SwissSidechain: a molecular and structural database of non-natural sidechains.

Amino acids form the building blocks of all proteins. Naturally occurring amino acids are restricted to a few tens of sidechains, even when considering post-translational modifications and rare amino acids such as selenocysteine and pyrrolysine. However, the potential chemical diversity of amino acid sidechains is nearly infinite. Exploiting this diversity by using non-natural sidechains to expand the building blocks of proteins and peptides has recently found widespread applications in biochemistry, protein engineering and drug design. Despite these applications, there is currently no unified online bioinformatics resource for non-natural sidechains. With the SwissSidechain database (http://www.swisssidechain.ch), we offer a central and curated platform about non-natural sidechains for researchers in biochemistry, medicinal chemistry, protein engineering and molecular modeling. SwissSidechain provides biophysical, structural and molecular data for hundreds of commercially available non-natural amino acid sidechains, both in l- and d-configurations. The database can be easily browsed by sidechain names, families or physico-chemical properties. We also provide plugins to seamlessly insert non-natural sidechains into peptides and proteins using molecular visualization software, as well as topologies and parameters compatible with molecular mechanics software.

Integración de visualización científica molecular en el salón de clases

For some years, Chemistry teachers have used scientific visualization software of molecular models in computing rooms and chemistry laboratories for educational purposes. However, its application in classrooms has been limited. This article describes the integration and use of computer programs for scientific molecular visualization in a traditional classroom. We consider that the improvement of technical aspects of their application and use (usability) has a direct effect on students' understanding of molecular structures (including students' extrinsic motivation), among other factors. Consequently, we developed a guide for the integration of hardware and software of molecular visualization for its use in the classroom.

Estudio de usabilidad de visualización molecular educativa en un teléfono inteligente

Chemistry students have difficulty understanding molecular structures and their functions. To aide their comprehension, molecular visualization software has been developed to run on smart phones, but in order to positively influence learning it must have a high degree of usability (usability measures how software is used in terms of efficiency, efficacy and satisfaction). This paper describes a usability study of molecular visualization software running on a smart phone, where chemistry students analyzed molecular models. Results showed very good usability and 95% of students wanted to use it in further classes.

Molecular dynamics computer simulation of scratch resistance testing of polymers: visualization

Experimental scratch resistance testing provides two numbers: the penetration depth Rp and the healing depth Rh. In molecular dynamics computer simulations, we create a material consisting of N statistical chain segments by polymerization; a reinforcing phase can be included. Then we simulate the movement of an indenter and response of the segments during X time steps. Each segment at each time step has three Cartesian coordinates of position and three of momentum. We describe methods of visualization of results based on a record of 6NX coordinates. We obtain a continuous dependence on time t of positions of each of the segments on the path of the indenter. Scratch resistance at a given location can be connected to spatial structures of individual polymeric chains.

The BioDICE Taverna plugin for clustering and visualization of biological data: a workflow for molecular compounds exploration

Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets.

Neutron-mapping polymer flow: Scattering, flow visualization, and molecular theory

Flows of complex fluids need to be understood at both macroscopic and molecular scales, because it is the macroscopic response that controls the fluid behavior, but the molecular scale that ultimately gives rise to rheological and solid-state properties. Here the flow field of an entangled polymer melt through an extended contraction, typical of many polymer processes, is imaged optically and by small-angle neutron scattering. The dual-probe technique samples both the macroscopic stress field in the flow and the microscopic configuration of the polymer molecules at selected points. The results are compared with a recent tube model molecular theory of entangled melt flow that is able to calculate both the stress and the single-chain structure factor from first principles. The combined action of the three fundamental entangled processes of reptation, contour length fluctuation, and convective constraint release is essential to account quantitatively for the rich rheological behavior. The multiscale approach unearths a new feature: Orientation at the length scale of the entire chain decays considerably more slowly than at the smaller entanglement length.

Visualization of molecular fingerprints

A visualization plot of a data set of molecular data is a useful tool for gaining insight into a set of molecules. In chemoinformatics, most visualization plots are of molecular descriptors, and the statistical model most often used to produce a visualization is principal component analysis (PCA). This paper takes PCA, together with four other statistical models (NeuroScale, GTM, LTM, and LTM-LIN), and evaluates their ability to produce clustering in visualizations not of molecular descriptors but of molecular fingerprints. Two different tasks are addressed: understanding structural information (particularly combinatorial libraries) and relating structure to activity. The quality of the visualizations is compared both subjectively (by visual inspection) and objectively (with global distance comparisons and local k-nearest-neighbor predictors). On the data sets used to evaluate clustering by structure, LTM is found to perform significantly better than the other models. In particular, the clusters in LTM visualization space are consistent with the relationships between the core scaffolds that define the combinatorial sublibraries. On the data sets used to evaluate clustering by activity, LTM again gives the best performance but by a smaller margin. The results of this paper demonstrate the value of using both a nonlinear projection map and a Bernoulli noise model for modeling binary data.

On The Distinct Molecular Architectures Of Dipping- And Spray-lbl Films Containing Lipid Vesicles.

The introduction of spraying procedures to fabricate layer-by-layer (LbL) films has brought new possibilities for the control of molecular architectures and for making the LbL technique compliant with industrial processes. In this study we show that significantly distinct architectures are produced for dipping and spray-LbL films of the same components, which included DODAB/DPPG vesicles. The films differed notably in their thickness and stratified nature. The electrical response of the two types of films to aqueous solutions containing erythrosin was also different. With multidimensional projections we showed that the impedance for the DODAB/DPPG spray-LbL film is more sensitive to changes in concentration, being therefore more promising as sensing units. Furthermore, with surface-enhanced Raman scattering (SERS) we could ascribe the high sensitivity of the LbL films to adsorption of erythrosin.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Three-dimensional visualization of human hemoglobin phenotypes with HPLC

Hemoglobinopathies were included in the Brazilian Neonatal Screening Program on June 6, 2001. Automated high-performance liquid chromatography (HPLC) was indicated as one of the diagnostic methods. The amount of information generated by these systems is immense, and the behavior of groups cannot always be observed in individual analyses. Three-dimensional (3-D) visualization techniques can be applied to extract this information, for extracting patterns, trends or relations from the results stored in databases. We applied the 3-D visualization tool to analyze patterns in the results of hemoglobinopathy based on neonatal diagnosis by HPLC. The laboratory results of 2520 newborn analyses carried out in 2001 and 2002 were used. The ""Fast"", ""F1"", ""F"" and ""A"" peaks, which were detected by the analytical system, were chosen as attributes for mapping. To establish a behavior pattern, the results were classified into groups according to hemoglobin phenotype: normal (N = 2169), variant (N = 73) and thalassemia (N = 279). 3-D visualization was made with the FastMap DB tool; there were two distribution patterns in the normal group, due to variation in the amplitude of the values obtained by HPLC for the F1 window. It allowed separation of the samples with normal Hb from those with alpha thalassemia, based on a significant difference (P < 0.05) between the mean values of the ""Fast"" and ""A"" peaks, demonstrating the need for better evaluation of chromatograms; this method could be used to help diagnose alpha thalassemia in newborns.

Localization of Pantoea ananatis inside lesions of maize White Spot Disease using transmission electron microscopy and molecular techniques

The etiological agent of maize white spot (MWS) disease has been a subject of controversy and discussion. Initially the disease was described as Phaeosphaeria leaf spot caused by Phaeosphaeria maydis. Other authors have Suggested the existence of different fungal species causing similar symptoms. Recently, a bacterium, Pantoea ananatis, was described as the causal agent of this disease. The purpose of this Study was to offer additional information on the correct etiology of this disease by providing visual evidence of the presence of the bacterium in the interior of the MWS lesions by using transmission electron microscopy (TEM) and molecular techniques. The TEM allowed Visualization of a large amount of bacteria in the intercellular spaces of lesions collected from both artificially and naturally infected plants. Fungal structures were not visualized in young lesions. Bacterial primers for the 16S rRNA and rpoB genes were used in PCR reactions to amplify DNA extracted from water-soaked (young) and necrotic lesions. The universal fungal oligonucleotide ITS4 was also included to identity the possible presence of fungal structures inside lesions. Positive PCR products from water-soaked lesions, both from naturally and artificially inoculated plants, were produced with bacterial primers, whereas no amplification was observed when ITS4 oligonucleotide was used. On the other hand, DNA amplification with ITS4 primer was observed when DNA was isolated from necrotic (old) lesions. These results reinforced previous report of P. ananatis as the primary pathogen and the hypothesis that fungal species may colonize lesions pre-established by P. ananatis.

Expanding molecular modeling and design tools to non-natural sidechains.

Protein-protein interactions encode the wiring diagram of cellular signaling pathways and their deregulations underlie a variety of diseases, such as cancer. Inhibiting protein-protein interactions with peptide derivatives is a promising way to develop new biological and therapeutic tools. Here, we develop a general framework to computationally handle hundreds of non-natural amino acid sidechains and predict the effect of inserting them into peptides or proteins. We first generate all structural files (pdb and mol2), as well as parameters and topologies for standard molecular mechanics software (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non-natural sidechains are useful to increase peptide ligand binding affinity. Our results obtained on non-natural mutants of a BCL9 peptide targeting beta-catenin show very good correlation between predicted and experimental binding free-energies, indicating that such predictions can be used to design new inhibitors. Data generated in this work, as well as PyMOL and UCSF Chimera plug-ins for user-friendly visualization of non-natural sidechains, are all available at http://www.swisssidechain.ch. Our results enable researchers to rapidly and efficiently work with hundreds of non-natural sidechains.

Insertion of green fluorescent protein into nonstructural protein 5A allows direct visualization of functional hepatitis C virus replication complexes.

Hepatitis C virus (HCV) replicates its genome in a membrane-associated replication complex, composed of viral proteins, replicating RNA and altered cellular membranes. We describe here HCV replicons that allow the direct visualization of functional HCV replication complexes. Viable replicons selected from a library of Tn7-mediated random insertions in the coding sequence of nonstructural protein 5A (NS5A) allowed the identification of two sites near the NS5A C terminus that tolerated insertion of heterologous sequences. Replicons encoding green fluorescent protein (GFP) at these locations were only moderately impaired for HCV RNA replication. Expression of the NS5A-GFP fusion protein could be demonstrated by immunoblot, indicating that the GFP was retained during RNA replication and did not interfere with HCV polyprotein processing. More importantly, expression levels were robust enough to allow direct visualization of the fusion protein by fluorescence microscopy. NS5A-GFP appeared as brightly fluorescing dot-like structures in the cytoplasm. By confocal laser scanning microscopy, NS5A-GFP colocalized with other HCV nonstructural proteins and nascent viral RNA, indicating that the dot-like structures, identified as membranous webs by electron microscopy, represent functional HCV replication complexes. These findings reveal an unexpected flexibility of the C-terminal domain of NS5A and provide tools for studying the formation and turnover of HCV replication complexes in living cells.

Cerebellar cortical layers: in vivo visualization with structural high-field-strength MR imaging.

Purpose: To perform in vivo imaging of the cerebellum with an in-plane resolution of 120 mm to observe its cortical granular and molecular layers by taking advantage of the high signal-to-noise ratio and the increased magnetic susceptibility-related contrast available at high magnetic field strength such as 7 T. Materials and Methods: The study was approved by the institutional review board, and all patients provided written consent. Three healthy persons (two men, one woman; mean age, 30 years; age range, 28-31 years) underwent MR imaging with a 7-T system. Gradient-echo images (repetition time msec/echo time msec, 1000/25) of the human cerebellum were acquired with a nominal in-plane resolution of approximately 120 mum and a section thickness of 1 mm. Results: Structures with dimensions as small as 240 mum, such as the granular and molecular layers in the cerebellar cortex, were detected in vivo. The detection of these structures was confirmed by comparing the contrast obtained on T2*-weighted and phase images with that obtained on images of rat cerebellum acquired at 14 T with 30 mum in-plane resolution. Conclusion: In vivo cerebellar imaging at near-microscopic resolution is feasible at 7 T. Such detailed observation of an anatomic area that can be affected by a number of neurologic and psychiatric diseases, such as stroke, tumors, autism, and schizophrenia, could potentially provide newer markers for diagnosis and follow-up in patients with such pathologic conditions. (c) RSNA, 2010.

Dextramers: new generation of fluorescent MHC class I/peptide multimers for visualization of antigen-specific CD8+ T cells.

Direct identification as well as isolation of antigen-specific T cells became possible since the development of "tetramers" based on avidin-fluorochrome conjugates associated with mono-biotinylated class I MHC-peptide monomeric complexes. In principle, a series of distinct class I MHC-peptide tetramers, each labelled with a different fluorochrome, would allow to simultaneously enumerate as many unique antigen-specific CD8(+) T cells. Practically, however, only phycoerythrin and allophycocyanin conjugated tetramers have been generally available, imposing serious constraints for multiple labeling. To overcome this limitation, we have developed dextramers which are multimers based on a dextran backbone bearing multiple fluorescein and streptavidin moieties. Here we demonstrate the functionality and optimization of these new probes on human CD8(+) T cell clones with four independent antigen specificities. Their applications to the analysis of relatively low frequency antigen-specific T cells in peripheral blood, as well as their use in fluorescence microscopy, are demonstrated. The data show that dextramers produce a stronger signal than their fluoresceinated tetramer counterparts. Thus, these could become the reagents of choice as the antigen-specific T cell labeling transitions from basic research to clinical application.