrared spectroscopy. Spectroscopy yielded similar shape of light absorption curves of humic acids of different origin, which can reflect similarity of general structural principles of these substances. Alkaline humic acids have more developed system of polyconjugation, while molecular structures of pyrophosphate humic acids were characterized by higher aromaticity and condensation indexes. Biological activity of the studied humic acids was assessed by NO-stimulating capacity during their culturing with murine peritoneal macrophages in a wide concentration range. It was shown that due to dose-dependent enhancement of NO production humic acids can change the functional state of macrophages towards development of pro-inflammatory properties. These changes were associated with high activity of humic acids isolated by pyrophosphate extraction, which allows considering effects of isolation method on biological activity.

Research into acetone removal from air by biofiltration using a biofilter with straight structure plates

PubMed Central

Baltrėnas, Pranas; Zagorskis, Alvydas; Misevičius, Antonas

2015-01-01

The biological air treatment method is based on the biological destruction of organic compounds using certain cultures of microorganisms. This method is simple and may be applied in many branches of industry. The main element of biological air treatment devices is a filter charge. Tests were carried out using a new-generation laboratory air purifier with a plate structure. This purifier is called biofilter. The biofilter has a special system for packing material humidification which does not require additional energy inputs. In order to extend the packing material's durability, it was composed of thermally treated birch fibre. Pollutant (acetone) biodegradation occurred on thermally treated wood fibre in this research. According to the performed tests and the received results, the process of biodestruction was highly efficient. When acetone was passed through biofilter's packing material at 0.08 m s−1 rate, the efficiency of the biofiltration process was from 70% up to 90%. The species of bacteria capable of removing acetone vapour from the air, i.e. Bacillus (B. cereus, B. subtilis), Pseudomonas (P. aeruginosa, P. putida), Stapylococcus (S. aureus) and Rhodococcus sp., was identified in this study during the process of biofiltration. Their amount in the biological packing material changed from 1.6 × 107 to 3.7 × 1011 CFU g−1. PMID:26019659

Research into acetone removal from air by biofiltration using a biofilter with straight structure plates.

PubMed

Baltrėnas, Pranas; Zagorskis, Alvydas; Misevičius, Antonas

2015-03-04

The biological air treatment method is based on the biological destruction of organic compounds using certain cultures of microorganisms. This method is simple and may be applied in many branches of industry. The main element of biological air treatment devices is a filter charge. Tests were carried out using a new-generation laboratory air purifier with a plate structure. This purifier is called biofilter. The biofilter has a special system for packing material humidification which does not require additional energy inputs. In order to extend the packing material's durability, it was composed of thermally treated birch fibre. Pollutant (acetone) biodegradation occurred on thermally treated wood fibre in this research. According to the performed tests and the received results, the process of biodestruction was highly efficient. When acetone was passed through biofilter's packing material at 0.08 m s -1 rate, the efficiency of the biofiltration process was from 70% up to 90%. The species of bacteria capable of removing acetone vapour from the air, i.e. Bacillus ( B. cereus , B. subtilis ), Pseudomonas ( P. aeruginosa , P. putida ), Stapylococcus ( S. aureus ) and Rhodococcus sp., was identified in this study during the process of biofiltration. Their amount in the biological packing material changed from 1.6 × 10 7 to 3.7 × 10 11 CFU g -1 .

Discriminative graph embedding for label propagation.

PubMed

Nguyen, Canh Hao; Mamitsuka, Hiroshi

2011-09-01

In many applications, the available information is encoded in graph structures. This is a common problem in biological networks, social networks, web communities and document citations. We investigate the problem of classifying nodes' labels on a similarity graph given only a graph structure on the nodes. Conventional machine learning methods usually require data to reside in some Euclidean spaces or to have a kernel representation. Applying these methods to nodes on graphs would require embedding the graphs into these spaces. By embedding and then learning the nodes on graphs, most methods are either flexible with different learning objectives or efficient enough for large scale applications. We propose a method to embed a graph into a feature space for a discriminative purpose. Our idea is to include label information into the embedding process, making the space representation tailored to the task. We design embedding objective functions that the following learning formulations become spectral transforms. We then reformulate these spectral transforms into multiple kernel learning problems. Our method, while being tailored to the discriminative tasks, is efficient and can scale to massive data sets. We show the need of discriminative embedding on some simulations. Applying to biological network problems, our method is shown to outperform baselines.

Insights into biogenic and chemical production of inorganic nanomaterials and nanostructures.

PubMed

Faramarzi, Mohammad Ali; Sadighi, Armin

2013-03-01

The synthesis of inorganic nanomaterials and nanostructures by the means of diverse physical, chemical, and biological principles has been developed in recent decades. The nanoscale materials and structures creation continue to be an active area of researches due to the exciting properties of the resulting nanomaterials and their innovative applications. Despite physical and chemical approaches which have been used for a long time to produce nanomaterials, biological resources as green candidates that can replace old production methods have been focused in recent years to generate various inorganic nanoparticles (NPs) or other nanoscale structures. Cost-effective, eco-friendly, energy efficient, and nontoxic produced nanomaterials using diverse biological entities have been received increasing attention in the last two decades in contrast to physical and chemical methods owe using toxic solvents, generate unwanted by-products, and high energy consumption which restrict the popularity of these ways employed in nanometric science and engineering. In this review, the biosynthesis of gold, silver, gold-silver alloy, magnetic, semiconductor nanocrystals, silica, zirconia, titania, palladium, bismuth, selenium, antimony sulfide, and platinum NPs, using bacteria, actinomycetes, fungi, yeasts, plant extracts and also informational bio-macromolecules including proteins, polypeptides, DNA, and RNA have been reported extensively to mention the current status of the biological inorganic nanomaterial production. In other hand, two well-known wet chemical techniques, namely chemical reduction and sol-gel methods, used to produce various types of nanocrystalline powders, metal oxides, and hybrid organic-inorganic nanomaterials have presented. Copyright © 2012 Elsevier B.V. All rights reserved.

Modularization of biochemical networks based on classification of Petri net t-invariants

PubMed Central

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-01-01

Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. Results We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. Conclusion We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis. PMID:18257938

Membrane materials for storing biological samples intended for comparative nanotoxicological testing

NASA Astrophysics Data System (ADS)

Metelkin, A.; Kuznetsov, D.; Kolesnikov, E.; Chuprunov, K.; Kondakov, S.; Osipov, A.; Samsonova, J.

2015-11-01

The study is aimed at identifying the samples of most promising membrane materials for storing dry specimens of biological fluids (Dried Blood Spots, DBS technology). Existing sampling systems using cellulose fiber filter paper have a number of drawbacks such as uneven distribution of the sample spot, dependence of the spot spreading area on the individual biosample properties, incomplete washing-off of the sample due to partially inconvertible sorption of blood components on cellulose fibers, etc. Samples of membrane materials based on cellulose, polymers and glass fiber with applied biosamples were studied using methods of scanning electron microscopy, FT-IR spectroscopy and surface-wetting measurement. It was discovered that cellulose-based membrane materials sorb components of biological fluids inside their structure, while membranes based on glass fiber display almost no interaction with the samples and biological fluid components dry to films in the membrane pores between the structural fibers. This characteristic, together with the fact that membrane materials based on glass fiber possess sufficient strength, high wetting properties and good storage capacity, attests them as promising material for dry samples of biological fluids storage systems.

Biomolecular Deuteration for Neutron Structural Biology and Dynamics.

PubMed

Haertlein, Michael; Moulin, Martine; Devos, Juliette M; Laux, Valerie; Dunne, Orla; Forsyth, V Trevor

2016-01-01

Neutron scattering studies provide important information in structural biology that is not accessible using other approaches. The uniqueness of the technique, and its complementarity with X-ray scattering, is greatest when full use is made of deuterium labeling. The ability to produce tailor-made deuterium-labeled biological macromolecules allows neutron studies involving solution scattering, crystallography, reflection, and dynamics to be optimized in a manner that has major impact on the scope, quality, and throughput of work in these areas. Deuteration facilities have now been developed at many neutron centres throughout the world; these are having a crucial effect on neutron studies in the life sciences and on biologically related studies in soft matter. This chapter describes methods that have been developed for the efficient production of deuterium-labeled samples for a wide range of neutron scattering applications. Examples are given that illustrate the use of these samples for each of the main techniques. Perspectives for biological deuterium labeling are discussed in relation to developments at current facilities and those that are planned in the future. © 2016 Elsevier Inc. All rights reserved.

Structure-based Markov random field model for representing evolutionary constraints on functional sites.

PubMed

Jeong, Chan-Seok; Kim, Dongsup

2016-02-24

Elucidating the cooperative mechanism of interconnected residues is an important component toward understanding the biological function of a protein. Coevolution analysis has been developed to model the coevolutionary information reflecting structural and functional constraints. Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by focusing on the aspect of protein structure. In this study, we built an MRF model whose graphical topology is determined by the residue proximity in the protein structure, and derived a novel positional coevolution estimate utilizing the node weight of the MRF model. This structure-based MRF method was evaluated for three data sets, each of which annotates catalytic site, allosteric site, and comprehensively determined functional site information. We demonstrate that the structure-based MRF architecture can encode the evolutionary information associated with biological function. Furthermore, we show that the node weight can more accurately represent positional coevolution information compared to the edge weight. Lastly, we demonstrate that the structure-based MRF model can be reliably built with only a few aligned sequences in linear time. The results show that adoption of a structure-based architecture could be an acceptable approximation for coevolution modeling with efficient computation complexity.

From protein structure to function via single crystal optical spectroscopy

PubMed Central

Ronda, Luca; Bruno, Stefano; Bettati, Stefano; Storici, Paola; Mozzarelli, Andrea

2015-01-01

The more than 100,000 protein structures determined by X-ray crystallography provide a wealth of information for the characterization of biological processes at the molecular level. However, several crystallographic “artifacts,” including conformational selection, crystallization conditions and radiation damages, may affect the quality and the interpretation of the electron density maps, thus limiting the relevance of structure determinations. Moreover, for most of these structures, no functional data have been obtained in the crystalline state, thus posing serious questions on their validity in infereing protein mechanisms. In order to solve these issues, spectroscopic methods have been applied for the determination of equilibrium and kinetic properties of proteins in the crystalline state. These methods are UV-vis spectrophotometry, spectrofluorimetry, IR, EPR, Raman, and resonance Raman spectroscopy. Some of these approaches have been implemented with on-line instruments at X-ray synchrotron beamlines. Here, we provide an overview of investigations predominantly carried out in our laboratory by single crystal polarized absorption UV-vis microspectrophotometry, the most applied technique for the functional characterization of proteins in the crystalline state. Studies on hemoglobins, pyridoxal 5′-phosphate dependent enzymes and green fluorescent protein in the crystalline state have addressed key biological issues, leading to either straightforward structure-function correlations or limitations to structure-based mechanisms. PMID:25988179

Current strategies for protein production and purification enabling membrane protein structural biology.

PubMed

Pandey, Aditya; Shin, Kyungsoo; Patterson, Robin E; Liu, Xiang-Qin; Rainey, Jan K

2016-12-01

Membrane proteins are still heavily under-represented in the protein data bank (PDB), owing to multiple bottlenecks. The typical low abundance of membrane proteins in their natural hosts makes it necessary to overexpress these proteins either in heterologous systems or through in vitro translation/cell-free expression. Heterologous expression of proteins, in turn, leads to multiple obstacles, owing to the unpredictability of compatibility of the target protein for expression in a given host. The highly hydrophobic and (or) amphipathic nature of membrane proteins also leads to challenges in producing a homogeneous, stable, and pure sample for structural studies. Circumventing these hurdles has become possible through the introduction of novel protein production protocols; efficient protein isolation and sample preparation methods; and, improvement in hardware and software for structural characterization. Combined, these advances have made the past 10-15 years very exciting and eventful for the field of membrane protein structural biology, with an exponential growth in the number of solved membrane protein structures. In this review, we focus on both the advances and diversity of protein production and purification methods that have allowed this growth in structural knowledge of membrane proteins through X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryo-electron microscopy (cryo-EM).

Current strategies for protein production and purification enabling membrane protein structural biology

PubMed Central

Pandey, Aditya; Shin, Kyungsoo; Patterson, Robin E.; Liu, Xiang-Qin; Rainey, Jan K.

2017-01-01

Membrane proteins are still heavily underrepresented in the protein data bank (PDB) due to multiple bottlenecks. The typical low abundance of membrane proteins in their natural hosts makes it necessary to overexpress these proteins either in heterologous systems or through in vitro translation/cell-free expression. Heterologous expression of proteins, in turn, leads to multiple obstacles due to the unpredictability of compatibility of the target protein for expression in a given host. The highly hydrophobic and/or amphipathic nature of membrane proteins also leads to challenges in producing a homogeneous, stable, and pure sample for structural studies. Circumventing these hurdles has become possible through introduction of novel protein production protocols; efficient protein isolation and sample preparation methods; and, improvement in hardware and software for structural characterization. Combined, these advances have made the past 10–15 years very exciting and eventful for the field of membrane protein structural biology, with an exponential growth in the number of solved membrane protein structures. In this review, we focus on both the advances and diversity of protein production and purification methods that have allowed this growth in structural knowledge of membrane proteins through X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryo-electron microscopy (cryo-EM). PMID:27010607

Thin film composition with biological substance and method of making

DOEpatents

Campbell, Allison A.; Song, Lin

1999-01-01

The invention provides a thin-film composition comprising an underlying substrate of a first material including a plurality of attachment sites; a plurality of functional groups chemically attached to the attachment sites of the underlying substrate; and a thin film of a second material deposited onto the attachment sites of the underlying substrate, and a biologically active substance deposited with the thin-film. Preferably the functional groups are attached to a self assembling monolayer attached to the underlying substrate. Preferred functional groups attached to the underlying substrate are chosen from the group consisting of carboxylates, sulfonates, phosphates, optionally substituted, linear or cyclo, alkyl, alkene, alkyne, aryl, alkylaryl, amine, hydroxyl, thiol, silyl, phosphoryl, cyano, metallocenyl, carbonyl, and polyphosphate. Preferred materials for the underlying substrate are selected from the group consisting of a metal, a metal alloy, a plastic, a polymer, a proteic film, a membrane, a glass or a ceramic. The second material is selected from the group consisting of inorganic crystalline structures, inorganic amorphus structures, organic crystalline structures, and organic amorphus structures. Preferred second materials are phosphates, especially calcium phosphates and most particularly calcium apatite. The biologically active molecule is a protein, peptide, DNA segment, RNA segment, nucleotide, polynucleotide, nucleoside, antibiotic, antimicrobal, radioisotope, chelated radioisotope, chelated metal, metal salt, anti-inflamatory, steriod, nonsteriod anti-inflammatory, analgesic, antihistamine, receptor binding agent, or chemotherapeutic agent, or other biologically active material. Preferably the biologically active molecule is an osteogenic factor the compositions listed above.

Beyond bilateral symmetry: geometric morphometric methods for any type of symmetry

PubMed Central

2011-01-01

Background Studies of symmetric structures have made important contributions to evolutionary biology, for example, by using fluctuating asymmetry as a measure of developmental instability or for investigating the mechanisms of morphological integration. Most analyses of symmetry and asymmetry have focused on organisms or parts with bilateral symmetry. This is not the only type of symmetry in biological shapes, however, because a multitude of other types of symmetry exists in plants and animals. For instance, some organisms have two axes of reflection symmetry (biradial symmetry; e.g. many algae, corals and flowers) or rotational symmetry (e.g. sea urchins and many flowers). So far, there is no general method for the shape analysis of these types of symmetry. Results We generalize the morphometric methods currently used for the shape analysis of bilaterally symmetric objects so that they can be used for analyzing any type of symmetry. Our framework uses a mathematical definition of symmetry based on the theory of symmetry groups. This approach can be used to divide shape variation into a component of symmetric variation among individuals and one or more components of asymmetry. We illustrate this approach with data from a colonial coral that has ambiguous symmetry and thus can be analyzed in multiple ways. Our results demonstrate that asymmetric variation predominates in this dataset and that its amount depends on the type of symmetry considered in the analysis. Conclusions The framework for analyzing symmetry and asymmetry is suitable for studying structures with any type of symmetry in two or three dimensions. Studies of complex symmetries are promising for many contexts in evolutionary biology, such as fluctuating asymmetry, because these structures can potentially provide more information than structures with bilateral symmetry. PMID:21958045

Computational Design of Self-Assembling Cyclic Protein Homo-oligomers

PubMed Central

Fallas, Jorge A.; Ueda, George; Sheffler, William; Nguyen, Vanessa; McNamara, Dan E.; Sankaran, Banumathi; Pereira, Jose Henrique; Parmeggiani, Fabio; Brunette, TJ; Cascio, Duilio; Yeates, Todd R.; Zwart, Peter; Baker, David

2016-01-01

Self-assembling cyclic protein homo-oligomers play important roles in biology and the ability to generate custom homo-oligomeric structures could enable new approaches to probe biological function. Here we report a general approach to design cyclic homo-oligomers that employs a new residue pair transform method for assessing the design ability of a protein-protein interface. This method is sufficiently rapid to enable systematic enumeration of cyclically docked arrangements of a monomer followed by sequence design of the newly formed interfaces. We use this method to design interfaces onto idealized repeat proteins that direct their assembly into complexes that possess cyclic symmetry. Of 96 designs that were experimentally characterized, 21 were found to form stable monodisperse homo-oligomers in solution, and 15 (4 homodimers, 6 homotrimers, 6 homotetramers and 1 homopentamer) had solution small angle X-ray scattering data consistent with the design models. X-ray crystal structures were obtained for five of the designs and each of these were shown to be very close to their design model. PMID:28338692

Strategies for Directing the Structure and Function of 3D Collagen Biomaterials across Length Scales

PubMed Central

Walters, Brandan D.; Stegemann, Jan P.

2013-01-01

Collagen type I is a widely used natural biomaterial that has found utility in a variety of biological and medical applications. Its well characterized structure and role as an extracellular matrix protein make it a highly relevant material for controlling cell function and mimicking tissue properties. Collagen type I is abundant in a number of tissues, and can be isolated as a purified protein. This review focuses on hydrogel biomaterials made by reconstituting collagen type I from a solubilized form, with an emphasis on in vitro studies in which collagen structure can be controlled. The hierarchical structure of collagen from the nanoscale to the macroscale is described, with an emphasis on how structure is related to function across scales. Methods of reconstituting collagen into hydrogel materials are presented, including molding of macroscopic constructs, creation of microscale modules, and electrospinning of nanoscale fibers. The modification of collagen biomaterials to achieve desired structures and functions is also addressed, with particular emphasis on mechanical control of collagen structure, creation of collagen composite materials, and crosslinking of collagenous matrices. Biomaterials scientists have made remarkable progress in rationally designing collagen-based biomaterials and in applying them to both the study of biology and for therapeutic benefit. This broad review illustrates recent examples of techniques used to control collagen structure, and to thereby direct its biological and mechanical functions. PMID:24012608

Students' Personal Connection with Science: Investigating the Multidimensional Phenomenological Structure of Self-Relevance

ERIC Educational Resources Information Center

Hartwell, Matthew; Kaplan, Avi

2018-01-01

This paper presents findings from a two-phase mixed methods study investigating the phenomenological structure of self-relevance among ninth-grade junior high school biology students (Phase 1: N = 118; Phase 2: N = 139). We begin with a phenomenological multidimensional definition of self-relevance as comprising three dimensions: the academic…

3D structure of individual nanocrystals in solution by electron microscopy

DOE PAGES

Park, Jungwok; Elmlund, Hans; Ercius, Peter; ...

2015-07-17

Here, knowledge about the synthesis, growth mechanisms, and physical properties of colloidal nanoparticles has been limited by technical impediments. We introduce a method for determining three-dimensional (3D) structures of individual nanoparticles in solution. We combine a graphene liquid cell, high-resolution transmission electron microscopy, a direct electron detector, and an algorithm for single-particle 3D reconstruction originally developed for analysis of biological molecules. This method yielded two 3D structures of individual platinum nanocrystals at near-atomic resolution. Because our method derives the 3D structure from images of individual nanoparticles rotating freely in solution, it enables the analysis of heterogeneous populations of potentially unorderedmore » nanoparticles that are synthesized in solution, thereby providing a means to understand the structure and stability of defects at the nanoscale.« less

Nanoparticle imaging. 3D structure of individual nanocrystals in solution by electron microscopy.

PubMed

Park, Jungwon; Elmlund, Hans; Ercius, Peter; Yuk, Jong Min; Limmer, David T; Chen, Qian; Kim, Kwanpyo; Han, Sang Hoon; Weitz, David A; Zettl, A; Alivisatos, A Paul

2015-07-17

Knowledge about the synthesis, growth mechanisms, and physical properties of colloidal nanoparticles has been limited by technical impediments. We introduce a method for determining three-dimensional (3D) structures of individual nanoparticles in solution. We combine a graphene liquid cell, high-resolution transmission electron microscopy, a direct electron detector, and an algorithm for single-particle 3D reconstruction originally developed for analysis of biological molecules. This method yielded two 3D structures of individual platinum nanocrystals at near-atomic resolution. Because our method derives the 3D structure from images of individual nanoparticles rotating freely in solution, it enables the analysis of heterogeneous populations of potentially unordered nanoparticles that are synthesized in solution, thereby providing a means to understand the structure and stability of defects at the nanoscale. Copyright © 2015, American Association for the Advancement of Science.

3D structure of individual nanocrystals in solution by electron microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Jungwok; Elmlund, Hans; Ercius, Peter

Here, knowledge about the synthesis, growth mechanisms, and physical properties of colloidal nanoparticles has been limited by technical impediments. We introduce a method for determining three-dimensional (3D) structures of individual nanoparticles in solution. We combine a graphene liquid cell, high-resolution transmission electron microscopy, a direct electron detector, and an algorithm for single-particle 3D reconstruction originally developed for analysis of biological molecules. This method yielded two 3D structures of individual platinum nanocrystals at near-atomic resolution. Because our method derives the 3D structure from images of individual nanoparticles rotating freely in solution, it enables the analysis of heterogeneous populations of potentially unorderedmore » nanoparticles that are synthesized in solution, thereby providing a means to understand the structure and stability of defects at the nanoscale.« less

Identifying DNA-binding proteins using structural motifs and the electrostatic potential

PubMed Central

Shanahan, Hugh P.; Garcia, Mario A.; Jones, Susan; Thornton, Janet M.

2004-01-01

Robust methods to detect DNA-binding proteins from structures of unknown function are important for structural biology. This paper describes a method for identifying such proteins that (i) have a solvent accessible structural motif necessary for DNA-binding and (ii) a positive electrostatic potential in the region of the binding region. We focus on three structural motifs: helix–turn-helix (HTH), helix–hairpin–helix (HhH) and helix–loop–helix (HLH). We find that the combination of these variables detect 78% of proteins with an HTH motif, which is a substantial improvement over previous work based purely on structural templates and is comparable to more complex methods of identifying DNA-binding proteins. Similar true positive fractions are achieved for the HhH and HLH motifs. We see evidence of wide evolutionary diversity for DNA-binding proteins with an HTH motif, and much smaller diversity for those with an HhH or HLH motif. PMID:15356290

The biological response to laser-aided direct metal-coated Titanium alloy (Ti6Al4V)

PubMed Central

Shin, T.; Lim, D.; Kim, Y. S.; Kim, S. C.; Jo, W. L.

2018-01-01

Objectives Laser-engineered net shaping (LENS) of coated surfaces can overcome the limitations of conventional coating technologies. We compared the in vitro biological response with a titanium plasma spray (TPS)-coated titanium alloy (Ti6Al4V) surface with that of a Ti6Al4V surface coated with titanium using direct metal fabrication (DMF) with 3D printing technologies. Methods The in vitro ability of human osteoblasts to adhere to TPS-coated Ti6Al4V was compared with DMF-coating. Scanning electron microscopy (SEM) was used to assess the structure and morphology of the surfaces. Biological and morphological responses to human osteoblast cell lines were then examined by measuring cell proliferation, alkaline phosphatase activity, actin filaments, and RUNX2 gene expression. Results Morphological assessment of the cells after six hours of incubation using SEM showed that the TPS- and DMF-coated surfaces were largely covered with lamellipodia from the osteoblasts. Cell adhesion appeared similar in both groups. The differences in the rates of cell proliferation and alkaline phosphatase activities were not statistically significant. Conclusions The DMF coating applied using metal 3D printing is similar to the TPS coating, which is the most common coating process used for bone ingrowth. The DMF method provided an acceptable surface structure and a viable biological surface. Moreover, this method is automatable and less complex than plasma spraying. Cite this article: T. Shin, D. Lim, Y. S. Kim, S. C. Kim, W. L. Jo, Y. W. Lim. The biological response to laser-aided direct metal-coated Titanium alloy (Ti6Al4V). Bone Joint Res 2018;7:357–361. DOI: 10.1302/2046-3758.75.BJR-2017-0222.R1. PMID:29922456

Sensitivity to Structure in the Speech Signal by Children with Speech Sound Disorder and Reading Disability

ERIC Educational Resources Information Center

Johnson, Erin Phinney; Pennington, Bruce F.; Lowenstein, Joanna H.; Nittrouer, Susan

2011-01-01

Research Design;Intervention;Biology;Biotechnology;Teaching Methods;Hands on Science;Professional Development;Comparative Analysis;Genetics;Evaluation;Pretests Posttests;Control Groups;Science Education;Science Instruction;Pedagogical Content Knowledge;

Cellular Imaging | Center for Cancer Research

Cancer.gov

Innovative imaging methods developed and refined within CCR revealed atomic-level structures of biological molecules and unveiled dynamic views of a cell’s interior that are driving the design of new treatments and diagnostics for cancer.

Super-resolution binding activated localization microscopy through reversible change of DNA conformation.

PubMed

Szczurek, Aleksander; Birk, Udo; Knecht, Hans; Dobrucki, Jurek; Mai, Sabine; Cremer, Christoph

2018-01-01

Methods of super-resolving light microscopy (SRM) have found an exponentially growing range of applications in cell biology, including nuclear structure analyses. Recent developments have proven that Single Molecule Localization Microscopy (SMLM), a type of SRM, is particularly useful for enhanced spatial analysis of the cell nucleus due to its highest resolving capability combined with very specific fluorescent labeling. In this commentary we offer a brief review of the latest methodological development in the field of SMLM of chromatin designated DNA Structure Fluctuation Assisted Binding Activated Localization Microscopy (abbreviated as fBALM) as well as its potential future applications in biology and medicine.

Thickness determination of biological samples with a zeta-calibrated scanning tunneling microscope.

PubMed Central

Wang, Z H; Hartmann, T; Baumeister, W; Guckenberger, R

1990-01-01

A single-tube scanning tunneling microscope has been zeta-calibrated by using atomic steps of crystalline gold and was used for measuring the thickness of two biological samples, metal-coated as well as uncoated. The hexagonal surface layer of the bacterium Deinococcus radiodurans with an open network-type structure shows thickness values that are strongly influenced by the substrate and the preparation method. In contrast, the thickness of the purple membrane of Halobacterium halobium with its densely packed less-corrugated structure exhibits very little variation in thickness in coated preparations and the values obtained are in good agreement with x-ray data. Images PMID:2251276

Super-resolution binding activated localization microscopy through reversible change of DNA conformation

PubMed Central

Knecht, Hans; Dobrucki, Jurek; Mai, Sabine

2018-01-01

ABSTRACT Methods of super-resolving light microscopy (SRM) have found an exponentially growing range of applications in cell biology, including nuclear structure analyses. Recent developments have proven that Single Molecule Localization Microscopy (SMLM), a type of SRM, is particularly useful for enhanced spatial analysis of the cell nucleus due to its highest resolving capability combined with very specific fluorescent labeling. In this commentary we offer a brief review of the latest methodological development in the field of SMLM of chromatin designated DNA Structure Fluctuation Assisted Binding Activated Localization Microscopy (abbreviated as fBALM) as well as its potential future applications in biology and medicine. PMID:29297245

Discovering rules for protein-ligand specificity using support vector inductive logic programming.

PubMed

Kelley, Lawrence A; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2009-09-01

Structural genomics initiatives are rapidly generating vast numbers of protein structures. Comparative modelling is also capable of producing accurate structural models for many protein sequences. However, for many of the known structures, functions are not yet determined, and in many modelling tasks, an accurate structural model does not necessarily tell us about function. Thus, there is a pressing need for high-throughput methods for determining function from structure. The spatial arrangement of key amino acids in a folded protein, on the surface or buried in clefts, is often the determinants of its biological function. A central aim of molecular biology is to understand the relationship between such substructures or surfaces and biological function, leading both to function prediction and to function design. We present a new general method for discovering the features of binding pockets that confer specificity for particular ligands. Using a recently developed machine-learning technique which couples the rule-discovery approach of inductive logic programming with the statistical learning power of support vector machines, we are able to discriminate, with high precision (90%) and recall (86%) between pockets that bind FAD and those that bind NAD on a large benchmark set given only the geometry and composition of the backbone of the binding pocket without the use of docking. In addition, we learn rules governing this specificity which can feed into protein functional design protocols. An analysis of the rules found suggests that key features of the binding pocket may be tied to conformational freedom in the ligand. The representation is sufficiently general to be applicable to any discriminatory binding problem. All programs and data sets are freely available to non-commercial users at http://www.sbg.bio.ic.ac.uk/svilp_ligand/.

The Scottish Structural Proteomics Facility: targets, methods and outputs.

PubMed

Oke, Muse; Carter, Lester G; Johnson, Kenneth A; Liu, Huanting; McMahon, Stephen A; Yan, Xuan; Kerou, Melina; Weikart, Nadine D; Kadi, Nadia; Sheikh, Md Arif; Schmelz, Stefan; Dorward, Mark; Zawadzki, Michal; Cozens, Christopher; Falconer, Helen; Powers, Helen; Overton, Ian M; van Niekerk, C A Johannes; Peng, Xu; Patel, Prakash; Garrett, Roger A; Prangishvili, David; Botting, Catherine H; Coote, Peter J; Dryden, David T F; Barton, Geoffrey J; Schwarz-Linek, Ulrich; Challis, Gregory L; Taylor, Garry L; White, Malcolm F; Naismith, James H

2010-06-01

The Scottish Structural Proteomics Facility was funded to develop a laboratory scale approach to high throughput structure determination. The effort was successful in that over 40 structures were determined. These structures and the methods harnessed to obtain them are reported here. This report reflects on the value of automation but also on the continued requirement for a high degree of scientific and technical expertise. The efficiency of the process poses challenges to the current paradigm of structural analysis and publication. In the 5 year period we published ten peer-reviewed papers reporting structural data arising from the pipeline. Nevertheless, the number of structures solved exceeded our ability to analyse and publish each new finding. By reporting the experimental details and depositing the structures we hope to maximize the impact of the project by allowing others to follow up the relevant biology.

Quantum Monte Carlo Methods for First Principles Simulation of Liquid Water

ERIC Educational Resources Information Center

Gergely, John Robert

2009-01-01

Obtaining an accurate microscopic description of water structure and dynamics is of great interest to molecular biology researchers and in the physics and quantum chemistry simulation communities. This dissertation describes efforts to apply quantum Monte Carlo methods to this problem with the goal of making progress toward a fully "ab initio"…

An O(n(5)) algorithm for MFE prediction of kissing hairpins and 4-chains in nucleic acids.

PubMed

Chen, Ho-Lin; Condon, Anne; Jabbari, Hosna

2009-06-01

Efficient methods for prediction of minimum free energy (MFE) nucleic secondary structures are widely used, both to better understand structure and function of biological RNAs and to design novel nano-structures. Here, we present a new algorithm for MFE secondary structure prediction, which significantly expands the class of structures that can be handled in O(n(5)) time. Our algorithm can handle H-type pseudoknotted structures, kissing hairpins, and chains of four overlapping stems, as well as nested substructures of these types.

Biological materials by design.

PubMed

Qin, Zhao; Dimas, Leon; Adler, David; Bratzel, Graham; Buehler, Markus J

2014-02-19

In this topical review we discuss recent advances in the use of physical insight into the way biological materials function, to design novel engineered materials 'from scratch', or from the level of fundamental building blocks upwards and by using computational multiscale methods that link chemistry to material function. We present studies that connect advances in multiscale hierarchical material structuring with material synthesis and testing, review case studies of wood and other biological materials, and illustrate how engineered fiber composites and bulk materials are designed, modeled, and then synthesized and tested experimentally. The integration of experiment and simulation in multiscale design opens new avenues to explore the physics of materials from a fundamental perspective, and using complementary strengths from models and empirical techniques. Recent developments in this field illustrate a new paradigm by which complex material functionality is achieved through hierarchical structuring in spite of simple material constituents.

Distinguishing Biologically Relevant Hexoses by Water Adduction to the Lithium-Cationized Molecule.

PubMed

Campbell, Matthew T; Chen, Dazhe; Wallbillich, Nicholas J; Glish, Gary L

2017-10-03

A method to distinguish the four most common biologically relevant underivatized hexoses, d-glucose, d-galactose, d-mannose, and d-fructose, using only mass spectrometry with no prior separation/derivatization step has been developed. Electrospray of a solution containing hexose and a lithium salt generates [Hexose+Li] + . The lithium-cationized hexoses adduct water in a quadrupole ion trap. The rate of this water adduction reaction can be used to distinguish the four hexoses. Additionally, for each hexose, multiple lithiation sites are possible, allowing for multiple structures of [Hexose+Li] + . Electrospray produces at least one structure that reacts with water and at least one that does not. The ratio of unreactive lithium-cationized hexose to total lithium-cationized hexose is unique for the four hexoses studied, providing a second method for distinguishing the isomers. Use of the water adduction reaction rate or the unreactive ratio provides two separate methods for confidently (p ≤ 0.02) distinguishing the most common biologically relevant hexoses using only femtomoles of hexose. Additionally, binary mixtures of glucose and fructose were studied. A calibration curve was created by measuring the reaction rate of various samples with different ratios of fructose and glucose. The calibration curve was used to accurately measure the percentage of fructose in three samples of high fructose corn syrup (<4% error).

Fluid-structure interaction involving large deformations: 3D simulations and applications to biological systems

NASA Astrophysics Data System (ADS)

Tian, Fang-Bao; Dai, Hu; Luo, Haoxiang; Doyle, James F.; Rousseau, Bernard

2014-02-01

Three-dimensional fluid-structure interaction (FSI) involving large deformations of flexible bodies is common in biological systems, but accurate and efficient numerical approaches for modeling such systems are still scarce. In this work, we report a successful case of combining an existing immersed-boundary flow solver with a nonlinear finite-element solid-mechanics solver specifically for three-dimensional FSI simulations. This method represents a significant enhancement from the similar methods that are previously available. Based on the Cartesian grid, the viscous incompressible flow solver can handle boundaries of large displacements with simple mesh generation. The solid-mechanics solver has separate subroutines for analyzing general three-dimensional bodies and thin-walled structures composed of frames, membranes, and plates. Both geometric nonlinearity associated with large displacements and material nonlinearity associated with large strains are incorporated in the solver. The FSI is achieved through a strong coupling and partitioned approach. We perform several validation cases, and the results may be used to expand the currently limited database of FSI benchmark study. Finally, we demonstrate the versatility of the present method by applying it to the aerodynamics of elastic wings of insects and the flow-induced vocal fold vibration.

A Method for Decomposition of the Basic Reaction of Biological Macromolecules into Exponential Components

NASA Astrophysics Data System (ADS)

Barabash, Yu. M.; Lyamets, A. K.

2016-12-01

The structural and dynamical properties of biological macromolecules under non-equilibrium conditions determine the kinetics of their basic reaction to external stimuli. This kinetics is multiexponential in nature. This is due to the operation of various subsystems in the structure of macromolecules, as well as the effect of the basic reaction on the structure of macromolecules. The situation can be interpreted as a manifestation of the stationary states of macromolecules, which are represented by monoexponential components of the basic reaction (Monod-Wyman-Changeux model) Monod et al. (J Mol Cell Biol 12:88-118, 1965). The representation of multiexponential kinetics of the basic reaction in the form of a sum of exponential functions (A(t)={sum}_{i=1}^n{a}_i{e}^{-{k}_it}) is a multidimensional optimization problem. To solve this problem, a gradient method of optimization with software determination of the amount of exponents and reasonable calculation time is developed. This method is used to analyze the kinetics of photoinduced electron transport in the reaction centers (RC) of purple bacteria and the fluorescence induction in the granum thylakoid membranes which share a common function of converting light energy.

Fluid–structure interaction involving large deformations: 3D simulations and applications to biological systems

PubMed Central

Tian, Fang-Bao; Dai, Hu; Luo, Haoxiang; Doyle, James F.; Rousseau, Bernard

2013-01-01

Three-dimensional fluid–structure interaction (FSI) involving large deformations of flexible bodies is common in biological systems, but accurate and efficient numerical approaches for modeling such systems are still scarce. In this work, we report a successful case of combining an existing immersed-boundary flow solver with a nonlinear finite-element solid-mechanics solver specifically for three-dimensional FSI simulations. This method represents a significant enhancement from the similar methods that are previously available. Based on the Cartesian grid, the viscous incompressible flow solver can handle boundaries of large displacements with simple mesh generation. The solid-mechanics solver has separate subroutines for analyzing general three-dimensional bodies and thin-walled structures composed of frames, membranes, and plates. Both geometric nonlinearity associated with large displacements and material nonlinearity associated with large strains are incorporated in the solver. The FSI is achieved through a strong coupling and partitioned approach. We perform several validation cases, and the results may be used to expand the currently limited database of FSI benchmark study. Finally, we demonstrate the versatility of the present method by applying it to the aerodynamics of elastic wings of insects and the flow-induced vocal fold vibration. PMID:24415796

Single-subject structural networks with closed-form rotation invariant matching mprove power in developmental studies of the cortex.

PubMed

Kandel, Benjamin M; Wang, Danny J J; Gee, James C; Avants, Brian B

2014-01-01

Although much attention has recently been focused on single-subject functional networks, using methods such as resting-state functional MRI, methods for constructing single-subject structural networks are in their infancy. Single-subject cortical networks aim to describe the self-similarity across the cortical structure, possibly signifying convergent developmental pathways. Previous methods for constructing single-subject cortical networks have used patch-based correlations and distance metrics based on curvature and thickness. We present here a method for constructing similarity-based cortical structural networks that utilizes a rotation-invariant representation of structure. The resulting graph metrics are closely linked to age and indicate an increasing degree of closeness throughout development in nearly all brain regions, perhaps corresponding to a more regular structure as the brain matures. The derived graph metrics demonstrate a four-fold increase in power for detecting age as compared to cortical thickness. This proof of concept study indicates that the proposed metric may be useful in identifying biologically relevant cortical patterns.

The JCSG high-throughput structural biology pipeline.

PubMed

Elsliger, Marc André; Deacon, Ashley M; Godzik, Adam; Lesley, Scott A; Wooley, John; Wüthrich, Kurt; Wilson, Ian A

2010-10-01

The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years. The JCSG has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe, as well as making substantial inroads into structural coverage of an entire organism. Targets are processed through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize and optimize each target prior to selection for structure determination. The pipeline uses parallel processing methods at almost every step in the process and can adapt to a wide range of protein targets from bacterial to human. The construction, expansion and optimization of the JCSG gene-to-structure pipeline over the years have resulted in many technological and methodological advances and developments. The vast number of targets and the enormous amounts of associated data processed through the multiple stages of the experimental pipeline required the development of variety of valuable resources that, wherever feasible, have been converted to free-access web-based tools and applications.

A Theoretical Approach to Selection of a Biologically Active Substance in Ultra-Low Doses for Effective Action on a Biological System.

PubMed

Boldyreva, Liudmila Borisovna

2018-05-01

 An approach is offered to selecting a biologically active substance (BAS) in ultra-low dose for effective action on a biological system (BS). The technique is based on the assumption that BAS in ultra-low doses exerts action on BS by means of spin supercurrent emerging between the spin structure created by BAS, on the one hand, and the spin structure created by BS, on the other hand. According to modern quantum-mechanical concepts, these spin structures may be virtual particles pairs having precessing spin (that is, be essentially spin vortices in the physical vacuum) and created by the quantum entities that BAS and BS consist of. The action is effective provided there is equality of precession frequencies of spins in these spin structures.  In this work, some methods are considered for determining the precession frequencies of spins in virtual particles pairs: (1) determination of energy levels of quantum entities that BS and BAS consist of; (2) the use of spin-flip effect of the virtual particles pair spin, the effect being initiated by action of magnetic vector potential (the spin-flip effect takes place when the varied frequency of the magnetic vector potential equals the precession frequency of the spin); (3) determining the frequencies of photons effectively acting on BS.  It is shown that the effect of BAS in ultra-low doses on BS can be replaced by the effect of a beam of low-intensity photons, if the frequency of photons equals the precession frequency of spin in spin structures created by BS. Consequently, the color of bodies placed near a biological system is able to exert an effective action on the biological system: that is "color therapy" is possible. It is also supposed that the spin-flip effect may be used not only for determining the precession frequency of spin in spin structures created by BS but also for therapeutic action on biological systems. The Faculty of Homeopathy.

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws

USGS Publications Warehouse

Xiao, X.; White, E.P.; Hooten, M.B.; Durham, S.L.

2011-01-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain. ?? 2011 by the Ecological Society of America.

Integrative Chemical-Biological Read-Across Approach for Chemical Hazard Classification

PubMed Central

Low, Yen; Sedykh, Alexander; Fourches, Denis; Golbraikh, Alexander; Whelan, Maurice; Rusyn, Ivan; Tropsha, Alexander

2013-01-01

Traditional read-across approaches typically rely on the chemical similarity principle to predict chemical toxicity; however, the accuracy of such predictions is often inadequate due to the underlying complex mechanisms of toxicity. Here we report on the development of a hazard classification and visualization method that draws upon both chemical structural similarity and comparisons of biological responses to chemicals measured in multiple short-term assays (”biological” similarity). The Chemical-Biological Read-Across (CBRA) approach infers each compound's toxicity from those of both chemical and biological analogs whose similarities are determined by the Tanimoto coefficient. Classification accuracy of CBRA was compared to that of classical RA and other methods using chemical descriptors alone, or in combination with biological data. Different types of adverse effects (hepatotoxicity, hepatocarcinogenicity, mutagenicity, and acute lethality) were classified using several biological data types (gene expression profiling and cytotoxicity screening). CBRA-based hazard classification exhibited consistently high external classification accuracy and applicability to diverse chemicals. Transparency of the CBRA approach is aided by the use of radial plots that show the relative contribution of analogous chemical and biological neighbors. Identification of both chemical and biological features that give rise to the high accuracy of CBRA-based toxicity prediction facilitates mechanistic interpretation of the models. PMID:23848138

sbv IMPROVER: Modern Approach to Systems Biology.

PubMed

Guryanova, Svetlana; Guryanova, Anna

2017-01-01

The increasing amount and variety of data in biosciences call for innovative methods of visualization, scientific verification, and pathway analysis. Novel approaches to biological networks and research quality control are important because of their role in development of new products, improvement, and acceleration of existing health policies and research for novel ways of solving scientific challenges. One such approach is sbv IMPROVER. It is a platform that uses crowdsourcing and verification to create biological networks with easy public access. It contains 120 networks built in Biological Expression Language (BEL) to interpret data from PubMed articles with high-quality verification available for free on the CBN database. Computable, human-readable biological networks with a structured syntax are a powerful way of representing biological information generated from high-density data. This article presents sbv IMPROVER, a crowd-verification approach for the visualization and expansion of biological networks.

Nucleic Acid-Based Nanodevices in Biological Imaging.

PubMed

Chakraborty, Kasturi; Veetil, Aneesh T; Jaffrey, Samie R; Krishnan, Yamuna

2016-06-02

The nanoscale engineering of nucleic acids has led to exciting molecular technologies for high-end biological imaging. The predictable base pairing, high programmability, and superior new chemical and biological methods used to access nucleic acids with diverse lengths and in high purity, coupled with computational tools for their design, have allowed the creation of a stunning diversity of nucleic acid-based nanodevices. Given their biological origin, such synthetic devices have a tremendous capacity to interface with the biological world, and this capacity lies at the heart of several nucleic acid-based technologies that are finding applications in biological systems. We discuss these diverse applications and emphasize the advantage, in terms of physicochemical properties, that the nucleic acid scaffold brings to these contexts. As our ability to engineer this versatile scaffold increases, its applications in structural, cellular, and organismal biology are clearly poised to massively expand.

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stewart, R.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

WE-DE-202-01: Connecting Nanoscale Physics to Initial DNA Damage Through Track Structure Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schuemann, J.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Human cell structure-driven model construction for predicting protein subcellular location from biological images.

PubMed

Shao, Wei; Liu, Mingxia; Zhang, Daoqiang

2016-01-01

The systematic study of subcellular location pattern is very important for fully characterizing the human proteome. Nowadays, with the great advances in automated microscopic imaging, accurate bioimage-based classification methods to predict protein subcellular locations are highly desired. All existing models were constructed on the independent parallel hypothesis, where the cellular component classes are positioned independently in a multi-class classification engine. The important structural information of cellular compartments is missed. To deal with this problem for developing more accurate models, we proposed a novel cell structure-driven classifier construction approach (SC-PSorter) by employing the prior biological structural information in the learning model. Specifically, the structural relationship among the cellular components is reflected by a new codeword matrix under the error correcting output coding framework. Then, we construct multiple SC-PSorter-based classifiers corresponding to the columns of the error correcting output coding codeword matrix using a multi-kernel support vector machine classification approach. Finally, we perform the classifier ensemble by combining those multiple SC-PSorter-based classifiers via majority voting. We evaluate our method on a collection of 1636 immunohistochemistry images from the Human Protein Atlas database. The experimental results show that our method achieves an overall accuracy of 89.0%, which is 6.4% higher than the state-of-the-art method. The dataset and code can be downloaded from https://github.com/shaoweinuaa/. dqzhang@nuaa.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Enhancing multi-spot structured illumination microscopy with fluorescence difference

NASA Astrophysics Data System (ADS)

Ward, Edward N.; Torkelsen, Frida H.; Pal, Robert

2018-03-01

Structured illumination microscopy is a super-resolution technique used extensively in biological research. However, this technique is limited in the maximum possible resolution increase. Here we report the results of simulations of a novel enhanced multi-spot structured illumination technique. This method combines the super-resolution technique of difference microscopy with structured illumination deconvolution. Initial results give at minimum a 1.4-fold increase in resolution over conventional structured illumination in a low-noise environment. This new technique also has the potential to be expanded to further enhance axial resolution with three-dimensional difference microscopy. The requirement for precise pattern determination in this technique also led to the development of a new pattern estimation algorithm which proved more efficient and reliable than other methods tested.

Modeling the assembly order of multimeric heteroprotein complexes

PubMed Central

Esquivel-Rodriguez, Juan; Terashi, Genki; Christoffer, Charles; Shin, Woong-Hee

2018-01-01

Protein-protein interactions are the cornerstone of numerous biological processes. Although an increasing number of protein complex structures have been determined using experimental methods, relatively fewer studies have been performed to determine the assembly order of complexes. In addition to the insights into the molecular mechanisms of biological function provided by the structure of a complex, knowing the assembly order is important for understanding the process of complex formation. Assembly order is also practically useful for constructing subcomplexes as a step toward solving the entire complex experimentally, designing artificial protein complexes, and developing drugs that interrupt a critical step in the complex assembly. There are several experimental methods for determining the assembly order of complexes; however, these techniques are resource-intensive. Here, we present a computational method that predicts the assembly order of protein complexes by building the complex structure. The method, named Path-LzerD, uses a multimeric protein docking algorithm that assembles a protein complex structure from individual subunit structures and predicts assembly order by observing the simulated assembly process of the complex. Benchmarked on a dataset of complexes with experimental evidence of assembly order, Path-LZerD was successful in predicting the assembly pathway for the majority of the cases. Moreover, when compared with a simple approach that infers the assembly path from the buried surface area of subunits in the native complex, Path-LZerD has the strong advantage that it can be used for cases where the complex structure is not known. The path prediction accuracy decreased when starting from unbound monomers, particularly for larger complexes of five or more subunits, for which only a part of the assembly path was correctly identified. As the first method of its kind, Path-LZerD opens a new area of computational protein structure modeling and will be an indispensable approach for studying protein complexes. PMID:29329283

Modeling the assembly order of multimeric heteroprotein complexes.

PubMed

Peterson, Lenna X; Togawa, Yoichiro; Esquivel-Rodriguez, Juan; Terashi, Genki; Christoffer, Charles; Roy, Amitava; Shin, Woong-Hee; Kihara, Daisuke

2018-01-01

Protein-protein interactions are the cornerstone of numerous biological processes. Although an increasing number of protein complex structures have been determined using experimental methods, relatively fewer studies have been performed to determine the assembly order of complexes. In addition to the insights into the molecular mechanisms of biological function provided by the structure of a complex, knowing the assembly order is important for understanding the process of complex formation. Assembly order is also practically useful for constructing subcomplexes as a step toward solving the entire complex experimentally, designing artificial protein complexes, and developing drugs that interrupt a critical step in the complex assembly. There are several experimental methods for determining the assembly order of complexes; however, these techniques are resource-intensive. Here, we present a computational method that predicts the assembly order of protein complexes by building the complex structure. The method, named Path-LzerD, uses a multimeric protein docking algorithm that assembles a protein complex structure from individual subunit structures and predicts assembly order by observing the simulated assembly process of the complex. Benchmarked on a dataset of complexes with experimental evidence of assembly order, Path-LZerD was successful in predicting the assembly pathway for the majority of the cases. Moreover, when compared with a simple approach that infers the assembly path from the buried surface area of subunits in the native complex, Path-LZerD has the strong advantage that it can be used for cases where the complex structure is not known. The path prediction accuracy decreased when starting from unbound monomers, particularly for larger complexes of five or more subunits, for which only a part of the assembly path was correctly identified. As the first method of its kind, Path-LZerD opens a new area of computational protein structure modeling and will be an indispensable approach for studying protein complexes.

Photonic crystal materials and their application in biomedicine.

PubMed

Chen, Huadong; Lou, Rong; Chen, Yanxiao; Chen, Lili; Lu, Jingya; Dong, Qianqian

2017-11-01

Photonic crystal (PC) materials exhibit unique structural colors that originate from their intrinsic photonic band gap. Because of their highly ordered structure and distinct optical characteristics, PC-based biomaterials have advantages in the multiplex detection, biomolecular screening and real-time monitoring of biomolecules. In addition, PCs provide good platforms for drug loading and biomolecule modification, which could be applied to biosensors and biological carriers. A number of methods are now available to fabricate PC materials with variable structure colors, which could be applied in biomedicine. Emphasis is given to the description of various applications of PC materials in biomedicine, including drug delivery, biodetection and tumor screening. We believe that this article will promote greater communication among researchers in the fields of chemistry, material science, biology, medicine and pharmacy.

Study of magnetic nanoparticles and overcoatings for biological applications including a sensor device

NASA Astrophysics Data System (ADS)

Grancharov, Stephanie G.

I. A general introduction to the field of nanomaterials is presented, highlighting their special attributes and characteristics. Nanoparticles in general are discussed with respect to their structure, form and properties. Magnetic particles in particular are highlighted, especially the iron oxides. The importance and interest of integrating these materials with biological media is discussed, with emphasis on transferring particles from one medium to another, and subsequent modification of surfaces with different types of materials. II. A general route to making magnetic iron oxide nanoparticles is explained, both as maghemite and magnetite, including properties of the particles and characterization. A novel method of producing magnetite particles without a ligand is then presented, with subsequent characterization and properties described. III. Attempts to coat iron oxide nanoparticles with a view to creating biofunctional magnetic nanoparticles are presented, using a gold overcoating method. Methods of synthesis and characterization are examined, with unique problems to core-shell structures analyzed. IV. Solubility of nanoparticles in both aqueous and organic media is discussed and examined. The subsequent functionalization of the surface of maghemite and magnetite nanoparticles with a variety of biomaterials including block copolypeptides, phospholipids and carboxydextran is then presented. These methods are integral to the use of magnetic nanoparticles in biological applications, and therefore their properties are examined once tailored with these molecules. V. A new type of magnetic nanoparticle sensor-type device is described. This device integrates bio-and DNA-functionalized nanoparticles with conjugate functionalized silicon dioxide surfaces. These techniques to pattern particles to a surface are then incorporated into a device with a magnetic tunnel junction, which measures magnetoresistance in the presence of an external magnetic field. This configuration thereby introduces a new way to detect magnetic nanoparticles via their magnetic properties after conjugation via biological entities.

Biological Small Angle Scattering: Techniques, Strategies and Tips

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chaudhuri, Barnali; Muñoz, Inés G.; Urban, Volker S.

This book provides a clear, comprehensible and up-to-date description of how Small Angle Scattering (SAS) can help structural biology researchers. SAS is an efficient technique that offers structural information on how biological macromolecules behave in solution. SAS provides distinct and complementary data for integrative structural biology approaches in combination with other widely used probes, such as X-ray crystallography, Nuclear magnetic resonance, Mass spectrometry and Cryo-electron Microscopy. The development of brilliant synchrotron small-angle X-ray scattering (SAXS) beam lines has increased the number of researchers interested in solution scattering. SAS is especially useful for studying conformational changes in proteins, highly flexible proteins,more » and intrinsically disordered proteins. Small-angle neutron scattering (SANS) with neutron contrast variation is ideally suited for studying multi-component assemblies as well as membrane proteins that are stabilized in surfactant micelles or vesicles. SAS is also used for studying dynamic processes of protein fibrillation in amyloid diseases, and pharmaceutical drug delivery. The combination with size-exclusion chromatography further increases the range of SAS applications.The book is written by leading experts in solution SAS methodologies. The principles and theoretical background of various SAS techniques are included, along with practical aspects that range from sample preparation to data presentation for publication. Topics covered include techniques for improving data quality and analysis, as well as different scientific applications of SAS. With abundant illustrations and practical tips, we hope the clear explanations of the principles and the reviews on the latest progresses will serve as a guide through all aspects of biological solution SAS.The scope of this book is particularly relevant for structural biology researchers who are new to SAS. Advanced users of the technique will find it helpful for exploring the diversity of solution SAS methods and applications.« less

Shape-preserving transformations of organic matter and compositions thereof

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaehr, Bryan J.; Meyer, Kristin; Townson, Jason L.

The present invention relates to methods of transforming organic matter into organic-inorganic composites, inorganic replicas, or conductive replicas. Organic matter, such as biological cells and tissue and organs, can be converted into such composites and replicas using the methods described herein. In particular, such methods transform organic matter (into inorganic, organic-inorganic, or conductive constructs), while simultaneously preserving microscopic and/or macroscopic structural detail.

Tools to evaluate the conformation of protein products.

PubMed

Manta, Bruno; Obal, Gonzalo; Ricciardi, Alejandro; Pritsch, Otto; Denicola, Ana

2011-06-01

Production of recombinant proteins is a process intensively used in the research laboratory. In addition, the main biotechnology market products are recombinant proteins and monoclonal antibodies. The biological (and clinical) properties of the protein product strongly depend on the conformation of the polypeptide. Therefore, assessment of the correct conformation of the produced protein is crucial. There is no single method to assess every aspect of protein structure or function. Depending on the protein, the methods of choice vary. There are general methods to evaluate not only mass and primary sequence of the protein, but also higher-order structure. This review outlines the principal techniques for determining the conformation of a protein from structural (biophysical methods) to functional (in vitro binding assays) analyses. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease*

PubMed Central

Dewhurst, Henry; Sundararaman, Niveda

2016-01-01

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable body of potential regulatory elements that impact hundreds of different biological processes important in eukaryotic biology and human health. PMID:27697855

Micro- and nanofluidic systems in devices for biological, medical and environmental research

NASA Astrophysics Data System (ADS)

Evstrapov, A. A.

2017-11-01

The use of micro- and nanofluidic systems in modern analytical instruments allow you to implement a number of unique opportunities and achieve ultra-high measurement sensitivity. The possibility of manipulation of the individual biological objects (cells, bacteria, viruses, proteins, nucleic acids) in a liquid medium caused the development of devices on microchip platform for methods: chromatographic and electrophoretic analyzes; polymerase chain reaction; sequencing of nucleic acids; immunoassay; cytometric studies. Development of micro and nano fabrication technologies, materials science, surface chemistry, analytical chemistry, cell engineering have led to the creation of a unique systems such as “lab-on-a-chip”, “human-on-a-chip” and other. This article discusses common in microfluidics materials and methods of making functional structures. Examples of integration of nanoscale structures in microfluidic devices for the implementation of new features and improve the technical characteristics of devices and systems are shown.

Artificial 3D hierarchical and isotropic porous polymeric materials

PubMed Central

Musteata, Valentina-Elena; Behzad, Ali Reza

2018-01-01

Hierarchical porous materials that replicate complex living structures are attractive for a wide variety of applications, ranging from storage and catalysis to biological and artificial systems. However, the preparation of structures with a high level of complexity and long-range order at the mesoscale and microscale is challenging. We report a simple, nonextractive, and nonreactive method used to prepare three-dimensional porous materials that mimic biological systems such as marine skeletons and honeycombs. This method exploits the concurrent occurrence of the self-assembly of block copolymers in solution and macrophase separation by nucleation and growth. We obtained a long-range order of micrometer-sized compartments. These compartments are interconnected by ordered cylindrical nanochannels. The new approach is demonstrated using polystyrene-b-poly(t-butyl acrylate), which can be further explored for a broad range of applications, such as air purification filters for viruses and pollution particle removal or growth of bioinspired materials for bone regeneration.

Artificial 3D hierarchical and isotropic porous polymeric materials.

PubMed

Chisca, Stefan; Musteata, Valentina-Elena; Sougrat, Rachid; Behzad, Ali Reza; Nunes, Suzana P

2018-05-01

Hierarchical porous materials that replicate complex living structures are attractive for a wide variety of applications, ranging from storage and catalysis to biological and artificial systems. However, the preparation of structures with a high level of complexity and long-range order at the mesoscale and microscale is challenging. We report a simple, nonextractive, and nonreactive method used to prepare three-dimensional porous materials that mimic biological systems such as marine skeletons and honeycombs. This method exploits the concurrent occurrence of the self-assembly of block copolymers in solution and macrophase separation by nucleation and growth. We obtained a long-range order of micrometer-sized compartments. These compartments are interconnected by ordered cylindrical nanochannels. The new approach is demonstrated using polystyrene- b -poly( t -butyl acrylate), which can be further explored for a broad range of applications, such as air purification filters for viruses and pollution particle removal or growth of bioinspired materials for bone regeneration.

Correlated optical and isotopic nanoscopy

NASA Astrophysics Data System (ADS)

Saka, Sinem K.; Vogts, Angela; Kröhnert, Katharina; Hillion, François; Rizzoli, Silvio O.; Wessels, Johannes T.

2014-04-01

The isotopic composition of different materials can be imaged by secondary ion mass spectrometry. In biology, this method is mainly used to study cellular metabolism and turnover, by pulsing the cells with marker molecules such as amino acids labelled with stable isotopes (15N, 13C). The incorporation of the markers is then imaged with a lateral resolution that can surpass 100 nm. However, secondary ion mass spectrometry cannot identify specific subcellular structures like organelles, and needs to be correlated with a second technique, such as fluorescence imaging. Here, we present a method based on stimulated emission depletion microscopy that provides correlated optical and isotopic nanoscopy (COIN) images. We use this approach to study the protein turnover in different organelles from cultured hippocampal neurons. Correlated optical and isotopic nanoscopy can be applied to a variety of biological samples, and should therefore enable the investigation of the isotopic composition of many organelles and subcellular structures.

The Chemical Basis of Pharmacology

PubMed Central

2010-01-01

Molecular biology now dominates pharmacology so thoroughly that it is difficult to recall that only a generation ago the field was very different. To understand drug action today, we characterize the targets through which they act and new drug leads are discovered on the basis of target structure and function. Until the mid-1980s the information often flowed in reverse: investigators began with organic molecules and sought targets, relating receptors not by sequence or structure but by their ligands. Recently, investigators have returned to this chemical view of biology, bringing to it systematic and quantitative methods of relating targets by their ligands. This has allowed the discovery of new targets for established drugs, suggested the bases for their side effects, and predicted the molecular targets underlying phenotypic screens. The bases for these new methods, some of their successes and liabilities, and new opportunities for their use are described. PMID:21058655

Ultrastable gold substrates: Properties of a support for high-resolution electron cryomicroscopy of biological specimens

PubMed Central

Russo, Christopher J.; Passmore, Lori A.

2016-01-01

Electron cryomicroscopy (cryo-EM) allows structure determination of a wide range of biological molecules and specimens. All-gold supports improve cryo-EM images by reducing radiation-induced motion and image blurring. Here we compare the mechanical and electrical properties of all-gold supports to amorphous carbon foils. Gold supports are more conductive, and have suspended foils that are not compressed by differential contraction when cooled to liquid nitrogen temperatures. These measurements show how the choice of support material and geometry can reduce specimen movement by more than an order of magnitude during low-dose imaging. We provide methods for fabrication of all-gold supports and preparation of vitrified specimens. We also analyse illumination geometry for optimal collection of high resolution, low-dose data. Together, the support structures and methods herein can improve the resolution and quality of images from any electron cryomicroscope. PMID:26592474

A novel and rapid method for obtaining high titre intact prion strains from mammalian brain

PubMed Central

Wenborn, Adam; Terry, Cassandra; Gros, Nathalie; Joiner, Susan; D’Castro, Laura; Panico, Silvia; Sells, Jessica; Cronier, Sabrina; Linehan, Jacqueline M.; Brandner, Sebastian; Saibil, Helen R.; Collinge, John; Wadsworth, Jonathan D. F.

2015-01-01

Mammalian prions exist as multiple strains which produce characteristic and highly reproducible phenotypes in defined hosts. How this strain diversity is encoded by a protein-only agent remains one of the most interesting and challenging questions in biology with wide relevance to understanding other diseases involving the aggregation or polymerisation of misfolded host proteins. Progress in understanding mammalian prion strains has however been severely limited by the complexity and variability of the methods used for their isolation from infected tissue and no high resolution structures have yet been reported. Using high-throughput cell-based prion bioassay to re-examine prion purification from first principles we now report the isolation of prion strains to exceptional levels of purity from small quantities of infected brain and demonstrate faithful retention of biological and biochemical strain properties. The method’s effectiveness and simplicity should facilitate its wide application and expedite structural studies of prions. PMID:25950908

Glycan Engineering for Cell and Developmental Biology.

PubMed

Griffin, Matthew E; Hsieh-Wilson, Linda C

2016-01-21

Cell-surface glycans are a diverse class of macromolecules that participate in many key biological processes, including cell-cell communication, development, and disease progression. Thus, the ability to modulate the structures of glycans on cell surfaces provides a powerful means not only to understand fundamental processes but also to direct activity and elicit desired cellular responses. Here, we describe methods to sculpt glycans on cell surfaces and highlight recent successes in which artificially engineered glycans have been employed to control biological outcomes such as the immune response and stem cell fate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exploring Human Diseases and Biological Mechanisms by Protein Structure Prediction and Modeling.

PubMed

Wang, Juexin; Luttrell, Joseph; Zhang, Ning; Khan, Saad; Shi, NianQing; Wang, Michael X; Kang, Jing-Qiong; Wang, Zheng; Xu, Dong

2016-01-01

Protein structure prediction and modeling provide a tool for understanding protein functions by computationally constructing protein structures from amino acid sequences and analyzing them. With help from protein prediction tools and web servers, users can obtain the three-dimensional protein structure models and gain knowledge of functions from the proteins. In this chapter, we will provide several examples of such studies. As an example, structure modeling methods were used to investigate the relation between mutation-caused misfolding of protein and human diseases including epilepsy and leukemia. Protein structure prediction and modeling were also applied in nucleotide-gated channels and their interaction interfaces to investigate their roles in brain and heart cells. In molecular mechanism studies of plants, rice salinity tolerance mechanism was studied via structure modeling on crucial proteins identified by systems biology analysis; trait-associated protein-protein interactions were modeled, which sheds some light on the roles of mutations in soybean oil/protein content. In the age of precision medicine, we believe protein structure prediction and modeling will play more and more important roles in investigating biomedical mechanism of diseases and drug design.

A new method to improve network topological similarity search: applied to fold recognition

PubMed Central

Lhota, John; Hauptman, Ruth; Hart, Thomas; Ng, Clara; Xie, Lei

2015-01-01

Motivation: Similarity search is the foundation of bioinformatics. It plays a key role in establishing structural, functional and evolutionary relationships between biological sequences. Although the power of the similarity search has increased steadily in recent years, a high percentage of sequences remain uncharacterized in the protein universe. Thus, new similarity search strategies are needed to efficiently and reliably infer the structure and function of new sequences. The existing paradigm for studying protein sequence, structure, function and evolution has been established based on the assumption that the protein universe is discrete and hierarchical. Cumulative evidence suggests that the protein universe is continuous. As a result, conventional sequence homology search methods may be not able to detect novel structural, functional and evolutionary relationships between proteins from weak and noisy sequence signals. To overcome the limitations in existing similarity search methods, we propose a new algorithmic framework—Enrichment of Network Topological Similarity (ENTS)—to improve the performance of large scale similarity searches in bioinformatics. Results: We apply ENTS to a challenging unsolved problem: protein fold recognition. Our rigorous benchmark studies demonstrate that ENTS considerably outperforms state-of-the-art methods. As the concept of ENTS can be applied to any similarity metric, it may provide a general framework for similarity search on any set of biological entities, given their representation as a network. Availability and implementation: Source code freely available upon request Contact: lxie@iscb.org PMID:25717198

Detecting phenotype-driven transitions in regulatory network structure.

PubMed

Padi, Megha; Quackenbush, John

2018-01-01

Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes.

Using directed information for influence discovery in interconnected dynamical systems

NASA Astrophysics Data System (ADS)

Rao, Arvind; Hero, Alfred O.; States, David J.; Engel, James Douglas

2008-08-01

Structure discovery in non-linear dynamical systems is an important and challenging problem that arises in various applications such as computational neuroscience, econometrics, and biological network discovery. Each of these systems have multiple interacting variables and the key problem is the inference of the underlying structure of the systems (which variables are connected to which others) based on the output observations (such as multiple time trajectories of the variables). Since such applications demand the inference of directed relationships among variables in these non-linear systems, current methods that have a linear assumption on structure or yield undirected variable dependencies are insufficient. Hence, in this work, we present a methodology for structure discovery using an information-theoretic metric called directed time information (DTI). Using both synthetic dynamical systems as well as true biological datasets (kidney development and T-cell data), we demonstrate the utility of DTI in such problems.

Defining functional distance using manifold embeddings of gene ontology annotations

PubMed Central

Lerman, Gilad; Shakhnovich, Boris E.

2007-01-01

Although rigorous measures of similarity for sequence and structure are now well established, the problem of defining functional relationships has been particularly daunting. Here, we present several manifold embedding techniques to compute distances between Gene Ontology (GO) functional annotations and consequently estimate functional distances between protein domains. To evaluate accuracy, we correlate the functional distance to the well established measures of sequence, structural, and phylogenetic similarities. Finally, we show that manual classification of structures into folds and superfamilies is mirrored by proximity in the newly defined function space. We show how functional distances place structure–function relationships in biological context resulting in insight into divergent and convergent evolution. The methods and results in this paper can be readily generalized and applied to a wide array of biologically relevant investigations, such as accuracy of annotation transference, the relationship between sequence, structure, and function, or coherence of expression modules. PMID:17595300

Viral metagenomics, protein structure, and reverse genetics: Key strategies for investigating coronaviruses.

PubMed

Johnson, Bryan A; Graham, Rachel L; Menachery, Vineet D

2018-04-01

Viral metagenomics, modeling of protein structure, and manipulation of viral genetics are key approaches that have laid the foundations of our understanding of coronavirus biology. In this review, we discuss the major advances each method has provided and discuss how future studies should leverage these strategies synergistically to answer novel questions. Copyright © 2017 Elsevier Inc. All rights reserved.

Recent Advances and Applications in Synchrotron X-Ray Protein Footprinting for Protein Structure and Dynamics Elucidation.

PubMed

Gupta, Sayan; Feng, Jun; Chance, Mark; Ralston, Corie

2016-01-01

Synchrotron X-ray Footprinting is a powerful in situ hydroxyl radical labeling method for analysis of protein structure, interactions, folding and conformation change in solution. In this method, water is ionized by high flux density broad band synchrotron X-rays to produce a steady-state concentration of hydroxyl radicals, which then react with solvent accessible side-chains. The resulting stable modification products are analyzed by liquid chromatography coupled to mass spectrometry. A comparative reactivity rate between known and unknown states of a protein provides local as well as global information on structural changes, which is then used to develop structural models for protein function and dynamics. In this review we describe the XF-MS method, its unique capabilities and its recent technical advances at the Advanced Light Source. We provide a comparison of other hydroxyl radical and mass spectrometry based methods with XFMS. We also discuss some of the latest developments in its usage for studying bound water, transmembrane proteins and photosynthetic protein components, and the synergy of the method with other synchrotron based structural biology methods.

Detailed transient heme structures of Mb-CO in solution after CO dissociation: an X-ray transient absorption spectroscopic study.

PubMed

Stickrath, Andrew B; Mara, Michael W; Lockard, Jenny V; Harpham, Michael R; Huang, Jier; Zhang, Xiaoyi; Attenkofer, Klaus; Chen, Lin X

2013-04-25

Although understanding the structural dynamics associated with ligand photodissociation is necessary in order to correlate structure and function in biological systems, few techniques are capable of measuring the ultrafast dynamics of these systems in solution-phase at room temperature. We present here a detailed X-ray transient absorption (XTA) study of the photodissociation of CO-bound myoglobin (Fe(II)CO-Mb) in room-temperature aqueous buffer solution with a time resolution of 80 ps, along with a general procedure for handling biological samples under the harsh experimental conditions that transient X-ray experiments entail. The XTA spectra of (Fe(II)CO-Mb) exhibit significant XANES and XAFS alterations following 527 nm excitation, which remain unchanged for >47 μs. These spectral changes indicate loss of the CO ligand, resulting in a five-coordinate, domed heme, and significant energetic reorganization of the 3d orbitals of the Fe center. With the current experimental setup, each X-ray pulse in the pulse train, separated by ~153 ns, can be separately discriminated, yielding snapshots of the myoglobin evolution over time. These methods can be easily applied to other biological systems, allowing for simultaneous structural and electronic measurements of any biological system with both ultrafast and slow time resolutions, effectively mapping out all of the samples' relevant physiological processes.

Using Variable-Length Aligned Fragment Pairs and an Improved Transition Function for Flexible Protein Structure Alignment.

PubMed

Cao, Hu; Lu, Yonggang

2017-01-01

With the rapid growth of known protein 3D structures in number, how to efficiently compare protein structures becomes an essential and challenging problem in computational structural biology. At present, many protein structure alignment methods have been developed. Among all these methods, flexible structure alignment methods are shown to be superior to rigid structure alignment methods in identifying structure similarities between proteins, which have gone through conformational changes. It is also found that the methods based on aligned fragment pairs (AFPs) have a special advantage over other approaches in balancing global structure similarities and local structure similarities. Accordingly, we propose a new flexible protein structure alignment method based on variable-length AFPs. Compared with other methods, the proposed method possesses three main advantages. First, it is based on variable-length AFPs. The length of each AFP is separately determined to maximally represent a local similar structure fragment, which reduces the number of AFPs. Second, it uses local coordinate systems, which simplify the computation at each step of the expansion of AFPs during the AFP identification. Third, it decreases the number of twists by rewarding the situation where nonconsecutive AFPs share the same transformation in the alignment, which is realized by dynamic programming with an improved transition function. The experimental data show that compared with FlexProt, FATCAT, and FlexSnap, the proposed method can achieve comparable results by introducing fewer twists. Meanwhile, it can generate results similar to those of the FATCAT method in much less running time due to the reduced number of AFPs.

Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma

PubMed Central

Liu, Li; Dinu, Valentin

2018-01-01

Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway’s topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher’s exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov–Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level. PMID:29666752

Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma.

PubMed

Li, Chaoxing; Liu, Li; Dinu, Valentin

2018-01-01

Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level.

Kirigami design and fabrication for biomimetic robotics

NASA Astrophysics Data System (ADS)

Rossiter, Jonathan; Sareh, Sina

2014-03-01

Biomimetics faces a continual challenge of how to bridge the gap between what Nature has so effectively evolved and the current tools and materials that engineers and scientists can exploit. Kirigami, from the Japanese `cut' and `paper', is a method of design where laminar materials are cut and then forced out-of-plane to yield 3D structures. Kirimimetic design provides a convenient and relatively closed design space within which to replicate some of the most interesting niche biological mechanisms. These include complex flexing organelles such as cilia in algae, energy storage and buckled structures in plants, and organic appendages that actuate out-of-plane such as the myoneme of the Vorticella protozoa. Where traditional kirigami employs passive materials which must be forced to transition to higher dimensions, we can exploit planar smart actuators and artificial muscles to create self-actuating kirigami structures. Here we review biomimetics with respect to the kirigami design and fabrication methods and examine how smart materials, including electroactive polymers and shape memory polymers, can be used to realise effective biomimetic components for robotic, deployable structures and engineering systems. One-way actuation, for example using shape memory polymers, can yield complete self-deploying structures. Bi-directional actuation, in contrast, can be exploited to mimic fundamental biological mechanisms such as thrust generation and fluid control. We present recent examples of kirigami robotic mechanisms and actuators and discuss planar fabrication methods, including rapid prototyping and 3D printing, and how current technologies, and their limitations, affect Kirigami robotics.

Coarse-grained modeling of RNA 3D structure.

PubMed

Dawson, Wayne K; Maciejczyk, Maciej; Jankowska, Elzbieta J; Bujnicki, Janusz M

2016-07-01

Functional RNA molecules depend on three-dimensional (3D) structures to carry out their tasks within the cell. Understanding how these molecules interact to carry out their biological roles requires a detailed knowledge of RNA 3D structure and dynamics as well as thermodynamics, which strongly governs the folding of RNA and RNA-RNA interactions as well as a host of other interactions within the cellular environment. Experimental determination of these properties is difficult, and various computational methods have been developed to model the folding of RNA 3D structures and their interactions with other molecules. However, computational methods also have their limitations, especially when the biological effects demand computation of the dynamics beyond a few hundred nanoseconds. For the researcher confronted with such challenges, a more amenable approach is to resort to coarse-grained modeling to reduce the number of data points and computational demand to a more tractable size, while sacrificing as little critical information as possible. This review presents an introduction to the topic of coarse-grained modeling of RNA 3D structures and dynamics, covering both high- and low-resolution strategies. We discuss how physics-based approaches compare with knowledge based methods that rely on databases of information. In the course of this review, we discuss important aspects in the reasoning process behind building different models and the goals and pitfalls that can result. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Waste water biological purification plants of dairy products industry and energy management

NASA Astrophysics Data System (ADS)

Stepanov, Sergey; Solkina, Olga; Stepanov, Alexander; Zhukova, Maria

2017-10-01

The paper presents results of engineering and economical comparison of waste water biological purification plants of dairy products industry. Three methods of purification are compared: traditional biological purification with the use of secondary clarifiers and afterpurification through granular-bed filters, biomembrane technology and physical-and-chemical treatment together with biomembrane technology for new construction conditions. The improvement of the biological purification technology using nitro-denitrification and membrane un-mixing of sludge mixture is a promising trend in this area. In these calculations, an energy management which is widely applied abroad was used. The descriptions of the three methods are illustrated with structural schemes. Costs of equipment and production areas are taken from manufacturers’ data. The research is aimed at an engineering and economical comparison of new constructions of waste water purification of dairy products industry. The experiment demonstrates advantages of biomembrane technology in waste water purification. This technology offers prospects of 122 million rubles cost saving during 25 years of operation when compared with of the technology of preparatory reagent flotation and of 13.7 million rubles cost saving compared to the option of traditional biological purification.

Recommendations of the wwPDB NMR Validation Task Force

PubMed Central

Montelione, Gaetano T.; Nilges, Michael; Bax, Ad; Güntert, Peter; Herrmann, Torsten; Richardson, Jane S.; Schwieters, Charles; Vranken, Wim F.; Vuister, Geerten W.; Wishart, David S.; Berman, Helen M.; Kleywegt, Gerard J.; Markley, John L.

2013-01-01

As methods for analysis of biomolecular structure and dynamics using nuclear magnetic resonance spectroscopy (NMR) continue to advance, the resulting 3D structures, chemical shifts, and other NMR data are broadly impacting biology, chemistry, and medicine. Structure model assessment is a critical area of NMR methods development, and is an essential component of the process of making these structures accessible and useful to the wider scientific community. For these reasons, the Worldwide Protein Data Bank (wwPDB) has convened an NMR Validation Task Force (NMR-VTF) to work with the wwPDB partners in developing metrics and policies for biomolecular NMR data harvesting, structure representation, and structure quality assessment. This paper summarizes the recommendations of the NMR-VTF, and lays the groundwork for future work in developing standards and metrics for biomolecular NMR structure quality assessment. PMID:24010715

Density functional study of molecular interactions in secondary structures of proteins.

PubMed

Takano, Yu; Kusaka, Ayumi; Nakamura, Haruki

2016-01-01

Proteins play diverse and vital roles in biology, which are dominated by their three-dimensional structures. The three-dimensional structure of a protein determines its functions and chemical properties. Protein secondary structures, including α-helices and β-sheets, are key components of the protein architecture. Molecular interactions, in particular hydrogen bonds, play significant roles in the formation of protein secondary structures. Precise and quantitative estimations of these interactions are required to understand the principles underlying the formation of three-dimensional protein structures. In the present study, we have investigated the molecular interactions in α-helices and β-sheets, using ab initio wave function-based methods, the Hartree-Fock method (HF) and the second-order Møller-Plesset perturbation theory (MP2), density functional theory, and molecular mechanics. The characteristic interactions essential for forming the secondary structures are discussed quantitatively.

Coupling flash liquid chromatography with mass spectrometry for enrichment and isolation of milk oligosaccharides for functional studies.

PubMed

Strum, John S; Aldredge, Danielle; Barile, Daniela; Lebrilla, Carlito B

2012-05-15

Mass spectrometry has been coupled with flash liquid chromatography to yield new capabilities for isolating nonchromophoric material from complicated biological mixtures. A flash liquid chromatography/tandem mass spectrometry (LC/MS/MS) method enabled fraction collection of milk oligosaccharides from biological mixtures based on composition and structure. The method is compatible with traditional gas pressure-driven flow flash chromatography widely employed in organic chemistry laboratories. The online mass detector enabled real-time optimization of chromatographic parameters to favor separation of oligosaccharides that would otherwise be indistinguishable from coeluting components with a nonspecific detector. Unlike previously described preparative LC/MS techniques, we have employed a dynamic flow connection that permits any flow rate from the flash system to be delivered from 1 to 200 ml/min without affecting the ionization conditions of the mass spectrometer. A new way of packing large amounts of graphitized carbon allowed the enrichment and separation of milligram quantities of structurally heterogeneous mixtures of human milk oligosaccharides (HMOs) and bovine milk oligosaccharides (BMOs). Abundant saccharide components in milk, such as lactose and lacto-N-tetraose, were separated from the rarer and less abundant oligosaccharides that have greater structural diversity and biological functionality. Neutral and acidic HMOs and BMOs were largely separated and enriched with a dual binary solvent system. Published by Elsevier Inc.

General overview on structure prediction of twilight-zone proteins.

PubMed

Khor, Bee Yin; Tye, Gee Jun; Lim, Theam Soon; Choong, Yee Siew

2015-09-04

Protein structure prediction from amino acid sequence has been one of the most challenging aspects in computational structural biology despite significant progress in recent years showed by critical assessment of protein structure prediction (CASP) experiments. When experimentally determined structures are unavailable, the predictive structures may serve as starting points to study a protein. If the target protein consists of homologous region, high-resolution (typically <1.5 Å) model can be built via comparative modelling. However, when confronted with low sequence similarity of the target protein (also known as twilight-zone protein, sequence identity with available templates is less than 30%), the protein structure prediction has to be initiated from scratch. Traditionally, twilight-zone proteins can be predicted via threading or ab initio method. Based on the current trend, combination of different methods brings an improved success in the prediction of twilight-zone proteins. In this mini review, the methods, progresses and challenges for the prediction of twilight-zone proteins were discussed.

MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics.

PubMed

Egea, Jose A; Henriques, David; Cokelaer, Thomas; Villaverde, Alejandro F; MacNamara, Aidan; Danciu, Diana-Patricia; Banga, Julio R; Saez-Rodriguez, Julio

2014-05-10

Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools. We present MEIGO, an R and Matlab optimization toolbox (also available in Python via a wrapper of the R version), that implements metaheuristics capable of solving diverse problems arising in systems biology and bioinformatics. The toolbox includes the enhanced scatter search method (eSS) for continuous nonlinear programming (cNLP) and mixed-integer programming (MINLP) problems, and variable neighborhood search (VNS) for Integer Programming (IP) problems. Additionally, the R version includes BayesFit for parameter estimation by Bayesian inference. The eSS and VNS methods can be run on a single-thread or in parallel using a cooperative strategy. The code is supplied under GPLv3 and is available at http://www.iim.csic.es/~gingproc/meigo.html. Documentation and examples are included. The R package has been submitted to BioConductor. We evaluate MEIGO against optimization benchmarks, and illustrate its applicability to a series of case studies in bioinformatics and systems biology where it outperforms other state-of-the-art methods. MEIGO provides a free, open-source platform for optimization that can be applied to multiple domains of systems biology and bioinformatics. It includes efficient state of the art metaheuristics, and its open and modular structure allows the addition of further methods.

MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics

PubMed Central

2014-01-01

Background Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools. Results We present MEIGO, an R and Matlab optimization toolbox (also available in Python via a wrapper of the R version), that implements metaheuristics capable of solving diverse problems arising in systems biology and bioinformatics. The toolbox includes the enhanced scatter search method (eSS) for continuous nonlinear programming (cNLP) and mixed-integer programming (MINLP) problems, and variable neighborhood search (VNS) for Integer Programming (IP) problems. Additionally, the R version includes BayesFit for parameter estimation by Bayesian inference. The eSS and VNS methods can be run on a single-thread or in parallel using a cooperative strategy. The code is supplied under GPLv3 and is available at http://www.iim.csic.es/~gingproc/meigo.html. Documentation and examples are included. The R package has been submitted to BioConductor. We evaluate MEIGO against optimization benchmarks, and illustrate its applicability to a series of case studies in bioinformatics and systems biology where it outperforms other state-of-the-art methods. Conclusions MEIGO provides a free, open-source platform for optimization that can be applied to multiple domains of systems biology and bioinformatics. It includes efficient state of the art metaheuristics, and its open and modular structure allows the addition of further methods. PMID:24885957

Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions

PubMed Central

Putz, Mihai V.; Duda-Seiman, Corina; Duda-Seiman, Daniel; Putz, Ana-Maria; Alexandrescu, Iulia; Mernea, Maria; Avram, Speranta

2016-01-01

Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding) and quantitative (for predicting) mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR) offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD) as the revived precursor for comparative molecular field analyses (CoMFA) and comparative molecular similarity indices analysis (CoMSIA); all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio)thymine congeners’ (HEPT ligands) antiviral activity against Human Immunodeficiency Virus of first type (HIV-1) and new pharmacophores in treating severe genetic disorders (like depression and psychosis), respectively, all involving 3D pharmacophore interactions. PMID:27399692

Asymmetry at the molecular level in biology

NASA Astrophysics Data System (ADS)

Johnson, Louise N.

2005-10-01

Naturally occurring biological molecules are made of homochiral building blocks. Proteins are composed of L-amino acids (and not D-amino acids); nucleic acids such as DNA have D-ribose sugars (and not L-ribose sugars). It is not clear why nature selected a particular chirality. Selection could have occurred by chance or as a consequence of basic physical chemistry. Possible proposals, including the contribution of the parity violating the weak nuclear force, are discussed together with the mechanisms by which this very small contribution might be amplified. Homochirality of the amino acids has consequences for protein structure. Helices are right handed and beta sheets have a left-hand twist. When incorporated into the tertiary structure of a protein these chiralities limit the topologies of connections between helices and sheets. Polypeptides comprised of D-amino acids can be synthesized chemically and have been shown to adopt stable structures that are the mirror image of the naturally occurring L-amino acid polypeptides. Chirality is important in drug design. Three examples are discussed: penicillin; the CD4 antagonistic peptides; and thalidomide. The absolute hand of a biological structure can only be established by X-ray crystallographic methods using the technique of anomalous scattering.

LASER METHODS IN BIOLOGY: Optical anisotropy of fibrous biological tissues: analysis of the influence of structural properties

NASA Astrophysics Data System (ADS)

Zimnyakov, D. A.; Sinichkin, Yu P.; Ushakova, O. V.

2007-08-01

The results of theoretical analysis of the optical anisotropy of multiply scattering fibrillar biological tissues based on the model of an effective anisotropic medium are compared with the experimental in vivo birefringence data for the rat derma obtained earlier in spectral polarisation measurements of rat skin samples in the visible region. The disordered system of parallel dielectric cylinders embedded into an isotropic dielectric medium was considered as a model medium. Simulations were performed taking into account the influence of a partial mutual disordering of the bundles of collagen and elastin fibres in derma on birefringence in samples. The theoretical optical anisotropy averaged over the spectral interval 550-650 nm for the model medium with parameters corresponding to the structural parameters of derma is in good agreement with the results of spectral polarisation measurements of skin samples in the corresponding wavelength range.

Emerging opportunities in structural biology with X-ray free-electron lasers

PubMed Central

Schlichting, Ilme; Miao, Jianwei

2012-01-01

X-ray free-electron lasers (X-FELs) produce X-ray pulses with extremely brilliant peak intensity and ultrashort pulse duration. It has been proposed that radiation damage can be “outrun” by using an ultra intense and short X-FEL pulse that passes a biological sample before the onset of significant radiation damage. The concept of “diffraction-before-destruction” has been demonstrated recently at the Linac Coherent Light Source, the first operational hard X-ray FEL, for protein nanocrystals and giant virus particles. The continuous diffraction patterns from single particles allow solving the classical “phase problem” by the oversampling method with iterative algorithms. If enough data are collected from many identical copies of a (biological) particle, its three-dimensional structure can be reconstructed. We review the current status and future prospects of serial femtosecond crystallography (SFX) and single-particle coherent diffraction imaging (CDI) with X-FELs. PMID:22922042

Acenaphthenequinone thiosemicarbazone and its transition metal complexes: synthesis, structure, and biological activity.

PubMed

Rodriguez-Argüelles, M C; Belicchi Ferrari, M; Gasparri Fava, G; Pelizzi, C; Pelosi, G; Albertini, R; Bonati, A; Dall'Aglio, P P; Lunghi, P; Pinelli, S

1997-04-01

The reaction of iron, nickel, copper, and zinc chlorides or acetates with acenaphthenequinone thiosemicarbazone, Haqtsc leads to the formation of novel complexes that have been characterized by spectroscopic studies (NMR, IR) and biological properties. The crystal structures of the free ligand Haqtsc 1 and of the compound [Ni(aqtsc)2].DMF 2, have also been determined by X-ray methods from diffractometer data. In 1, the conformation of the two nonequivalent molecules is governed by intramolecular hydrogen bonds, while an intermolecular hydrogen bond is responsible for dimer-like groups formation. In 2, the coordination geometry about nickel is distorted octahedral, and the two ligand molecules are terdentate monodeprotonated. Biological studies have shown that, for the first time at least up the used doses, a free ligand is active both in the inhibition of cell proliferation and in the induced differentiation on Friend erythroleukemia cells (FLC).

Automated structure refinement of macromolecular assemblies from cryo-EM maps using Rosetta.

PubMed

Wang, Ray Yu-Ruei; Song, Yifan; Barad, Benjamin A; Cheng, Yifan; Fraser, James S; DiMaio, Frank

2016-09-26

Cryo-EM has revealed the structures of many challenging yet exciting macromolecular assemblies at near-atomic resolution (3-4.5Å), providing biological phenomena with molecular descriptions. However, at these resolutions, accurately positioning individual atoms remains challenging and error-prone. Manually refining thousands of amino acids - typical in a macromolecular assembly - is tedious and time-consuming. We present an automated method that can improve the atomic details in models that are manually built in near-atomic-resolution cryo-EM maps. Applying the method to three systems recently solved by cryo-EM, we are able to improve model geometry while maintaining the fit-to-density. Backbone placement errors are automatically detected and corrected, and the refinement shows a large radius of convergence. The results demonstrate that the method is amenable to structures with symmetry, of very large size, and containing RNA as well as covalently bound ligands. The method should streamline the cryo-EM structure determination process, providing accurate and unbiased atomic structure interpretation of such maps.

A survey of visual preprocessing and shape representation techniques

NASA Technical Reports Server (NTRS)

Olshausen, Bruno A.

1988-01-01

Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention).

3D Diffraction Microscope Provides a First Deep View

NASA Astrophysics Data System (ADS)

Miao, Jianwei

2005-03-01

When a coherent diffraction pattern is sampled at a spacing sufficiently finer than the Bragg peak frequency (i.e. the inverse of the sample size), the phase information is in principle encoded inside the diffraction pattern, and can be directly retrieved by using an iterative process. In combination of this oversampling phasing method with either coherent X-rays or electrons, a novel form of diffraction microscopy has recently been developed to image nanoscale materials and biological structures. In this talk, I will present the principle of the oversampling method, discuss the first experimental demonstration of this microscope, and illustrate some applications in nanoscience and biology.

Vertebrate Membrane Proteins: Structure, Function, and Insights from Biophysical Approaches

PubMed Central

MÜLLER, DANIEL J.; WU, NAN; PALCZEWSKI, KRZYSZTOF

2008-01-01

Membrane proteins are key targets for pharmacological intervention because they are vital for cellular function. Here, we analyze recent progress made in the understanding of the structure and function of membrane proteins with a focus on rhodopsin and development of atomic force microscopy techniques to study biological membranes. Membrane proteins are compartmentalized to carry out extra- and intracellular processes. Biological membranes are densely populated with membrane proteins that occupy approximately 50% of their volume. In most cases membranes contain lipid rafts, protein patches, or paracrystalline formations that lack the higher-order symmetry that would allow them to be characterized by diffraction methods. Despite many technical difficulties, several crystal structures of membrane proteins that illustrate their internal structural organization have been determined. Moreover, high-resolution atomic force microscopy, near-field scanning optical microscopy, and other lower resolution techniques have been used to investigate these structures. Single-molecule force spectroscopy tracks interactions that stabilize membrane proteins and those that switch their functional state; this spectroscopy can be applied to locate a ligand-binding site. Recent development of this technique also reveals the energy landscape of a membrane protein, defining its folding, reaction pathways, and kinetics. Future development and application of novel approaches during the coming years should provide even greater insights to the understanding of biological membrane organization and function. PMID:18321962

Quantitation of Permethylated N-Glycans through Multiple-Reaction Monitoring (MRM) LC-MS/MS

PubMed Central

Zhou, Shiyue; Hu, Yunli; DeSantos-Garcia, Janie L.; Mechref, Yehia

2015-01-01

The important biological roles of glycans and their implications in disease development and progression have created a demand for the development of sensitive quantitative glycomics methods. Quantitation of glycans existing at low abundance is still analytically challenging. In this study, an N-linked glycans quantitation method using multiple reaction monitoring (MRM) on a triple quadrupole instrument was developed. Optimum normalized collision energy (CE) for both sialylated and fucosylated N-glycan structures was determined to be 30% while it was found to be 35% for either fucosylated or sialylated structures The optimum CE for mannose and complex type N-glycan structures was determined to be 35%. Additionally, the use of three transitions was shown to facilitate reliable quantitation. A total of 88 N-glycan structures in human blood serum were quantified using this MRM approach. Reliable detection and quantitation of these structures was achieved when the equivalence of 0.005 μL of blood serum was analyzed. Accordingly, N-glycans down to the 100th of a μL level can be reliably quantified in pooled human blood serum, spanning a dynamic concentration range of three orders of magnitudes. MRM was also effectively utilized to quantitatively compare the expression of N-glycans derived from brain-targeting breast carcinoma cells (MDA-MB-231BR) and metastatic breast cancer cells (MDA-MB-231). Thus, the described MRM method of permethylated N-glycan structures enables a rapid and reliable identification and quantitation of glycans derived from glycoproteins purified or present in complex biological samples. PMID:25698222

Structure elucidation of two novel yak milk oligosaccharides and their DFT studies

NASA Astrophysics Data System (ADS)

Singh, Ashish Kumar; Ranjan, Ashok Kr.; Srivastava, Gaurav; Deepak, Desh

2016-03-01

Milk is a primary dynamic biological fluid responsible for development of neonates. Besides the other regular constituents it have oligosaccharides in it which are responsible for antitumor, anticancer, antigenic and immunostimulant activities. In our endeavor to find biologically active novel oligosaccharides, yak milk was taken, which is a rich source of oligosaccharide and its milk is used as antihypertensive, antioxidative and heart strengthening agent in folk medicine. For this purpose yak milk was processed by method of Kobata and Ginsburg followed by gel filtration HPLC and CC which resulted in the isolation of two novel milk oligosaccharides namely (I) Grunniose and (II) Vakose. The structure of purified milk oligosaccharides were elucidated with the help of chemical degradation, chemical transformation, spectroscopic techniques like NMR (1H, 13C and 2D-NMR), structure reporter group theory and mass spectrometry. The optimized geometry of compound Grunniose and Vakose, at B3LYP method and 6-311 + G basis set on Gaussian 09 program, show that the compound Grunniose is lower in energy as compared to compound Vakose.

Low-energy electron holographic imaging of individual tobacco mosaic virions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Longchamp, Jean-Nicolas, E-mail: longchamp@physik.uzh.ch; Latychevskaia, Tatiana; Escher, Conrad

2015-09-28

Modern structural biology relies on Nuclear Magnetic Resonance (NMR), X-ray crystallography, and cryo-electron microscopy for gaining information on biomolecules at nanometer, sub-nanometer, or atomic resolution. All these methods, however, require averaging over a vast ensemble of entities, and hence knowledge on the conformational landscape of an individual particle is lost. Unfortunately, there are now strong indications that even X-ray free electron lasers will not be able to image individual molecules but will require nanocrystal samples. Here, we show that non-destructive structural biology of single particles has now become possible by means of low-energy electron holography. As an example, individual tobaccomore » mosaic virions deposited on ultraclean freestanding graphene are imaged at 1 nm resolution revealing structural details arising from the helical arrangement of the outer protein shell of the virus. Since low-energy electron holography is a lens-less technique and since electrons with a deBroglie wavelength of approximately 1 Å do not impose radiation damage to biomolecules, the method has the potential for Angstrom resolution imaging of single biomolecules.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jeongho; Kim, Kyung Hwan; Oang, Key Young

Characterization of transient molecular structures formed during chemical and biological processes is essential for understanding their mechanisms and functions. Over the last decade, time-resolved X-ray liquidography (TRXL) and time-resolved X-ray absorption spectroscopy (TRXAS) have emerged as powerful techniques for molecular and electronic structural analysis of photoinduced reactions in the solution phase. Both techniques make use of a pump–probe scheme that consists of (1) an optical pump pulse to initiate a photoinduced process and (2) an X-ray probe pulse to monitor changes in the molecular structure as a function of time delay between pump and probe pulses. TRXL is sensitive tomore » changes in the global molecular structure and therefore can be used to elucidate structural changes of reacting solute molecules as well as the collective response of solvent molecules. On the other hand, TRXAS can be used to probe changes in both local geometrical and electronic structures of specific X-ray-absorbing atoms due to the element-specific nature of core-level transitions. These techniques are complementary to each other and a combination of the two methods will enhance the capability of accurately obtaining structural changes induced by photoexcitation. Here we review the principles of TRXL and TRXAS and present recent application examples of the two methods for studying chemical and biological processes in solution. Furthermore, we briefly discuss the prospect of using X-ray free electron lasers for the two techniques, which will allow us to keep track of structural dynamics on femtosecond time scales in various solution-phase molecular reactions.« less

Structure and composition of insulin fibril surfaces probed by TERS

PubMed Central

Kurouski, Dmitry; Deckert-Gaudig, Tanja; Deckert, Volker; Lednev, Igor K.

2012-01-01

Amyloid fibrils associated with many neurodegenerative diseases are the most intriguing targets of modern structural biology. Significant knowledge has been accumulated about the morphology and fibril-core structure recently. However, no conventional methods could probe the fibril surface despite its significant role in the biological activity. Tip-enhanced Raman spectroscopy (TERS) offers a unique opportunity to characterize the surface structure of an individual fibril due to a high depth and lateral spatial resolution of the method in the nanometer range. Here, TERS is utilized for characterizing the secondary structure and amino acid residue composition of the surface of insulin fibrils. It was found that the surface is strongly heterogeneous and consists of clusters with various protein conformations. More than 30% of the fibril surface is dominated by β-sheet secondary structure, further developing Dobson’s model of amyloid fibrils (Jimenez et al. Proc. Natl. Acad. Sci. USA 2002). The propensity of various amino acids on the fibril surface and specific surface secondary structure elements were evaluated. β-sheet areas are rich in cysteine and aromatic amino acids, such as phenylalanine and tyrosine, whereas proline was found only in α-helical and unordered protein clusters. In addition, we showed that carboxyl, amino and imino groups are nearly equally distributed over β-sheet and α-helix/unordered regions. Overall, this study provides valuable new information about the structure and composition of the insulin fibril surface and demonstrates the power of TERS for fibril characterization. PMID:22813355

On the state of crystallography at the dawn of the electron microscopy revolution.

PubMed

Higgins, Matthew K; Lea, Susan M

2017-10-01

While protein crystallography has, for many years, been the most used method for structural analysis of macromolecular complexes, remarkable recent advances in high-resolution electron cryo-microscopy led to suggestions that 'the revolution will not be crystallised'. Here we highlight the current success rate, speed and ease of modern crystallographic structure determination and some recent triumphs of both 'classical' crystallography and the use of X-ray free electron lasers. We also outline fundamental differences between structure determination using X-ray crystallography and electron microscopy. We suggest that crystallography will continue to co-exist with electron microscopy as part of an integrated array of methods, allowing structural biologists to focus on fundamental biological questions rather than being constrained by the methods available. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Recent Advances in the Synthesis and Stabilization of Nickel and Nickel Oxide Nanoparticles: A Green Adeptness

PubMed Central

Rani, Aneela

2016-01-01

Green protocols for the synthesis of nanoparticles have been attracting a lot of attention because they are eco-friendly, rapid, and cost-effective. Nickel and nickel oxide nanoparticles have been synthesized by green routes and characterized for impact of green chemistry on the properties and biological effects of nanoparticles in the last five years. Green synthesis, properties, and applications of nickel and nickel oxide nanoparticles have been reported in the literature. This review summarizes the synthesis of nickel and nickel oxide nanoparticles using different biological systems. This review also provides comparative overview of influence of chemical synthesis and green synthesis on structural properties of nickel and nickel oxide nanoparticles and their biological behavior. It concludes that green methods for synthesis of nickel and nickel oxide nanoparticles are better than chemical synthetic methods. PMID:27413375

Sequence co-evolution gives 3D contacts and structures of protein complexes

PubMed Central

Hopf, Thomas A; Schärfe, Charlotta P I; Rodrigues, João P G L M; Green, Anna G; Kohlbacher, Oliver; Sander, Chris; Bonvin, Alexandre M J J; Marks, Debora S

2014-01-01

Protein–protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein–protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein–protein interaction networks and used for interaction predictions at residue resolution. DOI: http://dx.doi.org/10.7554/eLife.03430.001 PMID:25255213

Experimental approaches to identify cellular G-quadruplex structures and functions.

PubMed

Di Antonio, Marco; Rodriguez, Raphaël; Balasubramanian, Shankar

2012-05-01

Guanine-rich nucleic acids can fold into non-canonical DNA secondary structures called G-quadruplexes. The formation of these structures can interfere with the biology that is crucial to sustain cellular homeostases and metabolism via mechanisms that include transcription, translation, splicing, telomere maintenance and DNA recombination. Thus, due to their implication in several biological processes and possible role promoting genomic instability, G-quadruplex forming sequences have emerged as potential therapeutic targets. There has been a growing interest in the development of synthetic molecules and biomolecules for sensing G-quadruplex structures in cellular DNA. In this review, we summarise and discuss recent methods developed for cellular imaging of G-quadruplexes, and the application of experimental genomic approaches to detect G-quadruplexes throughout genomic DNA. In particular, we will discuss the use of engineered small molecules and natural proteins to enable pull-down, ChIP-Seq, ChIP-chip and fluorescence imaging of G-quadruplex structures in cellular DNA. Copyright © 2012 Elsevier Inc. All rights reserved.

Climbing with adhesion: from bioinspiration to biounderstanding

PubMed Central

Cutkosky, Mark R.

2015-01-01

Bioinspiration is an increasingly popular design paradigm, especially as robots venture out of the laboratory and into the world. Animals are adept at coping with the variability that the world imposes. With advances in scientific tools for understanding biological structures in detail, we are increasingly able to identify design features that account for animals' robust performance. In parallel, advances in fabrication methods and materials are allowing us to engineer artificial structures with similar properties. The resulting robots become useful platforms for testing hypotheses about which principles are most important. Taking gecko-inspired climbing as an example, we show that the process of extracting principles from animals and adapting them to robots provides insights for both robotics and biology. PMID:26464786

Advanced techniques in placental biology -- workshop report.

PubMed

Nelson, D M; Sadovsky, Y; Robinson, J M; Croy, B A; Rice, G; Kniss, D A

2006-04-01

Major advances in placental biology have been realized as new technologies have been developed and existing methods have been refined in many areas of biological research. Classical anatomy and whole-organ physiology tools once used to analyze placental structure and function have been supplanted by more sophisticated techniques adapted from molecular biology, proteomics, and computational biology and bioinformatics. In addition, significant refinements in morphological study of the placenta and its constituent cell types have improved our ability to assess form and function in highly integrated manner. To offer an overview of modern technologies used by investigators to study the placenta, this workshop: Advanced techniques in placental biology, assembled experts who discussed fundamental principles and real time examples of four separate methodologies. Y. Sadovsky presented the principles of microRNA function as an endogenous mechanism of gene regulation. J. Robinson demonstrated the utility of correlative microscopy in which light-level and transmission electron microscopy are combined to provide cellular and subcellular views of placental cells. A. Croy provided a lecture on the use of microdissection techniques which are invaluable for isolating very small subsets of cell types for molecular analysis. Finally, G. Rice presented an overview methods on profiling of complex protein mixtures within tissue and/or fluid samples that, when refined, will offer databases that will underpin a systems approach to modern trophoblast biology.

Impact of computational structure-based methods on drug discovery.

PubMed

Reynolds, Charles H

2014-01-01

Structure-based drug design has become an indispensible tool in drug discovery. The emergence of structure-based design is due to gains in structural biology that have provided exponential growth in the number of protein crystal structures, new computational algorithms and approaches for modeling protein-ligand interactions, and the tremendous growth of raw computer power in the last 30 years. Computer modeling and simulation have made major contributions to the discovery of many groundbreaking drugs in recent years. Examples are presented that highlight the evolution of computational structure-based design methodology, and the impact of that methodology on drug discovery.

Detection of 224 candidate structured RNAs by comparative analysis of specific subsets of intergenic regions

PubMed Central

Lünse, Christina E.; Corbino, Keith A.; Ames, Tyler D.; Nelson, James W.; Roth, Adam; Perkins, Kevin R.; Sherlock, Madeline E.

2017-01-01

Abstract The discovery of structured non-coding RNAs (ncRNAs) in bacteria can reveal new facets of biology and biochemistry. Comparative genomics analyses executed by powerful computer algorithms have successfully been used to uncover many novel bacterial ncRNA classes in recent years. However, this general search strategy favors the discovery of more common ncRNA classes, whereas progressively rarer classes are correspondingly more difficult to identify. In the current study, we confront this problem by devising several methods to select subsets of intergenic regions that can concentrate these rare RNA classes, thereby increasing the probability that comparative sequence analysis approaches will reveal their existence. By implementing these methods, we discovered 224 novel ncRNA classes, which include ROOL RNA, an RNA class averaging 581 nt and present in multiple phyla, several highly conserved and widespread ncRNA classes with properties that suggest sophisticated biochemical functions and a multitude of putative cis-regulatory RNA classes involved in a variety of biological processes. We expect that further research on these newly found RNA classes will reveal additional aspects of novel biology, and allow for greater insights into the biochemistry performed by ncRNAs. PMID:28977401

COVARIANCE ESTIMATION USING CONJUGATE GRADIENT FOR 3D CLASSIFICATION IN CRYO-EM.

PubMed

Andén, Joakim; Katsevich, Eugene; Singer, Amit

2015-04-01

Classifying structural variability in noisy projections of biological macromolecules is a central problem in Cryo-EM. In this work, we build on a previous method for estimating the covariance matrix of the three-dimensional structure present in the molecules being imaged. Our proposed method allows for incorporation of contrast transfer function and non-uniform distribution of viewing angles, making it more suitable for real-world data. We evaluate its performance on a synthetic dataset and an experimental dataset obtained by imaging a 70S ribosome complex.

Entering an era of dynamic structural biology….

PubMed

Orville, Allen M

2018-05-31

A recent paper in BMC Biology presents a general method for mix-and-inject serial crystallography, to facilitate the visualization of enzyme intermediates via time-resolved serial femtosecond crystallography (tr-SFX). They apply their method to resolve in near atomic detail the cleavage and inactivation of the antibiotic ceftriaxone by a β-lactamase enzyme from Mycobacterium tuberculosis. Their work demonstrates the general applicability of time-resolved crystallography, from which dynamic structures, at atomic resolution, can be obtained.See research article: https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-018-0524-5 .

An inventory and evaluation of biological investigations that relate to stream-water quality in the upper Illinois River basin of Illinois, Indiana, and Wisconsin

USGS Publications Warehouse

Steffeck, D.W.; Striegl, Robert G.

1989-01-01

Results of studies of the aquatic biology of the upper Illinois River basin provide a historical data source from which inferences can be made about changes in the quality of water in the main stem river and its tributaries. The results of biological investigations that have been conducted throughout the basin since 1900 are summarized and their relevance to stream-water-quality assessment is described, particularly their relevance to the upper Illinois River basin pilot project for the National Water Quality Assessment program. Four general categories of biological investigations were identified: Populations and community structure, chemical concentrations in tissue, organism health, and toxicity measurements. Biological investigations were identified by their location in the basin and by their relevance to each general investigation category. The most abundant literature was in the populations and community structure category. Tissue data were limited to polychlorinated biphenyls, organochlorine pesticides, dioxin, and several metals. The most cited measure of organism health was a condition factor for fish that associates body length with weight or body depth. Toxicity measurements included bioassays and the Ames Tests. The bioassays included several testing methods and test organism. (USGS)

Modularization of biochemical networks based on classification of Petri net t-invariants.

PubMed

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.

Conception and development of the Second Life® Embryo Physics Course.

PubMed

Gordon, Richard

2013-06-01

The study of embryos with the tools and mindset of physics, started by Wilhelm His in the 1880s, has resumed after a hiatus of a century. The Embryo Physics Course convenes online allowing interested researchers and students, who are scattered around the world, to gather weekly in one place, the virtual world of Second Life®. It attracts people from a wide variety of disciplines and walks of life: applied mathematics, artificial life, bioengineering, biophysics, cancer biology, cellular automata, civil engineering, computer science, embryology, electrical engineering, evolution, finite element methods, history of biology, human genetics, mathematics, molecular developmental biology, molecular biology, nanotechnology, philosophy of biology, phycology, physics, self-reproducing systems, stem cells, tensegrity structures, theoretical biology, and tissue engineering. Now in its fifth year, the Embryo Physics Course provides a focus for research on the central question of how an embryo builds itself.

Evidence of pervasive biologically functional secondary structures within the genomes of eukaryotic single-stranded DNA viruses.

PubMed

Muhire, Brejnev Muhizi; Golden, Michael; Murrell, Ben; Lefeuvre, Pierre; Lett, Jean-Michel; Gray, Alistair; Poon, Art Y F; Ngandu, Nobubelo Kwanele; Semegni, Yves; Tanov, Emil Pavlov; Monjane, Adérito Luis; Harkins, Gordon William; Varsani, Arvind; Shepherd, Dionne Natalie; Martin, Darren Patrick

2014-02-01

Single-stranded DNA (ssDNA) viruses have genomes that are potentially capable of forming complex secondary structures through Watson-Crick base pairing between their constituent nucleotides. A few of the structural elements formed by such base pairings are, in fact, known to have important functions during the replication of many ssDNA viruses. Unknown, however, are (i) whether numerous additional ssDNA virus genomic structural elements predicted to exist by computational DNA folding methods actually exist and (ii) whether those structures that do exist have any biological relevance. We therefore computationally inferred lists of the most evolutionarily conserved structures within a diverse selection of animal- and plant-infecting ssDNA viruses drawn from the families Circoviridae, Anelloviridae, Parvoviridae, Nanoviridae, and Geminiviridae and analyzed these for evidence of natural selection favoring the maintenance of these structures. While we find evidence that is consistent with purifying selection being stronger at nucleotide sites that are predicted to be base paired than at sites predicted to be unpaired, we also find strong associations between sites that are predicted to pair with one another and site pairs that are apparently coevolving in a complementary fashion. Collectively, these results indicate that natural selection actively preserves much of the pervasive secondary structure that is evident within eukaryote-infecting ssDNA virus genomes and, therefore, that much of this structure is biologically functional. Lastly, we provide examples of various highly conserved but completely uncharacterized structural elements that likely have important functions within some of the ssDNA virus genomes analyzed here.

Evidence of Pervasive Biologically Functional Secondary Structures within the Genomes of Eukaryotic Single-Stranded DNA Viruses

PubMed Central

Muhire, Brejnev Muhizi; Golden, Michael; Murrell, Ben; Lefeuvre, Pierre; Lett, Jean-Michel; Gray, Alistair; Poon, Art Y. F.; Ngandu, Nobubelo Kwanele; Semegni, Yves; Tanov, Emil Pavlov; Monjane, Adérito Luis; Harkins, Gordon William; Varsani, Arvind; Shepherd, Dionne Natalie

2014-01-01

Single-stranded DNA (ssDNA) viruses have genomes that are potentially capable of forming complex secondary structures through Watson-Crick base pairing between their constituent nucleotides. A few of the structural elements formed by such base pairings are, in fact, known to have important functions during the replication of many ssDNA viruses. Unknown, however, are (i) whether numerous additional ssDNA virus genomic structural elements predicted to exist by computational DNA folding methods actually exist and (ii) whether those structures that do exist have any biological relevance. We therefore computationally inferred lists of the most evolutionarily conserved structures within a diverse selection of animal- and plant-infecting ssDNA viruses drawn from the families Circoviridae, Anelloviridae, Parvoviridae, Nanoviridae, and Geminiviridae and analyzed these for evidence of natural selection favoring the maintenance of these structures. While we find evidence that is consistent with purifying selection being stronger at nucleotide sites that are predicted to be base paired than at sites predicted to be unpaired, we also find strong associations between sites that are predicted to pair with one another and site pairs that are apparently coevolving in a complementary fashion. Collectively, these results indicate that natural selection actively preserves much of the pervasive secondary structure that is evident within eukaryote-infecting ssDNA virus genomes and, therefore, that much of this structure is biologically functional. Lastly, we provide examples of various highly conserved but completely uncharacterized structural elements that likely have important functions within some of the ssDNA virus genomes analyzed here. PMID:24284329

Computing the structural influence matrix for biological systems.

PubMed

Giordano, Giulia; Cuba Samaniego, Christian; Franco, Elisa; Blanchini, Franco

2016-06-01

We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics.

[BIOLOGICAL ACTIVITY OF ANTIMICROBIAL PEPTIDES FROM CHICKENS THROMBOCYTES].

PubMed

Sycheva, M V; Vasilchenko, A S; Rogozhin, E A; Pashkova, T M; Popova, L P; Kartashova, O L

2016-01-01

Isolation and study of biological activity of antimicrobial peptides from chickens thrombocytes. Peptides from chickens thrombocytes, obtained by reverse-phase high-performance liquid chromatography method with stepped and linear gradients of concentration increase of the organic solvent were used in the study. Their antimicrobial activity was determined by microtitration method in broth; mechanism of biological effect--by using fluorescent spectroscopy method with DNA-tropic dyes. Individual fractions of peptides were isolated from chickens thrombocytes, that possess antimicrobial activity against Staphylococcus aureus P209 and Escherichia coli K12. A disruption of integrity of barrier structures of microorganisms under the effect of thrombocyte antimicrobial peptides and predominance of cells with damaged membrane in the population of E. coli was established. The data obtained on antimicrobial activity and mechanism of bactericidal effect of the peptide fractions from chickens thrombocytes isolated for the first time expand the understanding of functional properties of chickens thrombocytes and open a perspective for their further study with the aim of use as antimicrobial means.

Scaling of Multimillion-Atom Biological Molecular Dynamics Simulation on a Petascale Supercomputer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schulz, Roland; Lindner, Benjamin; Petridis, Loukas

2009-01-01

A strategy is described for a fast all-atom molecular dynamics simulation of multimillion-atom biological systems on massively parallel supercomputers. The strategy is developed using benchmark systems of particular interest to bioenergy research, comprising models of cellulose and lignocellulosic biomass in an aqueous solution. The approach involves using the reaction field (RF) method for the computation of long-range electrostatic interactions, which permits efficient scaling on many thousands of cores. Although the range of applicability of the RF method for biomolecular systems remains to be demonstrated, for the benchmark systems the use of the RF produces molecular dipole moments, Kirkwood G factors,more » other structural properties, and mean-square fluctuations in excellent agreement with those obtained with the commonly used Particle Mesh Ewald method. With RF, three million- and five million atom biological systems scale well up to 30k cores, producing 30 ns/day. Atomistic simulations of very large systems for time scales approaching the microsecond would, therefore, appear now to be within reach.« less

Scaling of Multimillion-Atom Biological Molecular Dynamics Simulation on a Petascale Supercomputer.

PubMed

Schulz, Roland; Lindner, Benjamin; Petridis, Loukas; Smith, Jeremy C

2009-10-13

A strategy is described for a fast all-atom molecular dynamics simulation of multimillion-atom biological systems on massively parallel supercomputers. The strategy is developed using benchmark systems of particular interest to bioenergy research, comprising models of cellulose and lignocellulosic biomass in an aqueous solution. The approach involves using the reaction field (RF) method for the computation of long-range electrostatic interactions, which permits efficient scaling on many thousands of cores. Although the range of applicability of the RF method for biomolecular systems remains to be demonstrated, for the benchmark systems the use of the RF produces molecular dipole moments, Kirkwood G factors, other structural properties, and mean-square fluctuations in excellent agreement with those obtained with the commonly used Particle Mesh Ewald method. With RF, three million- and five million-atom biological systems scale well up to ∼30k cores, producing ∼30 ns/day. Atomistic simulations of very large systems for time scales approaching the microsecond would, therefore, appear now to be within reach.

Experiments in electron microscopy: from metals to nerves

NASA Astrophysics Data System (ADS)

Unwin, Nigel

2015-04-01

Electron microscopy has advanced remarkably as a tool for biological structure research since the development of methods to examine radiation-sensitive unstained specimens and the introduction of cryo-techniques. Structures of biological molecules at near-atomic resolution can now be obtained from images of single particles as well as crystalline arrays. It has also become possible to analyze structures of molecules in their functional context, i.e. in their natural membrane or cellular setting, and in an ionic environment like that in living tissue. Electron microscopy is thus opening ways to answer definitively questions about physiological mechanisms. Here I recall a number of experiments contributing to, and benefiting from the technical advances that have taken place. I begin—in the spirit of this crystallography series—with some biographical background, and then sketch the path to an analysis by time-resolved microscopy of the opening mechanism of an ion channel (nicotinic acetylcholine receptor). This analysis illustrates how electron imaging can be combined with freeze-trapping to illuminate a transient biological event: in our case, chemical-to-electrical transduction at the nerve-muscle synapse.

Stories of staying and leaving: A mixed methods analysis of biology undergraduate choice, persistence, and departure

NASA Astrophysics Data System (ADS)

Lang, Sarah Adrienne

Using a sequential, explanatory mixed methods design, this dissertation study compared students who persist in the biology major (persisters) with students who leave the biology major (switchers) in terms of how their pre-college experiences, college biology experiences, and biology performance figured into their choice of biology and their persistence in or departure from the biology major. This study combined (1) quantitative comparisons of biology persisters and switchers via a questionnaire developed for the study and survival analysis of a larger population of biology freshmen with (2) qualitative comparison of biology switchers and persisters via semi-structured life story interviews and homogenous focus groups. 319 students (207 persisters and 112 switchers) participated in the questionnaire and 36 students (20 persisters and 16 switchers) participated in life story and focus group interviews. All participants were undergraduates who entered The University of Texas at Austin as biology freshmen in the fall semesters of 2000 through 2004. Findings of this study suggest: (1) Regardless of eventual major, biology students enter college with generally the same suite of experiences, sources of personal encouragement, and reasons for choosing the biology major; (2) Despite the fact that they have also had poor experiences in the major, biology persisters do not actively decide to stay in the biology major; they simply do not leave; (3) Based upon survival analysis, biology students are most at-risk of leaving the biology major during the first two years of college and if they are African-American or Latino, women, or seeking a Bachelor of Arts degree (rather than a Bachelor of Science); (4) Biology switchers do not leave biology due to preference for other disciplines; they leave due to difficulties or dissatisfaction with aspects of the biology major, including their courses, faculty, and peers; (5) Biology performance has a differential effect on persistence in the biology major, depending on how well students perform in comparison to other courses or other students.

Enhancing multi-spot structured illumination microscopy with fluorescence difference

PubMed Central

Torkelsen, Frida H.

2018-01-01

Structured illumination microscopy is a super-resolution technique used extensively in biological research. However, this technique is limited in the maximum possible resolution increase. Here we report the results of simulations of a novel enhanced multi-spot structured illumination technique. This method combines the super-resolution technique of difference microscopy with structured illumination deconvolution. Initial results give at minimum a 1.4-fold increase in resolution over conventional structured illumination in a low-noise environment. This new technique also has the potential to be expanded to further enhance axial resolution with three-dimensional difference microscopy. The requirement for precise pattern determination in this technique also led to the development of a new pattern estimation algorithm which proved more efficient and reliable than other methods tested. PMID:29657751

Nonparametric Combinatorial Sequence Models

NASA Astrophysics Data System (ADS)

Wauthier, Fabian L.; Jordan, Michael I.; Jojic, Nebojsa

This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This paper presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three sequence datasets which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution induced by the prior. By integrating out the posterior our method compares favorably to leading binding predictors.

Microneedle arrays for biosensing and drug delivery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Joseph; Windmiller, Joshua Ray; Narayan, Roger

Methods, structures, and systems are disclosed for biosensing and drug delivery techniques. In one aspect, a^ device for detecting an analyte and/or releasing a biochemical into a biological fluid can include an array of hollowed needles, in which each needle includes a protruded needle structure including an exterior wall forming a hollow interior and an opening at a terminal end of the protruded needle structure that exposes the hollow interior, and a probe inside the exterior wall to interact with one or more chemical or biological substances that come in contact with the probe via the opening to produce amore » probe sensing signal, and an array of wires that are coupled to probes of the array of hollowed needles, respectively, each wire being electrically conductive to transmit the probe sensing signal produced by a respective probe.« less

Synthesis and biological assessment of 3,7-dihydroxytropolones.

PubMed

Hirsch, D R; Schiavone, D V; Berkowitz, A J; Morrison, L A; Masaoka, T; Wilson, J A; Lomonosova, E; Zhao, H; Patel, B S; Datla, S H; Hoft, S G; Majidi, S J; Pal, R K; Gallicchio, E; Tang, L; Tavis, J E; Le Grice, S F J; Beutler, J A; Murelli, R P

2017-12-19

3,7-Dihydroxytropolones (3,7-dHTs) are highly oxygenated troponoids that have been identified as lead compounds for several human diseases. To date, structure-function studies on these molecules have been limited due to a scarcity of synthetic methods for their preparation. New synthetic strategies towards structurally novel 3,7-dHTs would be valuable in further studying their therapeutic potential. Here we describe the successful adaptation of a [5 + 2] oxidopyrilium cycloaddition/ring-opening for 3,7-dHT synthesis, which we apply in the synthesis of a plausible biosynthetic intermediate to the natural products puberulic and puberulonic acid. We have also tested these new compounds in several biological assays related to human immunodeficiency virus (HIV), hepatitis B virus (HBV) and herpes simplex virus (HSV) in order to gain insight into structure-functional analysis related to antiviral troponoid development.

Mix-and-diffuse serial synchrotron crystallography

DOE PAGES

Beyerlein, Kenneth R.; Dierksmeyer, Dennis; Mariani, Valerio; ...

2017-10-09

Unravelling the interaction of biological macromolecules with ligands and substrates at high spatial and temporal resolution remains a major challenge in structural biology. The development of serial crystallography methods at X-ray free-electron lasers and subsequently at synchrotron light sources allows new approaches to tackle this challenge. Here, a new polyimide tape drive designed for mix-and-diffuse serial crystallography experiments is reported. The structure of lysozyme bound by the competitive inhibitor chitotriose was determined using this device in combination with microfluidic mixers. The electron densities obtained from mixing times of 2 and 50 s show clear binding of chitotriose to the enzymemore » at a high level of detail. Here, the success of this approach shows the potential for high-throughput drug screening and even structural enzymology on short timescales at bright synchrotron light sources.« less

Mix-and-diffuse serial synchrotron crystallography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beyerlein, Kenneth R.; Dierksmeyer, Dennis; Mariani, Valerio

Unravelling the interaction of biological macromolecules with ligands and substrates at high spatial and temporal resolution remains a major challenge in structural biology. The development of serial crystallography methods at X-ray free-electron lasers and subsequently at synchrotron light sources allows new approaches to tackle this challenge. Here, a new polyimide tape drive designed for mix-and-diffuse serial crystallography experiments is reported. The structure of lysozyme bound by the competitive inhibitor chitotriose was determined using this device in combination with microfluidic mixers. The electron densities obtained from mixing times of 2 and 50 s show clear binding of chitotriose to the enzymemore » at a high level of detail. Here, the success of this approach shows the potential for high-throughput drug screening and even structural enzymology on short timescales at bright synchrotron light sources.« less

Sesterterpenes as tubulin tyrosine ligase inhibitors. First insight of structure-activity relationships and discovery of new lead.

PubMed

Dal Piaz, Fabrizio; Vassallo, Antonio; Lepore, Laura; Tosco, Alessandra; Bader, Ammar; De Tommasi, Nunziatina

2009-06-25

Twenty-four new sesterterpenes, compounds 1-24, were isolated from the aerial parts of Salvia dominica. Their structures were elucidated by 1D and 2D NMR experiments as well as ESIMS analysis and chemical methods. The evaluation of the biological activity of Salvia dominica sesterterpenes by means of a panel of chemical and biological approaches, including chemical proteomics, surface plasmon resonance (SPR) measurements, and biochemical assays were realized. Obtained results showed that 18 out of the 24 sesterterpene lactones isolated from Salvia dominica interact with tubulin-tyrosine ligase (TTL) an enzyme involved in the tyrosination cycle of the C-terminal of tubulin, and inhibit TTL activity in cancer cells. Besides, results of our studies provided an activity/structure relationship that can be used to design effective TTL inhibitors.

Microneedle arrays for biosensing and drug delivery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Joseph; Windmiller, Joshua Ray; Narayan, Roger

Methods, structures, and systems are disclosed for biosensing and drug delivery techniques. In one aspect, a device for detecting an analyte and/or releasing a biochemical into a biological fluid can include an array of hollowed needles, in which each needle includes a protruded needle structure including an exterior wall forming a hollow interior and an opening at a terminal end of the protruded needle structure that exposes the hollow interior, and a probe inside the exterior wall to interact with one or more chemical or biological substances that come in contact with the probe via the opening to produce amore » probe sensing signal, and an array of wires that are coupled to probes of the array of hollowed needles, respectively, each wire being electrically conductive to transmit the probe sensing signal produced by a respective probe.« less

Mapping landscape corridors

Treesearch

Peter Vogt; Kurt H. Riitters; Marcin Iwanowski; Christine Estreguil; Jacek Kozak; Pierre Soille

2007-01-01

Corridors are important geographic features for biological conservation and biodiversity assessment. The identification and mapping of corridors is usually based on visual interpretations of movement patterns (functional corridors) or habitat maps (structural corridors). We present a method for automated corridor mapping with morphological image processing, and...

Comparative techno-economic analysis of steam explosion, dilute sulfuric acid, ammonia fiber explosion and biological pretreatments of corn stover.

PubMed

Baral, Nawa Raj; Shah, Ajay

2017-05-01

Pretreatment is required to destroy recalcitrant structure of lignocelluloses and then transform into fermentable sugars. This study assessed techno-economics of steam explosion, dilute sulfuric acid, ammonia fiber explosion and biological pretreatments, and identified bottlenecks and operational targets for process improvement. Techno-economic models of these pretreatment processes for a cellulosic biorefinery of 113.5 million liters butanol per year excluding fermentation and wastewater treatment sections were developed using a modelling software-SuperPro Designer. Experimental data of the selected pretreatment processes based on corn stover were gathered from recent publications, and used for this analysis. Estimated sugar production costs ($/kg) via steam explosion, dilute sulfuric acid, ammonia fiber explosion and biological methods were 0.43, 0.42, 0.65 and 1.41, respectively. The results suggest steam explosion and sulfuric acid pretreatment methods might be good alternatives at present state of technology and other pretreatment methods require research and development efforts to be competitive with these pretreatment methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Imaging of Vanadium in Microfossils: A New Potential Biosignature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marshall, Craig P.; Marshall, Alison Olcott; Aitken, Jade B.

Being able to distinguish unambiguously the biogenicity of microfossil-like structures in the ancient rock record is a fundamental predicament facing Archean paleobiologists and astrobiologists. Therefore, novel methods for discriminating biological from non-biological chemistries of microfossil-like structures are of the utmost importance in the search for evidence of early life on Earth. This too, is important for the search for life on Mars; either by in situ analyses via rovers, or sample return missions for future analysis here on Earth. Here, we report the application of synchrotron X-ray fluorescence imaging of vanadium, within thermally altered organic-walled microfossils of bona fide biologicalmore » origin. From our data, we demonstrate that vanadium is present within microfossils of undisputable biological origin. It is well known in the organic geochemistry literature, that elements such as vanadium are enriched and contained within crude oils, asphalts, and black shales that have been formed by diagensis of biological organic material. It has been demonstrated that the origin of vanadium is due to the diagenetic alteration of precursor chlorophyll and heme porphyrin pigment compounds from living organisms. Here, we propose that taken together, microfossil-like morphology, carbonaceous composition, and the presence of vanadium could be used in tandem as a biosignature to ascertain the biogenecity of putative microfossil-like structures.« less

Chemometric strategy for modeling metabolic biological space along the gastrointestinal tract and assessing microbial influences.

PubMed

Martin, François-Pierre J; Montoliu, Ivan; Kochhar, Sunil; Rezzi, Serge

2010-12-01

Over the past decade, the analysis of metabolic data with advanced chemometric techniques has offered the potential to explore functional relationships among biological compartments in relation to the structure and function of the intestine. However, the employed methodologies, generally based on regression modeling techniques, have given emphasis to region-specific metabolic patterns, while providing only limited insights into the spatiotemporal metabolic features of the complex gastrointestinal system. Hence, novel approaches are needed to analyze metabolic data to reconstruct the metabolic biological space associated with the evolving structures and functions of an organ such as the gastrointestinal tract. Here, we report the application of multivariate curve resolution (MCR) methodology to model metabolic relationships along the gastrointestinal compartments in relation to its structure and function using data from our previous metabonomic analysis. The method simultaneously summarizes metabolite occurrence and contribution to continuous metabolic signatures of the different biological compartments of the gut tract. This methodology sheds new light onto the complex web of metabolic interactions with gut symbionts that modulate host cell metabolism in surrounding gut tissues. In the future, such an approach will be key to provide new insights into the dynamic onset of metabolic deregulations involved in region-specific gastrointestinal disorders, such as Crohn's disease or ulcerative colitis.

Imaging of Vanadium in Microfossils: A New Potential Biosignature

DOE PAGES

Marshall, Craig P.; Marshall, Alison Olcott; Aitken, Jade B.; ...

2017-11-01

Being able to distinguish unambiguously the biogenicity of microfossil-like structures in the ancient rock record is a fundamental predicament facing Archean paleobiologists and astrobiologists. Therefore, novel methods for discriminating biological from non-biological chemistries of microfossil-like structures are of the utmost importance in the search for evidence of early life on Earth. This too, is important for the search for life on Mars; either by in situ analyses via rovers, or sample return missions for future analysis here on Earth. Here, we report the application of synchrotron X-ray fluorescence imaging of vanadium, within thermally altered organic-walled microfossils of bona fide biologicalmore » origin. From our data, we demonstrate that vanadium is present within microfossils of undisputable biological origin. It is well known in the organic geochemistry literature, that elements such as vanadium are enriched and contained within crude oils, asphalts, and black shales that have been formed by diagensis of biological organic material. It has been demonstrated that the origin of vanadium is due to the diagenetic alteration of precursor chlorophyll and heme porphyrin pigment compounds from living organisms. Here, we propose that taken together, microfossil-like morphology, carbonaceous composition, and the presence of vanadium could be used in tandem as a biosignature to ascertain the biogenecity of putative microfossil-like structures.« less

Imaging of Vanadium in Microfossils: A New Potential Biosignature

NASA Astrophysics Data System (ADS)

Marshall, Craig P.; Marshall, Alison Olcott; Aitken, Jade B.; Lai, Barry; Vogt, Stefan; Breuer, Pierre; Steemans, Philippe; Lay, Peter A.

2017-11-01

The inability to unambiguously distinguish the biogenicity of microfossil-like structures in the ancient rock record is a fundamental predicament facing Archean paleobiologists and astrobiologists. Therefore, novel methods for discriminating biological from nonbiological chemistries of microfossil-like structures are of the utmost importance in the search for evidence of early life on Earth. This, too, is important for the search for life on Mars by in situ analyses via rovers or sample return missions for future analysis here on Earth. Here, we report the application of synchrotron X-ray fluorescence imaging of vanadium, within thermally altered organic-walled microfossils of bona fide biological origin. From our data, we demonstrate that vanadium is present within microfossils of undisputable biological origin. It is well known in the organic geochemistry literature that elements such as vanadium are enriched and contained within crude oils, asphalts, and black shales that have been formed by diagenesis of biological organic material. It has been demonstrated that the origin of vanadium is due to the diagenetic alteration of precursor chlorophyll and heme porphyrin pigment compounds from living organisms. We propose that, taken together, microfossil-like morphology, carbonaceous composition, and the presence of vanadium could be used in tandem as a biosignature to ascertain the biogenicity of putative microfossil-like structures.

Gold nanostructures and methods of use

DOEpatents

Zhang, Jin Z [Santa Cruz, CA; Schwartzberg, Adam [Santa Cruz, CA; Olson, Tammy Y [Santa Cruz, CA

2012-03-20

The invention is drawn to novel nanostructures comprising hollow nanospheres and nanotubes for use as chemical sensors, conduits for fluids, and electronic conductors. The nanostructures can be used in microfluidic devices, for transporting fluids between devices and structures in analytical devices, for conducting electrical currents between devices and structure in analytical devices, and for conducting electrical currents between biological molecules and electronic devices, such as bio-microchips.

Gold nanostructures and methods of use

DOEpatents

Zhang, Jin Z.; Schwartzberg, Adam; Olson, Tammy Y.

2016-03-01

The invention is drawn to novel nanostructures comprising hollow nanospheres and nanotubes for use as chemical sensors, conduits for fluids, and electronic conductors. The nanostructures can be used in microfluidic devices, for transporting fluids between devices and structures in analytical devices, for conducting electrical currents between devices and structure in analytical devices, and for conducting electrical currents between biological molecules and electronic devices, such as bio-microchips.

LASER BIOLOGY: Peculiarities of studying an isolated neuron by the method of laser interference microscopy

NASA Astrophysics Data System (ADS)

Yusipovich, Alexander I.; Novikov, Sergey M.; Kazakova, Tatiana A.; Erokhova, Liudmila A.; Brazhe, Nadezda A.; Lazarev, Grigory L.; Maksimov, Georgy V.

2006-09-01

Actual aspects of using a new method of laser interference microscopy (LIM) for studying nerve cells are discussed. The peculiarities of the LIM display of neurons are demonstrated by the example of isolated neurons of a pond snail Lymnaea stagnalis. A comparative analysis of the images of the cell and subcellular structures of a neuron obtained by the methods of interference microscopy, optical transmission microscopy, and confocal microscopy is performed. Various aspects of the application of LIM for studying the lateral dimensions and internal structure of the cytoplasm and organelles of a neuron in cytology and cell physiology are discussed.

Time Hierarchies and Model Reduction in Canonical Non-linear Models

PubMed Central

Löwe, Hannes; Kremling, Andreas; Marin-Sanguino, Alberto

2016-01-01

The time-scale hierarchies of a very general class of models in differential equations is analyzed. Classical methods for model reduction and time-scale analysis have been adapted to this formalism and a complementary method is proposed. A unified theoretical treatment shows how the structure of the system can be much better understood by inspection of two sets of singular values: one related to the stoichiometric structure of the system and another to its kinetics. The methods are exemplified first through a toy model, then a large synthetic network and finally with numeric simulations of three classical benchmark models of real biological systems. PMID:27708665

Multifunctional 3D printing of heterogeneous hydrogel structures

NASA Astrophysics Data System (ADS)

Nadernezhad, Ali; Khani, Navid; Skvortsov, Gözde Akdeniz; Toprakhisar, Burak; Bakirci, Ezgi; Menceloglu, Yusuf; Unal, Serkan; Koc, Bahattin

2016-09-01

Multimaterial additive manufacturing or three-dimensional (3D) printing of hydrogel structures provides the opportunity to engineer geometrically dependent functionalities. However, current fabrication methods are mostly limited to one type of material or only provide one type of functionality. In this paper, we report a novel method of multimaterial deposition of hydrogel structures based on an aspiration-on-demand protocol, in which the constitutive multimaterial segments of extruded filaments were first assembled in liquid state by sequential aspiration of inks into a glass capillary, followed by in situ gel formation. We printed different patterned objects with varying chemical, electrical, mechanical, and biological properties by tuning process and material related parameters, to demonstrate the abilities of this method in producing heterogeneous and multi-functional hydrogel structures. Our results show the potential of proposed method in producing heterogeneous objects with spatially controlled functionalities while preserving structural integrity at the switching interface between different segments. We anticipate that this method would introduce new opportunities in multimaterial additive manufacturing of hydrogels for diverse applications such as biosensors, flexible electronics, tissue engineering and organ printing.

Multifunctional 3D printing of heterogeneous hydrogel structures

PubMed Central

Nadernezhad, Ali; Khani, Navid; Skvortsov, Gözde Akdeniz; Toprakhisar, Burak; Bakirci, Ezgi; Menceloglu, Yusuf; Unal, Serkan; Koc, Bahattin

2016-01-01

Multimaterial additive manufacturing or three-dimensional (3D) printing of hydrogel structures provides the opportunity to engineer geometrically dependent functionalities. However, current fabrication methods are mostly limited to one type of material or only provide one type of functionality. In this paper, we report a novel method of multimaterial deposition of hydrogel structures based on an aspiration-on-demand protocol, in which the constitutive multimaterial segments of extruded filaments were first assembled in liquid state by sequential aspiration of inks into a glass capillary, followed by in situ gel formation. We printed different patterned objects with varying chemical, electrical, mechanical, and biological properties by tuning process and material related parameters, to demonstrate the abilities of this method in producing heterogeneous and multi-functional hydrogel structures. Our results show the potential of proposed method in producing heterogeneous objects with spatially controlled functionalities while preserving structural integrity at the switching interface between different segments. We anticipate that this method would introduce new opportunities in multimaterial additive manufacturing of hydrogels for diverse applications such as biosensors, flexible electronics, tissue engineering and organ printing. PMID:27630079

Assembly of hydrogel units for 3D microenvironment in a poly(dimethylsiloxane) channel

NASA Astrophysics Data System (ADS)

Cho, Chang Hyun; Kwon, Seyong; Park, Je-Kyun

2017-12-01

Construction of three-dimensional (3D) microenvironment become an important issue in recent biological studies due to their biological relevance compared to conventional two-dimensional (2D) microenvironment. Various fabrication techniques have been employed to construct a 3D microenvironment, however, it is difficult to fully satisfy the biological and mechanical properties required for the 3D cell culture system, such as heterogeneous tissue structures generated from the functional differences or diseases. We propose here an assembly method for facile construction of 3D microenvironment in a poly(dimethylsiloxane) (PDMS) channel using hydrogel units. The high-aspect-ratio of hydrogel units was achieved by fabricating these units using a 2D mold. With this approach, 3D heterogeneous hydrogel units were produced and assembled in a PDMS channel by structural hookup. In vivo-like 3D heterogeneous microenvironment in a precisely controllable fluidic system was also demonstrated using a controlled assembly of different types of hydrogel units, which was difficult to obtain from previous methods. By regulating the flow condition, the mechanical stability of the assembled hydrogel units was verified by the flow-induced deformation of hydrogel units. In addition, in vivo-like cell culture environment was demonstrated using an assembly of cell-coated hydrogel units in the fluidic channel. Based on these features, our method expects to provide a beneficial tool for the 3D cell culture module and biomimetic engineering.

Solid-phase glycan isolation for glycomics analysis

PubMed Central

Yang, Shuang; Zhang, Hui

2013-01-01

Glycosylation is one of the most significant protein PTMs. The biological activities of proteins are dramatically changed by the glycans associated with them. Thus, structural analysis of the glycans of glycoproteins in complex biological or clinical samples is critical in correlation with the functions of glycans with diseases. Profiling of glycans by HPLC-MS is a commonly used technique in analyzing glycan structures and quantifying their relative abundance in different biological systems. Methods relied on MS require isolation of glycans from negligible salts and other contaminant ions since salts and ions may interfere with the glycans, resulting in poor glycan ionization. To accomplish those objectives, glycan isolation and clean-up methods including SPE, liquid-phase extraction, chromatography, and electrophoresis have been developed. Traditionally, glycans are isolated from proteins or peptides using a combination of hydrophobic and hydrophilic columns: proteins and peptides remain on hydrophobic absorbent while glycans, salts, and other hydrophilic reagents are collected as flowthrough. The glycans in the flowthrough are then purified through graphite-activated carbon column by hydrophilic interaction LC. Yet, the drawback in these affinity-based approaches is nonspecific binding. As a result, chemical methods by hydrazide or oxime have been developed for solid-phase isolation of glycans with high specificity and yield. Combined with high-resolution MS, specific glycan isolation techniques provide tremendous potentials as useful tools for glycomics analysis. PMID:23090885

Solid-phase glycan isolation for glycomics analysis.

PubMed

Yang, Shuang; Zhang, Hui

2012-12-01

Glycosylation is one of the most significant protein PTMs. The biological activities of proteins are dramatically changed by the glycans associated with them. Thus, structural analysis of the glycans of glycoproteins in complex biological or clinical samples is critical in correlation with the functions of glycans with diseases. Profiling of glycans by HPLC-MS is a commonly used technique in analyzing glycan structures and quantifying their relative abundance in different biological systems. Methods relied on MS require isolation of glycans from negligible salts and other contaminant ions since salts and ions may interfere with the glycans, resulting in poor glycan ionization. To accomplish those objectives, glycan isolation and clean-up methods including SPE, liquid-phase extraction, chromatography, and electrophoresis have been developed. Traditionally, glycans are isolated from proteins or peptides using a combination of hydrophobic and hydrophilic columns: proteins and peptides remain on hydrophobic absorbent while glycans, salts, and other hydrophilic reagents are collected as flowthrough. The glycans in the flowthrough are then purified through graphite-activated carbon column by hydrophilic interaction LC. Yet, the drawback in these affinity-based approaches is nonspecific binding. As a result, chemical methods by hydrazide or oxime have been developed for solid-phase isolation of glycans with high specificity and yield. Combined with high-resolution MS, specific glycan isolation techniques provide tremendous potentials as useful tools for glycomics analysis. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

MIANN models in medicinal, physical and organic chemistry.

PubMed

González-Díaz, Humberto; Arrasate, Sonia; Sotomayor, Nuria; Lete, Esther; Munteanu, Cristian R; Pazos, Alejandro; Besada-Porto, Lina; Ruso, Juan M

2013-01-01

Reducing costs in terms of time, animal sacrifice, and material resources with computational methods has become a promising goal in Medicinal, Biological, Physical and Organic Chemistry. There are many computational techniques that can be used in this sense. In any case, almost all these methods focus on few fundamental aspects including: type (1) methods to quantify the molecular structure, type (2) methods to link the structure with the biological activity, and others. In particular, MARCH-INSIDE (MI), acronym for Markov Chain Invariants for Networks Simulation and Design, is a well-known method for QSAR analysis useful in step (1). In addition, the bio-inspired Artificial-Intelligence (AI) algorithms called Artificial Neural Networks (ANNs) are among the most powerful type (2) methods. We can combine MI with ANNs in order to seek QSAR models, a strategy which is called herein MIANN (MI & ANN models). One of the first applications of the MIANN strategy was in the development of new QSAR models for drug discovery. MIANN strategy has been expanded to the QSAR study of proteins, protein-drug interactions, and protein-protein interaction networks. In this paper, we review for the first time many interesting aspects of the MIANN strategy including theoretical basis, implementation in web servers, and examples of applications in Medicinal and Biological chemistry. We also report new applications of the MIANN strategy in Medicinal chemistry and the first examples in Physical and Organic Chemistry, as well. In so doing, we developed new MIANN models for several self-assembly physicochemical properties of surfactants and large reaction networks in organic synthesis. In some of the new examples we also present experimental results which were not published up to date.

A simple method for identifying parameter correlations in partially observed linear dynamic models.

PubMed

Li, Pu; Vu, Quoc Dong

2015-12-14

Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a software packet.

How to integrate biological research into society and exclude errors in biomedical publications? Progress in theoretical and systems biology releases pressure on experimental research.

PubMed

Volkov, Vadim

2014-01-01

This brief opinion proposes measures to increase efficiency and exclude errors in biomedical research under the existing dynamic situation. Rapid changes in biology began with the description of the three dimensional structure of DNA 60 years ago; today biology has progressed by interacting with computer science and nanoscience together with the introduction of robotic stations for the acquisition of large-scale arrays of data. These changes have had an increasing influence on the entire research and scientific community. Future advance demands short-term measures to ensure error-proof and efficient development. They can include the fast publishing of negative results, publishing detailed methodical papers and excluding a strict connection between career progression and publication activity, especially for younger researchers. Further development of theoretical and systems biology together with the use of multiple experimental methods for biological experiments could also be helpful in the context of years and decades. With regards to the links between science and society, it is reasonable to compare both these systems, to find and describe specific features for biology and to integrate it into the existing stream of social life and financial fluxes. It will increase the level of scientific research and have mutual positive effects for both biology and society. Several examples are given for further discussion.

Structure of catalase determined by MicroED

PubMed Central

Nannenga, Brent L; Shi, Dan; Hattne, Johan; Reyes, Francis E; Gonen, Tamir

2014-01-01

MicroED is a recently developed method that uses electron diffraction for structure determination from very small three-dimensional crystals of biological material. Previously we used a series of still diffraction patterns to determine the structure of lysozyme at 2.9 Å resolution with MicroED (Shi et al., 2013). Here we present the structure of bovine liver catalase determined from a single crystal at 3.2 Å resolution by MicroED. The data were collected by continuous rotation of the sample under constant exposure and were processed and refined using standard programs for X-ray crystallography. The ability of MicroED to determine the structure of bovine liver catalase, a protein that has long resisted atomic analysis by traditional electron crystallography, demonstrates the potential of this method for structure determination. DOI: http://dx.doi.org/10.7554/eLife.03600.001 PMID:25303172

A method of online quantitative interpretation of diffuse reflection profiles of biological tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2013-02-01

We have developed a method of combined interpretation of spectral and spatial characteristics of diffuse reflection of biological tissues, which makes it possible to determine biophysical parameters of the tissue with a high accuracy in real time under conditions of their general variability. Using the Monte Carlo method, we have modeled a statistical ensemble of profiles of diffuse reflection coefficients of skin, which corresponds to a wave variation of its biophysical parameters. On its basis, we have estimated the retrieval accuracy of biophysical parameters using the developed method and investigated the stability of the method to errors of optical measurements. We have showed that it is possible to determine online the concentrations of melanin, hemoglobin, bilirubin, oxygen saturation of blood, and structural parameters of skin from measurements of its diffuse reflection in the spectral range 450-800 nm at three distances between the radiation source and detector.

Optimization of the molecular dynamics method for simulations of DNA and ion transport through biological nanopores.

PubMed

Wells, David B; Bhattacharya, Swati; Carr, Rogan; Maffeo, Christopher; Ho, Anthony; Comer, Jeffrey; Aksimentiev, Aleksei

2012-01-01

Molecular dynamics (MD) simulations have become a standard method for the rational design and interpretation of experimental studies of DNA translocation through nanopores. The MD method, however, offers a multitude of algorithms, parameters, and other protocol choices that can affect the accuracy of the resulting data as well as computational efficiency. In this chapter, we examine the most popular choices offered by the MD method, seeking an optimal set of parameters that enable the most computationally efficient and accurate simulations of DNA and ion transport through biological nanopores. In particular, we examine the influence of short-range cutoff, integration timestep and force field parameters on the temperature and concentration dependence of bulk ion conductivity, ion pairing, ion solvation energy, DNA structure, DNA-ion interactions, and the ionic current through a nanopore.

New Combinational Method for Noninvasive Treatments of Superficial Tissues for Body Aesthetics Applications

NASA Astrophysics Data System (ADS)

Rybyanets, A. N.; Naumenko, A. A.

The paper introduces an innovative combinational treatment method based on ultrasonic standing waves (USW) technology for noninvasive surgical, therapeutic, lypolitic or cosmetic treatment of tissues including subcutaneous adipose tissue, cellulite or skin on arbitrary body part of patient. The method is based on simultaneous or successive applying of constructively interfering physically and biologically sensed influences: USW, ultrasonic shear waves, radio-frequency (RF) heating, and vacuum massage. The paper provides basic physical principles of USW as well as critical comparison of USW and HIFU methods. The results of finite-elements and finite- difference modeling of USW transducer design and nodal pattern structure in tissue are presented. Biological effects of USW-tissue interaction and synergetic aspects of USW and RF combination are explored. Combinational treatment transducer designs and original in-vitro experiments on tissues are described.

Modeling Structure-Function Relationships in Synthetic DNA Sequences using Attribute Grammars

PubMed Central

Cai, Yizhi; Lux, Matthew W.; Adam, Laura; Peccoud, Jean

2009-01-01

Recognizing that certain biological functions can be associated with specific DNA sequences has led various fields of biology to adopt the notion of the genetic part. This concept provides a finer level of granularity than the traditional notion of the gene. However, a method of formally relating how a set of parts relates to a function has not yet emerged. Synthetic biology both demands such a formalism and provides an ideal setting for testing hypotheses about relationships between DNA sequences and phenotypes beyond the gene-centric methods used in genetics. Attribute grammars are used in computer science to translate the text of a program source code into the computational operations it represents. By associating attributes with parts, modifying the value of these attributes using rules that describe the structure of DNA sequences, and using a multi-pass compilation process, it is possible to translate DNA sequences into molecular interaction network models. These capabilities are illustrated by simple example grammars expressing how gene expression rates are dependent upon single or multiple parts. The translation process is validated by systematically generating, translating, and simulating the phenotype of all the sequences in the design space generated by a small library of genetic parts. Attribute grammars represent a flexible framework connecting parts with models of biological function. They will be instrumental for building mathematical models of libraries of genetic constructs synthesized to characterize the function of genetic parts. This formalism is also expected to provide a solid foundation for the development of computer assisted design applications for synthetic biology. PMID:19816554

Microarray missing data imputation based on a set theoretic framework and biological knowledge.

PubMed

Gan, Xiangchao; Liew, Alan Wee-Chung; Yan, Hong

2006-01-01

Gene expressions measured using microarrays usually suffer from the missing value problem. However, in many data analysis methods, a complete data matrix is required. Although existing missing value imputation algorithms have shown good performance to deal with missing values, they also have their limitations. For example, some algorithms have good performance only when strong local correlation exists in data while some provide the best estimate when data is dominated by global structure. In addition, these algorithms do not take into account any biological constraint in their imputation. In this paper, we propose a set theoretic framework based on projection onto convex sets (POCS) for missing data imputation. POCS allows us to incorporate different types of a priori knowledge about missing values into the estimation process. The main idea of POCS is to formulate every piece of prior knowledge into a corresponding convex set and then use a convergence-guaranteed iterative procedure to obtain a solution in the intersection of all these sets. In this work, we design several convex sets, taking into consideration the biological characteristic of the data: the first set mainly exploit the local correlation structure among genes in microarray data, while the second set captures the global correlation structure among arrays. The third set (actually a series of sets) exploits the biological phenomenon of synchronization loss in microarray experiments. In cyclic systems, synchronization loss is a common phenomenon and we construct a series of sets based on this phenomenon for our POCS imputation algorithm. Experiments show that our algorithm can achieve a significant reduction of error compared to the KNNimpute, SVDimpute and LSimpute methods.

Recent developments on ultrasound-assisted one-pot multicomponent synthesis of biologically relevant heterocycles.

PubMed

Banerjee, Bubun

2017-03-01

Heterocycles are the backbone of organic compounds. Specially, N- &O-containing heterocycles represent privileged structural subunits well distributed in naturally occurring compounds with immense biological activities. Multicomponent reactions (MCRs) are becoming valuable tool for synthesizing structurally diverse molecular entities. On the other hand, the last decade has seen a tremendous outburst in modifying chemical processes to make them sustainable for the betterment of our environment. The application of ultrasound in organic synthesis is fulfilling some of the goals of 'green and sustainable chemistry' as it has some advantages over the traditional thermal methods in terms of reaction rates, yields, purity of the products, product selectivity, etc. Therefore the synthesis of biologically relevant heterocycles using one-pot multi-component technique coupled with the application of ultrasound is one of the thrusting areas in the 21st Century among the organic chemists. The present review deals with the "up to date" developments on ultrasound assisted one-pot multi-component synthesis of biologically relevant heterocycles reported so far. Copyright © 2016 Elsevier B.V. All rights reserved.

Raman imaging at biological interfaces: applications in breast cancer diagnosis.

PubMed

Surmacki, Jakub; Musial, Jacek; Kordek, Radzislaw; Abramczyk, Halina

2013-05-24

One of the most important areas of Raman medical diagnostics is identification and characterization of cancerous and noncancerous tissues. The methods based on Raman scattering has shown significant potential for probing human breast tissue to provide valuable information for early diagnosis of breast cancer. A vibrational fingerprint from the biological tissue provides information which can be used to identify, characterize and discriminate structures in breast tissue, both in the normal and cancerous environment. The paper reviews recent progress in understanding structure and interactions at biological interfaces of the human tissue by using confocal Raman imaging and IR spectroscopy. The important differences between the noncancerous and cancerous human breast tissues were found in regions characteristic for vibrations of carotenoids, fatty acids, proteins, and interfacial water. Particular attention was paid to the role played by unsaturated fatty acids and their derivatives as well as carotenoids and interfacial water. We demonstrate that Raman imaging has reached a clinically relevant level in regard to breast cancer diagnosis applications. The results presented in the paper may have serious implications on understanding mechanisms of interactions in living cells under realistically crowded conditions of biological tissue.

Conference Report: ESF-COST High-Level Research Conference Natural Products Chemistry, Biology and Medicine III.

PubMed

Catino, Arthur

2010-12-01

Natural Products Chemistry, Biology and Medicine III was the third conference in a series of events sponsored by the European Science Foundation (ESF) and the European Cooperation in the field of Scientific and Technical Research (COST). Scientists came together from within and outside the EU to present cutting-edge developments in chemical synthesis. Research areas included the synthesis of natural products, methods development, isolation/structural elucidation and chemical biology. As our capacity to produce new chemotherapeutic agents relies on chemical synthesis, this year's conference has never been so timely. This report highlights several of the scientific contributions presented during the meeting.

Peptide radioimmunoassays in clinical medicine.

PubMed

Geokas, M C; Yalow, R S; Straus, E W; Gold, E M

1982-09-01

The radioimmunoassay technique, first developed for the determination of hormones, has been applied to many substances of biologic interest by clinical and research laboratories around the world. It has had an enormous effect in medicine and biology as a diagnostic tool, a guide to therapy, and a probe for the fine structure of biologic systems. For instance, the assays of insulin, gastrin, secretin, prolactin, and certain tissue-specific enzymes have been invaluable in patient care. Further refinements of current methods, as well as the emergence of new immunoassay techniques, are expected to enhance precision, specificity, reliability, and convenience of the radioimmunoassay in both clinical and research laboratories.

Physico-chemical properties and cytotoxic effects of sugar-based surfactants: Impact of structural variations.

PubMed

Lu, Biao; Vayssade, Muriel; Miao, Yong; Chagnault, Vincent; Grand, Eric; Wadouachi, Anne; Postel, Denis; Drelich, Audrey; Egles, Christophe; Pezron, Isabelle

2016-09-01

Surfactants derived from the biorefinery process can present interesting surface-active properties, low cytotoxicity, high biocompatibility and biodegradability. They are therefore considered as potential sustainable substitutes to currently used petroleum-based surfactants. To better understand and anticipate their performances, structure-property relationships need to be carefully investigated. For this reason, we applied a multidisciplinary approach to systematically explore the effect of subtle structural variations on both physico-chemical properties and biological effects. Four sugar-based surfactants, each with an eight carbon alkyl chain bound to a glucose or maltose head group by an amide linkage, were synthesized and evaluated together along with two commercially available standard surfactants. Physico-chemical properties including solubility, Krafft point, surface-tension lowering and critical micellar concentration (CMC) in water and biological medium were explored. Cytotoxicity evaluation by measuring proliferation index and metabolic activity against dermal fibroblasts showed that all surfactants studied may induce cell death at low concentrations (below their CMC). Results revealed significant differences in both physico-chemical properties and cytotoxic effects depending on molecule structural features, such as the position of the linkage on the sugar head-group, or the orientation of the amide linkage. Furthermore, the cytotoxic response increased with the reduction of surfactant CMC. This study underscores the relevance of a methodical and multidisciplinary approach that enables the consideration of surfactant solution properties when applied to biological materials. Overall, our results will contribute to a better understanding of the concomitant impact of surfactant structure at physico-chemical and biological levels. Copyright © 2016 Elsevier B.V. All rights reserved.

Personalized Biobehavioral HIV Prevention for Women and Adolescent Girls

PubMed Central

Teitelman, Anne M.; Bevilacqua, Amanda W.; Jemmott, Loretta Sweet

2013-01-01

Background: Women and adolescent girls bear a significant burden of the global HIV pandemic. Both behavioral and biomedical prevention approaches have been shown to be effective. In order to foster the most effective combination HIV-prevention approaches for women and girls, it is imperative to understand the unique biological, social, and structural considerations that increase vulnerability to acquiring HIV within this population. Primary Study Objective: The purpose of this article is to propose novel ideas for personalized biobehavioral HIV prevention for women and adolescent girls. The central argument is that we must transcend unilevel solutions for HIV prevention toward comprehensive, multilevel combination HIV prevention packages to actualize personalized biobehavioral HIV prevention. Our hope is to foster transnational dialogue among researchers, practitioners, educators, and policy makers toward the actualization of the proposed recommendations. Methods: We present a commentary organized to review biological, social, and structural factors that increase vulnerability to HIV acquisition among women and adolescent girls. The overview is followed by recommendations to curb HIV rates in the target population in a sustainable manner. Results: The physiology of the lower female reproductive system biologically increases HIV risk among women and girls. Social (eg, intimate partner violence) and structural (eg, gender inequality) factors exacerbate this risk by increasing the likelihood of viral exposure. Our recommendations for personalized biobehavioral HIV prevention are to (1) create innovative mechanisms for personalized HIV risk—reduction assessments; (2) develop mathematical models of local epidemics; (3) prepare personalized, evidence-based combination HIV risk—reduction packages; (4) structure gender equity into society; and (5) eliminate violence (both physical and structural) against women and girls. Conclusions: Generalized programs and interventions may not have universal, transnational, and crosscultural implications. Personalized biobehavioral strategies are needed to comprehensively address vulnerabilities at biological, social, and structural levels. PMID:24416702

Smiles2Monomers: a link between chemical and biological structures for polymers.

PubMed

Dufresne, Yoann; Noé, Laurent; Leclère, Valérie; Pupin, Maude

2015-01-01

The monomeric composition of polymers is powerful for structure comparison and synthetic biology, among others. Many databases give access to the atomic structure of compounds but the monomeric structure of polymers is often lacking. We have designed a smart algorithm, implemented in the tool Smiles2Monomers (s2m), to infer efficiently and accurately the monomeric structure of a polymer from its chemical structure. Our strategy is divided into two steps: first, monomers are mapped on the atomic structure by an efficient subgraph-isomorphism algorithm ; second, the best tiling is computed so that non-overlapping monomers cover all the structure of the target polymer. The mapping is based on a Markovian index built by a dynamic programming algorithm. The index enables s2m to search quickly all the given monomers on a target polymer. After, a greedy algorithm combines the mapped monomers into a consistent monomeric structure. Finally, a local branch and cut algorithm refines the structure. We tested this method on two manually annotated databases of polymers and reconstructed the structures de novo with a sensitivity over 90 %. The average computation time per polymer is 2 s. s2m automatically creates de novo monomeric annotations for polymers, efficiently in terms of time computation and sensitivity. s2m allowed us to detect annotation errors in the tested databases and to easily find the accurate structures. So, s2m could be integrated into the curation process of databases of small compounds to verify the current entries and accelerate the annotation of new polymers. The full method can be downloaded or accessed via a website for peptide-like polymers at http://bioinfo.lifl.fr/norine/smiles2monomers.jsp.Graphical abstract:.

Computational analysis of conserved RNA secondary structure in transcriptomes and genomes.

PubMed

Eddy, Sean R

2014-01-01

Transcriptomics experiments and computational predictions both enable systematic discovery of new functional RNAs. However, many putative noncoding transcripts arise instead from artifacts and biological noise, and current computational prediction methods have high false positive rates. I discuss prospects for improving computational methods for analyzing and identifying functional RNAs, with a focus on detecting signatures of conserved RNA secondary structure. An interesting new front is the application of chemical and enzymatic experiments that probe RNA structure on a transcriptome-wide scale. I review several proposed approaches for incorporating structure probing data into the computational prediction of RNA secondary structure. Using probabilistic inference formalisms, I show how all these approaches can be unified in a well-principled framework, which in turn allows RNA probing data to be easily integrated into a wide range of analyses that depend on RNA secondary structure inference. Such analyses include homology search and genome-wide detection of new structural RNAs.

A base-modified PNA-graphene oxide platform as a turn-on fluorescence sensor for the detection of human telomeric repeats

NASA Astrophysics Data System (ADS)

Sabale, Pramod M.; George, Jerrin Thomas; Srivatsan, Seergazhi G.

2014-08-01

Given the biological and therapeutic significance of telomeres and other G-quadruplex forming sequences in human genome, it is highly desirable to develop simple methods to study these structures, which can also be implemented in screening formats for the discovery of G-quadruplex binders. The majority of telomere detection methods developed so far are laborious and use elaborate assay and instrumental setups, and hence, are not amenable to discovery platforms. Here, we describe the development of a simple homogeneous fluorescence turn-on method, which uses a unique combination of an environment-sensitive fluorescent nucleobase analogue, the superior base pairing property of PNA, and DNA-binding and fluorescence quenching properties of graphene oxide, to detect human telomeric DNA repeats of varying lengths. Our results demonstrate that this method, which does not involve a rigorous assay setup, would provide new opportunities to study G-quadruplex structures.Given the biological and therapeutic significance of telomeres and other G-quadruplex forming sequences in human genome, it is highly desirable to develop simple methods to study these structures, which can also be implemented in screening formats for the discovery of G-quadruplex binders. The majority of telomere detection methods developed so far are laborious and use elaborate assay and instrumental setups, and hence, are not amenable to discovery platforms. Here, we describe the development of a simple homogeneous fluorescence turn-on method, which uses a unique combination of an environment-sensitive fluorescent nucleobase analogue, the superior base pairing property of PNA, and DNA-binding and fluorescence quenching properties of graphene oxide, to detect human telomeric DNA repeats of varying lengths. Our results demonstrate that this method, which does not involve a rigorous assay setup, would provide new opportunities to study G-quadruplex structures. Electronic supplementary information (ESI) available. Figures, tables, experimental procedures and NMR spectra. See DOI: 10.1039/c4nr00878b

Digital X-ray camera for quality evaluation three-dimensional topographic reconstruction of single crystals of biological macromolecules

NASA Technical Reports Server (NTRS)

Borgstahl, Gloria (Inventor); Lovelace, Jeff (Inventor); Snell, Edward Holmes (Inventor); Bellamy, Henry (Inventor)

2008-01-01

The present invention provides a digital topography imaging system for determining the crystalline structure of a biological macromolecule, wherein the system employs a charge coupled device (CCD) camera with antiblooming circuitry to directly convert x-ray signals to electrical signals without the use of phosphor and measures reflection profiles from the x-ray emitting source after x-rays are passed through a sample. Methods for using said system are also provided.

State-of-the-art technologies, current opinions and developments, and novel findings: news from the field of histochemistry and cell biology.

PubMed

Asan, Esther; Drenckhahn, Detlev

2008-12-01

Investigations of cell and tissue structure and function using innovative methods and approaches have again yielded numerous exciting findings in recent months and have added important data to current knowledge, inspiring new ideas and hypotheses in various fields of modern life sciences. Topics and contents of comprehensive expert reviews covering different aspects in methodological advances, cell biology, tissue function and morphology, and novel findings reported in original papers are summarized in the present review.

Two-Dimensional Spectroscopy Is Being Used to Address Core Scientific Questions in Biology and Materials Science.

PubMed

Petti, Megan K; Lomont, Justin P; Maj, Michał; Zanni, Martin T

2018-02-15

Two-dimensional spectroscopy is a powerful tool for extracting structural and dynamic information from a wide range of chemical systems. We provide a brief overview of the ways in which two-dimensional visible and infrared spectroscopies are being applied to elucidate fundamental details of important processes in biological and materials science. The topics covered include amyloid proteins, photosynthetic complexes, ion channels, photovoltaics, batteries, as well as a variety of promising new methods in two-dimensional spectroscopy.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Unkelbach, Jan, E-mail: junkelbach@mgh.harvard.edu; Botas, Pablo; Faculty of Physics, Ruprecht-Karls-Universität Heidelberg, Heidelberg

Purpose: We describe a treatment plan optimization method for intensity modulated proton therapy (IMPT) that avoids high values of linear energy transfer (LET) in critical structures located within or near the target volume while limiting degradation of the best possible physical dose distribution. Methods and Materials: To allow fast optimization based on dose and LET, a GPU-based Monte Carlo code was extended to provide dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dosemore » objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of LET and physical dose (LET×D). To first approximation, LET×D represents a measure of the additional biological dose that is caused by high LET. Results: The method is effective for treatments where serial critical structures with maximum dose constraints are located within or near the target. We report on 5 patients with intracranial tumors (high-grade meningiomas, base-of-skull chordomas, ependymomas) in whom the target volume overlaps with the brainstem and optic structures. In all cases, high LET×D in critical structures could be avoided while minimally compromising physical dose planning objectives. Conclusion: LET-based reoptimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose-based and relative biological effectiveness (RBE)-based planning. The method makes IMPT treatments safer by mitigating a potentially increased risk of side effects resulting from elevated RBE of proton beams near the end of range.« less

Motion estimation of subcellular structures from fluorescence microscopy images.

PubMed

Vallmitjana, A; Civera-Tregon, A; Hoenicka, J; Palau, F; Benitez, R

2017-07-01

We present an automatic image processing framework to study moving intracellular structures from live cell fluorescence microscopy. The system includes the identification of static and dynamic structures from time-lapse images using data clustering as well as the identification of the trajectory of moving objects with a probabilistic tracking algorithm. The method has been successfully applied to study mitochondrial movement in neurons. The approach provides excellent performance under different experimental conditions and is robust to common sources of noise including experimental, molecular and biological fluctuations.

Image Analysis of DNA Fiber and Nucleus in Plants.

PubMed

Ohmido, Nobuko; Wako, Toshiyuki; Kato, Seiji; Fukui, Kiichi

2016-01-01

Advances in cytology have led to the application of a wide range of visualization methods in plant genome studies. Image analysis methods are indispensable tools where morphology, density, and color play important roles in the biological systems. Visualization and image analysis methods are useful techniques in the analyses of the detailed structure and function of extended DNA fibers (EDFs) and interphase nuclei. The EDF is the highest in the spatial resolving power to reveal genome structure and it can be used for physical mapping, especially for closely located genes and tandemly repeated sequences. One the other hand, analyzing nuclear DNA and proteins would reveal nuclear structure and functions. In this chapter, we describe the image analysis protocol for quantitatively analyzing different types of plant genome, EDFs and interphase nuclei.

Estimating 3-dimensional colony surface area of field corals

EPA Science Inventory

Colony surface area is a critical descriptor for biological and physical attributes of reef-building (scleractinian, stony) corals. The three-dimensional (3D) size and structure of corals are directly related to many ecosystem values and functions. Most methods to estimate colony...

ADVANCED COMPUTATIONAL METHODS IN DOSE MODELING: APPLICATION OF COMPUTATIONAL BIOPHYSICAL TRANSPORT, COMPUTATIONAL CHEMISTRY, AND COMPUTATIONAL BIOLOGY

EPA Science Inventory

Computational toxicology (CompTox) leverages the significant gains in computing power and computational techniques (e.g., numerical approaches, structure-activity relationships, bioinformatics) realized over the last few years, thereby reducing costs and increasing efficiency i...

Decompositions of large-scale biological systems based on dynamical properties.

PubMed

Soranzo, Nicola; Ramezani, Fahimeh; Iacono, Giovanni; Altafini, Claudio

2012-01-01

Given a large-scale biological network represented as an influence graph, in this article we investigate possible decompositions of the network aimed at highlighting specific dynamical properties. The first decomposition we study consists in finding a maximal directed acyclic subgraph of the network, which dynamically corresponds to searching for a maximal open-loop subsystem of the given system. Another dynamical property investigated is strong monotonicity. We propose two methods to deal with this property, both aimed at decomposing the system into strongly monotone subsystems, but with different structural characteristics: one method tends to produce a single large strongly monotone component, while the other typically generates a set of smaller disjoint strongly monotone subsystems. Original heuristics for the methods investigated are described in the article. altafini@sissa.it

Directional acceleration vector-driven displacement of fluids (DAVD-DOF)

NASA Technical Reports Server (NTRS)

Clarke, Mark S. F. (Inventor); Feeback, Daniel L. (Inventor)

2004-01-01

Centrifugal analyzer and method for staining biological or non-biological samples in microgravity, wherein the method utilizes an increase in weight of a fluid sample as a function of g-load, to overcome cohesive and frictional forces from preventing its movement in a preselected direction. Apparatus is characterized by plural specimen reservoirs and channels in a slide, each channel being of differing cross-section, wherein respective samples are selectively dispensed, from the reservoirs in response to an imposed g-factor, precedent to sample staining. Within the method, one thus employs microscope slides which define channels, each being of a differing cross-section dimension relative to others. In combination therewith, centrifugal slide mounting apparatus controllably imposes g-vectors of differing magnitudes within a defined structure of the centrifuge such as a chip array.

Research Associate | Center for Cancer Research

Cancer.gov

PROGRAM DESCRIPTION The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). KEY ROLES/RESPONSIBILITIES - Research Associate III Dr. Zbigniew Dauter is the head investigator of the Synchrotron Radiation Research Section (SRRS) of CCR’s Macromolecular Crystallography Laboratory. The Synchrotron Radiation Research Section is located at Argonne National Laboratory, Argonne, Illinois; this is the site of the largest U.S. synchrotron facility. The SRRS uses X-ray diffraction technique to solve crystal structures of various proteins and nucleic acids of biological and medical relevance. The section is also specializing in analyzing crystal structures at extremely high resolution and accuracy and in developing methods of effective diffraction data collection and in using weak anomalous dispersion effects to solve structures of macromolecules. The areas of expertise are: Structural and molecular biology Macromolecular crystallography Diffraction data collection Dr. Dauter requires research support in these areas, and the individual will engage in the purification and preparation of samples, crystallize proteins using various techniques, and derivatize them with heavy atoms/anomalous scatterers, and establish conditions for cryogenic freezing. Individual will also participate in diffraction data collection at the Advanced Photon Source. In addition, the candidate will perform spectroscopic and chromatographic analyses of protein and nucleic acid samples in the context of their purity, oligomeric state and photophysical properties.

Insects as model systems in cell biology.

PubMed

Keil, Thomas A; Steinbrecht, R Alexander

2010-01-01

For almost 100 years, insects have been favorable "model systems" in biology. Just to mention a few examples: fruit flies in genetics and developmental biology; bugs and caterpillars in hormone research; houseflies, blowflies, and locusts in neurobiology; silk moths in pheromone research; honeybees and crickets in neuroethology. For more than 50 years the electron microscope (EM) has been a valuable tool in analyzing the structure of cells and organs of these creatures. However, progress in specimen preparation was relatively slow compared with mammalian material and, in 1970, it was taken for granted that insects were much more difficult to fix than mammals. Since then, methods have dramatically improved, and satisfactory results can now be obtained routinely with chemical as well as cryofixation. In this chapter we briefly demonstrate what can be achieved with insect material, and help the researcher to find the most appropriate method for her/his systems and scientific questions. Copyright © 2010 Elsevier Inc. All rights reserved.

A simple method of fabricating mask-free microfluidic devices for biological analysis

PubMed Central

Yi, Xin; Kodzius, Rimantas; Gong, Xiuqing; Xiao, Kang; Wen, Weijia

2010-01-01

We report a simple, low-cost, rapid, and mask-free method to fabricate two-dimensional (2D) and three-dimensional (3D) microfluidic chip for biological analysis researches. In this fabrication process, a laser system is used to cut through paper to form intricate patterns and differently configured channels for specific purposes. Bonded with cyanoacrylate-based resin, the prepared paper sheet is sandwiched between glass slides (hydrophilic) or polymer-based plates (hydrophobic) to obtain a multilayer structure. In order to examine the chip’s biocompatibility and applicability, protein concentration was measured while DNA capillary electrophoresis was carried out, and both of them show positive results. With the utilization of direct laser cutting and one-step gas-sacrificing techniques, the whole fabrication processes for complicated 2D and 3D microfluidic devices are shorten into several minutes which make it a good alternative of poly(dimethylsiloxane) microfluidic chips used in biological analysis researches. PMID:20890452

Improved measurements of RNA structure conservation with generalized centroid estimators.

PubMed

Okada, Yohei; Saito, Yutaka; Sato, Kengo; Sakakibara, Yasubumi

2011-01-01

Identification of non-protein-coding RNAs (ncRNAs) in genomes is a crucial task for not only molecular cell biology but also bioinformatics. Secondary structures of ncRNAs are employed as a key feature of ncRNA analysis since biological functions of ncRNAs are deeply related to their secondary structures. Although the minimum free energy (MFE) structure of an RNA sequence is regarded as the most stable structure, MFE alone could not be an appropriate measure for identifying ncRNAs since the free energy is heavily biased by the nucleotide composition. Therefore, instead of MFE itself, several alternative measures for identifying ncRNAs have been proposed such as the structure conservation index (SCI) and the base pair distance (BPD), both of which employ MFE structures. However, these measurements are unfortunately not suitable for identifying ncRNAs in some cases including the genome-wide search and incur high false discovery rate. In this study, we propose improved measurements based on SCI and BPD, applying generalized centroid estimators to incorporate the robustness against low quality multiple alignments. Our experiments show that our proposed methods achieve higher accuracy than the original SCI and BPD for not only human-curated structural alignments but also low quality alignments produced by CLUSTAL W. Furthermore, the centroid-based SCI on CLUSTAL W alignments is more accurate than or comparable with that of the original SCI on structural alignments generated with RAF, a high quality structural aligner, for which twofold expensive computational time is required on average. We conclude that our methods are more suitable for genome-wide alignments which are of low quality from the point of view on secondary structures than the original SCI and BPD.

Improving consensus structure by eliminating averaging artifacts

PubMed Central

KC, Dukka B

2009-01-01

Background Common structural biology methods (i.e., NMR and molecular dynamics) often produce ensembles of molecular structures. Consequently, averaging of 3D coordinates of molecular structures (proteins and RNA) is a frequent approach to obtain a consensus structure that is representative of the ensemble. However, when the structures are averaged, artifacts can result in unrealistic local geometries, including unphysical bond lengths and angles. Results Herein, we describe a method to derive representative structures while limiting the number of artifacts. Our approach is based on a Monte Carlo simulation technique that drives a starting structure (an extended or a 'close-by' structure) towards the 'averaged structure' using a harmonic pseudo energy function. To assess the performance of the algorithm, we applied our approach to Cα models of 1364 proteins generated by the TASSER structure prediction algorithm. The average RMSD of the refined model from the native structure for the set becomes worse by a mere 0.08 Å compared to the average RMSD of the averaged structures from the native structure (3.28 Å for refined structures and 3.36 A for the averaged structures). However, the percentage of atoms involved in clashes is greatly reduced (from 63% to 1%); in fact, the majority of the refined proteins had zero clashes. Moreover, a small number (38) of refined structures resulted in lower RMSD to the native protein versus the averaged structure. Finally, compared to PULCHRA [1], our approach produces representative structure of similar RMSD quality, but with much fewer clashes. Conclusion The benchmarking results demonstrate that our approach for removing averaging artifacts can be very beneficial for the structural biology community. Furthermore, the same approach can be applied to almost any problem where averaging of 3D coordinates is performed. Namely, structure averaging is also commonly performed in RNA secondary prediction [2], which could also benefit from our approach. PMID:19267905

Bacterial biomarkers thermally released from dissolved organic matter

USGS Publications Warehouse

Greenwood, P.F.; Leenheer, J.A.; McIntyre, C.; Berwick, L.; Franzmann, P.D.

2006-01-01

Hopane biomarker products were detected using microscale sealed vessel (MSSV) pyrolysis gas chromatography-mass spectrometry (GC-MS) analysis of dissolved organic matter from natural aquatic systems colonised by bacterial populations. MSSV pyrolysis can reduce the polyhydroxylated alkyl side chain of bacteriohopanepolyols, yielding saturated hopane products which are more amenable to GC-MS detection than their functionalised precursors. This example demonstrates how the thermal conditions of MSSV pyrolysis can reduce the biologically-inherited structural functionality of naturally occurring organic matter such that additional structural fragments can be detected using GC methods. This approach complements traditional analytical pyrolysis methods by providing additional speciation information useful for establishing the structures and source inputs of recent or extant organic material. ?? 2006.

Rapid Fabrication of Cell-Laden Alginate Hydrogel 3D Structures by Micro Dip-Coating.

PubMed

Ghanizadeh Tabriz, Atabak; Mills, Christopher G; Mullins, John J; Davies, Jamie A; Shu, Wenmiao

2017-01-01

Development of a simple, straightforward 3D fabrication method to culture cells in 3D, without relying on any complex fabrication methods, remains a challenge. In this paper, we describe a new technique that allows fabrication of scalable 3D cell-laden hydrogel structures easily, without complex machinery: the technique can be done using only apparatus already available in a typical cell biology laboratory. The fabrication method involves micro dip-coating of cell-laden hydrogels covering the surface of a metal bar, into the cross-linking reagents calcium chloride or barium chloride to form hollow tubular structures. This method can be used to form single layers with thickness ranging from 126 to 220 µm or multilayered tubular structures. This fabrication method uses alginate hydrogel as the primary biomaterial and a secondary biomaterial can be added depending on the desired application. We demonstrate the feasibility of this method, with survival rate over 75% immediately after fabrication and normal responsiveness of cells within these tubular structures using mouse dermal embryonic fibroblast cells and human embryonic kidney 293 cells containing a tetracycline-responsive, red fluorescent protein (tHEK cells).

Materiomics: biological protein materials, from nano to macro.

PubMed

Cranford, Steven; Buehler, Markus J

2010-11-12

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics - discovering Nature's complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature's materials have been hindered by our lack of fundamental understanding of these materials' intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure-property-process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering.

Anti-friction performance of FeS nanoparticle synthesized by biological method

NASA Astrophysics Data System (ADS)

Zhou, Lu Hai; Wei, Xi Cheng; Ma, Zi Jian; Mei, Bin

2017-06-01

FeS nanoparticle is prepared by a biological method. The size, morphology and structure of the FeS nanoparticle are characterized by the means of X-ray diffraction and transmission electron microscopy. The anti-friction behavior of the FeS nanoparticle as a lubricating oil additive is evaluated in the engine oil by using a face-to-face contact mode. The worn surface is characterized by using the scanning electron microscopy and secondary ion mass spectroscopy in order to find the reasons resulting in the reduction of friction coefficient due to the addition of the FeS nanoparticle. The anti-friction mechanism of the FeS nanoparticle is elucidated based on the experimental results.

How good can cryo-EM become?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glaeser, Robert M.

The suddenness with which single-particle cryo-electron microscopy (cryo-EM) has emerged as a method for determining high-resolution structures of biological macromolecules invites the questions, how much better can this technology get, and how fast is that likely to happen? While we can rightly celebrate the maturation of cryo-EM as a high-resolution structure-determination tool, I believe there still are many developments to look forward to.

Three Dimensional Object Recognition Using an Unsupervised Neural Network: Understanding the Distinguishing Features

DTIC Science & Technology

1992-12-23

predominance of structural models of recognition, of which a recent example is the Recognition By Components (RBC) theory ( Biederman , 1987 ). Structural...related to recent statistical theory (Huber, 1985; Friedman, 1987 ) and is derived from a biologically motivated computational theory (Bienenstock et...dimensional object recognition (Intrator and Gold, 1991). The method is related to recent statistical theory (Huber, 1985; Friedman, 1987 ) and is derived

Knowledge and Theme Discovery across Very Large Biological Data Sets Using Distributed Queries: A Prototype Combining Unstructured and Structured Data

PubMed Central

Repetski, Stephen; Venkataraman, Girish; Che, Anney; Luke, Brian T.; Girard, F. Pascal; Stephens, Robert M.

2013-01-01

As the discipline of biomedical science continues to apply new technologies capable of producing unprecedented volumes of noisy and complex biological data, it has become evident that available methods for deriving meaningful information from such data are simply not keeping pace. In order to achieve useful results, researchers require methods that consolidate, store and query combinations of structured and unstructured data sets efficiently and effectively. As we move towards personalized medicine, the need to combine unstructured data, such as medical literature, with large amounts of highly structured and high-throughput data such as human variation or expression data from very large cohorts, is especially urgent. For our study, we investigated a likely biomedical query using the Hadoop framework. We ran queries using native MapReduce tools we developed as well as other open source and proprietary tools. Our results suggest that the available technologies within the Big Data domain can reduce the time and effort needed to utilize and apply distributed queries over large datasets in practical clinical applications in the life sciences domain. The methodologies and technologies discussed in this paper set the stage for a more detailed evaluation that investigates how various data structures and data models are best mapped to the proper computational framework. PMID:24312478

Knowledge and theme discovery across very large biological data sets using distributed queries: a prototype combining unstructured and structured data.

PubMed

Mudunuri, Uma S; Khouja, Mohamad; Repetski, Stephen; Venkataraman, Girish; Che, Anney; Luke, Brian T; Girard, F Pascal; Stephens, Robert M

2013-01-01

As the discipline of biomedical science continues to apply new technologies capable of producing unprecedented volumes of noisy and complex biological data, it has become evident that available methods for deriving meaningful information from such data are simply not keeping pace. In order to achieve useful results, researchers require methods that consolidate, store and query combinations of structured and unstructured data sets efficiently and effectively. As we move towards personalized medicine, the need to combine unstructured data, such as medical literature, with large amounts of highly structured and high-throughput data such as human variation or expression data from very large cohorts, is especially urgent. For our study, we investigated a likely biomedical query using the Hadoop framework. We ran queries using native MapReduce tools we developed as well as other open source and proprietary tools. Our results suggest that the available technologies within the Big Data domain can reduce the time and effort needed to utilize and apply distributed queries over large datasets in practical clinical applications in the life sciences domain. The methodologies and technologies discussed in this paper set the stage for a more detailed evaluation that investigates how various data structures and data models are best mapped to the proper computational framework.

Biological and functional relevance of CASP predictions

PubMed Central

Liu, Tianyun; Ish‐Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D.

2017-01-01

Abstract Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo‐sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo‐sites), and Ten sites containing important motifs, loops, or key residues with important disease‐associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best‐ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand‐binding sites, most prediction methods have higher performance on apo‐sites than holo‐sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein‐protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein‐protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. PMID:28975675