Correcting ligands, metabolites, and pathways

PubMed Central

Ott, Martin A; Vriend, Gert

2006-01-01

Background A wide range of research areas in bioinformatics, molecular biology and medicinal chemistry require precise chemical structure information about molecules and reactions, e.g. drug design, ligand docking, metabolic network reconstruction, and systems biology. Most available databases, however, treat chemical structures more as illustrations than as a datafield in its own right. Lack of chemical accuracy impedes progress in the areas mentioned above. We present a database of metabolites called BioMeta that augments the existing pathway databases by explicitly assessing the validity, correctness, and completeness of chemical structure and reaction information. Description The main bulk of the data in BioMeta were obtained from the KEGG Ligand database. We developed a tool for chemical structure validation which assesses the chemical validity and stereochemical completeness of a molecule description. The validation tool was used to examine the compounds in BioMeta, showing that a relatively small number of compounds had an incorrect constitution (connectivity only, not considering stereochemistry) and that a considerable number (about one third) had incomplete or even incorrect stereochemistry. We made a large effort to correct the errors and to complete the structural descriptions. A total of 1468 structures were corrected and/or completed. We also established the reaction balance of the reactions in BioMeta and corrected 55% of the unbalanced (stoichiometrically incorrect) reactions in an automatic procedure. The BioMeta database was implemented in PostgreSQL and provided with a web-based interface. Conclusion We demonstrate that the validation of metabolite structures and reactions is a feasible and worthwhile undertaking, and that the validation results can be used to trigger corrections and improvements to BioMeta, our metabolite database. BioMeta provides some tools for rational drug design, reaction searches, and visualization. It is freely available at provided that the copyright notice of all original data is cited. The database will be useful for querying and browsing biochemical pathways, and to obtain reference information for identifying compounds. However, these applications require that the underlying data be correct, and that is the focus of BioMeta. PMID:17132165

Update of KDBI: Kinetic Data of Bio-molecular Interaction database

PubMed Central

Kumar, Pankaj; Han, B. C.; Shi, Z.; Jia, J.; Wang, Y. P.; Zhang, Y. T.; Liang, L.; Liu, Q. F.; Ji, Z. L.; Chen, Y. Z.

2009-01-01

Knowledge of the kinetics of biomolecular interactions is important for facilitating the study of cellular processes and underlying molecular events, and is essential for quantitative study and simulation of biological systems. Kinetic Data of Bio-molecular Interaction database (KDBI) has been developed to provide information about experimentally determined kinetic data of protein–protein, protein–nucleic acid, protein–ligand, nucleic acid–ligand binding or reaction events described in the literature. To accommodate increasing demand for studying and simulating biological systems, numerous improvements and updates have been made to KDBI, including new ways to access data by pathway and molecule names, data file in System Biology Markup Language format, more efficient search engine, access to published parameter sets of simulation models of 63 pathways, and 2.3-fold increase of data (19 263 entries of 10 532 distinctive biomolecular binding and 11 954 interaction events, involving 2635 proteins/protein complexes, 847 nucleic acids, 1603 small molecules and 45 multi-step processes). KDBI is publically available at http://bidd.nus.edu.sg/group/kdbi/kdbi.asp. PMID:18971255

Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction.

PubMed

Dhanasekaran, A Ranjitha; Pearson, Jon L; Ganesan, Balasubramanian; Weimer, Bart C

2015-02-25

Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism's genome as a database restricts metabolite identification to only those compounds that the organism can produce. To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment's MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis. Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome.

Effects of 5-h multimodal stress on the molecules and pathways involved in dendritic morphology and cognitive function.

PubMed

Xu, Yiran; Cheng, Xiaorui; Cui, Xiuliang; Wang, Tongxing; Liu, Gang; Yang, Ruishang; Wang, Jianhui; Bo, Xiaochen; Wang, Shengqi; Zhou, Wenxia; Zhang, Yongxiang

2015-09-01

Stress induces cognitive impairments, which are likely related to the damaged dendritic morphology in the brain. Treatments for stress-induced impairments remain limited because the molecules and pathways underlying these impairments are unknown. Therefore, the aim of this study was to find the potential molecules and pathways related to damage of the dendritic morphology induced by stress. To do this, we detected gene expression, constructed a protein-protein interaction (PPI) network, and analyzed the molecular pathways in the brains of mice exposed to 5-h multimodal stress. The results showed that stress increased plasma corticosterone concentration, decreased cognitive function, damaged dendritic morphologies, and altered APBB1, CLSTN1, KCNA4, NOTCH3, PLAU, RPS6KA1, SYP, TGFB1, KCNA1, NTRK3, and SNCA expression in the brains of mice. Further analyses found that the abnormal expressions of CLSTN1, PLAU, NOTCH3, and TGFB1 induced by stress were related to alterations in the dendritic morphology. These four genes demonstrated interactions with 55 other genes, and configured a closed PPI network. Molecular pathway analysis use the Database for Annotation, Visualization, and Integrated Discovery (DAVID), specifically the gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG), each identified three pathways that were significantly enriched in the gene list of the PPI network, with genes belonging to the Notch and transforming growth factor-beta (TGF-B) signaling pathways being the most enriched. Our results suggest that TGFB1, PLAU, NOTCH3, and CLSTN1 may be related to the alterations in dendritic morphology induced by stress, and imply that the Notch and TGF-B signaling pathways may be involved. Copyright © 2015 Elsevier Inc. All rights reserved.

An Integrated Human/Murine Transcriptome and Pathway Approach To Identify Prenatal Treatments For Down Syndrome.

PubMed

Guedj, Faycal; Pennings, Jeroen LA; Massingham, Lauren J; Wick, Heather C; Siegel, Ashley E; Tantravahi, Umadevi; Bianchi, Diana W

2016-09-02

Anatomical and functional brain abnormalities begin during fetal life in Down syndrome (DS). We hypothesize that novel prenatal treatments can be identified by targeting signaling pathways that are consistently perturbed in cell types/tissues obtained from human fetuses with DS and mouse embryos. We analyzed transcriptome data from fetuses with trisomy 21, age and sex-matched euploid controls, and embryonic day 15.5 forebrains from Ts1Cje, Ts65Dn, and Dp16 mice. The new datasets were compared to other publicly available datasets from humans with DS. We used the human Connectivity Map (CMap) database and created a murine adaptation to identify FDA-approved drugs that can rescue affected pathways. USP16 and TTC3 were dysregulated in all affected human cells and two mouse models. DS-associated pathway abnormalities were either the result of gene dosage specific effects or the consequence of a global cell stress response with activation of compensatory mechanisms. CMap analyses identified 56 molecules with high predictive scores to rescue abnormal gene expression in both species. Our novel integrated human/murine systems biology approach identified commonly dysregulated genes and pathways. This can help to prioritize therapeutic molecules on which to further test safety and efficacy. Additional studies in human cells are ongoing prior to pre-clinical prenatal treatment in mice.

An overview of bioinformatics methods for modeling biological pathways in yeast

PubMed Central

Hou, Jie; Acharya, Lipi; Zhu, Dongxiao

2016-01-01

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein–protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae. In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways in S. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. PMID:26476430

Computational analysis of microRNA function in heart development.

PubMed

Liu, Ganqiang; Ding, Min; Chen, Jiajia; Huang, Jinyan; Wang, Haiyun; Jing, Qing; Shen, Bairong

2010-09-01

Emerging evidence suggests that specific spatio-temporal microRNA (miRNA) expression is required for heart development. In recent years, hundreds of miRNAs have been discovered. In contrast, functional annotations are available only for a very small fraction of these regulatory molecules. In order to provide a global perspective for the biologists who study the relationship between differentially expressed miRNAs and heart development, we employed computational analysis to uncover the specific cellular processes and biological pathways targeted by miRNAs in mouse heart development. Here, we utilized Gene Ontology (GO) categories, KEGG Pathway, and GeneGo Pathway Maps as a gene functional annotation system for miRNA target enrichment analysis. The target genes of miRNAs were found to be enriched in functional categories and pathway maps in which miRNAs could play important roles during heart development. Meanwhile, we developed miRHrt (http://sysbio.suda.edu.cn/mirhrt/), a database aiming to provide a comprehensive resource of miRNA function in regulating heart development. These computational analysis results effectively illustrated the correlation of differentially expressed miRNAs with cellular functions and heart development. We hope that the identified novel heart development-associated pathways and the database presented here would facilitate further understanding of the roles and mechanisms of miRNAs in heart development.

AN OVERVIEW OF COMPUTATIONAL LIFE SCIENCE DATABASES & EXCHANGE FORMATS OF RELEVANCE TO CHEMICAL BIOLOGY RESEARCH

PubMed Central

Hall, Aaron Smalter; Shan, Yunfeng; Lushington, Gerald; Visvanathan, Mahesh

2016-01-01

Databases and exchange formats describing biological entities such as chemicals and proteins, along with their relationships, are a critical component of research in life sciences disciplines, including chemical biology wherein small information about small molecule properties converges with cellular and molecular biology. Databases for storing biological entities are growing not only in size, but also in type, with many similarities between them and often subtle differences. The data formats available to describe and exchange these entities are numerous as well. In general, each format is optimized for a particular purpose or database, and hence some understanding of these formats is required when choosing one for research purposes. This paper reviews a selection of different databases and data formats with the goal of summarizing their purposes, features, and limitations. Databases are reviewed under the categories of 1) protein interactions, 2) metabolic pathways, 3) chemical interactions, and 4) drug discovery. Representation formats will be discussed according to those describing chemical structures, and those describing genomic/proteomic entities. PMID:22934944

An overview of computational life science databases & exchange formats of relevance to chemical biology research.

PubMed

Smalter Hall, Aaron; Shan, Yunfeng; Lushington, Gerald; Visvanathan, Mahesh

2013-03-01

Databases and exchange formats describing biological entities such as chemicals and proteins, along with their relationships, are a critical component of research in life sciences disciplines, including chemical biology wherein small information about small molecule properties converges with cellular and molecular biology. Databases for storing biological entities are growing not only in size, but also in type, with many similarities between them and often subtle differences. The data formats available to describe and exchange these entities are numerous as well. In general, each format is optimized for a particular purpose or database, and hence some understanding of these formats is required when choosing one for research purposes. This paper reviews a selection of different databases and data formats with the goal of summarizing their purposes, features, and limitations. Databases are reviewed under the categories of 1) protein interactions, 2) metabolic pathways, 3) chemical interactions, and 4) drug discovery. Representation formats will be discussed according to those describing chemical structures, and those describing genomic/proteomic entities.

Identifying novel glioma associated pathways based on systems biology level meta-analysis.

PubMed

Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

2013-01-01

With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

cMapper: gene-centric connectivity mapper for EBI-RDF platform.

PubMed

Shoaib, Muhammad; Ansari, Adnan Ahmad; Ahn, Sung-Min

2017-01-15

In this era of biological big data, data integration has become a common task and a challenge for biologists. The Resource Description Framework (RDF) was developed to enable interoperability of heterogeneous datasets. The EBI-RDF platform enables an efficient data integration of six independent biological databases using RDF technologies and shared ontologies. However, to take advantage of this platform, biologists need to be familiar with RDF technologies and SPARQL query language. To overcome this practical limitation of the EBI-RDF platform, we developed cMapper, a web-based tool that enables biologists to search the EBI-RDF databases in a gene-centric manner without a thorough knowledge of RDF and SPARQL. cMapper allows biologists to search data entities in the EBI-RDF platform that are connected to genes or small molecules of interest in multiple biological contexts. The input to cMapper consists of a set of genes or small molecules, and the output are data entities in six independent EBI-RDF databases connected with the given genes or small molecules in the user's query. cMapper provides output to users in the form of a graph in which nodes represent data entities and the edges represent connections between data entities and inputted set of genes or small molecules. Furthermore, users can apply filters based on database, taxonomy, organ and pathways in order to focus on a core connectivity graph of their interest. Data entities from multiple databases are differentiated based on background colors. cMapper also enables users to investigate shared connections between genes or small molecules of interest. Users can view the output graph on a web browser or download it in either GraphML or JSON formats. cMapper is available as a web application with an integrated MySQL database. The web application was developed using Java and deployed on Tomcat server. We developed the user interface using HTML5, JQuery and the Cytoscape Graph API. cMapper can be accessed at http://cmapper.ewostech.net Readers can download the development manual from the website http://cmapper.ewostech.net/docs/cMapperDocumentation.pdf. Source Code is available at https://github.com/muhammadshoaib/cmapperContact:smahn@gachon.ac.krSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

DrugBank 3.0: a comprehensive resource for ‘Omics’ research on drugs

PubMed Central

Knox, Craig; Law, Vivian; Jewison, Timothy; Liu, Philip; Ly, Son; Frolkis, Alex; Pon, Allison; Banco, Kelly; Mak, Christine; Neveu, Vanessa; Djoumbou, Yannick; Eisner, Roman; Guo, An Chi; Wishart, David S.

2011-01-01

DrugBank (http://www.drugbank.ca) is a richly annotated database of drug and drug target information. It contains extensive data on the nomenclature, ontology, chemistry, structure, function, action, pharmacology, pharmacokinetics, metabolism and pharmaceutical properties of both small molecule and large molecule (biotech) drugs. It also contains comprehensive information on the target diseases, proteins, genes and organisms on which these drugs act. First released in 2006, DrugBank has become widely used by pharmacists, medicinal chemists, pharmaceutical researchers, clinicians, educators and the general public. Since its last update in 2008, DrugBank has been greatly expanded through the addition of new drugs, new targets and the inclusion of more than 40 new data fields per drug entry (a 40% increase in data ‘depth’). These data field additions include illustrated drug-action pathways, drug transporter data, drug metabolite data, pharmacogenomic data, adverse drug response data, ADMET data, pharmacokinetic data, computed property data and chemical classification data. DrugBank 3.0 also offers expanded database links, improved search tools for drug–drug and food–drug interaction, new resources for querying and viewing drug pathways and hundreds of new drug entries with detailed patent, pricing and manufacturer data. These additions have been complemented by enhancements to the quality and quantity of existing data, particularly with regard to drug target, drug description and drug action data. DrugBank 3.0 represents the result of 2 years of manual annotation work aimed at making the database much more useful for a wide range of ‘omics’ (i.e. pharmacogenomic, pharmacoproteomic, pharmacometabolomic and even pharmacoeconomic) applications. PMID:21059682

An overview of bioinformatics methods for modeling biological pathways in yeast.

PubMed

Hou, Jie; Acharya, Lipi; Zhu, Dongxiao; Cheng, Jianlin

2016-03-01

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Incorporating Information of microRNAs into Pathway Analysis in a Genome-Wide Association Study of Bipolar Disorder

PubMed Central

Shih, Wei-Liang; Kao, Chung-Feng; Chuang, Li-Chung; Kuo, Po-Hsiu

2012-01-01

MicroRNAs (miRNAs) are known to be important post-transcriptional regulators that are involved in the etiology of complex psychiatric traits. The present study aimed to incorporate miRNAs information into pathway analysis using a genome-wide association dataset to identify relevant biological pathways for bipolar disorder (BPD). We selected psychiatric- and neurological-associated miRNAs (N = 157) from PhenomiR database. The miRNA target genes (miTG) predictions were obtained from microRNA.org. Canonical pathways (N = 4,051) were downloaded from the Molecule Signature Database. We employed a novel weighting scheme for miTGs in pathway analysis using methods of gene set enrichment analysis and sum-statistic. Under four statistical scenarios, 38 significantly enriched pathways (P-value < 0.01 after multiple testing correction) were identified for the risk of developing BPD, including pathways of ion channels associated (e.g., gated channel activity, ion transmembrane transporter activity, and ion channel activity) and nervous related biological processes (e.g., nervous system development, cytoskeleton, and neuroactive ligand receptor interaction). Among them, 19 were identified only when the weighting scheme was applied. Many miRNA-targeted genes were functionally related to ion channels, collagen, and axonal growth and guidance that have been suggested to be associated with BPD previously. Some of these genes are linked to the regulation of miRNA machinery in the literature. Our findings provide support for the potential involvement of miRNAs in the psychopathology of BPD. Further investigations to elucidate the functions and mechanisms of identified candidate pathways are needed. PMID:23264780

A 3-hydroxypropionate/4-hydroxybutyrate autotrophic carbon dioxide assimilation pathway in Archaea.

PubMed

Berg, Ivan A; Kockelkorn, Daniel; Buckel, Wolfgang; Fuchs, Georg

2007-12-14

The assimilation of carbon dioxide (CO2) into organic material is quantitatively the most important biosynthetic process. We discovered that an autotrophic member of the archaeal order Sulfolobales, Metallosphaera sedula, fixed CO2 with acetyl-coenzyme A (acetyl-CoA)/propionyl-CoA carboxylase as the key carboxylating enzyme. In this system, one acetyl-CoA and two bicarbonate molecules were reductively converted via 3-hydroxypropionate to succinyl-CoA. This intermediate was reduced to 4-hydroxybutyrate and converted into two acetyl-CoA molecules via 4-hydroxybutyryl-CoA dehydratase. The key genes of this pathway were found not only in Metallosphaera but also in Sulfolobus, Archaeoglobus, and Cenarchaeum species. Moreover, the Global Ocean Sampling database contains half as many 4-hydroxybutyryl-CoA dehydratase sequences as compared with those found for another key photosynthetic CO2-fixing enzyme, ribulose-1,5-bisphosphate carboxylase-oxygenase. This indicates the importance of this enzyme in global carbon cycling.

Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer

PubMed Central

Makondi, Precious Takondwa; Lee, Chia-Hwa; Huang, Chien-Yu; Chu, Chi-Ming; Chang, Yu-Jia

2018-01-01

Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC) therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO) database (dataset, GSE86525) was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID). Protein–protein interaction (PPI) networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING) and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs); the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1A(CDKN1A), toll-like receptor 4 (TLR4), CD19 molecule (CD19), breast cancer 1, early onset (BRCA1), platelet-derived growth factor subunit A (PDGFA), and matrix metallopeptidase 1 (MMP1) were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4) revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS). The identified genes and pathways can be potential targets and predictors of therapeutic resistance and prognosis in bevacizumab-treated patients with mCRC. PMID:29342159

Modeling of cell signaling pathways in macrophages by semantic networks

PubMed Central

Hsing, Michael; Bellenson, Joel L; Shankey, Conor; Cherkasov, Artem

2004-01-01

Background Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly "compartmental" (i.e. individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways. Results We have applied a semantic network (SN) approach to develop and implement a model for cell signaling pathways. The semantic model has mapped biological concepts to a set of semantic agents and relationships, and characterized cell signaling events and their participants in the hierarchical and spatial context. In particular, the available information on the behaviors and interactions of the PI3K enzyme family has been integrated into the SN environment and a cell signaling network in human macrophages has been constructed. A SN-application has been developed to manipulate the locations and the states of molecules and to observe their actions under different biological scenarios. The approach allowed qualitative simulation of cell signaling events involving PI3Ks and identified pathways of molecular interactions that led to known cellular responses as well as other potential responses during bacterial invasions in macrophages. Conclusions We concluded from our results that the semantic network is an effective method to model cell signaling pathways. The semantic model allows proper representation and integration of information on biological structures and their interactions at different levels. The reconstruction of the cell signaling network in the macrophage allowed detailed investigation of connections among various essential molecules and reflected the cause-effect relationships among signaling events. The simulation demonstrated the dynamics of the semantic network, where a change of states on a molecule can alter its function and potentially cause a chain-reaction effect in the system. PMID:15494071

PathwayAccess: CellDesigner plugins for pathway databases.

PubMed

Van Hemert, John L; Dickerson, Julie A

2010-09-15

CellDesigner provides a user-friendly interface for graphical biochemical pathway description. Many pathway databases are not directly exportable to CellDesigner models. PathwayAccess is an extensible suite of CellDesigner plugins, which connect CellDesigner directly to pathway databases using respective Java application programming interfaces. The process is streamlined for creating new PathwayAccess plugins for specific pathway databases. Three PathwayAccess plugins, MetNetAccess, BioCycAccess and ReactomeAccess, directly connect CellDesigner to the pathway databases MetNetDB, BioCyc and Reactome. PathwayAccess plugins enable CellDesigner users to expose pathway data to analytical CellDesigner functions, curate their pathway databases and visually integrate pathway data from different databases using standard Systems Biology Markup Language and Systems Biology Graphical Notation. Implemented in Java, PathwayAccess plugins run with CellDesigner version 4.0.1 and were tested on Ubuntu Linux, Windows XP and 7, and MacOSX. Source code, binaries, documentation and video walkthroughs are freely available at http://vrac.iastate.edu/~jlv.

miRnalyze: an interactive database linking tool to unlock intuitive microRNA regulation of cell signaling pathways

PubMed Central

Subhra Das, Sankha; James, Mithun; Paul, Sandip

2017-01-01

Abstract The various pathophysiological processes occurring in living systems are known to be orchestrated by delicate interplays and cross-talks between different genes and their regulators. Among the various regulators of genes, there is a class of small non-coding RNA molecules known as microRNAs. Although, the relative simplicity of miRNAs and their ability to modulate cellular processes make them attractive therapeutic candidates, their presence in large numbers make it challenging for experimental researchers to interpret the intricacies of the molecular processes they regulate. Most of the existing bioinformatic tools fail to address these challenges. Here, we present a new web resource ‘miRnalyze’ that has been specifically designed to directly identify the putative regulation of cell signaling pathways by miRNAs. The tool integrates miRNA-target predictions with signaling cascade members by utilizing TargetScanHuman 7.1 miRNA-target prediction tool and the KEGG pathway database, and thus provides researchers with in-depth insights into modulation of signal transduction pathways by miRNAs. miRnalyze is capable of identifying common miRNAs targeting more than one gene in the same signaling pathway—a feature that further increases the probability of modulating the pathway and downstream reactions when using miRNA modulators. Additionally, miRnalyze can sort miRNAs according to the seed-match types and TargetScan Context ++ score, thus providing a hierarchical list of most valuable miRNAs. Furthermore, in order to provide users with comprehensive information regarding miRNAs, genes and pathways, miRnalyze also links to expression data of miRNAs (miRmine) and genes (TiGER) and proteome abundance (PaxDb) data. To validate the capability of the tool, we have documented the correlation of miRnalyze’s prediction with experimental confirmation studies. Database URL: http://www.mirnalyze.in PMID:28365733

Rationale of the FIBROTARGETS study designed to identify novel biomarkers of myocardial fibrosis

PubMed Central

Ferreira, João Pedro; Machu, Jean‐Loup; Girerd, Nicolas; Jaisser, Frederic; Thum, Thomas; Butler, Javed; González, Arantxa; Diez, Javier; Heymans, Stephane; McDonald, Kenneth; Gyöngyösi, Mariann; Firat, Hueseyin; Rossignol, Patrick; Pizard, Anne

2017-01-01

Abstract Aims Myocardial fibrosis alters the cardiac architecture favouring the development of cardiac dysfunction, including arrhythmias and heart failure. Reducing myocardial fibrosis may improve outcomes through the targeted diagnosis and treatment of emerging fibrotic pathways. The European‐Commission‐funded ‘FIBROTARGETS’ is a multinational academic and industrial consortium with the main aims of (i) characterizing novel key mechanistic pathways involved in the metabolism of fibrillary collagen that may serve as biotargets, (ii) evaluating the potential anti‐fibrotic properties of novel or repurposed molecules interfering with the newly identified biotargets, and (iii) characterizing bioprofiles based on distinct mechanistic phenotypes involving the aforementioned biotargets. These pathways will be explored by performing a systematic and collaborative search for mechanisms and targets of myocardial fibrosis. These mechanisms will then be translated into individualized diagnostic tools and specific therapeutic pharmacological options for heart failure. Methods and results The FIBROTARGETS consortium has merged data from 12 patient cohorts in a common database available to individual consortium partners. The database consists of >12 000 patients with a large spectrum of cardiovascular clinical phenotypes. It integrates community‐based population cohorts, cardiovascular risk cohorts, and heart failure cohorts. Conclusions The FIBROTARGETS biomarker programme is aimed at exploring fibrotic pathways allowing the bioprofiling of patients into specific ‘fibrotic’ phenotypes and identifying new therapeutic targets that will potentially enable the development of novel and tailored anti‐fibrotic therapies for heart failure. PMID:28988439

Transcriptome profiling analysis reveals biomarkers in colon cancer samples of various differentiation

PubMed Central

Yu, Tonghu; Zhang, Huaping; Qi, Hong

2018-01-01

The aim of the present study was to investigate more colon cancer-related genes in different stages. Gene expression profile E-GEOD-62932 was extracted for differentially expressed gene (DEG) screening. Series test of cluster analysis was used to obtain significant trending models. Based on the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, functional and pathway enrichment analysis were processed and a pathway relation network was constructed. Gene co-expression network and gene signal network were constructed for common DEGs. The DEGs with the same trend were clustered and in total, 16 clusters with statistical significance were obtained. The screened DEGs were enriched into small molecule metabolic process and metabolic pathways. The pathway relation network was constructed with 57 nodes. A total of 328 common DEGs were obtained. Gene signal network was constructed with 71 nodes. Gene co-expression network was constructed with 161 nodes and 211 edges. ABCD3, CPT2, AGL and JAM2 are potential biomarkers for the diagnosis of colon cancer. PMID:29928385

BioNetSim: a Petri net-based modeling tool for simulations of biochemical processes.

PubMed

Gao, Junhui; Li, Li; Wu, Xiaolin; Wei, Dong-Qing

2012-03-01

BioNetSim, a Petri net-based software for modeling and simulating biochemistry processes, is developed, whose design and implement are presented in this paper, including logic construction, real-time access to KEGG (Kyoto Encyclopedia of Genes and Genomes), and BioModel database. Furthermore, glycolysis is simulated as an example of its application. BioNetSim is a helpful tool for researchers to download data, model biological network, and simulate complicated biochemistry processes. Gene regulatory networks, metabolic pathways, signaling pathways, and kinetics of cell interaction are all available in BioNetSim, which makes modeling more efficient and effective. Similar to other Petri net-based softwares, BioNetSim does well in graphic application and mathematic construction. Moreover, it shows several powerful predominances. (1) It creates models in database. (2) It realizes the real-time access to KEGG and BioModel and transfers data to Petri net. (3) It provides qualitative analysis, such as computation of constants. (4) It generates graphs for tracing the concentration of every molecule during the simulation processes.

In silico screening for Plasmodium falciparum enoyl-ACP reductase inhibitors

NASA Astrophysics Data System (ADS)

Lindert, Steffen; Tallorin, Lorillee; Nguyen, Quynh G.; Burkart, Michael D.; McCammon, J. Andrew

2015-01-01

The need for novel therapeutics against Plasmodium falciparum is urgent due to recent emergence of multi-drug resistant malaria parasites. Since fatty acids are essential for both the liver and blood stages of the malarial parasite, targeting fatty acid biosynthesis is a promising strategy for combatting P. falciparum. We present a combined computational and experimental study to identify novel inhibitors of enoyl-acyl carrier protein reductase ( PfENR) in the fatty acid biosynthesis pathway. A small-molecule database from ChemBridge was docked into three distinct PfENR crystal structures that provide multiple receptor conformations. Two different docking algorithms were used to generate a consensus score in order to rank possible small molecule hits. Our studies led to the identification of five low-micromolar pyrimidine dione inhibitors of PfENR.

SolCyc: a database hub at the Sol Genomics Network (SGN) for the manual curation of metabolic networks in Solanum and Nicotiana specific databases

PubMed Central

Foerster, Hartmut; Bombarely, Aureliano; Battey, James N D; Sierro, Nicolas; Ivanov, Nikolai V; Mueller, Lukas A

2018-01-01

Abstract SolCyc is the entry portal to pathway/genome databases (PGDBs) for major species of the Solanaceae family hosted at the Sol Genomics Network. Currently, SolCyc comprises six organism-specific PGDBs for tomato, potato, pepper, petunia, tobacco and one Rubiaceae, coffee. The metabolic networks of those PGDBs have been computationally predicted by the pathologic component of the pathway tools software using the manually curated multi-domain database MetaCyc (http://www.metacyc.org/) as reference. SolCyc has been recently extended by taxon-specific databases, i.e. the family-specific SolanaCyc database, containing only curated data pertinent to species of the nightshade family, and NicotianaCyc, a genus-specific database that stores all relevant metabolic data of the Nicotiana genus. Through manual curation of the published literature, new metabolic pathways have been created in those databases, which are complemented by the continuously updated, relevant species-specific pathways from MetaCyc. At present, SolanaCyc comprises 199 pathways and 29 superpathways and NicotianaCyc accounts for 72 pathways and 13 superpathways. Curator-maintained, taxon-specific databases such as SolanaCyc and NicotianaCyc are characterized by an enrichment of data specific to these taxa and free of falsely predicted pathways. Both databases have been used to update recently created Nicotiana-specific databases for Nicotiana tabacum, Nicotiana benthamiana, Nicotiana sylvestris and Nicotiana tomentosiformis by propagating verifiable data into those PGDBs. In addition, in-depth curation of the pathways in N.tabacum has been carried out which resulted in the elimination of 156 pathways from the 569 pathways predicted by pathway tools. Together, in-depth curation of the predicted pathway network and the supplementation with curated data from taxon-specific databases has substantially improved the curation status of the species–specific N.tabacum PGDB. The implementation of this strategy will significantly advance the curation status of all organism-specific databases in SolCyc resulting in the improvement on database accuracy, data analysis and visualization of biochemical networks in those species. Database URL https://solgenomics.net/tools/solcyc/ PMID:29762652

Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.

PubMed

Ekins, Sean; Madrid, Peter B; Sarker, Malabika; Li, Shao-Gang; Mittal, Nisha; Kumar, Pradeep; Wang, Xin; Stratton, Thomas P; Zimmerman, Matthew; Talcott, Carolyn; Bourbon, Pauline; Travers, Mike; Yadav, Maneesh; Freundlich, Joel S

2015-01-01

Integrated computational approaches for Mycobacterium tuberculosis (Mtb) are useful to identify new molecules that could lead to future tuberculosis (TB) drugs. Our approach uses information derived from the TBCyc pathway and genome database, the Collaborative Drug Discovery TB database combined with 3D pharmacophores and dual event Bayesian models of whole-cell activity and lack of cytotoxicity. We have prioritized a large number of molecules that may act as mimics of substrates and metabolites in the TB metabolome. We computationally searched over 200,000 commercial molecules using 66 pharmacophores based on substrates and metabolites from Mtb and further filtering with Bayesian models. We ultimately tested 110 compounds in vitro that resulted in two compounds of interest, BAS 04912643 and BAS 00623753 (MIC of 2.5 and 5 μg/mL, respectively). These molecules were used as a starting point for hit-to-lead optimization. The most promising class proved to be the quinoxaline di-N-oxides, evidenced by transcriptional profiling to induce mRNA level perturbations most closely resembling known protonophores. One of these, SRI58 exhibited an MIC = 1.25 μg/mL versus Mtb and a CC50 in Vero cells of >40 μg/mL, while featuring fair Caco-2 A-B permeability (2.3 x 10-6 cm/s), kinetic solubility (125 μM at pH 7.4 in PBS) and mouse metabolic stability (63.6% remaining after 1 h incubation with mouse liver microsomes). Despite demonstration of how a combined bioinformatics/cheminformatics approach afforded a small molecule with promising in vitro profiles, we found that SRI58 did not exhibit quantifiable blood levels in mice.

Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery

PubMed Central

Sarker, Malabika; Li, Shao-Gang; Mittal, Nisha; Kumar, Pradeep; Wang, Xin; Stratton, Thomas P.; Zimmerman, Matthew; Talcott, Carolyn; Bourbon, Pauline; Travers, Mike; Yadav, Maneesh

2015-01-01

Integrated computational approaches for Mycobacterium tuberculosis (Mtb) are useful to identify new molecules that could lead to future tuberculosis (TB) drugs. Our approach uses information derived from the TBCyc pathway and genome database, the Collaborative Drug Discovery TB database combined with 3D pharmacophores and dual event Bayesian models of whole-cell activity and lack of cytotoxicity. We have prioritized a large number of molecules that may act as mimics of substrates and metabolites in the TB metabolome. We computationally searched over 200,000 commercial molecules using 66 pharmacophores based on substrates and metabolites from Mtb and further filtering with Bayesian models. We ultimately tested 110 compounds in vitro that resulted in two compounds of interest, BAS 04912643 and BAS 00623753 (MIC of 2.5 and 5 μg/mL, respectively). These molecules were used as a starting point for hit-to-lead optimization. The most promising class proved to be the quinoxaline di-N-oxides, evidenced by transcriptional profiling to induce mRNA level perturbations most closely resembling known protonophores. One of these, SRI58 exhibited an MIC = 1.25 μg/mL versus Mtb and a CC50 in Vero cells of >40 μg/mL, while featuring fair Caco-2 A-B permeability (2.3 x 10−6 cm/s), kinetic solubility (125 μM at pH 7.4 in PBS) and mouse metabolic stability (63.6% remaining after 1 h incubation with mouse liver microsomes). Despite demonstration of how a combined bioinformatics/cheminformatics approach afforded a small molecule with promising in vitro profiles, we found that SRI58 did not exhibit quantifiable blood levels in mice. PMID:26517557

Plasma Glycoproteomics Reveals Sepsis Outcomes Linked to Distinct Proteins in Common Pathways

PubMed Central

DeLeon-Pennell, Kristine Y.; Nguyen, Nguyen T.; de Castro Brás, Lisandra E.; Flynn, Elizabeth R.; Cannon, Presley L.; Griswold, Michael E.; Jin, Yu-Fang; Puskarich, Michael A.; Jones, Alan E.; Lindsey, Merry L.

2015-01-01

Objective Sepsis remains a predominant cause of mortality in the ICU, yet strategies to increase survival have proved largely unsuccessful. This study aimed to identify proteins linked to sepsis outcomes using a glycoproteomic approach to target extracellular proteins that trigger downstream pathways and direct patient outcomes. Design Plasma was obtained from the LacTATEs cohort. N-linked plasma glycopeptides were quantified by solid-phase extraction coupled with mass spectrometry. Glycopeptides were assigned to proteins using RefSeq and visualized in a heat map. Protein differences were validated by immunoblotting, and proteins were mapped for biological processes using Database for Annotation, Visualization and Integrated Discovery and for functional pathways using Kyoto Encyclopedia of Genes and Genomes databases. Setting Hospitalized care. Measurements and Main Results A total of 501 glycopeptides corresponding to 234 proteins were identified. Of these, 66 glycopeptides were unique to the survivor group and corresponded to 54 proteins, 60 were unique to the nonsurvivor group and corresponded to 43 proteins, and 375 were common responses between groups and corresponded to 137 proteins. Immunoblotting showed that nonsurvivors had increased total kininogen; decreased total cathepsin-L1, vascular cell adhesion molecule, periostin, and neutrophil gelatinase–associated lipocalin; and a two-fold decrease in glycosylated clusterin (all p < 0.05). Kyoto Encyclopedia of Genes and Genomes analysis identified six enriched pathways. Interestingly, survivors relied on the extrinsic pathway of the complement and coagulation cascade, whereas nonsurvivors relied on the intrinsic pathway. Conclusion This study identifies proteins linked to patient outcomes and provides insight into unexplored mechanisms that can be investigated for the identification of novel therapeutic targets. (Crit Care Med 2015; XX:00–00) PMID:26086942

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions.

PubMed

Gerlt, John A

2017-08-22

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of "genomic enzymology" web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence-function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence–Function Space and Genome Context to Discover Novel Functions

PubMed Central

2017-01-01

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of “genomic enzymology” web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence–function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems. PMID:28826221

An integrated one-step system to extract, analyze and annotate all relevant information from image-based cell screening of chemical libraries.

PubMed

Rabal, Obdulia; Link, Wolfgang; Serelde, Beatriz G; Bischoff, James R; Oyarzabal, Julen

2010-04-01

Here we report the development and validation of a complete solution to manage and analyze the data produced by image-based phenotypic screening campaigns of small-molecule libraries. In one step initial crude images are analyzed for multiple cytological features, statistical analysis is performed and molecules that produce the desired phenotypic profile are identified. A naïve Bayes classifier, integrating chemical and phenotypic spaces, is built and utilized during the process to assess those images initially classified as "fuzzy"-an automated iterative feedback tuning. Simultaneously, all this information is directly annotated in a relational database containing the chemical data. This novel fully automated method was validated by conducting a re-analysis of results from a high-content screening campaign involving 33 992 molecules used to identify inhibitors of the PI3K/Akt signaling pathway. Ninety-two percent of confirmed hits identified by the conventional multistep analysis method were identified using this integrated one-step system as well as 40 new hits, 14.9% of the total, originally false negatives. Ninety-six percent of true negatives were properly recognized too. A web-based access to the database, with customizable data retrieval and visualization tools, facilitates the posterior analysis of annotated cytological features which allows identification of additional phenotypic profiles; thus, further analysis of original crude images is not required.

Drug-Path: a database for drug-induced pathways

PubMed Central

Zeng, Hui; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. Database URL: http://www.cuilab.cn/drugpath PMID:26130661

Rhizoma Dioscoreae extract protects against alveolar bone loss by regulating the cell cycle: A predictive study based on the protein‑protein interaction network.

PubMed

Zhang, Zhi-Guo; Song, Chang-Heng; Zhang, Fang-Zhen; Chen, Yan-Jing; Xiang, Li-Hua; Xiao, Gary Guishan; Ju, Da-Hong

2016-06-01

Rhizoma Dioscoreae extract (RDE) exhibits a protective effect on alveolar bone loss in ovariectomized (OVX) rats. The aim of this study was to predict the pathways or targets that are regulated by RDE, by re‑assessing our previously reported data and conducting a protein‑protein interaction (PPI) network analysis. In total, 383 differentially expressed genes (≥3‑fold) between alveolar bone samples from the RDE and OVX group rats were identified, and a PPI network was constructed based on these genes. Furthermore, four molecular clusters (A‑D) in the PPI network with the smallest P‑values were detected by molecular complex detection (MCODE) algorithm. Using Database for Annotation, Visualization and Integrated Discovery (DAVID) and Ingenuity Pathway Analysis (IPA) tools, two molecular clusters (A and B) were enriched for biological process in Gene Ontology (GO). Only cluster A was associated with biological pathways in the IPA database. GO and pathway analysis results showed that cluster A, associated with cell cycle regulation, was the most important molecular cluster in the PPI network. In addition, cyclin‑dependent kinase 1 (CDK1) may be a key molecule achieving the cell‑cycle‑regulatory function of cluster A. From the PPI network analysis, it was predicted that delayed cell cycle progression in excessive alveolar bone remodeling via downregulation of CDK1 may be another mechanism underling the anti‑osteopenic effect of RDE on alveolar bone.

Internet Databases of the Properties, Enzymatic Reactions, and Metabolism of Small Molecules-Search Options and Applications in Food Science.

PubMed

Minkiewicz, Piotr; Darewicz, Małgorzata; Iwaniak, Anna; Bucholska, Justyna; Starowicz, Piotr; Czyrko, Emilia

2016-12-06

Internet databases of small molecules, their enzymatic reactions, and metabolism have emerged as useful tools in food science. Database searching is also introduced as part of chemistry or enzymology courses for food technology students. Such resources support the search for information about single compounds and facilitate the introduction of secondary analyses of large datasets. Information can be retrieved from databases by searching for the compound name or structure, annotating with the help of chemical codes or drawn using molecule editing software. Data mining options may be enhanced by navigating through a network of links and cross-links between databases. Exemplary databases reviewed in this article belong to two classes: tools concerning small molecules (including general and specialized databases annotating food components) and tools annotating enzymes and metabolism. Some problems associated with database application are also discussed. Data summarized in computer databases may be used for calculation of daily intake of bioactive compounds, prediction of metabolism of food components, and their biological activity as well as for prediction of interactions between food component and drugs.

Interleukins and their signaling pathways in the Reactome biological pathway database.

PubMed

Jupe, Steve; Ray, Keith; Roca, Corina Duenas; Varusai, Thawfeek; Shamovsky, Veronica; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning

2018-04-01

There is a wealth of biological pathway information available in the scientific literature, but it is spread across many thousands of publications. Alongside publications that contain definitive experimental discoveries are many others that have been dismissed as spurious, found to be irreproducible, or are contradicted by later results and consequently now considered controversial. Many descriptions and images of pathways are incomplete stylized representations that assume the reader is an expert and familiar with the established details of the process, which are consequently not fully explained. Pathway representations in publications frequently do not represent a complete, detailed, and unambiguous description of the molecules involved; their precise posttranslational state; or a full account of the molecular events they undergo while participating in a process. Although this might be sufficient to be interpreted by an expert reader, the lack of detail makes such pathways less useful and difficult to understand for anyone unfamiliar with the area and of limited use as the basis for computational models. Reactome was established as a freely accessible knowledge base of human biological pathways. It is manually populated with interconnected molecular events that fully detail the molecular participants linked to published experimental data and background material by using a formal and open data structure that facilitates computational reuse. These data are accessible on a Web site in the form of pathway diagrams that have descriptive summaries and annotations and as downloadable data sets in several formats that can be reused with other computational tools. The entire database and all supporting software can be downloaded and reused under a Creative Commons license. Pathways are authored by expert biologists who work with Reactome curators and editorial staff to represent the consensus in the field. Pathways are represented as interactive diagrams that include as much molecular detail as possible and are linked to literature citations that contain supporting experimental details. All newly created events undergo a peer-review process before they are added to the database and made available on the associated Web site. New content is added quarterly. The 63rd release of Reactome in December 2017 contains 10,996 human proteins participating in 11,426 events in 2,179 pathways. In addition, analytic tools allow data set submission for the identification and visualization of pathway enrichment and representation of expression profiles as an overlay on Reactome pathways. Protein-protein and compound-protein interactions from several sources, including custom user data sets, can be added to extend pathways. Pathway diagrams and analytic result displays can be downloaded as editable images, human-readable reports, and files in several standard formats that are suitable for computational reuse. Reactome content is available programmatically through a REpresentational State Transfer (REST)-based content service and as a Neo4J graph database. Signaling pathways for IL-1 to IL-38 are hierarchically classified within the pathway "signaling by interleukins." The classification used is largely derived from Akdis et al. The addition to Reactome of a complete set of the known human interleukins, their receptors, and established signaling pathways linked to annotations of relevant aspects of immune function provides a significant computationally accessible resource of information about this important family. This information can be extended easily as new discoveries become accepted as the consensus in the field. A key aim for the future is to increase coverage of gene expression changes induced by interleukin signaling. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Inforna 2.0: A Platform for the Sequence-Based Design of Small Molecules Targeting Structured RNAs.

PubMed

Disney, Matthew D; Winkelsas, Audrey M; Velagapudi, Sai Pradeep; Southern, Mark; Fallahi, Mohammad; Childs-Disney, Jessica L

2016-06-17

The development of small molecules that target RNA is challenging yet, if successful, could advance the development of chemical probes to study RNA function or precision therapeutics to treat RNA-mediated disease. Previously, we described Inforna, an approach that can mine motifs (secondary structures) within target RNAs, which is deduced from the RNA sequence, and compare them to a database of known RNA motif-small molecule binding partners. Output generated by Inforna includes the motif found in both the database and the desired RNA target, lead small molecules for that target, and other related meta-data. Lead small molecules can then be tested for binding and affecting cellular (dys)function. Herein, we describe Inforna 2.0, which incorporates all known RNA motif-small molecule binding partners reported in the scientific literature, a chemical similarity searching feature, and an improved user interface and is freely available via an online web server. By incorporation of interactions identified by other laboratories, the database has been doubled, containing 1936 RNA motif-small molecule interactions, including 244 unique small molecules and 1331 motifs. Interestingly, chemotype analysis of the compounds that bind RNA in the database reveals features in small molecule chemotypes that are privileged for binding. Further, this updated database expanded the number of cellular RNAs to which lead compounds can be identified.

The Hippo/YAP pathway interacts with EGFR signaling and HPV oncoproteins to regulate cervical cancer progression

PubMed Central

He, Chunbo; Mao, Dagan; Hua, Guohua; Lv, Xiangmin; Chen, Xingcheng; Angeletti, Peter C; Dong, Jixin; Remmenga, Steven W; Rodabaugh, Kerry J; Zhou, Jin; Lambert, Paul F; Yang, Peixin; Davis, John S; Wang, Cheng

2015-01-01

The Hippo signaling pathway controls organ size and tumorigenesis through a kinase cascade that inactivates Yes-associated protein (YAP). Here, we show that YAP plays a central role in controlling the progression of cervical cancer. Our results suggest that YAP expression is associated with a poor prognosis for cervical cancer. TGF-α and amphiregulin (AREG), via EGFR, inhibit the Hippo signaling pathway and activate YAP to induce cervical cancer cell proliferation and migration. Activated YAP allows for up-regulation of TGF-α, AREG, and EGFR, forming a positive signaling loop to drive cervical cancer cell proliferation. HPV E6 protein, a major etiological molecule of cervical cancer, maintains high YAP protein levels in cervical cancer cells by preventing proteasome-dependent YAP degradation to drive cervical cancer cell proliferation. Results from human cervical cancer genomic databases and an accepted transgenic mouse model strongly support the clinical relevance of the discovered feed-forward signaling loop. Our study indicates that combined targeting of the Hippo and the ERBB signaling pathways represents a novel therapeutic strategy for prevention and treatment of cervical cancer. PMID:26417066

Ligand.Info small-molecule Meta-Database.

PubMed

von Grotthuss, Marcin; Koczyk, Grzegorz; Pas, Jakub; Wyrwicz, Lucjan S; Rychlewski, Leszek

2004-12-01

Ligand.Info is a compilation of various publicly available databases of small molecules. The total size of the Meta-Database is over 1 million entries. The compound records contain calculated three-dimensional coordinates and sometimes information about biological activity. Some molecules have information about FDA drug approving status or about anti-HIV activity. Meta-Database can be downloaded from the http://Ligand.Info web page. The database can also be screened using a Java-based tool. The tool can interactively cluster sets of molecules on the user side and automatically download similar molecules from the server. The application requires the Java Runtime Environment 1.4 or higher, which can be automatically downloaded from Sun Microsystems or Apple Computer and installed during the first use of Ligand.Info on desktop systems, which support Java (Ms Windows, Mac OS, Solaris, and Linux). The Ligand.Info Meta-Database can be used for virtual high-throughput screening of new potential drugs. Presented examples showed that using a known antiviral drug as query the system was able to find others antiviral drugs and inhibitors.

Drug-Path: a database for drug-induced pathways.

PubMed

Zeng, Hui; Qiu, Chengxiang; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. © The Author(s) 2015. Published by Oxford University Press.

Molecule database framework: a framework for creating database applications with chemical structure search capability

PubMed Central

2013-01-01

Background Research in organic chemistry generates samples of novel chemicals together with their properties and other related data. The involved scientists must be able to store this data and search it by chemical structure. There are commercial solutions for common needs like chemical registration systems or electronic lab notebooks. However for specific requirements of in-house databases and processes no such solutions exist. Another issue is that commercial solutions have the risk of vendor lock-in and may require an expensive license of a proprietary relational database management system. To speed up and simplify the development for applications that require chemical structure search capabilities, I have developed Molecule Database Framework. The framework abstracts the storing and searching of chemical structures into method calls. Therefore software developers do not require extensive knowledge about chemistry and the underlying database cartridge. This decreases application development time. Results Molecule Database Framework is written in Java and I created it by integrating existing free and open-source tools and frameworks. The core functionality includes: • Support for multi-component compounds (mixtures) • Import and export of SD-files • Optional security (authorization) For chemical structure searching Molecule Database Framework leverages the capabilities of the Bingo Cartridge for PostgreSQL and provides type-safe searching, caching, transactions and optional method level security. Molecule Database Framework supports multi-component chemical compounds (mixtures). Furthermore the design of entity classes and the reasoning behind it are explained. By means of a simple web application I describe how the framework could be used. I then benchmarked this example application to create some basic performance expectations for chemical structure searches and import and export of SD-files. Conclusions By using a simple web application it was shown that Molecule Database Framework successfully abstracts chemical structure searches and SD-File import and export to simple method calls. The framework offers good search performance on a standard laptop without any database tuning. This is also due to the fact that chemical structure searches are paged and cached. Molecule Database Framework is available for download on the projects web page on bitbucket: https://bitbucket.org/kienerj/moleculedatabaseframework. PMID:24325762

Molecule database framework: a framework for creating database applications with chemical structure search capability.

PubMed

Kiener, Joos

2013-12-11

Research in organic chemistry generates samples of novel chemicals together with their properties and other related data. The involved scientists must be able to store this data and search it by chemical structure. There are commercial solutions for common needs like chemical registration systems or electronic lab notebooks. However for specific requirements of in-house databases and processes no such solutions exist. Another issue is that commercial solutions have the risk of vendor lock-in and may require an expensive license of a proprietary relational database management system. To speed up and simplify the development for applications that require chemical structure search capabilities, I have developed Molecule Database Framework. The framework abstracts the storing and searching of chemical structures into method calls. Therefore software developers do not require extensive knowledge about chemistry and the underlying database cartridge. This decreases application development time. Molecule Database Framework is written in Java and I created it by integrating existing free and open-source tools and frameworks. The core functionality includes:•Support for multi-component compounds (mixtures)•Import and export of SD-files•Optional security (authorization)For chemical structure searching Molecule Database Framework leverages the capabilities of the Bingo Cartridge for PostgreSQL and provides type-safe searching, caching, transactions and optional method level security. Molecule Database Framework supports multi-component chemical compounds (mixtures).Furthermore the design of entity classes and the reasoning behind it are explained. By means of a simple web application I describe how the framework could be used. I then benchmarked this example application to create some basic performance expectations for chemical structure searches and import and export of SD-files. By using a simple web application it was shown that Molecule Database Framework successfully abstracts chemical structure searches and SD-File import and export to simple method calls. The framework offers good search performance on a standard laptop without any database tuning. This is also due to the fact that chemical structure searches are paged and cached. Molecule Database Framework is available for download on the projects web page on bitbucket: https://bitbucket.org/kienerj/moleculedatabaseframework.

WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research.

PubMed

Slenter, Denise N; Kutmon, Martina; Hanspers, Kristina; Riutta, Anders; Windsor, Jacob; Nunes, Nuno; Mélius, Jonathan; Cirillo, Elisa; Coort, Susan L; Digles, Daniela; Ehrhart, Friederike; Giesbertz, Pieter; Kalafati, Marianthi; Martens, Marvin; Miller, Ryan; Nishida, Kozo; Rieswijk, Linda; Waagmeester, Andra; Eijssen, Lars M T; Evelo, Chris T; Pico, Alexander R; Willighagen, Egon L

2018-01-04

WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Creation of a Genome-Wide Metabolic Pathway Database for Populus trichocarpa Using a New Approach for Reconstruction and Curation of Metabolic Pathways for Plants1[W][OA

PubMed Central

Zhang, Peifen; Dreher, Kate; Karthikeyan, A.; Chi, Anjo; Pujar, Anuradha; Caspi, Ron; Karp, Peter; Kirkup, Vanessa; Latendresse, Mario; Lee, Cynthia; Mueller, Lukas A.; Muller, Robert; Rhee, Seung Yon

2010-01-01

Metabolic networks reconstructed from sequenced genomes or transcriptomes can help visualize and analyze large-scale experimental data, predict metabolic phenotypes, discover enzymes, engineer metabolic pathways, and study metabolic pathway evolution. We developed a general approach for reconstructing metabolic pathway complements of plant genomes. Two new reference databases were created and added to the core of the infrastructure: a comprehensive, all-plant reference pathway database, PlantCyc, and a reference enzyme sequence database, RESD, for annotating metabolic functions of protein sequences. PlantCyc (version 3.0) includes 714 metabolic pathways and 2,619 reactions from over 300 species. RESD (version 1.0) contains 14,187 literature-supported enzyme sequences from across all kingdoms. We used RESD, PlantCyc, and MetaCyc (an all-species reference metabolic pathway database), in conjunction with the pathway prediction software Pathway Tools, to reconstruct a metabolic pathway database, PoplarCyc, from the recently sequenced genome of Populus trichocarpa. PoplarCyc (version 1.0) contains 321 pathways with 1,807 assigned enzymes. Comparing PoplarCyc (version 1.0) with AraCyc (version 6.0, Arabidopsis [Arabidopsis thaliana]) showed comparable numbers of pathways distributed across all domains of metabolism in both databases, except for a higher number of AraCyc pathways in secondary metabolism and a 1.5-fold increase in carbohydrate metabolic enzymes in PoplarCyc. Here, we introduce these new resources and demonstrate the feasibility of using them to identify candidate enzymes for specific pathways and to analyze metabolite profiling data through concrete examples. These resources can be searched by text or BLAST, browsed, and downloaded from our project Web site (http://plantcyc.org). PMID:20522724

The Bioinformatic Analysis of the Dysregulated Genes and MicroRNAs in Entorhinal Cortex, Hippocampus, and Blood for Alzheimer's Disease

PubMed Central

Pang, Xiaocong; Zhao, Ying; Wang, Jinhua; Zhou, Qimeng; Xu, Lvjie; Kang, De

2017-01-01

Aim The incidence of Alzheimer's disease (AD) has been increasing in recent years, but there exists no cure and the pathological mechanisms are not fully understood. This study aimed to find out the pathogenesis of learning and memory impairment, new biomarkers, potential therapeutic targets, and drugs for AD. Methods We downloaded the microarray data of entorhinal cortex (EC) and hippocampus (HIP) of AD and controls from Gene Expression Omnibus (GEO) database, and then the differentially expressed genes (DEGs) in EC and HIP regions were analyzed for functional and pathway enrichment. Furthermore, we utilized the DEGs to construct coexpression networks to identify hub genes and discover the small molecules which were capable of reversing the gene expression profile of AD. Finally, we also analyzed microarray and RNA-seq dataset of blood samples to find the biomarkers related to gene expression in brain. Results We found some functional hub genes, such as ErbB2, ErbB4, OCT3, MIF, CDK13, and GPI. According to GO and KEGG pathway enrichment, several pathways were significantly dysregulated in EC and HIP. CTSD and VCAM1 were dysregulated significantly in blood, EC, and HIP, which were potential biomarkers for AD. Target genes of four microRNAs had similar GO_terms distribution with DEGs in EC and HIP. In addtion, small molecules were screened out for AD treatment. Conclusion These biological pathways and DEGs or hub genes will be useful to elucidate AD pathogenesis and identify novel biomarkers or drug targets for developing improved diagnostics and therapeutics against AD. PMID:29359159

The nuclear genome of Rhazya stricta and the evolution of alkaloid diversity in a medically relevant clade of Apocynaceae

PubMed Central

Sabir, Jamal S. M.; Jansen, Robert K.; Arasappan, Dhivya; Calderon, Virginie; Noutahi, Emmanuel; Zheng, Chunfang; Park, Seongjun; Sabir, Meshaal J.; Baeshen, Mohammed N.; Hajrah, Nahid H.; Khiyami, Mohammad A.; Baeshen, Nabih A.; Obaid, Abdullah Y.; Al-Malki, Abdulrahman L.; Sankoff, David; El-Mabrouk, Nadia; Ruhlman, Tracey A.

2016-01-01

Alkaloid accumulation in plants is activated in response to stress, is limited in distribution and specific alkaloid repertoires are variable across taxa. Rauvolfioideae (Apocynaceae, Gentianales) represents a major center of structural expansion in the monoterpenoid indole alkaloids (MIAs) yielding thousands of unique molecules including highly valuable chemotherapeutics. The paucity of genome-level data for Apocynaceae precludes a deeper understanding of MIA pathway evolution hindering the elucidation of remaining pathway enzymes and the improvement of MIA availability in planta or in vitro. We sequenced the nuclear genome of Rhazya stricta (Apocynaceae, Rauvolfioideae) and present this high quality assembly in comparison with that of coffee (Rubiaceae, Coffea canephora, Gentianales) and others to investigate the evolution of genome-scale features. The annotated Rhazya genome was used to develop the community resource, RhaCyc, a metabolic pathway database. Gene family trees were constructed to identify homologs of MIA pathway genes and to examine their evolutionary history. We found that, unlike Coffea, the Rhazya lineage has experienced many structural rearrangements. Gene tree analyses suggest recent, lineage-specific expansion and diversification among homologs encoding MIA pathway genes in Gentianales and provide candidate sequences with the potential to close gaps in characterized pathways and support prospecting for new MIA production avenues. PMID:27653669

The nuclear genome of Rhazya stricta and the evolution of alkaloid diversity in a medically relevant clade of Apocynaceae.

PubMed

Sabir, Jamal S M; Jansen, Robert K; Arasappan, Dhivya; Calderon, Virginie; Noutahi, Emmanuel; Zheng, Chunfang; Park, Seongjun; Sabir, Meshaal J; Baeshen, Mohammed N; Hajrah, Nahid H; Khiyami, Mohammad A; Baeshen, Nabih A; Obaid, Abdullah Y; Al-Malki, Abdulrahman L; Sankoff, David; El-Mabrouk, Nadia; Ruhlman, Tracey A

2016-09-22

Alkaloid accumulation in plants is activated in response to stress, is limited in distribution and specific alkaloid repertoires are variable across taxa. Rauvolfioideae (Apocynaceae, Gentianales) represents a major center of structural expansion in the monoterpenoid indole alkaloids (MIAs) yielding thousands of unique molecules including highly valuable chemotherapeutics. The paucity of genome-level data for Apocynaceae precludes a deeper understanding of MIA pathway evolution hindering the elucidation of remaining pathway enzymes and the improvement of MIA availability in planta or in vitro. We sequenced the nuclear genome of Rhazya stricta (Apocynaceae, Rauvolfioideae) and present this high quality assembly in comparison with that of coffee (Rubiaceae, Coffea canephora, Gentianales) and others to investigate the evolution of genome-scale features. The annotated Rhazya genome was used to develop the community resource, RhaCyc, a metabolic pathway database. Gene family trees were constructed to identify homologs of MIA pathway genes and to examine their evolutionary history. We found that, unlike Coffea, the Rhazya lineage has experienced many structural rearrangements. Gene tree analyses suggest recent, lineage-specific expansion and diversification among homologs encoding MIA pathway genes in Gentianales and provide candidate sequences with the potential to close gaps in characterized pathways and support prospecting for new MIA production avenues.

Redundancy control in pathway databases (ReCiPa): an application for improving gene-set enrichment analysis in Omics studies and "Big data" biology.

PubMed

Vivar, Juan C; Pemu, Priscilla; McPherson, Ruth; Ghosh, Sujoy

2013-08-01

Abstract Unparalleled technological advances have fueled an explosive growth in the scope and scale of biological data and have propelled life sciences into the realm of "Big Data" that cannot be managed or analyzed by conventional approaches. Big Data in the life sciences are driven primarily via a diverse collection of 'omics'-based technologies, including genomics, proteomics, metabolomics, transcriptomics, metagenomics, and lipidomics. Gene-set enrichment analysis is a powerful approach for interrogating large 'omics' datasets, leading to the identification of biological mechanisms associated with observed outcomes. While several factors influence the results from such analysis, the impact from the contents of pathway databases is often under-appreciated. Pathway databases often contain variously named pathways that overlap with one another to varying degrees. Ignoring such redundancies during pathway analysis can lead to the designation of several pathways as being significant due to high content-similarity, rather than truly independent biological mechanisms. Statistically, such dependencies also result in correlated p values and overdispersion, leading to biased results. We investigated the level of redundancies in multiple pathway databases and observed large discrepancies in the nature and extent of pathway overlap. This prompted us to develop the application, ReCiPa (Redundancy Control in Pathway Databases), to control redundancies in pathway databases based on user-defined thresholds. Analysis of genomic and genetic datasets, using ReCiPa-generated overlap-controlled versions of KEGG and Reactome pathways, led to a reduction in redundancy among the top-scoring gene-sets and allowed for the inclusion of additional gene-sets representing possibly novel biological mechanisms. Using obesity as an example, bioinformatic analysis further demonstrated that gene-sets identified from overlap-controlled pathway databases show stronger evidence of prior association to obesity compared to pathways identified from the original databases.

FreeSolv: A database of experimental and calculated hydration free energies, with input files

PubMed Central

Mobley, David L.; Guthrie, J. Peter

2014-01-01

This work provides a curated database of experimental and calculated hydration free energies for small neutral molecules in water, along with molecular structures, input files, references, and annotations. We call this the Free Solvation Database, or FreeSolv. Experimental values were taken from prior literature and will continue to be curated, with updated experimental references and data added as they become available. Calculated values are based on alchemical free energy calculations using molecular dynamics simulations. These used the GAFF small molecule force field in TIP3P water with AM1-BCC charges. Values were calculated with the GROMACS simulation package, with full details given in references cited within the database itself. This database builds in part on a previous, 504-molecule database containing similar information. However, additional curation of both experimental data and calculated values has been done here, and the total number of molecules is now up to 643. Additional information is now included in the database, such as SMILES strings, PubChem compound IDs, accurate reference DOIs, and others. One version of the database is provided in the Supporting Information of this article, but as ongoing updates are envisioned, the database is now versioned and hosted online. In addition to providing the database, this work describes its construction process. The database is available free-of-charge via http://www.escholarship.org/uc/item/6sd403pz. PMID:24928188

Photon entanglement signatures in difference-frequency-generation

PubMed Central

Roslyak, Oleksiy; Mukamel, Shaul

2010-01-01

In response to quantum optical fields, pairs of molecules generate coherent nonlinear spectroscopy signals. Homodyne signals are given by sums over terms each being a product of Liouville space pathways of the pair of molecules times the corresponding optical field correlation function. For classical fields all field correlation functions may be factorized and become identical products of field amplitudes. The signal is then given by the absolute square of a susceptibility which in turn is a sum over pathways of a single molecule. The molecular pathways of different molecules in the pair are uncorrelated in this case (each path of a given molecule can be accompanied by any path of the other). However, entangled photons create an entanglement between the molecular pathways. We use the superoperator nonequlibrium Green’s functions formalism to demonstrate the signatures of this pathway-entanglement in the difference frequency generation signal. Comparison is made with an analogous incoherent two-photon fluorescence signal. PMID:19158927

An update on the Enzyme Portal: an integrative approach for exploring enzyme knowledge

PubMed Central

Onwubiko, J.; Zaru, R.; Rosanoff, S.; Antunes, R.; Bingley, M.; Watkins, X.; O'Donovan, C.; Martin, M. J.

2017-01-01

Abstract Enzymes are a key part of life processes and are increasingly important for various areas of research such as medicine, biotechnology, bioprocessing and drug research. The goal of the Enzyme Portal is to provide an interface to all European Bioinformatics Institute (EMBL-EBI) data about enzymes (de Matos, P., et al., (2013), BMC Bioinformatics, 14 (1), 103). These data include enzyme function, sequence features and family classification, protein structure, reactions, pathways, small molecules, diseases and the associated literature. The sources of enzyme data are: the UniProt Knowledgebase (UniProtKB) (UniProt Consortium, 2015), the Protein Data Bank in Europe (PDBe), (Valenkar, S., et al., Nucleic Acids Res.2016; 44, D385–D395) Rhea—a database of enzyme-catalysed reactions (Morgat, A., et al., Nucleic Acids Res. 2015; 43, D459-D464), Reactome—a database of biochemical pathways (Fabregat, A., et al., Nucleic Acids Res. 2016; 44, D481–D487), IntEnz—a resource with enzyme nomenclature information (Fleischmann, A., et al., Nucleic Acids Res. 2004 32, D434–D437) and ChEBI (Hastings, J., et al., Nucleic Acids Res. 2013) and ChEMBL (Bento, A. P., et al., Nucleic Acids Res. 201442, 1083–1090)—resources which contain information about small-molecule chemistry and bioactivity. This article describes the redesign of Enzyme Portal and the increased functionality added to maximise integration and interpretation of these data. Use case examples of the Enzyme Portal and the versatile workflows its supports are illustrated. We welcome the suggestion of new resources for integration. PMID:28158609

An update on the Enzyme Portal: an integrative approach for exploring enzyme knowledge.

PubMed

Pundir, S; Onwubiko, J; Zaru, R; Rosanoff, S; Antunes, R; Bingley, M; Watkins, X; O'Donovan, C; Martin, M J

2017-03-01

Enzymes are a key part of life processes and are increasingly important for various areas of research such as medicine, biotechnology, bioprocessing and drug research. The goal of the Enzyme Portal is to provide an interface to all European Bioinformatics Institute (EMBL-EBI) data about enzymes (de Matos, P., et al. , (2013), BMC Bioinformatics , (1), 103). These data include enzyme function, sequence features and family classification, protein structure, reactions, pathways, small molecules, diseases and the associated literature. The sources of enzyme data are: the UniProt Knowledgebase (UniProtKB) (UniProt Consortium, 2015), the Protein Data Bank in Europe (PDBe), (Valenkar, S., et al ., Nucleic Acids Res. 2016; , D385-D395) Rhea-a database of enzyme-catalysed reactions (Morgat, A., et al .,  Nucleic Acids Res.  2015; , D459-D464), Reactome-a database of biochemical pathways (Fabregat, A., et al ., Nucleic Acids Res. 2016;  , D481-D487), IntEnz-a resource with enzyme nomenclature information (Fleischmann, A., et al ., Nucleic Acids Res.  2004 , D434-D437) and ChEBI (Hastings, J., et al .,  Nucleic Acids Res. 2013) and ChEMBL (Bento, A. P., et al ., Nucleic Acids Res.  2014 , 1083-1090)-resources which contain information about small-molecule chemistry and bioactivity. This article describes the redesign of Enzyme Portal and the increased functionality added to maximise integration and interpretation of these data. Use case examples of the Enzyme Portal and the versatile workflows its supports are illustrated. We welcome the suggestion of new resources for integration. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Morphinome Database - The database of proteins altered by morphine administration - An update.

PubMed

Bodzon-Kulakowska, Anna; Padrtova, Tereza; Drabik, Anna; Ner-Kluza, Joanna; Antolak, Anna; Kulakowski, Konrad; Suder, Piotr

2018-04-13

Morphine is considered a gold standard in pain treatment. Nevertheless, its use could be associated with severe side effects, including drug addiction. Thus, it is very important to understand the molecular mechanism of morphine action in order to develop new methods of pain therapy, or at least to attenuate the side effects of opioids usage. Proteomics allows for the indication of proteins involved in certain biological processes, but the number of items identified in a single study is usually overwhelming. Thus, researchers face the difficult problem of choosing the proteins which are really important for the investigated processes and worth further studies. Therefore, based on the 29 published articles, we created a database of proteins regulated by morphine administration - The Morphinome Database (addiction-proteomics.org). This web tool allows for indicating proteins that were identified during different proteomics studies. Moreover, the collection and organization of such a vast amount of data allows us to find the same proteins that were identified in various studies and to create their ranking, based on the frequency of their identification. STRING and KEGG databases indicated metabolic pathways which those molecules are involved in. This means that those molecular pathways seem to be strongly affected by morphine administration and could be important targets for further investigations. The data about proteins identified by different proteomics studies of molecular changes caused by morphine administration (29 published articles) were gathered in the Morphinome Database. Unification of those data allowed for the identification of proteins that were indicated several times by distinct proteomics studies, which means that they seem to be very well verified and important for the entire process. Those proteins might be now considered promising aims for more detailed studies of their role in the molecular mechanism of morphine action. Copyright © 2018. Published by Elsevier B.V.

AOP-DB Frontend: A user interface for the Adverse Outcome Pathways Database.

EPA Science Inventory

The EPA Adverse Outcome Pathway Database (AOP-DB) is a database resource that aggregates association relationships between AOPs, genes, chemicals, diseases, pathways, species orthology information, ontologies. The AOP-DB frontend is a simple yet powerful AOP-DB user interface in...

AOP-DB Frontend: A user interface for the Adverse Outcome Pathways Database

EPA Science Inventory

The EPA Adverse Outcome Pathway Database (AOP-DB) is a database resource that aggregates association relationships between AOPs, genes, chemicals, diseases, pathways, species orthology information, ontologies. The AOP-DB frontend is a simple yet powerful user interface in the for...

Diterpenes and Their Derivatives as Potential Anticancer Agents.

PubMed

Islam, Muhammad Torequl

2017-05-01

As therapeutic tools, diterpenes and their derivatives have gained much attention of the medicinal scientists nowadays. It is due to their pledging and important biological activities. This review congregates the anticancer diterpenes. For this, a search was made with selected keywords in PubMed, Science Direct, Web of Science, Scopus, The American Chemical Society and miscellaneous databases from January 2012 to January 2017 for the published articles. A total 28, 789 published articles were seen. Among them, 240 were included in this study. More than 250 important anticancer diterpenes and their derivatives were seen in the databases, acting in the different pathways. Some of them are already under clinical trials, while others are in the nonclinical and/or pre-clinical trials. In conclusion, diterpenes may be one of the lead molecules in the treatment of cancer. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

The origin of intermediary metabolism

NASA Technical Reports Server (NTRS)

Morowitz, H. J.; Kostelnik, J. D.; Yang, J.; Cody, G. D.

2000-01-01

The core of intermediary metabolism in autotrophs is the citric acid cycle. In a certain group of chemoautotrophs, the reductive citric acid cycle is an engine of synthesis, taking in CO(2) and synthesizing the molecules of the cycle. We have examined the chemistry of a model system of C, H, and O that starts with carbon dioxide and reductants and uses redox couples as the energy source. To inquire into the reaction networks that might emerge, we start with the largest available database of organic molecules, Beilstein on-line, and prune by a set of physical and chemical constraints applicable to the model system. From the 3.5 million entries in Beilstein we emerge with 153 molecules that contain all 11 members of the reductive citric acid cycle. A small number of selection rules generates a very constrained subset, suggesting that this is the type of reaction model that will prove useful in the study of biogenesis. The model indicates that the metabolism shown in the universal chart of pathways may be central to the origin of life, is emergent from organic chemistry, and may be unique.

The Molecule Pages database

PubMed Central

Saunders, Brian; Lyon, Stephen; Day, Matthew; Riley, Brenda; Chenette, Emily; Subramaniam, Shankar

2008-01-01

The UCSD-Nature Signaling Gateway Molecule Pages (http://www.signaling-gateway.org/molecule) provides essential information on more than 3800 mammalian proteins involved in cellular signaling. The Molecule Pages contain expert-authored and peer-reviewed information based on the published literature, complemented by regularly updated information derived from public data source references and sequence analysis. The expert-authored data includes both a full-text review about the molecule, with citations, and highly structured data for bioinformatics interrogation, including information on protein interactions and states, transitions between states and protein function. The expert-authored pages are anonymously peer reviewed by the Nature Publishing Group. The Molecule Pages data is present in an object-relational database format and is freely accessible to the authors, the reviewers and the public from a web browser that serves as a presentation layer. The Molecule Pages are supported by several applications that along with the database and the interfaces form a multi-tier architecture. The Molecule Pages and the Signaling Gateway are routinely accessed by a very large research community. PMID:17965093

The Molecule Pages database.

PubMed

Saunders, Brian; Lyon, Stephen; Day, Matthew; Riley, Brenda; Chenette, Emily; Subramaniam, Shankar; Vadivelu, Ilango

2008-01-01

The UCSD-Nature Signaling Gateway Molecule Pages (http://www.signaling-gateway.org/molecule) provides essential information on more than 3800 mammalian proteins involved in cellular signaling. The Molecule Pages contain expert-authored and peer-reviewed information based on the published literature, complemented by regularly updated information derived from public data source references and sequence analysis. The expert-authored data includes both a full-text review about the molecule, with citations, and highly structured data for bioinformatics interrogation, including information on protein interactions and states, transitions between states and protein function. The expert-authored pages are anonymously peer reviewed by the Nature Publishing Group. The Molecule Pages data is present in an object-relational database format and is freely accessible to the authors, the reviewers and the public from a web browser that serves as a presentation layer. The Molecule Pages are supported by several applications that along with the database and the interfaces form a multi-tier architecture. The Molecule Pages and the Signaling Gateway are routinely accessed by a very large research community.

A prototypic small molecule database for bronchoalveolar lavage-based metabolomics

NASA Astrophysics Data System (ADS)

Walmsley, Scott; Cruickshank-Quinn, Charmion; Quinn, Kevin; Zhang, Xing; Petrache, Irina; Bowler, Russell P.; Reisdorph, Richard; Reisdorph, Nichole

2018-04-01

The analysis of bronchoalveolar lavage fluid (BALF) using mass spectrometry-based metabolomics can provide insight into lung diseases, such as asthma. However, the important step of compound identification is hindered by the lack of a small molecule database that is specific for BALF. Here we describe prototypic, small molecule databases derived from human BALF samples (n=117). Human BALF was extracted into lipid and aqueous fractions and analyzed using liquid chromatography mass spectrometry. Following filtering to reduce contaminants and artifacts, the resulting BALF databases (BALF-DBs) contain 11,736 lipid and 658 aqueous compounds. Over 10% of these were found in 100% of samples. Testing the BALF-DBs using nested test sets produced a 99% match rate for lipids and 47% match rate for aqueous molecules. Searching an independent dataset resulted in 45% matching to the lipid BALF-DB compared to<25% when general databases are searched. The BALF-DBs are available for download from MetaboLights. Overall, the BALF-DBs can reduce false positives and improve confidence in compound identification compared to when general databases are used.

ChemProt-2.0: visual navigation in a disease chemical biology database

PubMed Central

Kim Kjærulff, Sonny; Wich, Louis; Kringelum, Jens; Jacobsen, Ulrik P.; Kouskoumvekaki, Irene; Audouze, Karine; Lund, Ole; Brunak, Søren; Oprea, Tudor I.; Taboureau, Olivier

2013-01-01

ChemProt-2.0 (http://www.cbs.dtu.dk/services/ChemProt-2.0) is a public available compilation of multiple chemical–protein annotation resources integrated with diseases and clinical outcomes information. The database has been updated to >1.15 million compounds with 5.32 millions bioactivity measurements for 15 290 proteins. Each protein is linked to quality-scored human protein–protein interactions data based on more than half a million interactions, for studying diseases and biological outcomes (diseases, pathways and GO terms) through protein complexes. In ChemProt-2.0, therapeutic effects as well as adverse drug reactions have been integrated allowing for suggesting proteins associated to clinical outcomes. New chemical structure fingerprints were computed based on the similarity ensemble approach. Protein sequence similarity search was also integrated to evaluate the promiscuity of proteins, which can help in the prediction of off-target effects. Finally, the database was integrated into a visual interface that enables navigation of the pharmacological space for small molecules. Filtering options were included in order to facilitate and to guide dynamic search of specific queries. PMID:23185041

The European Bioinformatics Institute's data resources: towards systems biology.

PubMed

Brooksbank, Catherine; Cameron, Graham; Thornton, Janet

2005-01-01

Genomic and post-genomic biological research has provided fine-grain insights into the molecular processes of life, but also threatens to drown biomedical researchers in data. Moreover, as new high-throughput technologies are developed, the types of data that are gathered en masse are diversifying. The need to collect, store and curate all this information in ways that allow its efficient retrieval and exploitation is greater than ever. The European Bioinformatics Institute's (EBI's) databases and tools have evolved to meet the changing needs of molecular biologists: since we last wrote about our services in the 2003 issue of Nucleic Acids Research, we have launched new databases covering protein-protein interactions (IntAct), pathways (Reactome) and small molecules (ChEBI). Our existing core databases have continued to evolve to meet the changing needs of biomedical researchers, and we have developed new data-access tools that help biologists to move intuitively through the different data types, thereby helping them to put the parts together to understand biology at the systems level. The EBI's data resources are all available on our website at http://www.ebi.ac.uk.

The European Bioinformatics Institute's data resources: towards systems biology

PubMed Central

Brooksbank, Catherine; Cameron, Graham; Thornton, Janet

2005-01-01

Genomic and post-genomic biological research has provided fine-grain insights into the molecular processes of life, but also threatens to drown biomedical researchers in data. Moreover, as new high-throughput technologies are developed, the types of data that are gathered en masse are diversifying. The need to collect, store and curate all this information in ways that allow its efficient retrieval and exploitation is greater than ever. The European Bioinformatics Institute's (EBI's) databases and tools have evolved to meet the changing needs of molecular biologists: since we last wrote about our services in the 2003 issue of Nucleic Acids Research, we have launched new databases covering protein–protein interactions (IntAct), pathways (Reactome) and small molecules (ChEBI). Our existing core databases have continued to evolve to meet the changing needs of biomedical researchers, and we have developed new data-access tools that help biologists to move intuitively through the different data types, thereby helping them to put the parts together to understand biology at the systems level. The EBI's data resources are all available on our website at http://www.ebi.ac.uk. PMID:15608238

The Hippo/YAP pathway interacts with EGFR signaling and HPV oncoproteins to regulate cervical cancer progression.

PubMed

He, Chunbo; Mao, Dagan; Hua, Guohua; Lv, Xiangmin; Chen, Xingcheng; Angeletti, Peter C; Dong, Jixin; Remmenga, Steven W; Rodabaugh, Kerry J; Zhou, Jin; Lambert, Paul F; Yang, Peixin; Davis, John S; Wang, Cheng

2015-11-01

The Hippo signaling pathway controls organ size and tumorigenesis through a kinase cascade that inactivates Yes-associated protein (YAP). Here, we show that YAP plays a central role in controlling the progression of cervical cancer. Our results suggest that YAP expression is associated with a poor prognosis for cervical cancer. TGF-α and amphiregulin (AREG), via EGFR, inhibit the Hippo signaling pathway and activate YAP to induce cervical cancer cell proliferation and migration. Activated YAP allows for up-regulation of TGF-α, AREG, and EGFR, forming a positive signaling loop to drive cervical cancer cell proliferation. HPV E6 protein, a major etiological molecule of cervical cancer, maintains high YAP protein levels in cervical cancer cells by preventing proteasome-dependent YAP degradation to drive cervical cancer cell proliferation. Results from human cervical cancer genomic databases and an accepted transgenic mouse model strongly support the clinical relevance of the discovered feed-forward signaling loop. Our study indicates that combined targeting of the Hippo and the ERBB signaling pathways represents a novel therapeutic strategy for prevention and treatment of cervical cancer. © 2015 The Authors. Published under the terms of the CC BY 4.0 license.

Gene expression profiles in liver of mouse after chronic exposure to drinking water.

PubMed

Wu, Bing; Zhang, Yan; Zhao, Dayong; Zhang, Xuxiang; Kong, Zhiming; Cheng, Shupei

2009-10-01

cDNA micorarray approach was applied to hepatic transcriptional profile analysis in male mouse (Mus musculus, ICR) to assess the potential health effects of drinking water in Nanjing, China. Mice were treated with continuous exposure to drinking water for 90 days. Hepatic gene expression was analyzed with Affymetrix Mouse Genome 430A 2.0 arrays, and pathway analysis was carried out by Molecule Annotation System 2.0 and KEGG pathway database. A total of 836 genes were found to be significantly altered (1.5-fold, P < or = 0.05), including 294 up-regulated genes and 542 down-regulated genes. According to biological pathway analysis, drinking water exposure resulted in aberration of gene expression and biological pathways linked to xenobiotic metabolism, signal transduction, cell cycle and oxidative stress response. Further, deregulation of several genes associated with carcinogenesis or tumor progression including Ccnd1, Egfr, Map2k3, Mcm2, Orc2l and Smad2 was observed. Although transcription changes in identified genes are unlikely to be used as a sole indicator of adverse health effects, the results of this study could enhance our understanding of early toxic effects of drinking water exposure and support future studies on drinking water safety.

A systematic analysis of a mi-RNA inter-pathway regulatory motif

PubMed Central

2013-01-01

Background The continuing discovery of new types and functions of small non-coding RNAs is suggesting the presence of regulatory mechanisms far more complex than the ones currently used to study and design Gene Regulatory Networks. Just focusing on the roles of micro RNAs (miRNAs), they have been found to be part of several intra-pathway regulatory motifs. However, inter-pathway regulatory mechanisms have been often neglected and require further investigation. Results In this paper we present the result of a systems biology study aimed at analyzing a high-level inter-pathway regulatory motif called Pathway Protection Loop, not previously described, in which miRNAs seem to play a crucial role in the successful behavior and activation of a pathway. Through the automatic analysis of a large set of public available databases, we found statistical evidence that this inter-pathway regulatory motif is very common in several classes of KEGG Homo Sapiens pathways and concurs in creating a complex regulatory network involving several pathways connected by this specific motif. The role of this motif seems also confirmed by a deeper review of other research activities on selected representative pathways. Conclusions Although previous studies suggested transcriptional regulation mechanism at the pathway level such as the Pathway Protection Loop, a high-level analysis like the one proposed in this paper is still missing. The understanding of higher-level regulatory motifs could, as instance, lead to new approaches in the identification of therapeutic targets because it could unveil new and “indirect” paths to activate or silence a target pathway. However, a lot of work still needs to be done to better uncover this high-level inter-pathway regulation including enlarging the analysis to other small non-coding RNA molecules. PMID:24152805

tRNAmodpred: a computational method for predicting posttranscriptional modifications in tRNAs

PubMed Central

Machnicka, Magdalena A.; Dunin-Horkawicz, Stanislaw; de Crécy-Lagard, Valerie; Bujnicki, Janusz M.

2016-01-01

tRNA molecules contain numerous chemically altered nucleosides, which are formed by enzymatic modification of the primary transcripts during the complex tRNA maturation process. Some of the modifications are introduced by single reactions, while other require complex series of reactions carried out by several different enzymes. The location and distribution of various types of modifications vary greatly between different tRNA molecules, organisms and organelles. We have developed a computational method tRNAmodpred, for predicting modifications in tRNA sequences. Briefly, our method takes as an input one or more unmodified tRNA sequences and a set of protein sequences corresponding to a proteome of a cell. Subsequently it identifies homologs of known tRNA modification enzymes in the proteome, predicts tRNA modification activities and maps them onto known pathways of RNA modification from the MODOMICS database. Thereby, theoretically possible modification pathways are identified, and products of these modification reactions are proposed for query tRNAs. This method allows for predicting modification patterns for newly sequenced genomes as well as for checking tentative modification status of tRNAs from one species treated with enzymes from another source, e.g. to predict the possible modifications of eukaryotic tRNAs expressed in bacteria. tRNAmodpred is freely available as web server at http://genesilico.pl/trnamodpred/. PMID:27016142

Internet Databases of the Properties, Enzymatic Reactions, and Metabolism of Small Molecules—Search Options and Applications in Food Science

PubMed Central

Minkiewicz, Piotr; Darewicz, Małgorzata; Iwaniak, Anna; Bucholska, Justyna; Starowicz, Piotr; Czyrko, Emilia

2016-01-01

Internet databases of small molecules, their enzymatic reactions, and metabolism have emerged as useful tools in food science. Database searching is also introduced as part of chemistry or enzymology courses for food technology students. Such resources support the search for information about single compounds and facilitate the introduction of secondary analyses of large datasets. Information can be retrieved from databases by searching for the compound name or structure, annotating with the help of chemical codes or drawn using molecule editing software. Data mining options may be enhanced by navigating through a network of links and cross-links between databases. Exemplary databases reviewed in this article belong to two classes: tools concerning small molecules (including general and specialized databases annotating food components) and tools annotating enzymes and metabolism. Some problems associated with database application are also discussed. Data summarized in computer databases may be used for calculation of daily intake of bioactive compounds, prediction of metabolism of food components, and their biological activity as well as for prediction of interactions between food component and drugs. PMID:27929431

miRwayDB: a database for experimentally validated microRNA-pathway associations in pathophysiological conditions

PubMed Central

Das, Sankha Subhra; Saha, Pritam

2018-01-01

Abstract MicroRNAs (miRNAs) are well-known as key regulators of diverse biological pathways. A series of experimental evidences have shown that abnormal miRNA expression profiles are responsible for various pathophysiological conditions by modulating genes in disease associated pathways. In spite of the rapid increase in research data confirming such associations, scientists still do not have access to a consolidated database offering these miRNA-pathway association details for critical diseases. We have developed miRwayDB, a database providing comprehensive information of experimentally validated miRNA-pathway associations in various pathophysiological conditions utilizing data collected from published literature. To the best of our knowledge, it is the first database that provides information about experimentally validated miRNA mediated pathway dysregulation as seen specifically in critical human diseases and hence indicative of a cause-and-effect relationship in most cases. The current version of miRwayDB collects an exhaustive list of miRNA-pathway association entries for 76 critical disease conditions by reviewing 663 published articles. Each database entry contains complete information on the name of the pathophysiological condition, associated miRNA(s), experimental sample type(s), regulation pattern (up/down) of miRNA, pathway association(s), targeted member of dysregulated pathway(s) and a brief description. In addition, miRwayDB provides miRNA, gene and pathway score to evaluate the role of a miRNA regulated pathways in various pathophysiological conditions. The database can also be used for other biomedical approaches such as validation of computational analysis, integrated analysis and prediction of computational model. It also offers a submission page to submit novel data from recently published studies. We believe that miRwayDB will be a useful tool for miRNA research community. Database URL: http://www.mirway.iitkgp.ac.in PMID:29688364

Far-field photostable optical nanoscopy (PHOTON) for real-time super-resolution single-molecular imaging of signaling pathways of single live cells

NASA Astrophysics Data System (ADS)

Huang, Tao; Browning, Lauren M.; Xu, Xiao-Hong Nancy

2012-04-01

Cellular signaling pathways play crucial roles in cellular functions and design of effective therapies. Unfortunately, study of cellular signaling pathways remains formidably challenging because sophisticated cascades are involved, and a few molecules are sufficient to trigger signaling responses of a single cell. Here we report the development of far-field photostable-optical-nanoscopy (PHOTON) with photostable single-molecule-nanoparticle-optical-biosensors (SMNOBS) for mapping dynamic cascades of apoptotic signaling pathways of single live cells in real-time at single-molecule (SM) and nanometer (nm) resolutions. We have quantitatively imaged single ligand molecules (tumor necrosis factor α, TNFα) and their binding kinetics with their receptors (TNFR1) on single live cells; tracked formation and internalization of their clusters and their initiation of intracellular signaling pathways in real-time; and studied apoptotic signaling dynamics and mechanisms of single live cells with sufficient temporal and spatial resolutions. This study provides new insights into complex real-time dynamic cascades and molecular mechanisms of apoptotic signaling pathways of single live cells. PHOTON provides superior imaging and sensing capabilities and SMNOBS offer unrivaled biocompatibility and photostability, which enable probing of signaling pathways of single live cells in real-time at SM and nm resolutions.Cellular signaling pathways play crucial roles in cellular functions and design of effective therapies. Unfortunately, study of cellular signaling pathways remains formidably challenging because sophisticated cascades are involved, and a few molecules are sufficient to trigger signaling responses of a single cell. Here we report the development of far-field photostable-optical-nanoscopy (PHOTON) with photostable single-molecule-nanoparticle-optical-biosensors (SMNOBS) for mapping dynamic cascades of apoptotic signaling pathways of single live cells in real-time at single-molecule (SM) and nanometer (nm) resolutions. We have quantitatively imaged single ligand molecules (tumor necrosis factor α, TNFα) and their binding kinetics with their receptors (TNFR1) on single live cells; tracked formation and internalization of their clusters and their initiation of intracellular signaling pathways in real-time; and studied apoptotic signaling dynamics and mechanisms of single live cells with sufficient temporal and spatial resolutions. This study provides new insights into complex real-time dynamic cascades and molecular mechanisms of apoptotic signaling pathways of single live cells. PHOTON provides superior imaging and sensing capabilities and SMNOBS offer unrivaled biocompatibility and photostability, which enable probing of signaling pathways of single live cells in real-time at SM and nm resolutions. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr11739h

SM-TF: A structural database of small molecule-transcription factor complexes.

PubMed

Xu, Xianjin; Ma, Zhiwei; Sun, Hongmin; Zou, Xiaoqin

2016-06-30

Transcription factors (TFs) are the proteins involved in the transcription process, ensuring the correct expression of specific genes. Numerous diseases arise from the dysfunction of specific TFs. In fact, over 30 TFs have been identified as therapeutic targets of about 9% of the approved drugs. In this study, we created a structural database of small molecule-transcription factor (SM-TF) complexes, available online at http://zoulab.dalton.missouri.edu/SM-TF. The 3D structures of the co-bound small molecule and the corresponding binding sites on TFs are provided in the database, serving as a valuable resource to assist structure-based drug design related to TFs. Currently, the SM-TF database contains 934 entries covering 176 TFs from a variety of species. The database is further classified into several subsets by species and organisms. The entries in the SM-TF database are linked to the UniProt database and other sequence-based TF databases. Furthermore, the druggable TFs from human and the corresponding approved drugs are linked to the DrugBank. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Dynamic expression patterns of ECM molecules in the developing mouse olfactory pathway

PubMed Central

Shay, Elaine L.; Greer, Charles A.; Treloar, Helen B.

2009-01-01

Olfactory sensory neuron (OSN) axons follow stereotypic spatio-temporal paths in the establishment of the olfactory pathway. Extracellular matrix (ECM) molecules are expressed early in the developing pathway and are proposed to have a role in its initial establishment. During later embryonic development, OSNs sort out and target specific glomeruli to form precise, complex topographic projections. We hypothesized that ECM cues may help to establish this complex topography. The aim of this study was to characterize expression of ECM molecules during the period of glomerulogenesis, when synaptic contacts are forming. We examined expression of laminin-1, perlecan, tenascin-C and CSPGs and found a coordinated pattern of expression of these cues in the pathway. These appear to restrict axons to the pathway while promoting axon outgrowth within. Thus, ECM molecules are present in dynamic spatio-temporal positions to affect OSN axons as they navigate to the olfactory bulb and establish synapses. PMID:18570250

The HITRAN 2008 Molecular Spectroscopic Database

NASA Technical Reports Server (NTRS)

Rothman, Laurence S.; Gordon, Iouli E.; Barbe, Alain; Benner, D. Chris; Bernath, Peter F.; Birk, Manfred; Boudon, V.; Brown, Linda R.; Campargue, Alain; Champion, J.-P.;

GPCR & company: databases and servers for GPCRs and interacting partners.

PubMed

Kowalsman, Noga; Niv, Masha Y

2014-01-01

G-protein-coupled receptors (GPCRs) are a large superfamily of membrane receptors that are involved in a wide range of signaling pathways. To fulfill their tasks, GPCRs interact with a variety of partners, including small molecules, lipids and proteins. They are accompanied by different proteins during all phases of their life cycle. Therefore, GPCR interactions with their partners are of great interest in basic cell-signaling research and in drug discovery.Due to the rapid development of computers and internet communication, knowledge and data can be easily shared within the worldwide research community via freely available databases and servers. These provide an abundance of biological, chemical and pharmacological information.This chapter describes the available web resources for investigating GPCR interactions. We review about 40 freely available databases and servers, and provide a few sentences about the essence and the data they supply. For simplification, the databases and servers were grouped under the following topics: general GPCR-ligand interactions; particular families of GPCRs and their ligands; GPCR oligomerization; GPCR interactions with intracellular partners; and structural information on GPCRs. In conclusion, a multitude of useful tools are currently available. Summary tables are provided to ease navigation between the numerous and partially overlapping resources. Suggestions for future enhancements of the online tools include the addition of links from general to specialized databases and enabling usage of user-supplied template for GPCR structural modeling.

The Alarmin Properties of DNA and DNA-associated Nuclear Proteins.

PubMed

Magna, Melinda; Pisetsky, David S

2016-05-01

The communication of cell injury and death is a critical element in host defense. Although immune cells can serve this function by elaborating cytokines and chemokines, somatic cells can repurpose nuclear macromolecules to function as damage-associated molecular patterns (DAMPs) or alarmins to exert similar activity. Among these molecules, DNA, high-mobility group box-1, and histone proteins can all act as DAMPs once they are in an extracellular location. This review describes current information on the role of the nuclear DAMPs, their translocation to the outside of cells, and pathways of activation after uptake into the inside of immune cells. MEDLINE and PubMed databases were searched for citations (1990-2016) in English related to the following terms: DAMPs, high-mobility group box-1, DNA, histones, cell death, danger, and immune activation. Selected articles with the most relevant studies were included for a more detailed consideration. Although nuclear molecules have important structural and genetic regulatory roles inside the cell nucleus, when released into the extracellular space during cell death, these molecules can acquire immune activity and serve as alarmins or DAMPs. Although apoptosis is generally considered the source of extracellular nuclear material, other cell death pathways such as necroptosis, NETosis, and pyroptosis can contribute to the release of nuclear molecules. Importantly, the release of nuclear DAMPs occurs with both soluble and particulate forms of these molecules. The activity of nuclear molecules may depend on posttranslational modifications, redox changes, and the binding of other molecules. Once in an extracellular location, nuclear DAMPs can engage the same pattern recognition receptors as do pathogen-associated molecular patterns. These interactions can activate immune cells and lead to cytokine and chemokine production. Among these receptors, internal receptors for DNA are key to the response to this molecule; the likely function of these internal sensors is the recognition of DNA from intracellular infection by bacteria or viruses. Activation of these receptors requires translocation of extracellular DNA into specialized compartments. In addition to nuclear DNA, mitochondrial DNA can also serve as a DAMP. The communication of cell injury and death is a critical element in host defense and involves the repurposing of nuclear molecules as immune triggers. As such, the presence of extracellular nuclear material can serve as novel biomarkers for conditions involving cell injury and death. Targeting of these molecules may also represent an important new approach to therapy. Published by Elsevier Inc.

Expanding Biosensing Abilities through Computer-Aided Design of Metabolic Pathways.

PubMed

Libis, Vincent; Delépine, Baudoin; Faulon, Jean-Loup

2016-10-21

Detection of chemical signals is critical for cells in nature as well as in synthetic biology, where they serve as inputs for designer circuits. Important progress has been made in the design of signal processing circuits triggering complex biological behaviors, but the range of small molecules recognized by sensors as inputs is limited. The ability to detect new molecules will increase the number of synthetic biology applications, but direct engineering of tailor-made sensors takes time. Here we describe a way to immediately expand the range of biologically detectable molecules by systematically designing metabolic pathways that transform nondetectable molecules into molecules for which sensors already exist. We leveraged computer-aided design to predict such sensing-enabling metabolic pathways, and we built several new whole-cell biosensors for molecules such as cocaine, parathion, hippuric acid, and nitroglycerin.

Reconstruction of metabolic pathways for the cattle genome

PubMed Central

Seo, Seongwon; Lewin, Harris A

2009-01-01

Background Metabolic reconstruction of microbial, plant and animal genomes is a necessary step toward understanding the evolutionary origins of metabolism and species-specific adaptive traits. The aims of this study were to reconstruct conserved metabolic pathways in the cattle genome and to identify metabolic pathways with missing genes and proteins. The MetaCyc database and PathwayTools software suite were chosen for this work because they are widely used and easy to implement. Results An amalgamated cattle genome database was created using the NCBI and Ensembl cattle genome databases (based on build 3.1) as data sources. PathwayTools was used to create a cattle-specific pathway genome database, which was followed by comprehensive manual curation for the reconstruction of metabolic pathways. The curated database, CattleCyc 1.0, consists of 217 metabolic pathways. A total of 64 mammalian-specific metabolic pathways were modified from the reference pathways in MetaCyc, and two pathways previously identified but missing from MetaCyc were added. Comparative analysis of metabolic pathways revealed the absence of mammalian genes for 22 metabolic enzymes whose activity was reported in the literature. We also identified six human metabolic protein-coding genes for which the cattle ortholog is missing from the sequence assembly. Conclusion CattleCyc is a powerful tool for understanding the biology of ruminants and other cetartiodactyl species. In addition, the approach used to develop CattleCyc provides a framework for the metabolic reconstruction of other newly sequenced mammalian genomes. It is clear that metabolic pathway analysis strongly reflects the quality of the underlying genome annotations. Thus, having well-annotated genomes from many mammalian species hosted in BioCyc will facilitate the comparative analysis of metabolic pathways among different species and a systems approach to comparative physiology. PMID:19284618

Combined use of computational chemistry and chemoinformatics methods for chemical discovery

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

Sugimoto, Manabu, E-mail: sugimoto@kumamoto-u.ac.jp; Institute for Molecular Science, 38 Nishigo-Naka, Myodaiji, Okazaki 444-8585; CREST, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012

2015-12-31

Data analysis on numerical data by the computational chemistry calculations is carried out to obtain knowledge information of molecules. A molecular database is developed to systematically store chemical, electronic-structure, and knowledge-based information. The database is used to find molecules related to a keyword of “cancer”. Then the electronic-structure calculations are performed to quantitatively evaluate quantum chemical similarity of the molecules. Among the 377 compounds registered in the database, 24 molecules are found to be “cancer”-related. This set of molecules includes both carcinogens and anticancer drugs. The quantum chemical similarity analysis, which is carried out by using numerical results of themore » density-functional theory calculations, shows that, when some energy spectra are referred to, carcinogens are reasonably distinguished from the anticancer drugs. Therefore these spectral properties are considered of as important measures for classification.« less

Possible association between Helicobacter pylori infection and nonalcoholic fatty liver disease.

PubMed

Chen, Chang-Xi; Mao, Yu-Shan; Foster, Parker; Zhu, Zhong-Wei; Du, Juan; Guo, Chuan-Yong

2017-03-01

Possible association between Helicobacter pylori infection (HPI) and nonalcoholic fatty liver disease (NAFLD) has been proposed by several studies with inconsistent conclusions. Here, we studied the association between HPI and NAFLD at 3 levels: (i) genetic level; (ii) small molecular level; and (iii) clinical level. Relation data between diseases, genes, and small molecules were acquired from Pathway Studio ResNet Mammalian database. Clinical data were acquired from 2263 elderly South Chinese subjects, including 603 NAFLD patients and 1660 subjects without NAFLD. Results showed that HPI and NAFLD present significantly shared genetic bases (95 genes, p value = 2.5E-72), demonstrating multiple common genetic pathways (enrichment p value ≤ 4.38E-20 for the top 10 pathways). Genetic network analysis suggested that mutual regulation may exist between HPI and NAFLD through 21 out of 95 genes. Furthermore, 85 out of the 95 genes manifested strong interaction with 12 small molecules/drugs that demonstrate effectiveness in treating both diseases. Clinical results showed that HPI rate in the NAFLD group was significantly higher than that in the group without NAFLD (51.9% vs. 43.6%; p value = 4.9E-4). Multivariate logistic regression results supported the observations and suggested that HPI served as a risk factor for NAFLD in the experiment data studied (odds ratio: 1.387, p value = 0.018). Results from this study support the hypothesis that complex biological association may exist between HPI and NAFLD, which partially explains the significant clinical co-incidence in the elderly population of south China.

Synthesis of eukaryotic lipid biomarkers in the bacterial domain

NASA Astrophysics Data System (ADS)

Welander, P. V.; Banta, A. B.; Lee, A. K.; Wei, J. H.

2017-12-01

Lipid biomarkers are organic molecules preserved in sediments and sedimentary rocks that can function as geological proxies for certain microbial taxa or for specific environmental conditions. These molecular fossils provide a link between organisms and their environments in both modern and ancient settings and have afforded significant insight into ancient climatic events, mass extinctions, and various evolutionary transitions throughout Earth's history. However, the proper interpretation of lipid biomarkers is dependent on a broad understanding of their diagenetic precursors in modern systems. This includes understanding the taphonomic transformations that these molecules undergo, their biosynthetic pathways, and the ecological conditions that affect their cellular production. In this study, we focus on one group of lipid biomarkers - the sterols. These are polycyclic isoprenoidal lipids that have a high preservation potential and play a critical role in the physiology of most eukaryotes. However, the synthesis and function of these lipids in the bacterial domain has not been fully explored. Here we utilize a combination of bioinformatics, microbial genetics, and biochemistry to demonstrate that bacterial sterol producers are more prevalent in environmental metagenomic samples than in the genomic databases of cultured organisms and to identify novel proteins required to synthesize and modify sterols in bacteria. These proteins represent a distinct pathway for sterol synthesis exclusive to bacteria and indicate that sterol synthesis in bacteria may have evolved independently of eukaryotic sterol biosynthesis. Taken together, these results demonstrate how studies in extant bacteria can provide insight into the biological sources and the biosynthetic pathways of specific lipid biomarkers and in turn may allow for more robust interpretation of biomarker signatures.

An editor for pathway drawing and data visualization in the Biopathways Workbench.

PubMed

Byrnes, Robert W; Cotter, Dawn; Maer, Andreia; Li, Joshua; Nadeau, David; Subramaniam, Shankar

2009-10-02

Pathway models serve as the basis for much of systems biology. They are often built using programs designed for the purpose. Constructing new models generally requires simultaneous access to experimental data of diverse types, to databases of well-characterized biological compounds and molecular intermediates, and to reference model pathways. However, few if any software applications provide all such capabilities within a single user interface. The Pathway Editor is a program written in the Java programming language that allows de-novo pathway creation and downloading of LIPID MAPS (Lipid Metabolites and Pathways Strategy) and KEGG lipid metabolic pathways, and of measured time-dependent changes to lipid components of metabolism. Accessed through Java Web Start, the program downloads pathways from the LIPID MAPS Pathway database (Pathway) as well as from the LIPID MAPS web server http://www.lipidmaps.org. Data arises from metabolomic (lipidomic), microarray, and protein array experiments performed by the LIPID MAPS consortium of laboratories and is arranged by experiment. Facility is provided to create, connect, and annotate nodes and processes on a drawing panel with reference to database objects and time course data. Node and interaction layout as well as data display may be configured in pathway diagrams as desired. Users may extend diagrams, and may also read and write data and non-lipidomic KEGG pathways to and from files. Pathway diagrams in XML format, containing database identifiers referencing specific compounds and experiments, can be saved to a local file for subsequent use. The program is built upon a library of classes, referred to as the Biopathways Workbench, that convert between different file formats and database objects. An example of this feature is provided in the form of read/construct/write access to models in SBML (Systems Biology Markup Language) contained in the local file system. Inclusion of access to multiple experimental data types and of pathway diagrams within a single interface, automatic updating through connectivity to an online database, and a focus on annotation, including reference to standardized lipid nomenclature as well as common lipid names, supports the view that the Pathway Editor represents a significant, practicable contribution to current pathway modeling tools.

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites

PubMed Central

Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K.

2018-01-01

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly. PMID:29470400

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites.

PubMed

Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A

2018-02-22

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly.

Pharmacogenomic identification of small molecules for lineage specific manipulation of subventricular zone germinal activity.

PubMed

Azim, Kasum; Angonin, Diane; Marcy, Guillaume; Pieropan, Francesca; Rivera, Andrea; Donega, Vanessa; Cantù, Claudio; Williams, Gareth; Berninger, Benedikt; Butt, Arthur M; Raineteau, Olivier

2017-03-01

Strategies for promoting neural regeneration are hindered by the difficulty of manipulating desired neural fates in the brain without complex genetic methods. The subventricular zone (SVZ) is the largest germinal zone of the forebrain and is responsible for the lifelong generation of interneuron subtypes and oligodendrocytes. Here, we have performed a bioinformatics analysis of the transcriptome of dorsal and lateral SVZ in early postnatal mice, including neural stem cells (NSCs) and their immediate progenies, which generate distinct neural lineages. We identified multiple signaling pathways that trigger distinct downstream transcriptional networks to regulate the diversity of neural cells originating from the SVZ. Next, we used a novel in silico genomic analysis, searchable platform-independent expression database/connectivity map (SPIED/CMAP), to generate a catalogue of small molecules that can be used to manipulate SVZ microdomain-specific lineages. Finally, we demonstrate that compounds identified in this analysis promote the generation of specific cell lineages from NSCs in vivo, during postnatal life and adulthood, as well as in regenerative contexts. This study unravels new strategies for using small bioactive molecules to direct germinal activity in the SVZ, which has therapeutic potential in neurodegenerative diseases.

The Pathway Tools software.

PubMed

Karp, Peter D; Paley, Suzanne; Romero, Pedro

2002-01-01

Bioinformatics requires reusable software tools for creating model-organism databases (MODs). The Pathway Tools is a reusable, production-quality software environment for creating a type of MOD called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc (see http://ecocyc.org) integrates our evolving understanding of the genes, proteins, metabolic network, and genetic network of an organism. This paper provides an overview of the four main components of the Pathway Tools: The PathoLogic component supports creation of new PGDBs from the annotated genome of an organism. The Pathway/Genome Navigator provides query, visualization, and Web-publishing services for PGDBs. The Pathway/Genome Editors support interactive updating of PGDBs. The Pathway Tools ontology defines the schema of PGDBs. The Pathway Tools makes use of the Ocelot object database system for data management services for PGDBs. The Pathway Tools has been used to build PGDBs for 13 organisms within SRI and by external users.

Nuclear Receptor Signaling Atlas: Opening Access to the Biology of Nuclear Receptor Signaling Pathways.

PubMed

Becnel, Lauren B; Darlington, Yolanda F; Ochsner, Scott A; Easton-Marks, Jeremy R; Watkins, Christopher M; McOwiti, Apollo; Kankanamge, Wasula H; Wise, Michael W; DeHart, Michael; Margolis, Ronald N; McKenna, Neil J

2015-01-01

Signaling pathways involving nuclear receptors (NRs), their ligands and coregulators, regulate tissue-specific transcriptomes in diverse processes, including development, metabolism, reproduction, the immune response and neuronal function, as well as in their associated pathologies. The Nuclear Receptor Signaling Atlas (NURSA) is a Consortium focused around a Hub website (www.nursa.org) that annotates and integrates diverse 'omics datasets originating from the published literature and NURSA-funded Data Source Projects (NDSPs). These datasets are then exposed to the scientific community on an Open Access basis through user-friendly data browsing and search interfaces. Here, we describe the redesign of the Hub, version 3.0, to deploy "Web 2.0" technologies and add richer, more diverse content. The Molecule Pages, which aggregate information relevant to NR signaling pathways from myriad external databases, have been enhanced to include resources for basic scientists, such as post-translational modification sites and targeting miRNAs, and for clinicians, such as clinical trials. A portal to NURSA's Open Access, PubMed-indexed journal Nuclear Receptor Signaling has been added to facilitate manuscript submissions. Datasets and information on reagents generated by NDSPs are available, as is information concerning periodic new NDSP funding solicitations. Finally, the new website integrates the Transcriptomine analysis tool, which allows for mining of millions of richly annotated public transcriptomic data points in the field, providing an environment for dataset re-use and citation, bench data validation and hypothesis generation. We anticipate that this new release of the NURSA database will have tangible, long term benefits for both basic and clinical research in this field.

Reactome graph database: Efficient access to complex pathway data

PubMed Central

Korninger, Florian; Viteri, Guilherme; Marin-Garcia, Pablo; Ping, Peipei; Wu, Guanming; Stein, Lincoln; D’Eustachio, Peter

2018-01-01

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types. PMID:29377902

Reactome graph database: Efficient access to complex pathway data.

PubMed

Fabregat, Antonio; Korninger, Florian; Viteri, Guilherme; Sidiropoulos, Konstantinos; Marin-Garcia, Pablo; Ping, Peipei; Wu, Guanming; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning

2018-01-01

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.

Computational Chemistry Comparison and Benchmark Database

National Institute of Standards and Technology Data Gateway

SRD 101 NIST Computational Chemistry Comparison and Benchmark Database (Web, free access)   The NIST Computational Chemistry Comparison and Benchmark Database is a collection of experimental and ab initio thermochemical properties for a selected set of molecules. The goals are to provide a benchmark set of molecules for the evaluation of ab initio computational methods and allow the comparison between different ab initio computational methods for the prediction of thermochemical properties.

Open, Cross Platform Chemistry Application Unifying Structure Manipulation, External Tools, Databases and Visualization

DTIC Science & Technology

2014-05-30

mol.addBond(o1, h2, 1); Avogadro ::Core::Bond b2 = mol.addBond(o1, h3, 1); The QtGui::Molecule class inherits from Core::Molecule and Qt’s QObject...populated as an input (although they are all implemented in terms of the Core::Molecule class. The third is QtGui::RWMolecule which inherits from just...shown in Figure 16. The use of molecule fingerprinting techniques gives the database the ability to be searched by similarity to a desired structure, as

Creating and Using a Consumer Chemical Molecular Graphics Database: The "Molecule of the Day" - A Great Way To Begin Your Lecture

NASA Astrophysics Data System (ADS)

Scharberg, Maureen A.; Cox, Oran E.; Barelli, Carl A.

1997-07-01

"The Molecule of the Day" consumer chemical database has been created to allow introductory chemistry students to explore molecular structures of chemicals in household products, and to provide opportunities in molecular modeling for undergraduate chemistry students. Before class begins, an overhead transparency is displayed which shows a three-dimensional molecular structure of a household chemical, and lists relevant features and uses of this chemical. Within answers to questionnaires, students have commented that this molecular graphics database has helped them to visually connect the microscopic structure of a molecule with its physical and chemical properties, as well as its uses in consumer products. It is anticipated that this database will be incorporated into a navigational software package such as Netscape.

NALDB: nucleic acid ligand database for small molecules targeting nucleic acid

PubMed Central

Kumar Mishra, Subodh; Kumar, Amit

2016-01-01

Nucleic acid ligand database (NALDB) is a unique database that provides detailed information about the experimental data of small molecules that were reported to target several types of nucleic acid structures. NALDB is the first ligand database that contains ligand information for all type of nucleic acid. NALDB contains more than 3500 ligand entries with detailed pharmacokinetic and pharmacodynamic information such as target name, target sequence, ligand 2D/3D structure, SMILES, molecular formula, molecular weight, net-formal charge, AlogP, number of rings, number of hydrogen bond donor and acceptor, potential energy along with their Ki, Kd, IC50 values. All these details at single platform would be helpful for the development and betterment of novel ligands targeting nucleic acids that could serve as a potential target in different diseases including cancers and neurological disorders. With maximum 255 conformers for each ligand entry, our database is a multi-conformer database and can facilitate the virtual screening process. NALDB provides powerful web-based search tools that make database searching efficient and simplified using option for text as well as for structure query. NALDB also provides multi-dimensional advanced search tool which can screen the database molecules on the basis of molecular properties of ligand provided by database users. A 3D structure visualization tool has also been included for 3D structure representation of ligands. NALDB offers an inclusive pharmacological information and the structurally flexible set of small molecules with their three-dimensional conformers that can accelerate the virtual screening and other modeling processes and eventually complement the nucleic acid-based drug discovery research. NALDB can be routinely updated and freely available on bsbe.iiti.ac.in/bsbe/naldb/HOME.php. Database URL: http://bsbe.iiti.ac.in/bsbe/naldb/HOME.php PMID:26896846

Synthetic Small Molecule Inhibitors of Hh Signaling As Anti-Cancer Chemotherapeutics

PubMed Central

Maschinot, C.A.; Pace, J.R.; Hadden, M.K.

2016-01-01

The hedgehog (Hh) pathway is a developmental signaling pathway that is essential to the proper embryonic development of many vertebrate systems. Dysregulation of Hh signaling has been implicated as a causative factor in the development and progression of several forms of human cancer. As such, the development of small molecule inhibitors of Hh signaling as potential anti-cancer chemotherapeutics has been a major area of research interest in both academics and industry over the past ten years. Through these efforts, synthetic small molecules that target multiple components of the Hh pathway have been identified and advanced to preclinical or clinical development. The goal of this review is to provide an update on the current status of several synthetic small molecule Hh pathway inhibitors and explore the potential of several recently disclosed inhibitory scaffolds. PMID:26310919

Cancer-related marketing centrality motifs acting as pivot units in the human signaling network and mediating cross-talk between biological pathways.

PubMed

Li, Wan; Chen, Lina; Li, Xia; Jia, Xu; Feng, Chenchen; Zhang, Liangcai; He, Weiming; Lv, Junjie; He, Yuehan; Li, Weiguo; Qu, Xiaoli; Zhou, Yanyan; Shi, Yuchen

2013-12-01

Network motifs in central positions are considered to not only have more in-coming and out-going connections but are also localized in an area where more paths reach the networks. These central motifs have been extensively investigated to determine their consistent functions or associations with specific function categories. However, their functional potentials in the maintenance of cross-talk between different functional communities are unclear. In this paper, we constructed an integrated human signaling network from the Pathway Interaction Database. We identified 39 essential cancer-related motifs in central roles, which we called cancer-related marketing centrality motifs, using combined centrality indices on the system level. Our results demonstrated that these cancer-related marketing centrality motifs were pivotal units in the signaling network, and could mediate cross-talk between 61 biological pathways (25 could be mediated by one motif on average), most of which were cancer-related pathways. Further analysis showed that molecules of most marketing centrality motifs were in the same or adjacent subcellular localizations, such as the motif containing PI3K, PDK1 and AKT1 in the plasma membrane, to mediate signal transduction between 32 cancer-related pathways. Finally, we analyzed the pivotal roles of cancer genes in these marketing centrality motifs in the pathogenesis of cancers, and found that non-cancer genes were potential cancer-related genes.

Programmed Cell Death-1/Programmed Death-ligand 1 Pathway: A New Target for Sepsis.

PubMed

Liu, Qiang; Li, Chun-Sheng

2017-04-20

Sepsis remains a leading cause of death in many Intensive Care Units worldwide. Immunosuppression has been a primary focus of sepsis research as a key pathophysiological mechanism. Given the important role of the negative costimulatory molecules programmed cell death-1 (PD-1) and programmed death-ligand 1 (PD-L1) in the occurrence of immunosuppression during sepsis, we reviewed literatures related to the PD-1/PD-L1 pathway to examine its potential as a new target for sepsis treatment. Studies of the association between PD-1/PD-L1 and sepsis published up to January 31, 2017, were obtained by searching the PubMed database. English language studies, including those based on animal models, clinical research, and reviews, with data related to PD-1/PD-L1 and sepsis, were evaluated. Immunomodulatory therapeutics could reverse the deactivation of immune cells caused by sepsis and restore immune cell activation and function. Blockade of the PD-1/PD-L1 pathway could reduce the exhaustion of T-cells and enhance the proliferation and activation of T-cells. The anti-PD-1/PD-L1 pathway shows promise as a new target for sepsis treatment. This review provides a basis for clinical trials and future studies aimed at revaluating the efficacy and safety of this targeted approach.

Exploring Chemical Space for Drug Discovery Using the Chemical Universe Database

PubMed Central

2012-01-01

Herein we review our recent efforts in searching for bioactive ligands by enumeration and virtual screening of the unknown chemical space of small molecules. Enumeration from first principles shows that almost all small molecules (>99.9%) have never been synthesized and are still available to be prepared and tested. We discuss open access sources of molecules, the classification and representation of chemical space using molecular quantum numbers (MQN), its exhaustive enumeration in form of the chemical universe generated databases (GDB), and examples of using these databases for prospective drug discovery. MQN-searchable GDB, PubChem, and DrugBank are freely accessible at www.gdb.unibe.ch. PMID:23019491

Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing

PubMed Central

de Anda-Jáuregui, Guillermo; Guo, Kai; McGregor, Brett A.; Hur, Junguk

2018-01-01

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space. PMID:29545755

Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing.

PubMed

de Anda-Jáuregui, Guillermo; Guo, Kai; McGregor, Brett A; Hur, Junguk

2018-01-01

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space.

Screening key candidate genes and pathways involved in insulinoma by microarray analysis.

PubMed

Zhou, Wuhua; Gong, Li; Li, Xuefeng; Wan, Yunyan; Wang, Xiangfei; Li, Huili; Jiang, Bin

2018-06-01

Insulinoma is a rare type tumor and its genetic features remain largely unknown. This study aimed to search for potential key genes and relevant enriched pathways of insulinoma.The gene expression data from GSE73338 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified between insulinoma tissues and normal pancreas tissues, followed by pathway enrichment analysis, protein-protein interaction (PPI) network construction, and module analysis. The expressions of candidate key genes were validated by quantitative real-time polymerase chain reaction (RT-PCR) in insulinoma tissues.A total of 1632 DEGs were obtained, including 1117 upregulated genes and 514 downregulated genes. Pathway enrichment results showed that upregulated DEGs were significantly implicated in insulin secretion, and downregulated DEGs were mainly enriched in pancreatic secretion. PPI network analysis revealed 7 hub genes with degrees more than 10, including GCG (glucagon), GCGR (glucagon receptor), PLCB1 (phospholipase C, beta 1), CASR (calcium sensing receptor), F2R (coagulation factor II thrombin receptor), GRM1 (glutamate metabotropic receptor 1), and GRM5 (glutamate metabotropic receptor 5). DEGs involved in the significant modules were enriched in calcium signaling pathway, protein ubiquitination, and platelet degranulation. Quantitative RT-PCR data confirmed that the expression trends of these hub genes were similar to the results of bioinformatic analysis.The present study demonstrated that candidate DEGs and enriched pathways were the potential critical molecule events involved in the development of insulinoma, and these findings were useful for better understanding of insulinoma genesis.

Comparison of human cell signaling pathway databases—evolution, drawbacks and challenges

PubMed Central

Chowdhury, Saikat; Sarkar, Ram Rup

2015-01-01

Elucidating the complexities of cell signaling pathways is of immense importance to gain understanding about various biological phenomenon, such as dynamics of gene/protein expression regulation, cell fate determination, embryogenesis and disease progression. The successful completion of human genome project has also helped experimental and theoretical biologists to analyze various important pathways. To advance this study, during the past two decades, systematic collections of pathway data from experimental studies have been compiled and distributed freely by several databases, which also integrate various computational tools for further analysis. Despite significant advancements, there exist several drawbacks and challenges, such as pathway data heterogeneity, annotation, regular update and automated image reconstructions, which motivated us to perform a thorough review on popular and actively functioning 24 cell signaling databases. Based on two major characteristics, pathway information and technical details, freely accessible data from commercial and academic databases are examined to understand their evolution and enrichment. This review not only helps to identify some novel and useful features, which are not yet included in any of the databases but also highlights their current limitations and subsequently propose the reasonable solutions for future database development, which could be useful to the whole scientific community. PMID:25632107

GraphSAW: a web-based system for graphical analysis of drug interactions and side effects using pharmaceutical and molecular data.

PubMed

Shoshi, Alban; Hoppe, Tobias; Kormeier, Benjamin; Ogultarhan, Venus; Hofestädt, Ralf

2015-02-28

Adverse drug reactions are one of the most common causes of death in industrialized Western countries. Nowadays, empirical data from clinical studies for the approval and monitoring of drugs and molecular databases is available. The integration of database information is a promising method for providing well-based knowledge to avoid adverse drug reactions. This paper presents our web-based decision support system GraphSAW which analyzes and evaluates drug interactions and side effects based on data from two commercial and two freely available molecular databases. The system is able to analyze single and combined drug-drug interactions, drug-molecule interactions as well as single and cumulative side effects. In addition, it allows exploring associative networks of drugs, molecules, metabolic pathways, and diseases in an intuitive way. The molecular medication analysis includes the capabilities of the upper features. A statistical evaluation of the integrated data and top 20 drugs concerning drug interactions and side effects is performed. The results of the data analysis give an overview of all theoretically possible drug interactions and side effects. The evaluation shows a mismatch between pharmaceutical and molecular databases. The concordance of drug interactions was about 12% and 9% of drug side effects. An application case with prescribed data of 11 patients is presented in order to demonstrate the functionality of the system under real conditions. For each patient at least two interactions occured in every medication and about 8% of total diseases were possibly induced by drug therapy. GraphSAW (http://tunicata.techfak.uni-bielefeld.de/graphsaw/) is meant to be a web-based system for health professionals and researchers. GraphSAW provides comprehensive drug-related knowledge and an improved medication analysis which may support efforts to reduce the risk of medication errors and numerous drastic side effects.

PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization.

PubMed

Dogrusoz, U; Erson, E Z; Giral, E; Demir, E; Babur, O; Cetintas, A; Colak, R

2006-02-01

Patikaweb provides a Web interface for retrieving and analyzing biological pathways in the Patika database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats.

Expression profiling indicating low selenium-sensitive microRNA levels linked to cell cycle and cell stress response pathways in the CaCo-2 cell line.

PubMed

McCann, Mark J; Rotjanapun, Kunjana; Hesketh, John E; Roy, Nicole C

2017-05-01

Se is an essential micronutrient for human health, and fluctuations in Se levels and the potential cellular dysfunction associated with it may increase the risk for disease. Although Se has been shown to influence several biological pathways important in health, little is known about the effect of Se on the expression of microRNA (miRNA) molecules regulating these pathways. To explore the potential role of Se-sensitive miRNA in regulating pathways linked with colon cancer, we profiled the expression of 800 miRNA in the CaCo-2 human adenocarcinoma cell line in response to a low-Se (72 h at <40 nm) environment using nCounter direct quantification. These data were then examined using a range of in silico databases to identify experimentally validated miRNA-mRNA interactions and the biological pathways involved. We identified ten Se-sensitive miRNA (hsa-miR-93-5p, hsa-miR-106a-5p, hsa-miR-205-5p, hsa-miR-200c-3p, hsa-miR-99b-5p, hsa-miR-302d-3p, hsa-miR-373-3p, hsa-miR-483-3p, hsa-miR-512-5p and hsa-miR-4454), which regulate 3588 mRNA in key pathways such as the cell cycle, the cellular response to stress, and the canonical Wnt/β-catenin, p53 and ERK/MAPK signalling pathways. Our data show that the effects of low Se on biological pathways may, in part, be due to these ten Se-sensitive miRNA. Dysregulation of the cell cycle and of the stress response pathways due to low Se may influence key genes involved in carcinogenesis.

TB Mobile: a mobile app for anti-tuberculosis molecules with known targets

PubMed Central

2013-01-01

Background An increasing number of researchers are focused on strategies for developing inhibitors of Mycobacterium tuberculosis (Mtb) as tuberculosis (TB) drugs. Results In order to learn from prior work we have collated information on molecules screened versus Mtb and their targets which has been made available in the Collaborative Drug Discovery (CDD) database. This dataset contains published data on target, essentiality, links to PubMed, TBDB, TBCyc (which provides a pathway-based visualization of the entire cellular biochemical network) and human homolog information. The development of mobile cheminformatics apps could lower the barrier to drug discovery and promote collaboration. Therefore we have used this set of over 700 molecules screened versus Mtb and their targets to create a free mobile app (TB Mobile) that displays molecule structures and links to the bioinformatics data. By input of a molecular structures and performing a similarity search within the app we can infer potential targets or search by targets to retrieve compounds known to be active. Conclusions TB Mobile may assist researchers as part of their workflow in identifying potential targets for hits generated from phenotypic screening and in prioritizing them for further follow-up. The app is designed to lower the barriers to accessing this information, so that all researchers with an interest in combatting this deadly disease can use it freely to the benefit of their own efforts. PMID:23497706

A Methodology for Cancer Therapeutics by Systems Pharmacology-Based Analysis: A Case Study on Breast Cancer-Related Traditional Chinese Medicines.

PubMed

Li, Yan; Wang, Jinghui; Lin, Feng; Yang, Yinfeng; Chen, Su-Shing

2017-01-01

Breast cancer is the most common carcinoma in women. Comprehensive therapy on breast cancer including surgical operation, chemotherapy, radiotherapy, endocrinotherapy, etc. could help, but still has serious side effect and resistance against anticancer drugs. Complementary and alternative medicine (CAM) may avoid these problems, in which traditional Chinese medicine (TCM) has been highlighted. In this section, to analyze the mechanism through which TCM act on breast cancer, we have built a virtual model consisting of the construction of database, oral bioavailability prediction, drug-likeness evaluation, target prediction, network construction. The 20 commonly employed herbs for the treatment of breast cancer were used as a database to carry out research. As a result, 150 ingredient compounds were screened out as active molecules for the herbs, with 33 target proteins predicted. Our analysis indicates that these herbs 1) takes a 'Jun-Chen-Zuo-Shi" as rule of prescription, 2) which function mainly through perturbing three pathways involving the epidermal growth factor receptor, estrogen receptor, and inflammatory pathways, to 3) display the breast cancer-related anti-estrogen, anti-inflammatory, regulation of cell metabolism and proliferation activities. To sum it up, by providing a novel in silico strategy for investigation of the botanical drugs, this work may be of some help for understanding the action mechanisms of herbal medicines and for discovery of new drugs from plants.

NAViGaTing the Micronome – Using Multiple MicroRNA Prediction Databases to Identify Signalling Pathway-Associated MicroRNAs

PubMed Central

Shirdel, Elize A.; Xie, Wing; Mak, Tak W.; Jurisica, Igor

2011-01-01

Background MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome – referred to as the micronome – to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal — mirDIP (http://ophid.utoronto.ca/mirDIP). Results mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05), suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001), to be more studied (p<0.0002), and to have higher degree in the KEGG cancer pathway (p<0.0001), compared to intra-pathway microRNAs. Conclusions Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level. PMID:21364759

Identifying osteosarcoma metastasis associated genes by weighted gene co-expression network analysis (WGCNA).

PubMed

Tian, Honglai; Guan, Donghui; Li, Jianmin

2018-06-01

Osteosarcoma (OS), the most common malignant bone tumor, accounts for the heavy healthy threat in the period of children and adolescents. OS occurrence usually correlates with early metastasis and high death rate. This study aimed to better understand the mechanism of OS metastasis.Based on Gene Expression Omnibus (GEO) database, we downloaded 4 expression profile data sets associated with OS metastasis, and selected differential expressed genes. Weighted gene co-expression network analysis (WGCNA) approach allowed us to investigate the most OS metastasis-correlated module. Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to give annotation of selected OS metastasis-associated genes.We select 897 differential expressed genes from OS metastasis and OS non-metastasis groups. Based on these selected genes, WGCNA further explored 142 genes included in the most OS metastasis-correlated module. Gene Ontology functional and KEGG pathway enrichment analyses showed that significantly OS metastasis-associated genes were involved in pathway correlated with insulin-like growth factor binding.Our research figured out several potential molecules participating in metastasis process and factors acting as biomarker. With this study, we could better explore the mechanism of OS metastasis and further discover more therapy targets.

Target of obstructive sleep apnea syndrome merge lung cancer: based on big data platform.

PubMed

Li, Lifeng; Lu, Jingli; Xue, Wenhua; Wang, Liping; Zhai, Yunkai; Fan, Zhirui; Wu, Ge; Fan, Feifei; Li, Jieyao; Zhang, Chaoqi; Zhang, Yi; Zhao, Jie

2017-03-28

Based on our hospital database, the incidence of lung cancer diagnoses was similar in obstructive sleep apnea Syndrome (OSAS) and hospital general population; among individual with a diagnosis of lung cancer, the presence of OSAS was associated with an increased risk for mortality. In the gene expression and network-level information, we revealed significant alterations of molecules related to HIF1 and metabolic pathways in the hypoxic-conditioned lung cancer cells. We also observed that GBE1 and HK2 are downstream of HIF1 pathway important in hypoxia-conditioned lung cancer cell. Furthermore, we used publicly available datasets to validate that the late-stage lung adenocarcinoma patients showed higher expression HK2 and GBE1 than early-stage ones. In terms of prognostic features, a survival analysis revealed that the high GBE1 and HK2 expression group exhibited poorer survival in lung adenocarcinoma patients. By analyzing and integrating multiple datasets, we identify molecular convergence between hypoxia and lung cancer that reflects their clinical profiles and reveals molecular pathways involved in hypoxic-induced lung cancer progression. In conclusion, we show that OSAS severity appears to increase the risk of lung cancer mortality.

Identification of Thiotetronic Acid Antibiotic Biosynthetic Pathways by Target-directed Genome Mining.

PubMed

Tang, Xiaoyu; Li, Jie; Millán-Aguiñaga, Natalie; Zhang, Jia Jia; O'Neill, Ellis C; Ugalde, Juan A; Jensen, Paul R; Mantovani, Simone M; Moore, Bradley S

2015-12-18

Recent genome sequencing efforts have led to the rapid accumulation of uncharacterized or "orphaned" secondary metabolic biosynthesis gene clusters (BGCs) in public databases. This increase in DNA-sequenced big data has given rise to significant challenges in the applied field of natural product genome mining, including (i) how to prioritize the characterization of orphan BGCs and (ii) how to rapidly connect genes to biosynthesized small molecules. Here, we show that by correlating putative antibiotic resistance genes that encode target-modified proteins with orphan BGCs, we predict the biological function of pathway specific small molecules before they have been revealed in a process we call target-directed genome mining. By querying the pan-genome of 86 Salinispora bacterial genomes for duplicated house-keeping genes colocalized with natural product BGCs, we prioritized an orphan polyketide synthase-nonribosomal peptide synthetase hybrid BGC (tlm) with a putative fatty acid synthase resistance gene. We employed a new synthetic double-stranded DNA-mediated cloning strategy based on transformation-associated recombination to efficiently capture tlm and the related ttm BGCs directly from genomic DNA and to heterologously express them in Streptomyces hosts. We show the production of a group of unusual thiotetronic acid natural products, including the well-known fatty acid synthase inhibitor thiolactomycin that was first described over 30 years ago, yet never at the genetic level in regards to biosynthesis and autoresistance. This finding not only validates the target-directed genome mining strategy for the discovery of antibiotic producing gene clusters without a priori knowledge of the molecule synthesized but also paves the way for the investigation of novel enzymology involved in thiotetronic acid natural product biosynthesis.

Biomedical Requirements for High Productivity Computing Systems

DTIC Science & Technology

2005-04-01

server at http://www.ncbi.nlm.nih.gov/BLAST/. There are many variants of BLAST, including: 1. BLASTN - Compares a DNA query to a DNA database. Searches ...database (3 reading frames from each strand of the DNA) searching . 13 4. TBLASTN - Compares a protein query to a DNA database, in the 6 possible...the molecular during this phase. After eliminating molecules that could not match the query , an atom-by-atom search for the molecules in conducted

Determining the elastic properties of aptamer-ricin single molecule multiple pathway interactions

NASA Astrophysics Data System (ADS)

Wang, Bin; Park, Bosoon; Kwon, Yongkuk; Xu, Bingqian

2014-05-01

We report on the elastic properties of ricin and anti-ricin aptamer interactions, which showed three stable binding conformations, each of which has its special elastic properties. These different unbinding pathways were investigated by the dynamic force spectroscopy. A series-spring model combining the worm-like-chain model and Hook's law was used to estimate the apparent spring constants of the aptamer and linker molecule polyethylene glycol. The aptamer in its three different unbinding pathways showed different apparent spring constants. The two reaction barriers in the unbinding pathways also influence the apparent spring constant of the aptamer. This special elastic behavior of aptamer was used to distinguish its three unbinding pathways under different loading rates. This method also offered a way to distinguish and discard the non-specific interactions in single molecule experiments.

Modulation of dendritic cell and T cell cross-talk during aging: The potential role of checkpoint inhibitory molecules.

PubMed

Gardner, Joanne K; Mamotte, Cyril D S; Jackaman, Connie; Nelson, Delia J

2017-09-01

Dendritic cells (DCs) undergo continuous changes throughout life, and there is evidence that elderly DCs have a reduced capacity to stimulate T cells, which may contribute to impaired anti-tumour immune responses in elderly people with cancer. Changes in checkpoint inhibitory molecules/pathways during aging may be one mechanism that impairs the ability of elderly DCs to activate T cells. However, little is currently known regarding the combined effects of aging and cancer on DC and T cell inhibitory molecules/pathways. In this review, we discuss our current understanding of the influence of aging and cancer on key DC and T cell inhibitory molecules/pathways, the potential underlying cellular and molecular mechanisms contributing to their modulation, and the possibility of therapeutically targeting inhibitory molecules in elderly cancer patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Pathway Analysis and Omics Data Visualization Using Pathway Genome Databases: FragariaCyc, a Case Study.

PubMed

Naithani, Sushma; Jaiswal, Pankaj

2017-01-01

The species-specific plant Pathway Genome Databases (PGDBs) based on the BioCyc platform provide a conceptual model of the cellular metabolic network of an organism. Such frameworks allow analysis of the genome-scale expression data to understand changes in the overall metabolisms of an organism (or organs, tissues, and cells) in response to various extrinsic (e.g. developmental and differentiation) and/or extrinsic signals (e.g. pathogens and abiotic stresses) from the surrounding environment. Using FragariaCyc, a pathway database for the diploid strawberry Fragaria vesca, we show (1) the basic navigation across a PGDB; (2) a case study of pathway comparison across plant species; and (3) an example of RNA-Seq data analysis using Omics Viewer tool. The protocols described here generally apply to other Pathway Tools-based PGDBs.

DOMMINO 2.0: integrating structurally resolved protein-, RNA-, and DNA-mediated macromolecular interactions

PubMed Central

Kuang, Xingyan; Dhroso, Andi; Han, Jing Ginger; Shyu, Chi-Ren; Korkin, Dmitry

2016-01-01

Macromolecular interactions are formed between proteins, DNA and RNA molecules. Being a principle building block in macromolecular assemblies and pathways, the interactions underlie most of cellular functions. Malfunctioning of macromolecular interactions is also linked to a number of diseases. Structural knowledge of the macromolecular interaction allows one to understand the interaction’s mechanism, determine its functional implications and characterize the effects of genetic variations, such as single nucleotide polymorphisms, on the interaction. Unfortunately, until now the interactions mediated by different types of macromolecules, e.g. protein–protein interactions or protein–DNA interactions, are collected into individual and unrelated structural databases. This presents a significant obstacle in the analysis of macromolecular interactions. For instance, the homogeneous structural interaction databases prevent scientists from studying structural interactions of different types but occurring in the same macromolecular complex. Here, we introduce DOMMINO 2.0, a structural Database Of Macro-Molecular INteractiOns. Compared to DOMMINO 1.0, a comprehensive database on protein-protein interactions, DOMMINO 2.0 includes the interactions between all three basic types of macromolecules extracted from PDB files. DOMMINO 2.0 is automatically updated on a weekly basis. It currently includes ∼1 040 000 interactions between two polypeptide subunits (e.g. domains, peptides, termini and interdomain linkers), ∼43 000 RNA-mediated interactions, and ∼12 000 DNA-mediated interactions. All protein structures in the database are annotated using SCOP and SUPERFAMILY family annotation. As a result, protein-mediated interactions involving protein domains, interdomain linkers, C- and N- termini, and peptides are identified. Our database provides an intuitive web interface, allowing one to investigate interactions at three different resolution levels: whole subunit network, binary interaction and interaction interface. Database URL: http://dommino.org PMID:26827237

Synergistic Inhibition of Her2/neu and p53-MDM2 Pathways. Addendum

DTIC Science & Technology

2007-09-01

Therefore, combination of drugs targeting HER2/neu and MDM2 pathways will allow for a two-pronged attack on breast cancer. The overall objective of our...proposal is to determine if small molecule drugs designed to inhibit HER2/neu can be applied in combination with drugs designed to inhibit p53-MDM2...able to inhibit either the HER2/neu pathway or the p53-MDM2 pathway. Subsequently, designed small molecule drugs able to strongly induce apoptosis

Validation and extraction of molecular-geometry information from small-molecule databases.

PubMed

Long, Fei; Nicholls, Robert A; Emsley, Paul; Graǽulis, Saulius; Merkys, Andrius; Vaitkus, Antanas; Murshudov, Garib N

2017-02-01

A freely available small-molecule structure database, the Crystallography Open Database (COD), is used for the extraction of molecular-geometry information on small-molecule compounds. The results are used for the generation of new ligand descriptions, which are subsequently used by macromolecular model-building and structure-refinement software. To increase the reliability of the derived data, and therefore the new ligand descriptions, the entries from this database were subjected to very strict validation. The selection criteria made sure that the crystal structures used to derive atom types, bond and angle classes are of sufficiently high quality. Any suspicious entries at a crystal or molecular level were removed from further consideration. The selection criteria included (i) the resolution of the data used for refinement (entries solved at 0.84 Å resolution or higher) and (ii) the structure-solution method (structures must be from a single-crystal experiment and all atoms of generated molecules must have full occupancies), as well as basic sanity checks such as (iii) consistency between the valences and the number of connections between atoms, (iv) acceptable bond-length deviations from the expected values and (v) detection of atomic collisions. The derived atom types and bond classes were then validated using high-order moment-based statistical techniques. The results of the statistical analyses were fed back to fine-tune the atom typing. The developed procedure was repeated four times, resulting in fine-grained atom typing, bond and angle classes. The procedure will be repeated in the future as and when new entries are deposited in the COD. The whole procedure can also be applied to any source of small-molecule structures, including the Cambridge Structural Database and the ZINC database.

NALDB: nucleic acid ligand database for small molecules targeting nucleic acid.

PubMed

Kumar Mishra, Subodh; Kumar, Amit

2016-01-01

Nucleic acid ligand database (NALDB) is a unique database that provides detailed information about the experimental data of small molecules that were reported to target several types of nucleic acid structures. NALDB is the first ligand database that contains ligand information for all type of nucleic acid. NALDB contains more than 3500 ligand entries with detailed pharmacokinetic and pharmacodynamic information such as target name, target sequence, ligand 2D/3D structure, SMILES, molecular formula, molecular weight, net-formal charge, AlogP, number of rings, number of hydrogen bond donor and acceptor, potential energy along with their Ki, Kd, IC50 values. All these details at single platform would be helpful for the development and betterment of novel ligands targeting nucleic acids that could serve as a potential target in different diseases including cancers and neurological disorders. With maximum 255 conformers for each ligand entry, our database is a multi-conformer database and can facilitate the virtual screening process. NALDB provides powerful web-based search tools that make database searching efficient and simplified using option for text as well as for structure query. NALDB also provides multi-dimensional advanced search tool which can screen the database molecules on the basis of molecular properties of ligand provided by database users. A 3D structure visualization tool has also been included for 3D structure representation of ligands. NALDB offers an inclusive pharmacological information and the structurally flexible set of small molecules with their three-dimensional conformers that can accelerate the virtual screening and other modeling processes and eventually complement the nucleic acid-based drug discovery research. NALDB can be routinely updated and freely available on bsbe.iiti.ac.in/bsbe/naldb/HOME.php. Database URL: http://bsbe.iiti.ac.in/bsbe/naldb/HOME.php. © The Author(s) 2016. Published by Oxford University Press.

Nuclear Receptor Signaling Atlas: Opening Access to the Biology of Nuclear Receptor Signaling Pathways

PubMed Central

Becnel, Lauren B.; Darlington, Yolanda F.; Ochsner, Scott A.; Easton-Marks, Jeremy R.; Watkins, Christopher M.; McOwiti, Apollo; Kankanamge, Wasula H.; Wise, Michael W.; DeHart, Michael; Margolis, Ronald N.; McKenna, Neil J.

2015-01-01

Signaling pathways involving nuclear receptors (NRs), their ligands and coregulators, regulate tissue-specific transcriptomes in diverse processes, including development, metabolism, reproduction, the immune response and neuronal function, as well as in their associated pathologies. The Nuclear Receptor Signaling Atlas (NURSA) is a Consortium focused around a Hub website (www.nursa.org) that annotates and integrates diverse ‘omics datasets originating from the published literature and NURSA-funded Data Source Projects (NDSPs). These datasets are then exposed to the scientific community on an Open Access basis through user-friendly data browsing and search interfaces. Here, we describe the redesign of the Hub, version 3.0, to deploy “Web 2.0” technologies and add richer, more diverse content. The Molecule Pages, which aggregate information relevant to NR signaling pathways from myriad external databases, have been enhanced to include resources for basic scientists, such as post-translational modification sites and targeting miRNAs, and for clinicians, such as clinical trials. A portal to NURSA’s Open Access, PubMed-indexed journal Nuclear Receptor Signaling has been added to facilitate manuscript submissions. Datasets and information on reagents generated by NDSPs are available, as is information concerning periodic new NDSP funding solicitations. Finally, the new website integrates the Transcriptomine analysis tool, which allows for mining of millions of richly annotated public transcriptomic data points in the field, providing an environment for dataset re-use and citation, bench data validation and hypothesis generation. We anticipate that this new release of the NURSA database will have tangible, long term benefits for both basic and clinical research in this field. PMID:26325041

SerpentinaDB: a database of plant-derived molecules of Rauvolfia serpentina.

PubMed

Pathania, Shivalika; Ramakrishnan, Sai Mukund; Randhawa, Vinay; Bagler, Ganesh

2015-08-04

Plant-derived molecules (PDMs) are known to be a rich source of diverse scaffolds that could serve as a basis for rational drug design. Structured compilation of phytochemicals from traditional medicinal plants can facilitate prospection for novel PDMs and their analogs as therapeutic agents. Rauvolfia serpentina is an important medicinal plant, endemic to Himalayan mountain ranges of Indian subcontinent, reported to be of immense therapeutic value against various diseases. We present SerpentinaDB, a structured compilation of 147 R. serpentina PDMs, inclusive of their plant part source, chemical classification, IUPAC, SMILES, physicochemical properties, and 3D chemical structures with associated references. It also provides refined search option for identification of analogs of natural molecules against ZINC database at user-defined cut-off. SerpentinaDB is an exhaustive resource of R. serpentina molecules facilitating prospection for therapeutic molecules from a medicinally important source of natural products. It also provides refined search option to explore the neighborhood of chemical space against ZINC database to identify analogs of natural molecules obtained as leads. In a previous study, we have demonstrated the utility of this resource by identifying novel aldose reductase inhibitors towards intervention of complications of diabetes.

VitisCyc: a metabolic pathway knowledgebase for grapevine (Vitis vinifera)

PubMed Central

Naithani, Sushma; Raja, Rajani; Waddell, Elijah N.; Elser, Justin; Gouthu, Satyanarayana; Deluc, Laurent G.; Jaiswal, Pankaj

2014-01-01

We have developed VitisCyc, a grapevine-specific metabolic pathway database that allows researchers to (i) search and browse the database for its various components such as metabolic pathways, reactions, compounds, genes and proteins, (ii) compare grapevine metabolic networks with other publicly available plant metabolic networks, and (iii) upload, visualize and analyze high-throughput data such as transcriptomes, proteomes, metabolomes etc. using OMICs-Viewer tool. VitisCyc is based on the genome sequence of the nearly homozygous genotype PN40024 of Vitis vinifera “Pinot Noir” cultivar with 12X v1 annotations and was built on BioCyc platform using Pathway Tools software and MetaCyc reference database. Furthermore, VitisCyc was enriched for plant-specific pathways and grape-specific metabolites, reactions and pathways. Currently VitisCyc harbors 68 super pathways, 362 biosynthesis pathways, 118 catabolic pathways, 5 detoxification pathways, 36 energy related pathways and 6 transport pathways, 10,908 enzymes, 2912 enzymatic reactions, 31 transport reactions and 2024 compounds. VitisCyc, as a community resource, can aid in the discovery of candidate genes and pathways that are regulated during plant growth and development, and in response to biotic and abiotic stress signals generated from a plant's immediate environment. VitisCyc version 3.18 is available online at http://pathways.cgrb.oregonstate.edu. PMID:25538713

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors.

PubMed

Sable, Rushikesh; Jois, Seetharama

2015-06-23

Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

PubMed

Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

2017-11-13

The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly correlated with BMI (r = 0.56, P = 0.04), and hub genes of KCNN1 and AQP10 were differentially expressed. We identified significant genes and specific modules potentially related to BMI based on the gene expression profile data of monozygotic twins. The findings may help further elucidate the underlying mechanisms of obesity development and provide novel insights to research potential gene biomarkers and signaling pathways for obesity treatment. Further analysis and validation of the findings reported here are important and necessary when more sample size is acquired.

Identification of Key Transcription Factors Associated with Lung Squamous Cell Carcinoma

PubMed Central

Zhang, Feng; Chen, Xia; Wei, Ke; Liu, Daoming; Xu, Xiaodong; Zhang, Xing; Shi, Hong

2017-01-01

Background Lung squamous cell carcinoma (lung SCC) is a common type of lung cancer, but its mechanism of pathogenesis is unclear. The aim of this study was to identify key transcription factors in lung SCC and elucidate its mechanism. Material/Methods Six published microarray datasets of lung SCC were downloaded from Gene Expression Omnibus (GEO) for integrated bioinformatics analysis. Significance analysis of microarrays was used to identify differentially expressed genes (DEGs) between lung SCC and normal controls. The biological functions and signaling pathways of DEGs were mapped in the Gene Otology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, respectively. A transcription factor gene regulatory network was used to obtain insights into the functions of DEGs. Results A total of 1,011 genes, including 539 upregulated genes and 462 downregulated genes, were filtered as DEGs between lung SCC and normal controls. DEGs were significantly enriched in cell cycle, DNA replication, p53 signaling pathway, pathways in cancer, adherens junction, and cell adhesion molecules signaling pathways. There were 57 transcription factors identified, which were used to construct a regulatory network. The network consisted of 736 interactions between 49 transcription factors and 486 DEGs. NFIC, BRCA1, and NFATC2 were the top 3 transcription factors that had the highest connectivity with DEGs and that regulated 83, 82, and 75 DEGs in the network, respectively. Conclusions NFIC, BRCA1, and NFATC2 might be the key transcription factors in the development of lung SCC by regulating the genes involved in cell cycle and DNA replication pathways. PMID:28081052

MoCha: Molecular Characterization of Unknown Pathways.

PubMed

Lobo, Daniel; Hammelman, Jennifer; Levin, Michael

2016-04-01

Automated methods for the reverse-engineering of complex regulatory networks are paving the way for the inference of mechanistic comprehensive models directly from experimental data. These novel methods can infer not only the relations and parameters of the known molecules defined in their input datasets, but also unknown components and pathways identified as necessary by the automated algorithms. Identifying the molecular nature of these unknown components is a crucial step for making testable predictions and experimentally validating the models, yet no specific and efficient tools exist to aid in this process. To this end, we present here MoCha (Molecular Characterization), a tool optimized for the search of unknown proteins and their pathways from a given set of known interacting proteins. MoCha uses the comprehensive dataset of protein-protein interactions provided by the STRING database, which currently includes more than a billion interactions from over 2,000 organisms. MoCha is highly optimized, performing typical searches within seconds. We demonstrate the use of MoCha with the characterization of unknown components from reverse-engineered models from the literature. MoCha is useful for working on network models by hand or as a downstream step of a model inference engine workflow and represents a valuable and efficient tool for the characterization of unknown pathways using known data from thousands of organisms. MoCha and its source code are freely available online under the GPLv3 license.

PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database.

PubMed

Huang, Weiliang; Brewer, Luke K; Jones, Jace W; Nguyen, Angela T; Marcu, Ana; Wishart, David S; Oglesby-Sherrouse, Amanda G; Kane, Maureen A; Wilks, Angela

2018-01-04

The Pseudomonas aeruginosaMetabolome Database (PAMDB, http://pseudomonas.umaryland.edu) is a searchable, richly annotated metabolite database specific to P. aeruginosa. P. aeruginosa is a soil organism and significant opportunistic pathogen that adapts to its environment through a versatile energy metabolism network. Furthermore, P. aeruginosa is a model organism for the study of biofilm formation, quorum sensing, and bioremediation processes, each of which are dependent on unique pathways and metabolites. The PAMDB is modelled on the Escherichia coli (ECMDB), yeast (YMDB) and human (HMDB) metabolome databases and contains >4370 metabolites and 938 pathways with links to over 1260 genes and proteins. The database information was compiled from electronic databases, journal articles and mass spectrometry (MS) metabolomic data obtained in our laboratories. For each metabolite entered, we provide detailed compound descriptions, names and synonyms, structural and physiochemical information, nuclear magnetic resonance (NMR) and MS spectra, enzymes and pathway information, as well as gene and protein sequences. The database allows extensive searching via chemical names, structure and molecular weight, together with gene, protein and pathway relationships. The PAMBD and its future iterations will provide a valuable resource to biologists, natural product chemists and clinicians in identifying active compounds, potential biomarkers and clinical diagnostics. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Proposal for probing energy transfer pathway by single-molecule pump-dump experiment.

PubMed

Tao, Ming-Jie; Ai, Qing; Deng, Fu-Guo; Cheng, Yuan-Chung

2016-06-09

The structure of Fenna-Matthews-Olson (FMO) light-harvesting complex had long been recognized as containing seven bacteriochlorophyll (BChl) molecules. Recently, an additional BChl molecule was discovered in the crystal structure of the FMO complex, which may serve as a link between baseplate and the remaining seven molecules. Here, we investigate excitation energy transfer (EET) process by simulating single-molecule pump-dump experiment in the eight-molecules complex. We adopt the coherent modified Redfield theory and non-Markovian quantum jump method to simulate EET dynamics. This scheme provides a practical approach of detecting the realistic EET pathway in BChl complexes with currently available experimental technology. And it may assist optimizing design of artificial light-harvesting devices.

Proposal for probing energy transfer pathway by single-molecule pump-dump experiment

NASA Astrophysics Data System (ADS)

Tao, Ming-Jie; Ai, Qing; Deng, Fu-Guo; Cheng, Yuan-Chung

2016-06-01

The structure of Fenna-Matthews-Olson (FMO) light-harvesting complex had long been recognized as containing seven bacteriochlorophyll (BChl) molecules. Recently, an additional BChl molecule was discovered in the crystal structure of the FMO complex, which may serve as a link between baseplate and the remaining seven molecules. Here, we investigate excitation energy transfer (EET) process by simulating single-molecule pump-dump experiment in the eight-molecules complex. We adopt the coherent modified Redfield theory and non-Markovian quantum jump method to simulate EET dynamics. This scheme provides a practical approach of detecting the realistic EET pathway in BChl complexes with currently available experimental technology. And it may assist optimizing design of artificial light-harvesting devices.

Proposal for probing energy transfer pathway by single-molecule pump-dump experiment

PubMed Central

Tao, Ming-Jie; Ai, Qing; Deng, Fu-Guo; Cheng, Yuan-Chung

2016-01-01

The structure of Fenna-Matthews-Olson (FMO) light-harvesting complex had long been recognized as containing seven bacteriochlorophyll (BChl) molecules. Recently, an additional BChl molecule was discovered in the crystal structure of the FMO complex, which may serve as a link between baseplate and the remaining seven molecules. Here, we investigate excitation energy transfer (EET) process by simulating single-molecule pump-dump experiment in the eight-molecules complex. We adopt the coherent modified Redfield theory and non-Markovian quantum jump method to simulate EET dynamics. This scheme provides a practical approach of detecting the realistic EET pathway in BChl complexes with currently available experimental technology. And it may assist optimizing design of artificial light-harvesting devices. PMID:27277702

Heterogeneous Biomedical Database Integration Using a Hybrid Strategy: A p53 Cantcer Research Database

PubMed Central

Bichutskiy, Vadim Y.; Colman, Richard; Brachmann, Rainer K.; Lathrop, Richard H.

2006-01-01

Complex problems in life science research give rise to multidisciplinary collaboration, and hence, to the need for heterogeneous database integration. The tumor suppressor p53 is mutated in close to 50% of human cancers, and a small drug-like molecule with the ability to restore native function to cancerous p53 mutants is a long-held medical goal of cancer treatment. The Cancer Research DataBase (CRDB) was designed in support of a project to find such small molecules. As a cancer informatics project, the CRDB involved small molecule data, computational docking results, functional assays, and protein structure data. As an example of the hybrid strategy for data integration, it combined the mediation and data warehousing approaches. This paper uses the CRDB to illustrate the hybrid strategy as a viable approach to heterogeneous data integration in biomedicine, and provides a design method for those considering similar systems. More efficient data sharing implies increased productivity, and, hopefully, improved chances of success in cancer research. (Code and database schemas are freely downloadable, http://www.igb.uci.edu/research/research.html.) PMID:19458771

Differential Attenuation of NMR Signals by Complementary Ion-Exchange Resin Beads for De Novo Analysis of Complex Metabolomics Mixtures.

PubMed

Zhang, Bo; Yuan, Jiaqi; Brüschweiler, Rafael

2017-07-12

A primary goal of metabolomics is the characterization of a potentially very large number of metabolites that are part of complex mixtures. Application to biofluids and tissue samples offers insights into biochemical metabolic pathways and their role in health and disease. 1D 1 H and 2D 13 C- 1 H HSQC NMR spectra are most commonly used for this purpose. They yield quantitative information about each proton of the mixture, but do not tell which protons belong to the same molecule. Interpretation requires the use of NMR spectral databases, which naturally limits these investigations to known metabolites. Here, a new method is presented that uses complementary ion exchange resin beads to differentially attenuate 2D NMR cross-peaks that belong to different metabolites. Based on their characteristic attenuation patterns, cross-peaks could be clustered and assigned to individual molecules, including unknown metabolites with multiple spin systems, as demonstrated for a metabolite model mixture and E. coli cell lysate. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

1-CMDb: A Curated Database of Genomic Variations of the One-Carbon Metabolism Pathway.

PubMed

Bhat, Manoj K; Gadekar, Veerendra P; Jain, Aditya; Paul, Bobby; Rai, Padmalatha S; Satyamoorthy, Kapaettu

2017-01-01

The one-carbon metabolism pathway is vital in maintaining tissue homeostasis by driving the critical reactions of folate and methionine cycles. A myriad of genetic and epigenetic events mark the rate of reactions in a tissue-specific manner. Integration of these to predict and provide personalized health management requires robust computational tools that can process multiomics data. The DNA sequences that may determine the chain of biological events and the endpoint reactions within one-carbon metabolism genes remain to be comprehensively recorded. Hence, we designed the one-carbon metabolism database (1-CMDb) as a platform to interrogate its association with a host of human disorders. DNA sequence and network information of a total of 48 genes were extracted from a literature survey and KEGG pathway that are involved in the one-carbon folate-mediated pathway. The information generated, collected, and compiled for all these genes from the UCSC genome browser included the single nucleotide polymorphisms (SNPs), CpGs, copy number variations (CNVs), and miRNAs, and a comprehensive database was created. Furthermore, a significant correlation analysis was performed for SNPs in the pathway genes. Detailed data of SNPs, CNVs, CpG islands, and miRNAs for 48 folate pathway genes were compiled. The SNPs in CNVs (9670), CpGs (984), and miRNAs (14) were also compiled for all pathway genes. The SIFT score, the prediction and PolyPhen score, as well as the prediction for each of the SNPs were tabulated and represented for folate pathway genes. Also included in the database for folate pathway genes were the links to 124 various phenotypes and disease associations as reported in the literature and from publicly available information. A comprehensive database was generated consisting of genomic elements within and among SNPs, CNVs, CpGs, and miRNAs of one-carbon metabolism pathways to facilitate (a) single source of information and (b) integration into large-genome scale network analysis to be developed in the future by the scientific community. The database can be accessed at http://slsdb.manipal.edu/ocm/. © 2017 S. Karger AG, Basel.

VisANT 3.0: new modules for pathway visualization, editing, prediction and construction.

PubMed

Hu, Zhenjun; Ng, David M; Yamada, Takuji; Chen, Chunnuan; Kawashima, Shuichi; Mellor, Joe; Linghu, Bolan; Kanehisa, Minoru; Stuart, Joshua M; DeLisi, Charles

2007-07-01

With the integration of the KEGG and Predictome databases as well as two search engines for coexpressed genes/proteins using data sets obtained from the Stanford Microarray Database (SMD) and Gene Expression Omnibus (GEO) database, VisANT 3.0 supports exploratory pathway analysis, which includes multi-scale visualization of multiple pathways, editing and annotating pathways using a KEGG compatible visual notation and visualization of expression data in the context of pathways. Expression levels are represented either by color intensity or by nodes with an embedded expression profile. Multiple experiments can be navigated or animated. Known KEGG pathways can be enriched by querying either coexpressed components of known pathway members or proteins with known physical interactions. Predicted pathways for genes/proteins with unknown functions can be inferred from coexpression or physical interaction data. Pathways produced in VisANT can be saved as computer-readable XML format (VisML), graphic images or high-resolution Scalable Vector Graphics (SVG). Pathways in the format of VisML can be securely shared within an interested group or published online using a simple Web link. VisANT is freely available at http://visant.bu.edu.

ASD: a comprehensive database of allosteric proteins and modulators

PubMed Central

Huang, Zhimin; Zhu, Liang; Cao, Yan; Wu, Geng; Liu, Xinyi; Chen, Yingyi; Wang, Qi; Shi, Ting; Zhao, Yaxue; Wang, Yuefei; Li, Weihua; Li, Yixue; Chen, Haifeng; Chen, Guoqiang; Zhang, Jian

2011-01-01

Allostery is the most direct, rapid and efficient way of regulating protein function, ranging from the control of metabolic mechanisms to signal-transduction pathways. However, an enormous amount of unsystematic allostery information has deterred scientists who could benefit from this field. Here, we present the AlloSteric Database (ASD), the first online database that provides a central resource for the display, search and analysis of structure, function and related annotation for allosteric molecules. Currently, ASD contains 336 allosteric proteins from 101 species and 8095 modulators in three categories (activators, inhibitors and regulators). Proteins are annotated with a detailed description of allostery, biological process and related diseases, and modulators with binding affinity, physicochemical properties and therapeutic area. Integrating the information of allosteric proteins in ASD should allow for the identification of specific allosteric sites of a given subtype among proteins of the same family that can potentially serve as ideal targets for experimental validation. In addition, modulators curated in ASD can be used to investigate potent allosteric targets for the query compound, and also help chemists to implement structure modifications for novel allosteric drug design. Therefore, ASD could be a platform and a starting point for biologists and medicinal chemists for furthering allosteric research. ASD is freely available at http://mdl.shsmu.edu.cn/ASD/. PMID:21051350

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems

PubMed Central

Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K.; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C.; Hoeng, Julia

2015-01-01

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com PMID:25887162

A Staphylococcus aureus TIR domain protein virulence factor blocks TLR2-mediated NF-κB signaling.

PubMed

Askarian, Fatemeh; van Sorge, Nina M; Sangvik, Maria; Beasley, Federico C; Henriksen, Jørn R; Sollid, Johanna U E; van Strijp, Jos A G; Nizet, Victor; Johannessen, Mona

2014-01-01

Signaling through Toll-like receptors (TLRs), crucial molecules in the induction of host defense responses, requires adaptor proteins that contain a Toll/interleukin-1 receptor (TIR) domain. The pathogen Staphylococcus aureus produces several innate immune-evasion molecules that interfere with the host's innate immune response. A database search analysis suggested the presence of a gene encoding a homologue of the human TIR domain in S. aureus MSSA476 which was named staphylococcal TIR domain protein (TirS). Ectopic expression of TirS in human embryonic kidney, macrophage and keratinocyte cell lines interfered with signaling through TLR2, including MyD88 and TIRAP, NF-κB and/or mitogen-activated protein kinase pathways. Moreover, the presence of TirS reduced the levels of cytokines MCP-1 and G-CSF secreted in response to S. aureus. The effects on NF-κB pathway were confirmed using S. aureus MSSA476 wild type, an isogenic mutant MSSA476ΔtirS, and complemented MSSA476ΔtirS +pTirS in a Transwell system where bacteria and host cells were physically separated. Finally, in a systematic mouse infection model, TirS promoted bacterial accumulation in several organs 4 days postinfection. The results of this study reveal a new S. aureus virulence factor that can interfere with PAMP-induced innate immune signaling in vitro and bacterial survival in vivo. © 2014 S. Karger AG, Basel.

Platelet Activating Factor Receptor Activation Improves siRNA Uptake and RNAi Responses in Well-differentiated Airway Epithelia.

PubMed

Krishnamurthy, Sateesh; Behlke, Mark A; Apicella, Michael A; McCray, Paul B; Davidson, Beverly L

2014-07-15

Well-differentiated human airway epithelia present formidable barriers to efficient siRNA delivery. We previously reported that treatment of airway epithelia with specific small molecules improves oligonucleotide uptake and facilitates RNAi responses. Here, we exploited the platelet activating factor receptor (PAFR) pathway, utilized by specific bacteria to transcytose into epithelia, as a trigger for internalization of Dicer-substrate siRNAs (DsiRNA). PAFR is a G-protein coupled receptor which can be engaged and activated by phosphorylcholine residues on the lipooligosaccharide (LOS) of nontypeable Haemophilus influenzae and the teichoic acid of Streptococcus pneumoniae as well as by its natural ligand, platelet activating factor (PAF). When well-differentiated airway epithelia were simultaneously treated with either nontypeable Haemophilus influenzae LOS or PAF and transduced with DsiRNA formulated with the peptide transductin, we observed silencing of both endogenous and exogenous targets. PAF receptor antagonists prevented LOS or PAF-assisted DsiRNA silencing, demonstrating that ligand engagement of PAFR is essential for this process. Additionally, PAF-assisted DsiRNA transfection decreased CFTR protein expression and function and reduced exogenous viral protein levels and titer in human airway epithelia. Treatment with spiperone, a small molecule identified using the Connectivity map database to correlate gene expression changes in response to drug treatment with those associated with PAFR stimulation, also induced silencing. These results suggest that the signaling pathway activated by PAFR binding can be manipulated to facilitate siRNA entry and function in difficult to transfect well-differentiated airway epithelial cells.

Lipid Metabolism, Apoptosis and Cancer Therapy

PubMed Central

Huang, Chunfa; Freter, Carl

2015-01-01

Lipid metabolism is regulated by multiple signaling pathways, and generates a variety of bioactive lipid molecules. These bioactive lipid molecules known as signaling molecules, such as fatty acid, eicosanoids, diacylglycerol, phosphatidic acid, lysophophatidic acid, ceramide, sphingosine, sphingosine-1-phosphate, phosphatidylinositol-3 phosphate, and cholesterol, are involved in the activation or regulation of different signaling pathways. Lipid metabolism participates in the regulation of many cellular processes such as cell growth, proliferation, differentiation, survival, apoptosis, inflammation, motility, membrane homeostasis, chemotherapy response, and drug resistance. Bioactive lipid molecules promote apoptosis via the intrinsic pathway by modulating mitochondrial membrane permeability and activating different enzymes including caspases. In this review, we discuss recent data in the fields of lipid metabolism, lipid-mediated apoptosis, and cancer therapy. In conclusion, understanding the underlying molecular mechanism of lipid metabolism and the function of different lipid molecules could provide the basis for cancer cell death rationale, discover novel and potential targets, and develop new anticancer drugs for cancer therapy. PMID:25561239

EDULISS: a small-molecule database with data-mining and pharmacophore searching capabilities

PubMed Central

Hsin, Kun-Yi; Morgan, Hugh P.; Shave, Steven R.; Hinton, Andrew C.; Taylor, Paul; Walkinshaw, Malcolm D.

2011-01-01

We present the relational database EDULISS (EDinburgh University Ligand Selection System), which stores structural, physicochemical and pharmacophoric properties of small molecules. The database comprises a collection of over 4 million commercially available compounds from 28 different suppliers. A user-friendly web-based interface for EDULISS (available at http://eduliss.bch.ed.ac.uk/) has been established providing a number of data-mining possibilities. For each compound a single 3D conformer is stored along with over 1600 calculated descriptor values (molecular properties). A very efficient method for unique compound recognition, especially for a large scale database, is demonstrated by making use of small subgroups of the descriptors. Many of the shape and distance descriptors are held as pre-calculated bit strings permitting fast and efficient similarity and pharmacophore searches which can be used to identify families of related compounds for biological testing. Two ligand searching applications are given to demonstrate how EDULISS can be used to extract families of molecules with selected structural and biophysical features. PMID:21051336

Proteomics reveals novel components of the Anopheles gambiae eggshell

PubMed Central

Amenya, Dolphine A.; Chou, Wayne; Li, Jianyong; Yan, Guiyun; Gershon, Paul D.; James, Anthony A.; Marinotti, Osvaldo

2010-01-01

While genome and transcriptome sequencing has revealed a large number and diversity of Anopheles gambiae predicted proteins, identifying their functions and biosynthetic pathways remains challenging. Applied mass spectrometry based proteomics in conjunction with mosquito genome and transcriptome databases were used to identify 44 proteins as putative components of the eggshell. Among the identified molecules are two vitelline membrane proteins and a group of seven putative chorion proteins. Enzymes with peroxidase, laccase and phenoloxidase activities, likely involved in cross-linking reactions that stabilize the eggshell structure, also were identified. Seven odorant binding proteins were found in association with the mosquito eggshell, although their role has yet to be demonstrated. This analysis fills a considerable gap of knowledge about proteins that build the eggshell of anopheline mosquitoes. PMID:20433845

EDCs DataBank: 3D-Structure database of endocrine disrupting chemicals.

PubMed

Montes-Grajales, Diana; Olivero-Verbel, Jesus

2015-01-02

Endocrine disrupting chemicals (EDCs) are a group of compounds that affect the endocrine system, frequently found in everyday products and epidemiologically associated with several diseases. The purpose of this work was to develop EDCs DataBank, the only database of EDCs with three-dimensional structures. This database was built on MySQL using the EU list of potential endocrine disruptors and TEDX list. It contains the three-dimensional structures available on PubChem, as well as a wide variety of information from different databases and text mining tools, useful for almost any kind of research regarding EDCs. The web platform was developed employing HTML, CSS and PHP languages, with dynamic contents in a graphic environment, facilitating information analysis. Currently EDCs DataBank has 615 molecules, including pesticides, natural and industrial products, cosmetics, drugs and food additives, among other low molecular weight xenobiotics. Therefore, this database can be used to study the toxicological effects of these molecules, or to develop pharmaceuticals targeting hormone receptors, through docking studies, high-throughput virtual screening and ligand-protein interaction analysis. EDCs DataBank is totally user-friendly and the 3D-structures of the molecules can be downloaded in several formats. This database is freely available at http://edcs.unicartagena.edu.co. Copyright © 2014. Published by Elsevier Ireland Ltd.

SASD: the Synthetic Alternative Splicing Database for identifying novel isoform from proteomics

PubMed Central

2013-01-01

Background Alternative splicing is an important and widespread mechanism for generating protein diversity and regulating protein expression. High-throughput identification and analysis of alternative splicing in the protein level has more advantages than in the mRNA level. The combination of alternative splicing database and tandem mass spectrometry provides a powerful technique for identification, analysis and characterization of potential novel alternative splicing protein isoforms from proteomics. Therefore, based on the peptidomic database of human protein isoforms for proteomics experiments, our objective is to design a new alternative splicing database to 1) provide more coverage of genes, transcripts and alternative splicing, 2) exclusively focus on the alternative splicing, and 3) perform context-specific alternative splicing analysis. Results We used a three-step pipeline to create a synthetic alternative splicing database (SASD) to identify novel alternative splicing isoforms and interpret them at the context of pathway, disease, drug and organ specificity or custom gene set with maximum coverage and exclusive focus on alternative splicing. First, we extracted information on gene structures of all genes in the Ensembl Genes 71 database and incorporated the Integrated Pathway Analysis Database. Then, we compiled artificial splicing transcripts. Lastly, we translated the artificial transcripts into alternative splicing peptides. The SASD is a comprehensive database containing 56,630 genes (Ensembl gene IDs), 95,260 transcripts (Ensembl transcript IDs), and 11,919,779 Alternative Splicing peptides, and also covering about 1,956 pathways, 6,704 diseases, 5,615 drugs, and 52 organs. The database has a web-based user interface that allows users to search, display and download a single gene/transcript/protein, custom gene set, pathway, disease, drug, organ related alternative splicing. Moreover, the quality of the database was validated with comparison to other known databases and two case studies: 1) in liver cancer and 2) in breast cancer. Conclusions The SASD provides the scientific community with an efficient means to identify, analyze, and characterize novel Exon Skipping and Intron Retention protein isoforms from mass spectrometry and interpret them at the context of pathway, disease, drug and organ specificity or custom gene set with maximum coverage and exclusive focus on alternative splicing. PMID:24267658

SMMRNA: a database of small molecule modulators of RNA

PubMed Central

Mehta, Ankita; Sonam, Surabhi; Gouri, Isha; Loharch, Saurabh; Sharma, Deepak K.; Parkesh, Raman

2014-01-01

We have developed SMMRNA, an interactive database, available at http://www.smmrna.org, with special focus on small molecule ligands targeting RNA. Currently, SMMRNA consists of ∼770 unique ligands along with structural images of RNA molecules. Each ligand in the SMMRNA contains information such as Kd, Ki, IC50, ΔTm, molecular weight (MW), hydrogen donor and acceptor count, XlogP, number of rotatable bonds, number of aromatic rings and 2D and 3D structures. These parameters can be explored using text search, advanced search, substructure and similarity-based analysis tools that are embedded in SMMRNA. A structure editor is provided for 3D visualization of ligands. Advance analysis can be performed using substructure and OpenBabel-based chemical similarity fingerprints. Upload facility for both RNA and ligands is also provided. The physicochemical properties of the ligands were further examined using OpenBabel descriptors, hierarchical clustering, binning partition and multidimensional scaling. We have also generated a 3D conformation database of ligands to support the structure and ligand-based screening. SMMRNA provides comprehensive resource for further design, development and refinement of small molecule modulators for selective targeting of RNA molecules. PMID:24163098

Targetome Analysis Revealed Involvement of MiR-126 in Neurotrophin Signaling Pathway: A Possible Role in Prevention of Glioma Development.

PubMed

Rouigari, Maedeh; Dehbashi, Moein; Ghaedi, Kamran; Pourhossein, Meraj

2018-07-01

For the first time, we used molecular signaling pathway enrichment analysis to determine possible involvement of miR-126 and IRS-1 in neurotrophin pathway. In this prospective study, Validated and predicted targets (targetome) of miR-126 were collected following searching miRtarbase (http://mirtarbase.mbc.nctu.edu.tw/) and miRWalk 2.0 databases, respectively. Then, approximate expression of miR-126 targeting in Glioma tissue was examined using UniGene database (http://www.ncbi. nlm.nih.gov/unigene). In silico molecular pathway enrichment analysis was carried out by DAVID 6.7 database (http://david. abcc.ncifcrf.gov/) to explore which signaling pathway is related to miR-126 targeting and how miR-126 attributes to glioma development. MiR-126 exerts a variety of functions in cancer pathogenesis via suppression of expression of target gene including PI3K, KRAS, EGFL7, IRS-1 and VEGF. Our bioinformatic studies implementing DAVID database, showed the involvement of miR-126 target genes in several signaling pathways including cancer pathogenesis, neurotrophin functions, Glioma formation, insulin function, focal adhesion production, chemokine synthesis and secretion and regulation of the actin cytoskeleton. Taken together, we concluded that miR-126 enhances the formation of glioma cancer stem cell probably via down regulation of IRS-1 in neurotrophin signaling pathway. Copyright© by Royan Institute. All rights reserved.

The Listeria monocytogenes strain 10403S BioCyc database

PubMed Central

Orsi, Renato H.; Bergholz, Teresa M.; Wiedmann, Martin; Boor, Kathryn J.

2015-01-01

Listeria monocytogenes is a food-borne pathogen of humans and other animals. The striking ability to survive several stresses usually used for food preservation makes L. monocytogenes one of the biggest concerns to the food industry, while the high mortality of listeriosis in specific groups of humans makes it a great concern for public health. Previous studies have shown that a regulatory network involving alternative sigma (σ) factors and transcription factors is pivotal to stress survival. However, few studies have evaluated at the metabolic networks controlled by these regulatory mechanisms. The L. monocytogenes BioCyc database uses the strain 10403S as a model. Computer-generated initial annotation for all genes also allowed for identification, annotation and display of predicted reactions and pathways carried out by a single cell. Further ongoing manual curation based on published data as well as database mining for selected genes allowed the more refined annotation of functions, which, in turn, allowed for annotation of new pathways and fine-tuning of previously defined pathways to more L. monocytogenes-specific pathways. Using RNA-Seq data, several transcription start sites and promoter regions were mapped to the 10403S genome and annotated within the database. Additionally, the identification of promoter regions and a comprehensive review of available literature allowed the annotation of several regulatory interactions involving σ factors and transcription factors. The L. monocytogenes 10403S BioCyc database is a new resource for researchers studying Listeria and related organisms. It allows users to (i) have a comprehensive view of all reactions and pathways predicted to take place within the cell in the cellular overview, as well as to (ii) upload their own data, such as differential expression data, to visualize the data in the scope of predicted pathways and regulatory networks and to carry on enrichment analyses using several different annotations available within the database. Database URL: http://biocyc.org/organism-summary?object=10403S_RAST PMID:25819074

cPath: open source software for collecting, storing, and querying biological pathways.

PubMed

Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris

2006-11-13

Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling.

Disentangling the multigenic and pleiotropic nature of molecular function

PubMed Central

2015-01-01

Background Biological processes at the molecular level are usually represented by molecular interaction networks. Function is organised and modularity identified based on network topology, however, this approach often fails to account for the dynamic and multifunctional nature of molecular components. For example, a molecule engaging in spatially or temporally independent functions may be inappropriately clustered into a single functional module. To capture biologically meaningful sets of interacting molecules, we use experimentally defined pathways as spatial/temporal units of molecular activity. Results We defined functional profiles of Saccharomyces cerevisiae based on a minimal set of Gene Ontology terms sufficient to represent each pathway's genes. The Gene Ontology terms were used to annotate 271 pathways, accounting for pathway multi-functionality and gene pleiotropy. Pathways were then arranged into a network, linked by shared functionality. Of the genes in our data set, 44% appeared in multiple pathways performing a diverse set of functions. Linking pathways by overlapping functionality revealed a modular network with energy metabolism forming a sparse centre, surrounded by several denser clusters comprised of regulatory and metabolic pathways. Signalling pathways formed a relatively discrete cluster connected to the centre of the network. Genetic interactions were enriched within the clusters of pathways by a factor of 5.5, confirming the organisation of our pathway network is biologically significant. Conclusions Our representation of molecular function according to pathway relationships enables analysis of gene/protein activity in the context of specific functional roles, as an alternative to typical molecule-centric graph-based methods. The pathway network demonstrates the cooperation of multiple pathways to perform biological processes and organises pathways into functionally related clusters with interdependent outcomes. PMID:26678917

The mevalonate pathway in neurons: It's not just about cholesterol.

PubMed

Moutinho, Miguel; Nunes, Maria João; Rodrigues, Elsa

2017-11-01

Cholesterol homeostasis greatly impacts neuronal function due to the essential role of this sterol in the brain. The mevalonate (MVA) pathway leads to the synthesis of cholesterol, but also supplies cells with many other intermediary molecules crucial for neuronal function. Compelling evidence point to a model in which neurons shutdown cholesterol synthesis, and rely on a shuttle derived from astrocytes to meet their cholesterol needs. Nevertheless, several reports suggest that neurons maintain the MVA pathway active, even with sustained cholesterol supply by astrocytes. Hence, in this review we focus not on cholesterol production, but rather on the role of the MVA pathway in the synthesis of particular intermediaries, namely isoprenoids, and on their role on neuronal function. Isoprenoids act as anchors for membrane association, after being covalently bound to proteins, such as most of the small guanosine triphosphate-binding proteins, which are critical to neuronal cell function. Based on literature, on our own results, and on the analysis of public transcriptomics databases, we raise the idea that in neurons there is a shift of the MVA pathway towards the non-sterol branch, responsible for isoprenoid synthesis, in detriment to post-squalene branch, and that this is ultimately essential for synaptic activity. Nevertheless new tools that facilitate imaging and the biochemical characterization and quantification of the prenylome in neurons and astrocytes are needed to understand the regulation of isoprenoid production and protein prenylation in the brain, and to analyze its differences on diverse physiological or pathological conditions, such as aging and neurodegenerative states. Copyright © 2017 Elsevier Inc. All rights reserved.

The imidazopyridine derivative JK184 reveals dual roles for microtubules in Hedgehog signaling.

PubMed

Cupido, Tommaso; Rack, Paul G; Firestone, Ari J; Hyman, Joel M; Han, Kyuho; Sinha, Surajit; Ocasio, Cory A; Chen, James K

2009-01-01

Eradicating hedgehogs: The title molecule has been previously identified as a potent inhibitor of the Hedgehog signaling pathway, which gives embryonic cells information needed to develop properly. This molecule is shown to modulate Hedgehog target gene expression by depolymerizing microtubules, thus revealing dual roles of the cytoskeleton in pathway regulation (see figure).

[Down-regulatory effect of Nucleostemin expression on signal molecule of PI3K/AKT/mTOR pathway in HL-60 cells].

PubMed

Jia, Yu; Wei, Yuan-Yu; Zhang, Fan; Li, Zhao-Bo; Liu, Shuai; Yue, Bao-Hong

2014-02-01

This study was purpose to explore the down-regulatory effect of nucleostemin (NS) expression on signal molecules of PI3K/AKT/mTOR pathway belonged to candidate ways of p53-independent signal pathway in the leukemia cells. The expression of NS was interfered by using recombinant lentivirus expression vector NS-RNAi-GV248 to transfect HL-60 cells of p53 deficiency. The expression of NS and signal molecules of PI3K/AKT/mTOR pathway were detected by using Real-time PCR. The results of showed that the HL-60 cells were transfected by recombinant lentivirus vector NS-RNAi-GV248 successfully and with transfection rate up to 80%. According to results of Real-time PCR detection, the inhibition rate of NS gene was 56.5% in HL-60 cells. And the expression levels of PI3K,AKT and GβL mRNA (0.491 ± 0.084,0.398 ± 0.164, 0.472 ± 0.097 respectively) were obviously down-regulated by silencing NS, and showed statistical difference (P < 0.05) in comparison with control (1.002 ± 0.171, 1.000 ± 0.411, 1.001 ± 0.206 respectively) . It is concluded that the changes of signal molecules of PI3K/AKT/mTOR pathway positively correlate with NS down-regulation, which provides evidence for confirming PI3K/AKT/mTOR signal pathway possible as a type of NS p53-independent pathway.

Exploring consumer exposure pathways and patterns of use for chemicals in the environment through the Chemical/Product Categories Database

EPA Pesticide Factsheets

Exploring consumer exposure pathways and patterns of use for chemicals in the environment through the Chemical/Product Categories Database (CPCat) (Presented by: Kathie Dionisio, Sc.D., NERL, US EPA, Research Triangle Park, NC (1/23/2014).

Elucidation of metabolic pathways from enzyme classification data.

PubMed

McDonald, Andrew G; Tipton, Keith F

2014-01-01

The IUBMB Enzyme List is widely used by other databases as a source for avoiding ambiguity in the recognition of enzymes as catalytic entities. However, it was not designed for metabolic pathway tracing, which has become increasingly important in systems biology. A Reactions Database has been created from the material in the Enzyme List to allow reactions to be searched by substrate/product, and pathways to be traced from any selected starting/seed substrate. An extensive synonym glossary allows searches by many of the alternative names, including accepted abbreviations, by which a chemical compound may be known. This database was necessary for the development of the application Reaction Explorer ( http://www.reaction-explorer.org ), which was written in Real Studio ( http://www.realsoftware.com/realstudio/ ) to search the Reactions Database and draw metabolic pathways from reactions selected by the user. Having input the name of the starting compound (the "seed"), the user is presented with a list of all reactions containing that compound and then selects the product of interest as the next point on the ensuing graph. The pathway diagram is then generated as the process iterates. A contextual menu is provided, which allows the user: (1) to remove a compound from the graph, along with all associated links; (2) to search the reactions database again for additional reactions involving the compound; (3) to search for the compound within the Enzyme List.

Immunoglobulin superfamily members encoded by viruses and their multiple roles in immune evasion.

PubMed

Farré, Domènec; Martínez-Vicente, Pablo; Engel, Pablo; Angulo, Ana

2017-05-01

Pathogens have developed a plethora of strategies to undermine host immune defenses in order to guarantee their survival. For large DNA viruses, these immune evasion mechanisms frequently rely on the expression of genes acquired from host genomes. Horizontally transferred genes include members of the immunoglobulin superfamily, whose products constitute the most diverse group of proteins of vertebrate genomes. Their promiscuous immunoglobulin domains, which comprise the building blocks of these molecules, are involved in a large variety of functions mediated by ligand-binding interactions. The flexible structural nature of the immunoglobulin domains makes them appealing targets for viral capture due to their capacity to generate high functional diversity. Here, we present an up-to-date review of immunoglobulin superfamily gene homologs encoded by herpesviruses, poxviruses, and adenoviruses, that include CD200, CD47, Fc receptors, interleukin-1 receptor 2, interleukin-18 binding protein, CD80, carcinoembryonic antigen-related cell adhesion molecules, and signaling lymphocyte activation molecules. We discuss their distinct structural attributes, binding properties, and functions, shaped by evolutionary pressures to disarm specific immune pathways. We include several novel genes identified from extensive genome database surveys. An understanding of the properties and modes of action of these viral proteins may guide the development of novel immune-modulatory therapeutic tools. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The RhoA/ROCK Pathway Ameliorates Adhesion and Inflammatory Infiltration Induced by AGEs in Glomerular Endothelial Cells.

PubMed

Rao, Jialing; Ye, Zengchun; Tang, Hua; Wang, Cheng; Peng, Hui; Lai, Weiyan; Li, Yin; Huang, Wanbing; Lou, Tanqi

2017-01-05

A recent study demonstrated that advanced glycation end products (AGEs) play a role in monocyte infiltration in mesangial areas in diabetic nephropathy. The Ras homolog gene family, member A Rho kinase (RhoA/ROCK) pathway plays a role in regulating cell migration. We hypothesized that the RhoA/ROCK pathway affects adhesion and inflammation in endothelial cells induced by AGEs. Rat glomerular endothelial cells (rGECs) were cultured with AGEs (80 μg/ml) in vitro. The ROCK inhibitor Y27632 (10 nmol/l) and ROCK1-siRNA were used to inhibit ROCK. We investigated levels of the intercellular adhesion molecule 1 (ICAM-1) and monocyte chemoattractant protein1 (MCP-1) in rGECs. Db/db mice were used as a diabetes model and received Fasudil (10 mg/kg/d, n = 6) via intraperitoneal injection for 12 weeks. We found that AGEs increased the expression of ICAM-1 and MCP-1 in rGECs, and the RhoA/ROCK pathway inhibitor Y27632 depressed the release of adhesion molecules. Moreover, blocking the RhoA/ROCK pathway ameliorated macrophage transfer to the endothelium. Reduced expression of adhesion molecules and amelioration of inflammatory cell infiltration in the glomerulus were observed in db/db mice treated with Fasudil. The RhoA/ROCK pathway plays a role in adhesion molecule expression and inflammatory cell infiltration in glomerular endothelial cells induced by AGEs.

The emerging role of Hippo signaling pathway in regulating osteoclast formation.

PubMed

Yang, Wanlei; Han, Weiqi; Qin, An; Wang, Ziyi; Xu, Jiake; Qian, Yu

2018-06-01

A delicate balance between osteoblastic bone formation and osteoclastic bone resorption is crucial for bone homeostasis. This process is regulated by the Hippo signaling pathway including key regulatory molecules RASSF2, NF2, MST1/2, SAV1, LATS1/2, MOB1, YAP, and TAZ. It is well established that the Hippo signaling pathway plays an important part in regulating osteoblast differentiation, but its role in osteoclast formation and activation remains poorly understood. In this review, we discuss the emerging role of Hippo-signaling pathway in osteoclast formation and bone homeostasis. It is revealed that specific molecules of the Hippo-signaling pathway take part in a stage specific regulation in pre-osteoclast proliferation, osteoclast differentiation and osteoclast apoptosis and survival. Upon activation, MST and LAST, transcriptional co-activators YAP and TAZ bind to the members of the TEA domain (TEAD) family transcription factors, and influence osteoclast differentiation via regulating the expression of downstream target genes such as connective tissue growth factor (CTGF/CCN2) and cysteine-rich protein 61 (CYR61/CCN1). In addition, through interacting or cross talking with RANKL-mediated signaling cascades including NF-κB, MAPKs, AP1, and NFATc1, Hippo-signaling molecules such as YAP/TAZ/TEAD complex, RASSF2, MST2, and Ajuba could also potentially modulate osteoclast differentiation and function. Elucidating the roles of the Hippo-signaling pathway in osteoclast development and specific molecules involved is important for understanding the mechanism of bone homeostasis and diseases. © 2017 Wiley Periodicals, Inc.

Enhancing a Pathway-Genome Database (PGDB) to capture subcellular localization of metabolites and enzymes: the nucleotide-sugar biosynthetic pathways of Populus trichocarpa.

PubMed

Nag, Ambarish; Karpinets, Tatiana V; Chang, Christopher H; Bar-Peled, Maor

2012-01-01

Understanding how cellular metabolism works and is regulated requires that the underlying biochemical pathways be adequately represented and integrated with large metabolomic data sets to establish a robust network model. Genetically engineering energy crops to be less recalcitrant to saccharification requires detailed knowledge of plant polysaccharide structures and a thorough understanding of the metabolic pathways involved in forming and regulating cell-wall synthesis. Nucleotide-sugars are building blocks for synthesis of cell wall polysaccharides. The biosynthesis of nucleotide-sugars is catalyzed by a multitude of enzymes that reside in different subcellular organelles, and precise representation of these pathways requires accurate capture of this biological compartmentalization. The lack of simple localization cues in genomic sequence data and annotations however leads to missing compartmentalization information for eukaryotes in automatically generated databases, such as the Pathway-Genome Databases (PGDBs) of the SRI Pathway Tools software that drives much biochemical knowledge representation on the internet. In this report, we provide an informal mechanism using the existing Pathway Tools framework to integrate protein and metabolite sub-cellular localization data with the existing representation of the nucleotide-sugar metabolic pathways in a prototype PGDB for Populus trichocarpa. The enhanced pathway representations have been successfully used to map SNP abundance data to individual nucleotide-sugar biosynthetic genes in the PGDB. The manually curated pathway representations are more conducive to the construction of a computational platform that will allow the simulation of natural and engineered nucleotide-sugar precursor fluxes into specific recalcitrant polysaccharide(s). Database URL: The curated Populus PGDB is available in the BESC public portal at http://cricket.ornl.gov/cgi-bin/beocyc_home.cgi and the nucleotide-sugar biosynthetic pathways can be directly accessed at http://cricket.ornl.gov:1555/PTR/new-image?object=SUGAR-NUCLEOTIDES.

Enhancing a Pathway-Genome Database (PGDB) to capture subcellular localization of metabolites and enzymes: the nucleotide-sugar biosynthetic pathways of Populus trichocarpa

PubMed Central

Nag, Ambarish; Karpinets, Tatiana V.; Chang, Christopher H.; Bar-Peled, Maor

2012-01-01

Understanding how cellular metabolism works and is regulated requires that the underlying biochemical pathways be adequately represented and integrated with large metabolomic data sets to establish a robust network model. Genetically engineering energy crops to be less recalcitrant to saccharification requires detailed knowledge of plant polysaccharide structures and a thorough understanding of the metabolic pathways involved in forming and regulating cell-wall synthesis. Nucleotide-sugars are building blocks for synthesis of cell wall polysaccharides. The biosynthesis of nucleotide-sugars is catalyzed by a multitude of enzymes that reside in different subcellular organelles, and precise representation of these pathways requires accurate capture of this biological compartmentalization. The lack of simple localization cues in genomic sequence data and annotations however leads to missing compartmentalization information for eukaryotes in automatically generated databases, such as the Pathway-Genome Databases (PGDBs) of the SRI Pathway Tools software that drives much biochemical knowledge representation on the internet. In this report, we provide an informal mechanism using the existing Pathway Tools framework to integrate protein and metabolite sub-cellular localization data with the existing representation of the nucleotide-sugar metabolic pathways in a prototype PGDB for Populus trichocarpa. The enhanced pathway representations have been successfully used to map SNP abundance data to individual nucleotide-sugar biosynthetic genes in the PGDB. The manually curated pathway representations are more conducive to the construction of a computational platform that will allow the simulation of natural and engineered nucleotide-sugar precursor fluxes into specific recalcitrant polysaccharide(s). Database URL: The curated Populus PGDB is available in the BESC public portal at http://cricket.ornl.gov/cgi-bin/beocyc_home.cgi and the nucleotide-sugar biosynthetic pathways can be directly accessed at http://cricket.ornl.gov:1555/PTR/new-image?object=SUGAR-NUCLEOTIDES. PMID:22465851

Evaluations of the trans-sulfuration pathway in multiple liver toxicity studies

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

Schnackenberg, Laura K.; Chen Minjun; Sun, Jinchun

2009-02-15

Drug-induced liver injury has been associated with the generation of reactive metabolites, which are primarily detoxified via glutathione conjugation. In this study, it was hypothesized that molecules involved in the synthesis of glutathione would be diminished to replenish the glutathione depleted through conjugation reactions. Since S-adenosylmethionine (SAMe) is the primary source of the sulfur atom in glutathione, UPLC/MS and NMR were used to evaluate metabolites involved with the transulfuration pathway in urine samples collected during studies of eight liver toxic compounds in Sprague-Dawley rats. Urinary levels of creatine were increased on day 1 or day 2 in 8 high dosemore » liver toxicity studies. Taurine concentration in urine was increased in only 3 of 8 liver toxicity studies while SAMe was found to be reduced in 4 of 5 liver toxicity studies. To further validate the results from the metabonomic studies, microarray data from rat liver samples following treatment with acetaminophen was obtained from the Gene Expression Omnibus (GEO) database. Some genes involved in the trans-sulfuration pathway, including guanidinoacetate N-methyltransferase, glycine N-methyltransferase, betaine-homocysteine methyltransferase and cysteine dioxygenase were found to be significantly decreased while methionine adenosyl transferase II, alpha increased at 24 h post-dosing, which is consistent with the SAMe and creatine findings. The metabolic and transcriptomic results show that the trans-sulfuration pathway from SAMe to glutathione was disturbed due to the administration of heptatotoxicants.« less

Dynamics of NAD-metabolism: everything but constant.

PubMed

Opitz, Christiane A; Heiland, Ines

2015-12-01

NAD, as well as its phosphorylated form, NADP, are best known as electron carriers and co-substrates of various redox reactions. As such they participate in approximately one quarter of all reactions listed in the reaction database KEGG. In metabolic pathway analysis, the total amount of NAD is usually assumed to be constant. That means that changes in the redox state might be considered, but concentration changes of the NAD moiety are usually neglected. However, a growing number of NAD-consuming reactions have been identified, showing that this assumption does not hold true in general. NAD-consuming reactions are common characteristics of NAD(+)-dependent signalling pathways and include mono- and poly-ADP-ribosylation of proteins, NAD(+)-dependent deacetylation by sirtuins and the formation of messenger molecules such as cyclic ADP-ribose (cADPR) and nicotinic acid (NA)-ADP (NAADP). NAD-consuming reactions are thus involved in major signalling and gene regulation pathways such as DNA-repair or regulation of enzymes central in metabolism. All known NAD(+)-dependent signalling processes include the release of nicotinamide (Nam). Thus cellular NAD pools need to be constantly replenished, mostly by recycling Nam to NAD(+). This process is, among others, regulated by the circadian clock, causing complex dynamic changes in NAD concentration. As disturbances in NAD homoeostasis are associated with a large number of diseases ranging from cancer to diabetes, it is important to better understand the dynamics of NAD metabolism to develop efficient pharmacological invention strategies to target this pathway. © 2015 Authors; published by Portland Press Limited.

Bias-Free Chemically Diverse Test Sets from Machine Learning.

PubMed

Swann, Ellen T; Fernandez, Michael; Coote, Michelle L; Barnard, Amanda S

2017-08-14

Current benchmarking methods in quantum chemistry rely on databases that are built using a chemist's intuition. It is not fully understood how diverse or representative these databases truly are. Multivariate statistical techniques like archetypal analysis and K-means clustering have previously been used to summarize large sets of nanoparticles however molecules are more diverse and not as easily characterized by descriptors. In this work, we compare three sets of descriptors based on the one-, two-, and three-dimensional structure of a molecule. Using data from the NIST Computational Chemistry Comparison and Benchmark Database and machine learning techniques, we demonstrate the functional relationship between these structural descriptors and the electronic energy of molecules. Archetypes and prototypes found with topological or Coulomb matrix descriptors can be used to identify smaller, statistically significant test sets that better capture the diversity of chemical space. We apply this same method to find a diverse subset of organic molecules to demonstrate how the methods can easily be reapplied to individual research projects. Finally, we use our bias-free test sets to assess the performance of density functional theory and quantum Monte Carlo methods.

A simple biosynthetic pathway for large product generation from small substrate amounts

NASA Astrophysics Data System (ADS)

Djordjevic, Marko; Djordjevic, Magdalena

2012-10-01

A recently emerging discipline of synthetic biology has the aim of constructing new biosynthetic pathways with useful biological functions. A major application of these pathways is generating a large amount of the desired product. However, toxicity due to the possible presence of toxic precursors is one of the main problems for such production. We consider here the problem of generating a large amount of product from a potentially toxic substrate. To address this, we propose a simple biosynthetic pathway, which can be induced in order to produce a large number of the product molecules, by keeping the substrate amount at low levels. Surprisingly, we show that the large product generation crucially depends on fast non-specific degradation of the substrate molecules. We derive an optimal induction strategy, which allows as much as three orders of magnitude increase in the product amount through biologically realistic parameter values. We point to a recently discovered bacterial immune system (CRISPR/Cas in E. coli) as a putative example of the pathway analysed here. We also argue that the scheme proposed here can be used not only as a stand-alone pathway, but also as a strategy to produce a large amount of the desired molecules with small perturbations of endogenous biosynthetic pathways.

Power-law-distributed dark states are the main pathway for photobleaching of single organic molecules.

PubMed

Hoogenboom, Jacob P; van Dijk, Erik M H P; Hernando, Jordi; van Hulst, Niek F; García-Parajó, María F

2005-08-26

We exploit the strong excitonic coupling in a superradiant trimer molecule to distinguish between long-lived collective dark states and photobleaching events. The population and depopulation kinetics of the dark states in a single molecule follow power-law statistics over 5 orders of magnitude in time. This result is consistent with the formation of a radical unit via electron tunneling to a time-varying distribution of trapping sites in the surrounding polymer matrix. We furthermore demonstrate that this radicalization process forms the dominant pathway for molecular photobleaching.

Developing a Multi-Dimensional Hydrodynamics Code with Astrochemical Reactions

NASA Astrophysics Data System (ADS)

Kwak, Kyujin; Yang, Seungwon

2015-08-01

The Atacama Large Millimeter/submillimeter Array (ALMA) revealed high resolution molecular lines some of which are still unidentified yet. Because formation of these astrochemical molecules has been seldom studied in traditional chemistry, observations of new molecular lines drew a lot of attention from not only astronomers but also chemists both experimental and theoretical. Theoretical calculations for the formation of these astrochemical molecules have been carried out providing reaction rates for some important molecules, and some of theoretical predictions have been measured in laboratories. The reaction rates for the astronomically important molecules are now collected to form databases some of which are publically available. By utilizing these databases, we develop a multi-dimensional hydrodynamics code that includes the reaction rates of astrochemical molecules. Because this type of hydrodynamics code is able to trace the molecular formation in a non-equilibrium fashion, it is useful to study the formation history of these molecules that affects the spatial distribution of some specific molecules. We present the development procedure of this code and some test problems in order to verify and validate the developed code.

Identifying pathways affected by cancer mutations.

PubMed

Iengar, Prathima

2017-12-16

Mutations in 15 cancers, sourced from the COSMIC Whole Genomes database, and 297 human pathways, arranged into pathway groups based on the processes they orchestrate, and sourced from the KEGG pathway database, have together been used to identify pathways affected by cancer mutations. Genes studied in ≥15, and mutated in ≥10 samples of a cancer have been considered recurrently mutated, and pathways with recurrently mutated genes have been considered affected in the cancer. Novel doughnut plots have been presented which enable visualization of the extent to which pathways and genes, in each pathway group, are targeted, in each cancer. The 'organismal systems' pathway group (including organism-level pathways; e.g., nervous system) is the most targeted, more than even the well-recognized signal transduction, cell-cycle and apoptosis, and DNA repair pathway groups. The important, yet poorly-recognized, role played by the group merits attention. Pathways affected in ≥7 cancers yielded insights into processes affected. Copyright © 2017 Elsevier Inc. All rights reserved.

SInCRe—structural interactome computational resource for Mycobacterium tuberculosis

PubMed Central

Metri, Rahul; Hariharaputran, Sridhar; Ramakrishnan, Gayatri; Anand, Praveen; Raghavender, Upadhyayula S.; Ochoa-Montaño, Bernardo; Higueruelo, Alicia P.; Sowdhamini, Ramanathan; Chandra, Nagasuma R.; Blundell, Tom L.; Srinivasan, Narayanaswamy

2015-01-01

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein–protein and protein–small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein–protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host–pathogen protein–protein interactions. Together they provide prerequisites for identification of off-target binding. Database URL: http://proline.biochem.iisc.ernet.in/sincre PMID:26130660

miRSponge: a manually curated database for experimentally supported miRNA sponges and ceRNAs.

PubMed

Wang, Peng; Zhi, Hui; Zhang, Yunpeng; Liu, Yue; Zhang, Jizhou; Gao, Yue; Guo, Maoni; Ning, Shangwei; Li, Xia

2015-01-01

In this study, we describe miRSponge, a manually curated database, which aims at providing an experimentally supported resource for microRNA (miRNA) sponges. Recent evidence suggests that miRNAs are themselves regulated by competing endogenous RNAs (ceRNAs) or 'miRNA sponges' that contain miRNA binding sites. These competitive molecules can sequester miRNAs to prevent them interacting with their natural targets to play critical roles in various biological and pathological processes. It has become increasingly important to develop a high quality database to record and store ceRNA data to support future studies. To this end, we have established the experimentally supported miRSponge database that contains data on 599 miRNA-sponge interactions and 463 ceRNA relationships from 11 species following manual curating from nearly 1200 published articles. Database classes include endogenously generated molecules including coding genes, pseudogenes, long non-coding RNAs and circular RNAs, along with exogenously introduced molecules including viral RNAs and artificial engineered sponges. Approximately 70% of the interactions were identified experimentally in disease states. miRSponge provides a user-friendly interface for convenient browsing, retrieval and downloading of dataset. A submission page is also included to allow researchers to submit newly validated miRNA sponge data. Database URL: http://www.bio-bigdata.net/miRSponge. © The Author(s) 2015. Published by Oxford University Press.

miRSponge: a manually curated database for experimentally supported miRNA sponges and ceRNAs

PubMed Central

Wang, Peng; Zhi, Hui; Zhang, Yunpeng; Liu, Yue; Zhang, Jizhou; Gao, Yue; Guo, Maoni; Ning, Shangwei; Li, Xia

2015-01-01

In this study, we describe miRSponge, a manually curated database, which aims at providing an experimentally supported resource for microRNA (miRNA) sponges. Recent evidence suggests that miRNAs are themselves regulated by competing endogenous RNAs (ceRNAs) or ‘miRNA sponges’ that contain miRNA binding sites. These competitive molecules can sequester miRNAs to prevent them interacting with their natural targets to play critical roles in various biological and pathological processes. It has become increasingly important to develop a high quality database to record and store ceRNA data to support future studies. To this end, we have established the experimentally supported miRSponge database that contains data on 599 miRNA-sponge interactions and 463 ceRNA relationships from 11 species following manual curating from nearly 1200 published articles. Database classes include endogenously generated molecules including coding genes, pseudogenes, long non-coding RNAs and circular RNAs, along with exogenously introduced molecules including viral RNAs and artificial engineered sponges. Approximately 70% of the interactions were identified experimentally in disease states. miRSponge provides a user-friendly interface for convenient browsing, retrieval and downloading of dataset. A submission page is also included to allow researchers to submit newly validated miRNA sponge data. Database URL: http://www.bio-bigdata.net/miRSponge. PMID:26424084

Design of nucleic acid strands with long low-barrier folding pathways.

PubMed

Condon, Anne; Kirkpatrick, Bonnie; Maňuch, Ján

2017-01-01

A major goal of natural computing is to design biomolecules, such as nucleic acid sequences, that can be used to perform computations. We design sequences of nucleic acids that are "guaranteed" to have long folding pathways relative to their length. This particular sequences with high probability follow low-barrier folding pathways that visit a large number of distinct structures. Long folding pathways are interesting, because they demonstrate that natural computing can potentially support long and complex computations. Formally, we provide the first scalable designs of molecules whose low-barrier folding pathways, with respect to a simple, stacked pair energy model, grow superlinearly with the molecule length, but for which all significantly shorter alternative folding pathways have an energy barrier that is [Formula: see text] times that of the low-barrier pathway for any [Formula: see text] and a sufficiently long sequence.

Identification of small molecules capable of regulating conformational changes of telomeric G-quadruplex

NASA Astrophysics Data System (ADS)

Chen, Shuo-Bin; Liu, Guo-Cai; Gu, Lian-Quan; Huang, Zhi-Shu; Tan, Jia-Heng

2018-02-01

Design of small molecules targeted at human telomeric G-quadruplex DNA is an extremely active research area. Interestingly, the telomeric G-quadruplex is a highly polymorphic structure. Changes in its conformation upon small molecule binding may be a powerful method to achieve a desired biological effect. However, the rational development of small molecules capable of regulating conformational change of telomeric G-quadruplex structures is still challenging. In this study, we developed a reliable ligand-based pharmacophore model based on isaindigotone derivatives with conformational change activity toward telomeric G-quadruplex DNA. Furthermore, virtual screening of database was conducted using this pharmacophore model and benzopyranopyrimidine derivatives in the database were identified as a strong inducer of the telomeric G-quadruplex DNA conformation, transforming it from hybrid-type structure to parallel structure.

Investigational therapies up to Phase II which target PDGF receptors: potential anti-cancer therapeutics.

PubMed

Arrondeau, Jennifer; Huillard, Olivier; Tlemsani, Camille; Cessot, Anatole; Boudou-Rouquette, Pascaline; Blanchet, Benoit; Thomas-Schoemann, Audrey; Vidal, Michel; Tigaud, Jean-Marie; Durand, Jean-Philippe; Alexandre, Jerome; Goldwasser, Francois

2015-05-01

The platelet-derived growth factor receptor (PDGFR) pathway has important functions in cell growth and, by overexpression or mutation, could also be a driver for tumor development. Moreover, PDGFR is expressed in a tumoral microenvironment and could promote tumorigenesis. With these biological considerations, the PDGFR pathway could be an interesting target for therapeutics. Currently, there are many molecules under development that target the PDGFR pathway in different types of cancer. In this review, the authors report the different molecules under development, as well as those approved albeit briefly, which inhibit the PDGFR pathway. Furthermore, the authors summarize their specificities, their toxicities, and their development. Currently, most PDGFR kinase inhibitors are multikinase inhibitors and therefore do not simply target the PDGFR pathway. The development of more specific PDGFR inhibitors could improve drug efficacy. Moreover, selecting tumors harboring mutations or amplifications of PDGFR could improve outcomes associated with the use of these molecules. The authors believe that new technologies, such as kinome arrays or pharmacologic assays, could be of benefit to understanding resistance mechanisms and develop more selective PDGFR inhibitors.

THE ADVERSE OUTCOME PATHWAY (AOP) FRAMEWORK: A FRAMEWORK FOR ORGANIZING BIOLOGICAL KNOWLEDGE LEADING TO HEALTH RISKS.

EPA Science Inventory

An Adverse Outcome Pathway (AOP) represents the organization of current and newly acquired knowledge of biological pathways. These pathways contain a series of nodes (Key Events, KEs) that when sufficiently altered influence the next node on the pathway, beginning from an Molecul...

Global Metabolic Reconstruction and Metabolic Gene Evolution in the Cattle Genome

PubMed Central

Kim, Woonsu; Park, Hyesun; Seo, Seongwon

2016-01-01

The sequence of cattle genome provided a valuable opportunity to systematically link genetic and metabolic traits of cattle. The objectives of this study were 1) to reconstruct genome-scale cattle-specific metabolic pathways based on the most recent and updated cattle genome build and 2) to identify duplicated metabolic genes in the cattle genome for better understanding of metabolic adaptations in cattle. A bioinformatic pipeline of an organism for amalgamating genomic annotations from multiple sources was updated. Using this, an amalgamated cattle genome database based on UMD_3.1, was created. The amalgamated cattle genome database is composed of a total of 33,292 genes: 19,123 consensus genes between NCBI and Ensembl databases, 8,410 and 5,493 genes only found in NCBI or Ensembl, respectively, and 266 genes from NCBI scaffolds. A metabolic reconstruction of the cattle genome and cattle pathway genome database (PGDB) was also developed using Pathway Tools, followed by an intensive manual curation. The manual curation filled or revised 68 pathway holes, deleted 36 metabolic pathways, and added 23 metabolic pathways. Consequently, the curated cattle PGDB contains 304 metabolic pathways, 2,460 reactions including 2,371 enzymatic reactions, and 4,012 enzymes. Furthermore, this study identified eight duplicated genes in 12 metabolic pathways in the cattle genome compared to human and mouse. Some of these duplicated genes are related with specific hormone biosynthesis and detoxifications. The updated genome-scale metabolic reconstruction is a useful tool for understanding biology and metabolic characteristics in cattle. There has been significant improvements in the quality of cattle genome annotations and the MetaCyc database. The duplicated metabolic genes in the cattle genome compared to human and mouse implies evolutionary changes in the cattle genome and provides a useful information for further research on understanding metabolic adaptations of cattle. PMID:26992093

Advancing Biological Understanding and Therapeutics Discovery with Small Molecule Probes

PubMed Central

Schreiber, Stuart L.; Kotz, Joanne D.; Li, Min; Aubé, Jeffrey; Austin, Christopher P.; Reed, John C.; Rosen, Hugh; White, E. Lucile; Sklar, Larry A.; Lindsley, Craig W.; Alexander, Benjamin R.; Bittker, Joshua A.; Clemons, Paul A.; de Souza, Andrea; Foley, Michael A.; Palmer, Michelle; Shamji, Alykhan F.; Wawer, Mathias J.; McManus, Owen; Wu, Meng; Zou, Beiyan; Yu, Haibo; Golden, Jennifer E.; Schoenen, Frank J.; Simeonov, Anton; Jadhav, Ajit; Jackson, Michael R.; Pinkerton, Anthony B.; Chung, Thomas D.Y.; Griffin, Patrick R.; Cravatt, Benjamin F.; Hodder, Peter S.; Roush, William R.; Roberts, Edward; Chung, Dong-Hoon; Jonsson, Colleen B.; Noah, James W.; Severson, William E.; Ananthan, Subramaniam; Edwards, Bruce; Oprea, Tudor I.; Conn, P. Jeffrey; Hopkins, Corey R.; Wood, Michael R.; Stauffer, Shaun R.; Emmitte, Kyle A.

2015-01-01

Small-molecule probes can illuminate biological processes and aid in the assessment of emerging therapeutic targets by perturbing biological systems in a manner distinct from other experimental approaches. Despite the tremendous promise of chemical tools for investigating biology and disease, small-molecule probes were unavailable for most targets and pathways as recently as a decade ago. In 2005, the U.S. National Institutes of Health launched the decade-long Molecular Libraries Program with the intent of innovating in and broadening access to small-molecule science. This Perspective describes how novel small-molecule probes identified through the program are enabling the exploration of biological pathways and therapeutic hypotheses not otherwise testable. These experiences illustrate how small-molecule probes can help bridge the chasm between biological research and the development of medicines, but also highlight the need to innovate the science of therapeutic discovery. PMID:26046436

Long-Peptide Cross-Presentation by Human Dendritic Cells Occurs in Vacuoles by Peptide Exchange on Nascent MHC Class I Molecules.

PubMed

Ma, Wenbin; Zhang, Yi; Vigneron, Nathalie; Stroobant, Vincent; Thielemans, Kris; van der Bruggen, Pierre; Van den Eynde, Benoît J

2016-02-15

Cross-presentation enables dendritic cells to present on their MHC class I molecules antigenic peptides derived from exogenous material, through a mechanism that remains partly unclear. It is particularly efficient with long peptides, which are used in cancer vaccines. We studied the mechanism of long-peptide cross-presentation using human dendritic cells and specific CTL clones against melanoma Ags gp100 and Melan-A/MART1. We found that cross-presentation of those long peptides does not depend on the proteasome or the transporter associated with Ag processing, and therefore follows a vacuolar pathway. We also observed that it makes use of newly synthesized MHC class I molecules, through peptide exchange in vesicles distinct from the endoplasmic reticulum and classical secretory pathway, in an SEC22b- and CD74-independent manner. Our results indicate a nonclassical secretion pathway followed by nascent HLA-I molecules that are used for cross-presentation of those long melanoma peptides in the vacuolar pathway. Our results may have implications for the development of vaccines based on long peptides. Copyright © 2016 by The American Association of Immunologists, Inc.

Enhancement of methanol resistance of Yarrowia lipolytica lipase 2 using β-cyclodextrin as an additive: Insights from experiments and molecular dynamics simulation.

PubMed

Cao, Hao; Jiang, Yang; Zhang, Haiyang; Nie, Kaili; Lei, Ming; Deng, Li; Wang, Fang; Tan, Tianwei

2017-01-01

The methanol resistance of lipase is a critical parameter in enzymatic biodiesel production. In the present work, the methanol resistance of Yarrowia lipolytica Lipase 2 (YLLIP2) was significantly improved using β-cyclodextrin (β-CD) as an additive. According to the results, YLLIP2 with β-CD exhibited approximately 7000U/mg specific activity in 30wt% methanol for 60min compared with no activity without β-CD under the same conditions. Molecular dynamics (MD) simulation results indicated that the β-CD molecules weakened the conformational change of YLLIP2 and maintained a semi-open state of the lid by overcoming the interference caused by methanol molecules. Furthermore, the β-CD molecule could directly stabilize "pathway" regions (e.g., Asp61-Asp67) and indirectly stabilize "pathway" regions (e.g., Gly44-Phe50) by forming hydrogen bonds with "pathway" regions and nearby "pathway" regions, respectively. The regions stabilized by the β-CD molecule then prevented the closure of active pockets, thus retaining the enzymatic activity of YLLIP2 with β-CD in methanol solvent. Copyright © 2016. Published by Elsevier Inc.

cPath: open source software for collecting, storing, and querying biological pathways

PubMed Central

Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris

2006-01-01

Background Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. Results We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. Conclusion cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling. PMID:17101041

Integrated Bio-Entity Network: A System for Biological Knowledge Discovery

PubMed Central

Bell, Lindsey; Chowdhary, Rajesh; Liu, Jun S.; Niu, Xufeng; Zhang, Jinfeng

2011-01-01

A significant part of our biological knowledge is centered on relationships between biological entities (bio-entities) such as proteins, genes, small molecules, pathways, gene ontology (GO) terms and diseases. Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places. Most of such information is buried in scientific literature as unstructured text. Organizing heterogeneous information in a structured form not only facilitates study of biological systems using integrative approaches, but also allows discovery of new knowledge in an automatic and systematic way. In this study, we performed a large scale integration of bio-entity relationship information from both databases containing manually annotated, structured information and automatic information extraction of unstructured text in scientific literature. The relationship information we integrated in this study includes protein–protein interactions, protein/gene regulations, protein–small molecule interactions, protein–GO relationships, protein–pathway relationships, and pathway–disease relationships. The relationship information is organized in a graph data structure, named integrated bio-entity network (IBN), where the vertices are the bio-entities and edges represent their relationships. Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks. We designed breadth-first search with pruning (BFSP) and most probable path (MPP) algorithms to automatically generate hypotheses—the indirect relationships with high probabilities in the network. We show that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs. PMID:21738677

Platelet Activating Factor Receptor Activation Improves siRNA Uptake and RNAi Responses in Well-differentiated Airway Epithelia

PubMed Central

Krishnamurthy, Sateesh; Behlke, Mark A; Apicella, Michael A; McCray, Paul B; Davidson, Beverly L

2014-01-01

Well-differentiated human airway epithelia present formidable barriers to efficient siRNA delivery. We previously reported that treatment of airway epithelia with specific small molecules improves oligonucleotide uptake and facilitates RNAi responses. Here, we exploited the platelet activating factor receptor (PAFR) pathway, utilized by specific bacteria to transcytose into epithelia, as a trigger for internalization of Dicer-substrate siRNAs (DsiRNA). PAFR is a G-protein coupled receptor which can be engaged and activated by phosphorylcholine residues on the lipooligosaccharide (LOS) of nontypeable Haemophilus influenzae and the teichoic acid of Streptococcus pneumoniae as well as by its natural ligand, platelet activating factor (PAF). When well-differentiated airway epithelia were simultaneously treated with either nontypeable Haemophilus influenzae LOS or PAF and transduced with DsiRNA formulated with the peptide transductin, we observed silencing of both endogenous and exogenous targets. PAF receptor antagonists prevented LOS or PAF-assisted DsiRNA silencing, demonstrating that ligand engagement of PAFR is essential for this process. Additionally, PAF-assisted DsiRNA transfection decreased CFTR protein expression and function and reduced exogenous viral protein levels and titer in human airway epithelia. Treatment with spiperone, a small molecule identified using the Connectivity map database to correlate gene expression changes in response to drug treatment with those associated with PAFR stimulation, also induced silencing. These results suggest that the signaling pathway activated by PAFR binding can be manipulated to facilitate siRNA entry and function in difficult to transfect well-differentiated airway epithelial cells. PMID:25025465

Modulation of the Kynurenine Pathway for the Potential Treatment of Neurodegenerative Diseases

NASA Astrophysics Data System (ADS)

Courtney, Stephen; Scheel, Andreas

Modulation of tryptophan metabolism and in particular the kynurenine pathway is of considerable interest in the discovery of potential new treatments for neurodegenerative diseases. A number of small molecule inhibitors of the kynurenine metabolic pathway enzymes have been identified over recent years; a summary of these and their utility has been reviewed in this chapter. In particular, inhibitors of kynurenine monooxygenase represent an opportunity to develop a therapy for Huntington's disease; progress in the optimization of small molecule inhibitors of this enzyme is also described.

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

PubMed

Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia

2015-01-01

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.

BioWarehouse: a bioinformatics database warehouse toolkit

PubMed Central

Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David WJ; Tenenbaum, Jessica D; Karp, Peter D

2006-01-01

Background This article addresses the problem of interoperation of heterogeneous bioinformatics databases. Results We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. Conclusion BioWarehouse embodies significant progress on the database integration problem for bioinformatics. PMID:16556315

BioWarehouse: a bioinformatics database warehouse toolkit.

PubMed

Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David W J; Tenenbaum, Jessica D; Karp, Peter D

2006-03-23

This article addresses the problem of interoperation of heterogeneous bioinformatics databases. We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. BioWarehouse embodies significant progress on the database integration problem for bioinformatics.

Reversion of antibiotic resistance in Mycobacterium tuberculosis by spiroisoxazoline SMARt-420.

PubMed

Blondiaux, Nicolas; Moune, Martin; Desroses, Matthieu; Frita, Rosangela; Flipo, Marion; Mathys, Vanessa; Soetaert, Karine; Kiass, Mehdi; Delorme, Vincent; Djaout, Kamel; Trebosc, Vincent; Kemmer, Christian; Wintjens, René; Wohlkönig, Alexandre; Antoine, Rudy; Huot, Ludovic; Hot, David; Coscolla, Mireia; Feldmann, Julia; Gagneux, Sebastien; Locht, Camille; Brodin, Priscille; Gitzinger, Marc; Déprez, Benoit; Willand, Nicolas; Baulard, Alain R

2017-03-17

Antibiotic resistance is one of the biggest threats to human health globally. Alarmingly, multidrug-resistant and extensively drug-resistant Mycobacterium tuberculosis have now spread worldwide. Some key antituberculosis antibiotics are prodrugs, for which resistance mechanisms are mainly driven by mutations in the bacterial enzymatic pathway required for their bioactivation. We have developed drug-like molecules that activate a cryptic alternative bioactivation pathway of ethionamide in M. tuberculosis , circumventing the classic activation pathway in which resistance mutations have now been observed. The first-of-its-kind molecule, named SMARt-420 (Small Molecule Aborting Resistance), not only fully reverses ethionamide-acquired resistance and clears ethionamide-resistant infection in mice, it also increases the basal sensitivity of bacteria to ethionamide. Copyright © 2017, American Association for the Advancement of Science.

Using augmented reality to teach and learn biochemistry.

PubMed

Vega Garzón, Juan Carlos; Magrini, Marcio Luiz; Galembeck, Eduardo

2017-09-01

Understanding metabolism and metabolic pathways constitutes one of the central aims for students of biological sciences. Learning metabolic pathways should be focused on the understanding of general concepts and core principles. New technologies such Augmented Reality (AR) have shown potential to improve assimilation of biochemistry abstract concepts because students can manipulate 3D molecules in real time. Here we describe an application named Augmented Reality Metabolic Pathways (ARMET), which allowed students to visualize the 3D molecular structure of substrates and products, thus perceiving changes in each molecule. The structural modification of molecules shows students the flow and exchange of compounds and energy through metabolism. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(5):417-420, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

In silico analysis of expressed sequence tags from Trichostrongylus vitrinus (Nematoda): comparison of the automated ESTExplorer workflow platform with conventional database searches.

PubMed

Nagaraj, Shivashankar H; Gasser, Robin B; Nisbet, Alasdair J; Ranganathan, Shoba

2008-01-01

The analysis of expressed sequence tags (EST) offers a rapid and cost effective approach to elucidate the transcriptome of an organism, but requires several computational methods for assembly and annotation. Researchers frequently analyse each step manually, which is laborious and time consuming. We have recently developed ESTExplorer, a semi-automated computational workflow system, in order to achieve the rapid analysis of EST datasets. In this study, we evaluated EST data analysis for the parasitic nematode Trichostrongylus vitrinus (order Strongylida) using ESTExplorer, compared with database matching alone. We functionally annotated 1776 ESTs obtained via suppressive-subtractive hybridisation from T. vitrinus, an important parasitic trichostrongylid of small ruminants. Cluster and comparative genomic analyses of the transcripts using ESTExplorer indicated that 290 (41%) sequences had homologues in Caenorhabditis elegans, 329 (42%) in parasitic nematodes, 202 (28%) in organisms other than nematodes, and 218 (31%) had no significant match to any sequence in the current databases. Of the C. elegans homologues, 90 were associated with 'non-wildtype' double-stranded RNA interference (RNAi) phenotypes, including embryonic lethality, maternal sterility, sterile progeny, larval arrest and slow growth. We could functionally classify 267 (38%) sequences using the Gene Ontologies (GO) and establish pathway associations for 230 (33%) sequences using the Kyoto Encyclopedia of Genes and Genomes (KEGG). Further examination of this EST dataset revealed a number of signalling molecules, proteases, protease inhibitors, enzymes, ion channels and immune-related genes. In addition, we identified 40 putative secreted proteins that could represent potential candidates for developing novel anthelmintics or vaccines. We further compared the automated EST sequence annotations, using ESTExplorer, with database search results for individual T. vitrinus ESTs. ESTExplorer reliably and rapidly annotated 301 ESTs, with pathway and GO information, eliminating 60 low quality hits from database searches. We evaluated the efficacy of ESTExplorer in analysing EST data, and demonstrate that computational tools can be used to accelerate the process of gene discovery in EST sequencing projects. The present study has elucidated sets of relatively conserved and potentially novel genes for biological investigation, and the annotated EST set provides further insight into the molecular biology of T. vitrinus, towards the identification of novel drug targets.

Inhibitor of PI3K/Akt Signaling Pathway Small Molecule Promotes Motor Neuron Differentiation of Human Endometrial Stem Cells Cultured on Electrospun Biocomposite Polycaprolactone/Collagen Scaffolds.

PubMed

Ebrahimi-Barough, Somayeh; Hoveizi, Elham; Yazdankhah, Meysam; Ai, Jafar; Khakbiz, Mehrdad; Faghihi, Faezeh; Tajerian, Roksana; Bayat, Neda

2017-05-01

Small molecules as useful chemical tools can affect cell differentiation and even change cell fate. It is demonstrated that LY294002, a small molecule inhibitor of phosphatidylinositol 3-kinase (PI3K)/Akt signal pathway, can inhibit proliferation and promote neuronal differentiation of mesenchymal stem cells (MSCs). The purpose of this study was to investigate the differentiation effect of Ly294002 small molecule on the human endometrial stem cells (hEnSCs) into motor neuron-like cells on polycaprolactone (PCL)/collagen scaffolds. hEnSCs were cultured in a neurogenic inductive medium containing 1 μM LY294002 on the surface of PCL/collagen electrospun fibrous scaffolds. Cell attachment and viability of cells on scaffolds were characterized by scanning electron microscope (SEM) and 3-(4,5-dimethylthiazoyl-2-yl)2,5-diphenyltetrazolium bromide (MTT) assay. The expression of neuron-specific markers was assayed by real-time PCR and immunocytochemistry analysis after 15 days post induction. Results showed that attachment and differentiation of hEnSCs into motor neuron-like cells on the scaffolds with Ly294002 small molecule were higher than that of the cells on tissue culture plates as control group. In conclusion, PCL/collagen electrospun scaffolds with Ly294002 have potential for being used in neural tissue engineering because of its bioactive and three-dimensional structure which enhances viability and differentiation of hEnSCs into neurons through inhibition of the PI3K/Akt pathway. Thus, manipulation of this pathway by small molecules can enhance neural differentiation.

An Electrostatic Funnel in the GABA-Binding Pathway

PubMed Central

Lightstone, Felice C.

2016-01-01

The γ-aminobutyric acid type A receptor (GABAA-R) is a major inhibitory neuroreceptor that is activated by the binding of GABA. The structure of the GABAA-R is well characterized, and many of the binding site residues have been identified. However, most of these residues are obscured behind the C-loop that acts as a cover to the binding site. Thus, the mechanism by which the GABA molecule recognizes the binding site, and the pathway it takes to enter the binding site are both unclear. Through the completion and detailed analysis of 100 short, unbiased, independent molecular dynamics simulations, we have investigated this phenomenon of GABA entering the binding site. In each system, GABA was placed quasi-randomly near the binding site of a GABAA-R homology model, and atomistic simulations were carried out to observe the behavior of the GABA molecules. GABA fully entered the binding site in 19 of the 100 simulations. The pathway taken by these molecules was consistent and non-random; the GABA molecules approach the binding site from below, before passing up behind the C-loop and into the binding site. This binding pathway is driven by long-range electrostatic interactions, whereby the electrostatic field acts as a ‘funnel’ that sweeps the GABA molecules towards the binding site, at which point more specific atomic interactions take over. These findings define a nuanced mechanism whereby the GABAA-R uses the general zwitterionic features of the GABA molecule to identify a potential ligand some 2 nm away from the binding site. PMID:27119953

Adaptive Control Model Reveals Systematic Feedback and Key Molecules in Metabolic Pathway Regulation

PubMed Central

Moffitt, Richard A.; Merrill, Alfred H.; Wang, May D.

2011-01-01

Abstract Robust behavior in metabolic pathways resembles stabilized performance in systems under autonomous control. This suggests we can apply control theory to study existing regulation in these cellular networks. Here, we use model-reference adaptive control (MRAC) to investigate the dynamics of de novo sphingolipid synthesis regulation in a combined theoretical and experimental case study. The effects of serine palmitoyltransferase over-expression on this pathway are studied in vitro using human embryonic kidney cells. We report two key results from comparing numerical simulations with observed data. First, MRAC simulations of pathway dynamics are comparable to simulations from a standard model using mass action kinetics. The root-sum-square (RSS) between data and simulations in both cases differ by less than 5%. Second, MRAC simulations suggest systematic pathway regulation in terms of adaptive feedback from individual molecules. In response to increased metabolite levels available for de novo sphingolipid synthesis, feedback from molecules along the main artery of the pathway is regulated more frequently and with greater amplitude than from other molecules along the branches. These biological insights are consistent with current knowledge while being new that they may guide future research in sphingolipid biology. In summary, we report a novel approach to study regulation in cellular networks by applying control theory in the context of robust metabolic pathways. We do this to uncover potential insight into the dynamics of regulation and the reverse engineering of cellular networks for systems biology. This new modeling approach and the implementation routines designed for this case study may be extended to other systems. Supplementary Material is available at www.liebertonline.com/cmb. PMID:21314456

miRPathDB: a new dictionary on microRNAs and target pathways.

PubMed

Backes, Christina; Kehl, Tim; Stöckel, Daniel; Fehlmann, Tobias; Schneider, Lara; Meese, Eckart; Lenhof, Hans-Peter; Keller, Andreas

2017-01-04

In the last decade, miRNAs and their regulatory mechanisms have been intensively studied and many tools for the analysis of miRNAs and their targets have been developed. We previously presented a dictionary on single miRNAs and their putative target pathways. Since then, the number of miRNAs has tripled and the knowledge on miRNAs and targets has grown substantially. This, along with changes in pathway resources such as KEGG, leads to an improved understanding of miRNAs, their target genes and related pathways. Here, we introduce the miRNA Pathway Dictionary Database (miRPathDB), freely accessible at https://mpd.bioinf.uni-sb.de/ With the database we aim to complement available target pathway web-servers by providing researchers easy access to the information which pathways are regulated by a miRNA, which miRNAs target a pathway and how specific these regulations are. The database contains a large number of miRNAs (2595 human miRNAs), different miRNA target sets (14 773 experimentally validated target genes as well as 19 281 predicted targets genes) and a broad selection of functional biochemical categories (KEGG-, WikiPathways-, BioCarta-, SMPDB-, PID-, Reactome pathways, functional categories from gene ontology (GO), protein families from Pfam and chromosomal locations totaling 12 875 categories). In addition to Homo sapiens, also Mus musculus data are stored and can be compared to human target pathways. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of some novel pyrazolo[1,5-a]pyrimidine derivatives as InhA inhibitors through pharmacophore-based virtual screening and molecular docking.

PubMed

Modi, Palmi; Patel, Shivani; Chhabria, Mahesh T

2018-05-04

The InhA inhibitors play key role in mycolic acid synthesis by preventing the fatty acid biosynthesis pathway. In this present article, Pharmacophore modelling and molecular docking study followed by in silico virtual screening could be considered as effective strategy to identify newer enoyl-ACP reductase inhibitors. Pyrrolidine carboxamide derivatives were opted to generate pharmacophore models using HypoGen algorithm in Discovery studio 2.1. Further it was employed to screen Zinc and Minimaybridge databases to identify and design newer potent hit molecules. The retrieved newer hits were further evaluated for their drug likeliness and docked against enoyl acyl carrier protein reductase. Here, novel pyrazolo[1,5-a]pyrimidine analogues were designed and synthesized with good yields. Structural elucidation of synthesized final molecules was perform through IR, MASS, 1 H-NMR, 13 C-NMR spectroscopy and further tested for its in vitro anti-tubercular activity against H37Rv strain using Microplate Alamar blue assay (MABA) method. Most of the synthesized compounds displayed strong anti-tubercular activities. Further, these potent compounds were gauged for MDR-TB, XDR-TB and cytotoxic study.

Wnt pathway curation using automated natural language processing: combining statistical methods with partial and full parse for knowledge extraction.

PubMed

Santos, Carlos; Eggle, Daniela; States, David J

2005-04-15

Wnt signaling is a very active area of research with highly relevant publications appearing at a rate of more than one per day. Building and maintaining databases describing signal transduction networks is a time-consuming and demanding task that requires careful literature analysis and extensive domain-specific knowledge. For instance, more than 50 factors involved in Wnt signal transduction have been identified as of late 2003. In this work we describe a natural language processing (NLP) system that is able to identify references to biological interaction networks in free text and automatically assembles a protein association and interaction map. A 'gold standard' set of names and assertions was derived by manual scanning of the Wnt genes website (http://www.stanford.edu/~rnusse/wntwindow.html) including 53 interactions involved in Wnt signaling. This system was used to analyze a corpus of peer-reviewed articles related to Wnt signaling including 3369 Pubmed and 1230 full text papers. Names for key Wnt-pathway associated proteins and biological entities are identified using a chi-squared analysis of noun phrases over-represented in the Wnt literature as compared to the general signal transduction literature. Interestingly, we identified several instances where generic terms were used on the website when more specific terms occur in the literature, and one typographic error on the Wnt canonical pathway. Using the named entity list and performing an exhaustive assertion extraction of the corpus, 34 of the 53 interactions in the 'gold standard' Wnt signaling set were successfully identified (64% recall). In addition, the automated extraction found several interactions involving key Wnt-related molecules which were missing or different from those in the canonical diagram, and these were confirmed by manual review of the text. These results suggest that a combination of NLP techniques for information extraction can form a useful first-pass tool for assisting human annotation and maintenance of signal pathway databases. The pipeline software components are freely available on request to the authors. dstates@umich.edu http://stateslab.bioinformatics.med.umich.edu/software.html.

Solvent effects on the ultrafast nonradiative deactivation mechanisms of thymine in aqueous solution: Excited-state QM/MM molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Nakayama, Akira; Arai, Gaku; Yamazaki, Shohei; Taketsugu, Tetsuya

2013-12-01

On-the-fly excited-state quantum mechanics/molecular mechanics molecular dynamics (QM/MM-MD) simulations of thymine in aqueous solution are performed to investigate the role of solvent water molecules on the nonradiative deactivation process. The complete active space second-order perturbation theory (CASPT2) method is employed for a thymine molecule as the QM part in order to provide a reliable description of the excited-state potential energies. It is found that, in addition to the previously reported deactivation pathway involving the twisting of the C-C double bond in the pyrimidine ring, another efficient deactivation pathway leading to conical intersections that accompanies the out-of-plane displacement of the carbonyl group is observed in aqueous solution. Decay through this pathway is not observed in the gas phase simulations, and our analysis indicates that the hydrogen bonds with solvent water molecules play a key role in stabilizing the potential energies of thymine in this additional decay pathway.

[Hyponatremia associated with SSRI/NRSI: Descriptive and comparative epidemiological study of the incidence rates of the notified cases from the data of the French National Pharmacovigilance Database and the French National Health Insurance].

PubMed

Revol, R; Rault, C; Polard, E; Bellet, F; Guy, C

2018-06-01

Selective Serotonin Reuptake Inhibitors (SSRIs) and Serotonin-Norepinephrine Reuptake Inhibitors (SNRIs) are frequently prescribed. These antidepressants can potentially induce serious hyponatremia through the SIADH syndrome. That seems to concern all molecules of these classes but the individual risk of each molecule is not well known. The aims of the study were to compare the incidence rate of each molecule in order to identify the existence of molecules more at risk of inducing hyponatremia and to characterize a profile of patients at risk for hyponatremia during a treatment with a SSRI or a SNRI. The cases of hyponatremia under SSRI/SNRI were extracted from the French pharmacovigilance database (BPNV). The exposition to the different SSRIs/SNRIs in the French population was estimated from the French National Health Insurance database (SNIIRAM) using a sampled database (Echantillon Généralistes des Bénéficiaires). The study ran from 01/01/2011 to 31/12/2013. The primary study endpoint was the incidence rate of notifications of the hyponatremia cases in patients treated by SSRI/SNRI and recorded into the BNPV database, related to the average annual number of corresponding treatments initiated during the same period. The number of cases of hyponatremia included in the study was 169 for 3 749 800 adult patients initiating treatment. The incidence rate of cases was 1.64 for 100 000 persons per year (PY). The standardized incidence rates between the different molecules showed no difference except for duloxetine (2.79/100 000 PY p > 0.03). Identified risk factors were age, with a large increase of incidence rate from 75 years old (incidence 12.5 higher) and female gender. Comparison of the incidence rates from spontaneous reports indicates a greater risk of hyponatremia for duloxetine for 2011-2013. This result needs to be confirmed by other studies. The advanced age and female sex are risk factors, irrespective of the molecule. Copyright © 2017 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

The Listeria monocytogenes strain 10403S BioCyc database.

PubMed

Orsi, Renato H; Bergholz, Teresa M; Wiedmann, Martin; Boor, Kathryn J

2015-01-01

Listeria monocytogenes is a food-borne pathogen of humans and other animals. The striking ability to survive several stresses usually used for food preservation makes L. monocytogenes one of the biggest concerns to the food industry, while the high mortality of listeriosis in specific groups of humans makes it a great concern for public health. Previous studies have shown that a regulatory network involving alternative sigma (σ) factors and transcription factors is pivotal to stress survival. However, few studies have evaluated at the metabolic networks controlled by these regulatory mechanisms. The L. monocytogenes BioCyc database uses the strain 10403S as a model. Computer-generated initial annotation for all genes also allowed for identification, annotation and display of predicted reactions and pathways carried out by a single cell. Further ongoing manual curation based on published data as well as database mining for selected genes allowed the more refined annotation of functions, which, in turn, allowed for annotation of new pathways and fine-tuning of previously defined pathways to more L. monocytogenes-specific pathways. Using RNA-Seq data, several transcription start sites and promoter regions were mapped to the 10403S genome and annotated within the database. Additionally, the identification of promoter regions and a comprehensive review of available literature allowed the annotation of several regulatory interactions involving σ factors and transcription factors. The L. monocytogenes 10403S BioCyc database is a new resource for researchers studying Listeria and related organisms. It allows users to (i) have a comprehensive view of all reactions and pathways predicted to take place within the cell in the cellular overview, as well as to (ii) upload their own data, such as differential expression data, to visualize the data in the scope of predicted pathways and regulatory networks and to carry on enrichment analyses using several different annotations available within the database. © The Author(s) 2015. Published by Oxford University Press.

Bioinformatics analysis on molecular mechanism of rheum officinale in treatment of jaundice

NASA Astrophysics Data System (ADS)

Shan, Si; Tu, Jun; Nie, Peng; Yan, Xiaojun

2017-01-01

Objective: To study the molecular mechanism of Rheum officinale in the treatment of Jaundice by building molecular networks and comparing canonical pathways. Methods: Target proteins of Rheum officinale and related genes of Jaundice were searched from Pubchem and Gene databases online respectively. Molecular networks and canonical pathways comparison analyses were performed by Ingenuity Pathway Analysis (IPA). Results: The molecular networks of Rheum officinale and Jaundice were complex and multifunctional. The 40 target proteins of Rheum officinale and 33 Homo sapiens genes of Jaundice were found in databases. There were 19 common pathways both related networks. Rheum officinale could regulate endothelial differentiation, Interleukin-1B (IL-1B) and Tumor Necrosis Factor (TNF) in these pathways. Conclusions: Rheum officinale treat Jaundice by regulating many effective nodes of Apoptotic pathway and cellular immunity related pathways.

Frontier of Epilepsy Research - mTOR signaling pathway

PubMed Central

2011-01-01

Studies of epilepsy have mainly focused on the membrane proteins that control neuronal excitability. Recently, attention has been shifting to intracellular proteins and their interactions, signaling cascades and feedback regulation as they relate to epilepsy. The mTOR (mammalian target of rapamycin) signal transduction pathway, especially, has been suggested to play an important role in this regard. These pathways are involved in major physiological processes as well as in numerous pathological conditions. Here, involvement of the mTOR pathway in epilepsy will be reviewed by presenting; an overview of the pathway, a brief description of key signaling molecules, a summary of independent reports and possible implications of abnormalities of those molecules in epilepsy, a discussion of the lack of experimental data, and questions raised for the understanding its epileptogenic mechanism. PMID:21467839

Distinguishing Signatures of Multipathway Conformational Transitions

NASA Astrophysics Data System (ADS)

Pierse, Christopher A.; Dudko, Olga K.

2017-02-01

The folding and binding of biomolecules into functional conformations are thought to be commonly mediated by multiple pathways rather than a unique route. Yet even in experiments where one can "see" individual conformational transitions, their stochastic nature generally precludes one from determining whether the transitions occurred through one or multiple pathways. We establish model-free, observable signatures in the response of macromolecules to force that unambiguously identify multiple pathways—even when the pathways themselves cannot be resolved. The unified analytical description reveals that, through multiple pathways, the response of molecules to external forces can be shaped in diverse ways, resulting in a rich design space for a tailored biological function already at the single-molecule level.

Theoretical Modeling of Interstellar Chemistry

NASA Technical Reports Server (NTRS)

Charnley, Steven

2009-01-01

The chemistry of complex interstellar organic molecules will be described. Gas phase processes that may build large carbon-chain species in cold molecular clouds will be summarized. Catalytic reactions on grain surfaces can lead to a large variety of organic species, and models of molecule formation by atom additions to multiply-bonded molecules will be presented. The subsequent desorption of these mixed molecular ices can initiate a distinctive organic chemistry in hot molecular cores. The general ion-molecule pathways leading to even larger organics will be outlined. The predictions of this theory will be compared with observations to show how possible organic formation pathways in the interstellar medium may be constrained. In particular, the success of the theory in explaining trends in the known interstellar organics, in predicting recently-detected interstellar molecules, and, just as importantly, non-detections, will be discussed.

Growth and stress response mechanisms underlying post-feeding regenerative organ growth in the Burmese python.

PubMed

Andrew, Audra L; Perry, Blair W; Card, Daren C; Schield, Drew R; Ruggiero, Robert P; McGaugh, Suzanne E; Choudhary, Amit; Secor, Stephen M; Castoe, Todd A

2017-05-02

Previous studies examining post-feeding organ regeneration in the Burmese python (Python molurus bivittatus) have identified thousands of genes that are significantly differentially regulated during this process. However, substantial gaps remain in our understanding of coherent mechanisms and specific growth pathways that underlie these rapid and extensive shifts in organ form and function. Here we addressed these gaps by comparing gene expression in the Burmese python heart, liver, kidney, and small intestine across pre- and post-feeding time points (fasted, one day post-feeding, and four days post-feeding), and by conducting detailed analyses of molecular pathways and predictions of upstream regulatory molecules across these organ systems. Identified enriched canonical pathways and upstream regulators indicate that while downstream transcriptional responses are fairly tissue specific, a suite of core pathways and upstream regulator molecules are shared among responsive tissues. Pathways such as mTOR signaling, PPAR/LXR/RXR signaling, and NRF2-mediated oxidative stress response are significantly differentially regulated in multiple tissues, indicative of cell growth and proliferation along with coordinated cell-protective stress responses. Upstream regulatory molecule analyses identify multiple growth factors, kinase receptors, and transmembrane receptors, both within individual organs and across separate tissues. Downstream transcription factors MYC and SREBF are induced in all tissues. These results suggest that largely divergent patterns of post-feeding gene regulation across tissues are mediated by a core set of higher-level signaling molecules. Consistent enrichment of the NRF2-mediated oxidative stress response indicates this pathway may be particularly important in mediating cellular stress during such extreme regenerative growth.

BioPAX – A community standard for pathway data sharing

PubMed Central

Demir, Emek; Cary, Michael P.; Paley, Suzanne; Fukuda, Ken; Lemer, Christian; Vastrik, Imre; Wu, Guanming; D’Eustachio, Peter; Schaefer, Carl; Luciano, Joanne; Schacherer, Frank; Martinez-Flores, Irma; Hu, Zhenjun; Jimenez-Jacinto, Veronica; Joshi-Tope, Geeta; Kandasamy, Kumaran; Lopez-Fuentes, Alejandra C.; Mi, Huaiyu; Pichler, Elgar; Rodchenkov, Igor; Splendiani, Andrea; Tkachev, Sasha; Zucker, Jeremy; Gopinath, Gopal; Rajasimha, Harsha; Ramakrishnan, Ranjani; Shah, Imran; Syed, Mustafa; Anwar, Nadia; Babur, Ozgun; Blinov, Michael; Brauner, Erik; Corwin, Dan; Donaldson, Sylva; Gibbons, Frank; Goldberg, Robert; Hornbeck, Peter; Luna, Augustin; Murray-Rust, Peter; Neumann, Eric; Reubenacker, Oliver; Samwald, Matthias; van Iersel, Martijn; Wimalaratne, Sarala; Allen, Keith; Braun, Burk; Whirl-Carrillo, Michelle; Dahlquist, Kam; Finney, Andrew; Gillespie, Marc; Glass, Elizabeth; Gong, Li; Haw, Robin; Honig, Michael; Hubaut, Olivier; Kane, David; Krupa, Shiva; Kutmon, Martina; Leonard, Julie; Marks, Debbie; Merberg, David; Petri, Victoria; Pico, Alex; Ravenscroft, Dean; Ren, Liya; Shah, Nigam; Sunshine, Margot; Tang, Rebecca; Whaley, Ryan; Letovksy, Stan; Buetow, Kenneth H.; Rzhetsky, Andrey; Schachter, Vincent; Sobral, Bruno S.; Dogrusoz, Ugur; McWeeney, Shannon; Aladjem, Mirit; Birney, Ewan; Collado-Vides, Julio; Goto, Susumu; Hucka, Michael; Le Novère, Nicolas; Maltsev, Natalia; Pandey, Akhilesh; Thomas, Paul; Wingender, Edgar; Karp, Peter D.; Sander, Chris; Bader, Gary D.

2010-01-01

BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery. PMID:20829833

New spectroscopy in the HITRAN2016 database and its impact on atmospheric retrievals

NASA Astrophysics Data System (ADS)

Gordon, I.; Rothman, L. S.; Kochanov, R. V.; Tan, Y.; Toon, G. C.

2017-12-01

The HITRAN spectroscopic database is a backbone of the interpretation of spectral atmospheric retrievals and is an important input to the radiative transfer codes. The database is serving the atmospheric community for nearly half-a-century with every new edition being released every four years. The most recent release of the database is HITRAN2016 [1]. It consists of line-by-line lists, experimental absorption cross-sections, collision-induced absorption data and aerosol indices of refraction. In this presentation it will be stressed the importance of using the most recent edition of the database in the radiative transfer codes. The line-by-line lists for most of the HITRAN molecules were updated (and two new molecules added) in comparison with the previous compilation HITRAN2012 [2] that has been in use, along with some intermediate updates, since 2012. The extent of the updates ranges from updating a few lines of certain molecules to complete replacements of the lists and introduction of additional isotopologues. In addition, the amount of molecules in cross-sectional part of the database has increased dramatically from nearly 50 to over 300. The molecules covered by the HITRAN database are important in planetary remote sensing, environment monitoring (in particular, biomass burning detection), climate applications, industrial pollution tracking, atrophysics, and more. Taking advantage of the new structure and interface available at www.hitran.org [3] and the HITRAN Application Programming Interface [4] the amount of parameters has also been significantly increased, now incorporating, for instance, non-Voigt line profiles [5]; broadening by gases other than air and "self" [6]; and other phenomena, including line mixing. This is a very important novelty that needs to be properly introduced in the radiative transfer codes in order to advance accurate interpretation of the remote sensing retrievals. This work is supported by the NASA PDART (NNX16AG51G) and AURA (NNX 17AI78G) programs. References[1] I.E. Gordon et al, JQSRT in press (2017) http://doi.org/10.1016/j.jqsrt.2017.06.038. [2] L.S. Rothman et al, JQSRT 130, 4 (2013). [3] C. Hill et al, JQSRT 177, 4 (2016). [4] R.V. Kochanov et al, JQSRT 177, 15 (2016). [5] P. Wcisło et al., JQSRT 177, 75 (2016). [6] J. S. Wilzewski et al., JQSRT 168, 193 (2016).

Database for chemical weapons detection: first results

NASA Astrophysics Data System (ADS)

Bellecci, C.; Gaudio, P.; Gelfusa, M.; Martellucci, S.; Richetta, M.; Ventura, P.; Antonucci, A.; Pasquino, F.; Ricci, V.; Sassolini, A.

2008-10-01

The quick increase of terrorism and asymmetric war is leading towards new needs involving defense and security. Nowadays we have to fight several kind of threats and use of chemical weapons against civil or military objectives is one of the most dangerous. For this reason it is necessary to find equipment, know-how and information that are useful in order to detect and identify dangerous molecules as quickly and far away as possible, so to minimize damage. Lidar/Dial are some of the most powerful optical technologies. Dial technology use two different wavelengths, in order to measure concentration profile of an investigated molecule. For this reason it is needed a "fingerprint" database which consists of an exhaustive collection of absorption coefficients data so to identify each molecule avoiding confusion with interfering ones. Nowadays there is not such a collection of data in scientific and technical literature. We used an FT-IR spectrometer and a CO2 laser source for absorption spectroscopy measurements using cells filled with the investigated molecules. The CO2 source is the transmitter of our DIAL facility. In this way we can make a proper "fingerprint" database necessary to identify dangerous molecules. The CO2 laser has been chosen because it is eye safe and, mainly, because it covers a spectral band where there is good absorption for this kind of molecules. In this paper IR spectra of mustard will be presented and compared to other substances which may interfere producing a false alarm. Methodology, experimental setup and first results are described.

p38 Mitogen-Activated Protein Kinase/Signal Transducer and Activator of Transcription-3 Pathway Signaling Regulates Expression of Inhibitory Molecules in T Cells Activated by HIV-1–Exposed Dendritic Cells

PubMed Central

Che, Karlhans Fru; Shankar, Esaki Muthu; Muthu, Sundaram; Zandi, Sasan; Sigvardsson, Mikael; Hinkula, Jorma; Messmer, Davorka; Larsson, Marie

2012-01-01

Human immunodeficiency virus type 1 (HIV-1) infection enhances the expression of inhibitory molecules on T cells, leading to T-cell impairment. The signaling pathways underlying the regulation of inhibitory molecules and subsequent onset of T-cell impairment remain elusive. We showed that both autologous and allogeneic T cells exposed to HIV-pulsed dendritic cells (DCs) upregulated cytotoxic T-lymphocyte antigen (CTLA-4), tumor-necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL), lymphocyte-activation gene-3 (LAG3), T-cell immunoglobulin mucin-3 (TIM-3), CD160 and certain suppression-associated transcription factors, such as B-lymphocyte induced maturation protein-1 (BLIMP-1), deltex homolog 1 protein (DTX1) and forkhead box P3 (FOXP3), leading to T-cell suppression. This induction was regulated by p38 mitogen-activated protein kinase/signal transducer and activator of transcription-3 (P38MAPK/STAT3) pathways, because their blockade significantly abrogated expression of all the inhibitory molecules studied and a subsequent recovery in T-cell proliferation. Neither interleukin-6 (IL-6) nor IL-10 nor growth factors known to activate STAT3 signaling events were responsible for STAT3 activation. Involvement of the P38MAPK/STAT3 pathways was evident because these proteins had a higher level of phosphorylation in the HIV-1–primed cells. Furthermore, blockade of viral CD4 binding and fusion significantly reduced the negative effects DCs imposed on primed T cells. In conclusion, HIV-1 interaction with DCs modulated their functionality, causing them to trigger the activation of the P38MAPK/STAT3 pathway in T cells, which was responsible for the upregulation of inhibitory molecules. PMID:22777388

A reverse glyoxylate shunt to build a non-native route from C-4 to C-2 in Escherichia coli

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

Mainguet, SE; Gronenberg, LS; Wong, SS

2013-09-01

Most central metabolic pathways such as glycolysis, fatty acid synthesis, and the TCA cycle have complementary pathways that run in the reverse direction to allow flexible storage and utilization of resources. However, the glyoxylate shunt, which allows for the synthesis of four-carbon TCA cycle intermediates from acetyl-CoA, has not been found to be reversible to date. As a result, glucose can only be converted to acetyl-CoA via the decarboxylation of the three-carbon molecule pyruvate in heterotrophs. A reverse glyoxylate shunt (rGS) could be extended into a pathway that converts C-4 carboxylates into two molecules of acetyl-CoA without loss of CO2.more » Here, as a proof of concept, we engineered in Escherichia coli such a pathway to convert malate and succinate to oxaloacetate and two molecules of acetyl-CoA. We introduced ATP-coupled heterologous enzymes at the thermodynamically unfavorable steps to drive the pathway in the desired direction. This synthetic pathway in essence reverses the glyoxylate shunt at the expense of ATP. When integrated with central metabolism, this pathway has the potential to increase the carbon yield of acetate and biofuels from many carbon sources in heterotrophic microorganisms, and could be the basis of novel carbon fixation cycles. (C) 2013 Elsevier Inc. All rights reserved.« less

A reverse glyoxylate shunt to build a non-native route from C4 to C2 in Escherichia coli.

PubMed

Mainguet, Samuel E; Gronenberg, Luisa S; Wong, Sio Si; Liao, James C

2013-09-01

Most central metabolic pathways such as glycolysis, fatty acid synthesis, and the TCA cycle have complementary pathways that run in the reverse direction to allow flexible storage and utilization of resources. However, the glyoxylate shunt, which allows for the synthesis of four-carbon TCA cycle intermediates from acetyl-CoA, has not been found to be reversible to date. As a result, glucose can only be converted to acetyl-CoA via the decarboxylation of the three-carbon molecule pyruvate in heterotrophs. A reverse glyoxylate shunt (rGS) could be extended into a pathway that converts C4 carboxylates into two molecules of acetyl-CoA without loss of CO2. Here, as a proof of concept, we engineered in Escherichia coli such a pathway to convert malate and succinate to oxaloacetate and two molecules of acetyl-CoA. We introduced ATP-coupled heterologous enzymes at the thermodynamically unfavorable steps to drive the pathway in the desired direction. This synthetic pathway in essence reverses the glyoxylate shunt at the expense of ATP. When integrated with central metabolism, this pathway has the potential to increase the carbon yield of acetate and biofuels from many carbon sources in heterotrophic microorganisms, and could be the basis of novel carbon fixation cycles. © 2013 Elsevier Inc. All rights reserved.

c-di-AMP: An Essential Molecule in the Signaling Pathways that Regulate the Viability and Virulence of Gram-Positive Bacteria

PubMed Central

Fahmi, Tazin; Port, Gary C.

2017-01-01

Signal transduction pathways enable organisms to monitor their external environment and adjust gene regulation to appropriately modify their cellular processes. Second messenger nucleotides including cyclic adenosine monophosphate (c-AMP), cyclic guanosine monophosphate (c-GMP), cyclic di-guanosine monophosphate (c-di-GMP), and cyclic di-adenosine monophosphate (c-di-AMP) play key roles in many signal transduction pathways used by prokaryotes and/or eukaryotes. Among the various second messenger nucleotides molecules, c-di-AMP was discovered recently and has since been shown to be involved in cell growth, survival, and regulation of virulence, primarily within Gram-positive bacteria. The cellular level of c-di-AMP is maintained by a family of c-di-AMP synthesizing enzymes, diadenylate cyclases (DACs), and degradation enzymes, phosphodiesterases (PDEs). Genetic manipulation of DACs and PDEs have demonstrated that alteration of c-di-AMP levels impacts both growth and virulence of microorganisms. Unlike other second messenger molecules, c-di-AMP is essential for growth in several bacterial species as many basic cellular functions are regulated by c-di-AMP including cell wall maintenance, potassium ion homeostasis, DNA damage repair, etc. c-di-AMP follows a typical second messenger signaling pathway, beginning with binding to receptor molecules to subsequent regulation of downstream cellular processes. While c-di-AMP binds to specific proteins that regulate pathways in bacterial cells, c-di-AMP also binds to regulatory RNA molecules that control potassium ion channel expression in Bacillus subtilis. c-di-AMP signaling also occurs in eukaryotes, as bacterially produced c-di-AMP stimulates host immune responses during infection through binding of innate immune surveillance proteins. Due to its existence in diverse microorganisms, its involvement in crucial cellular activities, and its stimulating activity in host immune responses, c-di-AMP signaling pathway has become an attractive antimicrobial drug target and therefore has been the focus of intensive study in several important pathogens. PMID:28783096

Cross-talk between estradiol receptor and EGFR/IGF-IR signaling pathways in estrogen-responsive breast cancers: focus on the role and impact of proteoglycans.

PubMed

Skandalis, Spyros S; Afratis, Nikolaos; Smirlaki, Gianna; Nikitovic, Dragana; Theocharis, Achilleas D; Tzanakakis, George N; Karamanos, Nikos K

2014-04-01

In hormone-dependent breast cancer, estrogen receptors are the principal signaling molecules that regulate several cell functions either by the genomic pathway acting directly as transcription factors in the nucleus or by the non-genomic pathway interacting with other receptors and their adjacent pathways like EGFR/IGFR. It is well established in literature that EGFR and IGFR signaling pathways promote cell proliferation and differentiation. Moreover, recent data indicate the cross-talk between ERs and EGFR/IGFR signaling pathways causing a transformation of cell functions as well as deregulation on normal expression pattern of matrix molecules. Specifically, proteoglycans, a major category of extracellular matrix (ECM) and cell surface macromolecules, are modified during malignancy and cause alterations in cancer cell signaling, affecting eventually functional cell properties such as proliferation, adhesion and migration. The on-going strategies to block only one of the above signaling effectors result cancer cells to overcome such inactivation using alternative signaling pathways. In this article, we therefore review the underlying mechanisms in respect to the role of ERs and the involvement of cross-talk between ERs, IGFR and EGFR in breast cancer cell properties and expression of extracellular secreted and cell bound proteoglycans involved in cancer progression. Understanding such signaling pathways may help to establish new potential pharmacological targets in terms of using ECM molecules to design novel anticancer therapies. © 2013. Published by Elsevier B.V. All rights reserved.

The 2015 edition of the GEISA spectroscopic database

NASA Astrophysics Data System (ADS)

Jacquinet-Husson, N.; Armante, R.; Scott, N. A.; Chédin, A.; Crépeau, L.; Boutammine, C.; Bouhdaoui, A.; Crevoisier, C.; Capelle, V.; Boonne, C.; Poulet-Crovisier, N.; Barbe, A.; Chris Benner, D.; Boudon, V.; Brown, L. R.; Buldyreva, J.; Campargue, A.; Coudert, L. H.; Devi, V. M.; Down, M. J.; Drouin, B. J.; Fayt, A.; Fittschen, C.; Flaud, J.-M.; Gamache, R. R.; Harrison, J. J.; Hill, C.; Hodnebrog, Ø.; Hu, S.-M.; Jacquemart, D.; Jolly, A.; Jiménez, E.; Lavrentieva, N. N.; Liu, A.-W.; Lodi, L.; Lyulin, O. M.; Massie, S. T.; Mikhailenko, S.; Müller, H. S. P.; Naumenko, O. V.; Nikitin, A.; Nielsen, C. J.; Orphal, J.; Perevalov, V. I.; Perrin, A.; Polovtseva, E.; Predoi-Cross, A.; Rotger, M.; Ruth, A. A.; Yu, S. S.; Sung, K.; Tashkun, S. A.; Tennyson, J.; Tyuterev, Vl. G.; Vander Auwera, J.; Voronin, B. A.; Makie, A.

2016-09-01

The GEISA database (Gestion et Etude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information) has been developed and maintained by the http://ara.abct.lmd.polytechnique.fr. The "line parameters database" contains 52 molecular species (118 isotopologues) and transitions in the spectral range from 10-6 to 35,877.031 cm-1, representing 5,067,351 entries, against 3,794,297 in GEISA-2011. Among the previously existing molecules, 20 molecular species have been updated. A new molecule (SO3) has been added. HDO, isotopologue of H2O, is now identified as an independent molecular species. Seven new isotopologues have been added to the GEISA-2015 database. The "cross section sub-database" has been enriched by the addition of 43 new molecular species in its infrared part, 4 molecules (ethane, propane, acetone, acetonitrile) are also updated; they represent 3% of the update. A new section is added, in the near-infrared spectral region, involving 7 molecular species: CH3CN, CH3I, CH3O2, H2CO, HO2, HONO, NH3. The "microphysical and optical properties of atmospheric aerosols sub-database" has been updated for the first time since 2003. It contains more than 40 species originating from NCAR and 20 from the http://eodg.atm.ox.ac.uk/ARIA/introduction_nocol.html. As for the previous versions, this new release of GEISA and associated management software facilities are implemented and freely accessible on the http://cds-espri.ipsl.fr/etherTypo/?id=950.

Human Mesenchymal Stem Cell Treatment Normalizes Cortical Gene Expression after Traumatic Brain Injury.

PubMed

Darkazalli, Ali; Vied, Cynthia; Badger, Crystal-Dawn; Levenson, Cathy W

2017-01-01

Traumatic brain injury (TBI) results in a progressive disease state with many adverse and long-term neurological consequences. Mesenchymal stem cells (MSCs) have emerged as a promising cytotherapy and have been previously shown to reduce secondary apoptosis and cognitive deficits associated with TBI. Consistent with the established literature, we observed that systemically administered human MSCs (hMSCs) accumulate with high specificity at the TBI lesion boundary zone known as the penumbra. Substantial work has been done to illuminate the mechanisms by which MSCs, and the bioactive molecules they secrete, exert their therapeutic effect. However, no such work has been published to examine the effect of MSC treatment on gene expression in the brain post-TBI. In the present study, we use high-throughput RNA sequencing (RNAseq) of cortical tissue from the TBI penumbra to assess the molecular effects of both TBI and subsequent treatment with intravenously delivered hMSCs. RNAseq revealed that expression of almost 7000 cortical genes in the penumbra were differentially regulated by TBI. Pathway analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway database revealed that TBI regulated a large number of genes belonging to pathways involved in metabolism, receptor-mediated cell signaling, neuronal plasticity, immune cell recruitment and infiltration, and neurodegenerative disease. Remarkably, hMSC treatment was found to normalize 49% of all genes disrupted by TBI, with notably robust normalization of specific pathways within the categories mentioned above, including neuroactive receptor-ligand interactions (57%), glycolysis and gluconeogenesis (81%), and Parkinson's disease (100%). These data provide evidence in support of the multi-mechanistic nature of stem cell therapy and suggest that hMSC treatment is capable of simultaneously normalizing a wide variety of important molecular pathways that are disrupted by brain injury.

Systematically Studying Kinase Inhibitor Induced Signaling Network Signatures by Integrating Both Therapeutic and Side Effects

PubMed Central

Shao, Hongwei; Peng, Tao; Ji, Zhiwei; Su, Jing; Zhou, Xiaobo

2013-01-01

Substantial effort in recent years has been devoted to analyzing data based large-scale biological networks, which provide valuable insight into the topologies of complex biological networks but are rarely context specific and cannot be used to predict the responses of cell signaling proteins to specific ligands or compounds. In this work, we proposed a novel strategy to investigate kinase inhibitor induced pathway signatures by integrating multiplex data in Library of Integrated Network-based Cellular Signatures (LINCS), e.g. KINOMEscan data and cell proliferation/mitosis imaging data. Using this strategy, we first established a PC9 cell line specific pathway model to investigate the pathway signatures in PC9 cell line when perturbed by a small molecule kinase inhibitor GW843682. This specific pathway revealed the role of PI3K/AKT in modulating the cell proliferation process and the absence of two anti-proliferation links, which indicated a potential mechanism of abnormal expansion in PC9 cell number. Incorporating the pathway model for side effects on primary human hepatocytes, it was used to screen 27 kinase inhibitors in LINCS database and PF02341066, known as Crizotinib, was finally suggested with an optimal concentration 4.6 uM to suppress PC9 cancer cell expansion while avoiding severe damage to primary human hepatocytes. Drug combination analysis revealed that the synergistic effect region can be predicted straightforwardly based on a threshold which is an inherent property of each kinase inhibitor. Furthermore, this integration strategy can be easily extended to other specific cell lines to be a powerful tool for drug screen before clinical trials. PMID:24339888

The Dendritic Cell Major Histocompatibility Complex II (MHC II) Peptidome Derives from a Variety of Processing Pathways and Includes Peptides with a Broad Spectrum of HLA-DM Sensitivity*

PubMed Central

Clement, Cristina C.; Becerra, Aniuska; Yin, Liusong; Zolla, Valerio; Huang, Liling; Merlin, Simone; Follenzi, Antonia; Shaffer, Scott A.; Stern, Lawrence J.; Santambrogio, Laura

2016-01-01

The repertoire of peptides displayed in vivo by MHC II molecules derives from a wide spectrum of proteins produced by different cell types. Although intracellular endosomal processing in dendritic cells and B cells has been characterized for a few antigens, the overall range of processing pathways responsible for generating the MHC II peptidome are currently unclear. To determine the contribution of non-endosomal processing pathways, we eluted and sequenced over 3000 HLA-DR1-bound peptides presented in vivo by dendritic cells. The processing enzymes were identified by reference to a database of experimentally determined cleavage sites and experimentally validated for four epitopes derived from complement 3, collagen II, thymosin β4, and gelsolin. We determined that self-antigens processed by tissue-specific proteases, including complement, matrix metalloproteases, caspases, and granzymes, and carried by lymph, contribute significantly to the MHC II self-peptidome presented by conventional dendritic cells in vivo. Additionally, the presented peptides exhibited a wide spectrum of binding affinity and HLA-DM susceptibility. The results indicate that the HLA-DR1-restricted self-peptidome presented under physiological conditions derives from a variety of processing pathways. Non-endosomal processing enzymes add to the number of epitopes cleaved by cathepsins, altogether generating a wider peptide repertoire. Taken together with HLA-DM-dependent and-independent loading pathways, this ensures that a broad self-peptidome is presented by dendritic cells. This work brings attention to the role of “self-recognition” as a dynamic interaction between dendritic cells and the metabolic/catabolic activities ongoing in every parenchymal organ as part of tissue growth, remodeling, and physiological apoptosis. PMID:26740625

Elucidation of Proton-Assisted Fluxionality in Transition-Metal Oxide Clusters

NASA Astrophysics Data System (ADS)

Ramabhadran, Raghunath O.; Mayhall, Nicholas J.; Becher, Edwin L. Becher, Iii; Chowdhury, Arefin; Raghavachari, Krishnan

2012-06-01

The phenomenon of fluxionality in the reactions of transition-metal oxide clusters provides many opportunities in various industrial and catalytic processes. We present an electronic structure investigation of the fluxionality pathways when anionic W3O6- and Mo3O6- clusters react with three small molecules - water, ammonia and hydrogen sulfide. The presentation features a detailed understanding of (a) how the fluxionality pathway occurs and (b) the various factors that affect the fluxionality pathway - such as the metal, different spin-states and the nature of the non-metal in the reacting small molecule.

ChemBank: a small-molecule screening and cheminformatics resource database.

PubMed

Seiler, Kathleen Petri; George, Gregory A; Happ, Mary Pat; Bodycombe, Nicole E; Carrinski, Hyman A; Norton, Stephanie; Brudz, Steve; Sullivan, John P; Muhlich, Jeremy; Serrano, Martin; Ferraiolo, Paul; Tolliday, Nicola J; Schreiber, Stuart L; Clemons, Paul A

2008-01-01

ChemBank (http://chembank.broad.harvard.edu/) is a public, web-based informatics environment developed through a collaboration between the Chemical Biology Program and Platform at the Broad Institute of Harvard and MIT. This knowledge environment includes freely available data derived from small molecules and small-molecule screens and resources for studying these data. ChemBank is unique among small-molecule databases in its dedication to the storage of raw screening data, its rigorous definition of screening experiments in terms of statistical hypothesis testing, and its metadata-based organization of screening experiments into projects involving collections of related assays. ChemBank stores an increasingly varied set of measurements derived from cells and other biological assay systems treated with small molecules. Analysis tools are available and are continuously being developed that allow the relationships between small molecules, cell measurements, and cell states to be studied. Currently, ChemBank stores information on hundreds of thousands of small molecules and hundreds of biomedically relevant assays that have been performed at the Broad Institute by collaborators from the worldwide research community. The goal of ChemBank is to provide life scientists unfettered access to biomedically relevant data and tools heretofore available primarily in the private sector.

The TL1A/DR3/DcR3 pathway in autoimmune rheumatic diseases.

PubMed

Siakavellas, Spyros I; Sfikakis, Petros P; Bamias, Giorgos

2015-08-01

TNF-like cytokine 1A (TL1A) and its receptors, death receptor 3 (DR3) and decoy receptor 3 (DcR3) are members of the TNF and TNF receptor superfamilies of proteins, respectively. They constitute a cytokine system that actively interferes with the regulation of immune responses and may participate in the pathogenesis of autoimmune diseases. This review aims to present the current knowledge on the role of the TL1A/DR3/DcR3 system in the pathophysiology of autoimmune rheumatic diseases, with a focus on rheumatoid arthritis (RA). An extensive literature search was performed in the PubMed database using the following keywords: TL1A, death receptor 3, DR3, decoy receptor 3, DcR3, TNFSF15, TNFRSF25, and TNFSF6B. Studies were assessed and selected in view of their relevance to autoimmune rheumatic diseases. The TL1A/DR3/DcR3 axis is a novel immune pathway that participates in the pathogenesis of a variety of autoimmune rheumatic diseases. These molecules may be promising therapeutic targets for inflammatory arthritis. Copyright © 2015 Elsevier Inc. All rights reserved.

From genomics to chemical genomics: new developments in KEGG

PubMed Central

Kanehisa, Minoru; Goto, Susumu; Hattori, Masahiro; Aoki-Kinoshita, Kiyoko F.; Itoh, Masumi; Kawashima, Shuichi; Katayama, Toshiaki; Araki, Michihiro; Hirakawa, Mika

2006-01-01

The increasing amount of genomic and molecular information is the basis for understanding higher-order biological systems, such as the cell and the organism, and their interactions with the environment, as well as for medical, industrial and other practical applications. The KEGG resource () provides a reference knowledge base for linking genomes to biological systems, categorized as building blocks in the genomic space (KEGG GENES) and the chemical space (KEGG LIGAND), and wiring diagrams of interaction networks and reaction networks (KEGG PATHWAY). A fourth component, KEGG BRITE, has been formally added to the KEGG suite of databases. This reflects our attempt to computerize functional interpretations as part of the pathway reconstruction process based on the hierarchically structured knowledge about the genomic, chemical and network spaces. In accordance with the new chemical genomics initiatives, the scope of KEGG LIGAND has been significantly expanded to cover both endogenous and exogenous molecules. Specifically, RPAIR contains curated chemical structure transformation patterns extracted from known enzymatic reactions, which would enable analysis of genome-environment interactions, such as the prediction of new reactions and new enzyme genes that would degrade new environmental compounds. Additionally, drug information is now stored separately and linked to new KEGG DRUG structure maps. PMID:16381885

Comparative peptidomic profile between human hypertrophic scar tissue and matched normal skin for identification of endogenous peptides involved in scar pathology.

PubMed

Li, Jingyun; Chen, Ling; Li, Qian; Cao, Jing; Gao, Yanli; Li, Jun

2018-08-01

Endogenous peptides recently attract increasing attention for their participation in various biological processes. Their roles in the pathogenesis of human hypertrophic scar remains poorly understood. In this study, we used liquid chromatography-tandem mass spectrometry to construct a comparative peptidomic profiling between human hypertrophic scar tissue and matched normal skin. A total of 179 peptides were significantly differentially expressed in human hypertrophic scar tissue, with 95 upregulated and 84 downregulated peptides between hypertrophic scar tissue and matched normal skin. Further bioinformatics analysis (Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis) indicated that precursor proteins of these differentially expressed peptides correlate with cellular process, biological regulation, cell part, binding and structural molecule activity ribosome, and PPAR signaling pathway occurring during pathological changes of hypertrophic scar. Based on prediction database, we found that 78 differentially expressed peptides shared homology with antimicrobial peptides and five matched known immunomodulatory peptides. In conclusion, our results show significantly altered expression profiles of peptides in human hypertrophic scar tissue. These peptides may participate in the etiology of hypertrophic scar and provide beneficial scheme for scar evaluation and treatments. © 2017 Wiley Periodicals, Inc.

Induction of Syndecan-4 by Organic-Inorganic Hybrid Molecules with a 1,10-Phenanthroline Structure in Cultured Vascular Endothelial Cells.

PubMed

Hara, Takato; Kojima, Takayuki; Matsuzaki, Hiroka; Nakamura, Takehiro; Yoshida, Eiko; Fujiwara, Yasuyuki; Yamamoto, Chika; Saito, Shinichi; Kaji, Toshiyuki

2017-02-08

Organic-inorganic hybrid molecules constitute analytical tools used in biological systems. Vascular endothelial cells synthesize and secrete proteoglycans, which are macromolecules consisting of a core protein and glycosaminoglycan side chains. Although the expression of endothelial proteoglycans is regulated by several cytokines/growth factors, there may be alternative pathways for proteoglycan synthesis aside from downstream pathways activated by these cytokines/growth factors. Here, we investigated organic-inorganic hybrid molecules to determine a variant capable of analyzing the expression of syndecan-4, a transmembrane heparan-sulfate proteoglycan, and identified 1,10-phenanthroline ( o -Phen) with or without zinc (Zn-Phen) or rhodium (Rh-Phen). Bovine aortic endothelial cells in culture were treated with these compounds, and the expression of syndecan-4 mRNA and core proteins was determined by real-time reverse transcription polymerase chain reaction and Western blot analysis, respectively. Our findings indicated that o -Phen and Zn-Phen specifically and strongly induced syndecan-4 expression in cultured vascular endothelial cells through activation of the hypoxia-inducible factor-1α/β pathway via inhibition of prolyl hydroxylase-domain-containing protein 2. These results demonstrated an alternative pathway involved in mediating induction of endothelial syndecan-4 expression and revealed organic-inorganic hybrid molecules as effective tools for analyzing biological systems.

Expression of Fas, FasL, caspase-8 and other factors of the extrinsic apoptotic pathway during the onset of interdigital tissue elimination.

PubMed

Svandova, E Budisova; Vesela, B; Lesot, H; Poliard, A; Matalova, E

2017-04-01

Elimination of the interdigital web is considered to be the classical model for assessing apoptosis. So far, most of the molecules described in the process have been connected to the intrinsic (mitochondrial) pathway. The extrinsic (receptor mediated) apoptotic pathway has been rather neglected, although it is important in development, immunomodulation and cancer therapy. This work aimed to investigate factors of the extrinsic apoptotic machinery during interdigital regression with a focus on three crucial initiators: Fas, Fas ligand and caspase-8. Immunofluorescent analysis of mouse forelimb histological sections revealed abundant expression of these molecules prior to digit separation. Subsequent PCR Array analyses indicated the expression of several markers engaged in the extrinsic pathway. Between embryonic days 11 and 13, statistically significant increases in the expression of Fas and caspase-8 were observed, along with other molecules involved in the extrinsic apoptotic pathway such as Dapk1, Traf3, Tnsf12, Tnfrsf1A and Ripk1. These results demonstrate for the first time the presence of extrinsic apoptotic components in mouse limb development and indicate novel candidates in the molecular network accompanying the regression of interdigital tissue during digitalisation.

Biological therapy targeting the IL-23/IL-17 axis in inflammatory bowel disease.

PubMed

Verstockt, Bram; Van Assche, Gert; Vermeire, Séverine; Ferrante, Marc

2017-01-01

As many inflammatory bowel disease (IBD) patients do not benefit from long-term anti-tumour necrosis factor treatment, new anti-inflammatories are urgently needed. After the discovery of the interleukin (IL) 23/17 axis being pivotal in IBD pathogenesis, many different compounds were developed, targeting different components within this pathway. Areas covered: A literature search to March 2016 was performed to identify the most relevant reports on the role of the IL-23/IL-17 axis in IBD and on the different molecules targeting this pathway. First, the authors briefly summarize the immunology of the IL-23/IL-17 pathway to elucidate the mode of action of all different agents. Second, they describe all different molecules targeting this pathway. Besides discussing efficacy and safety data, they also explore immunogenicity, exposure during pregnancy and pharmacokinetics. Expert opinion: A new era in IBD treatment has recently been initiated: besides immunomodulators and TNF-antagonists, anti-adhesion molecules and monoclonal antibodies targeting the IL-23/IL-17 pathway have been developed. Biomarkers for personalized medicine are urgently needed. This therapeutic (r)evolution will further improve disease-related and patient-reported outcome, though a lot of questions should still be addressed in future years.

A theoretical-electron-density databank using a model of real and virtual spherical atoms.

PubMed

Nassour, Ayoub; Domagala, Slawomir; Guillot, Benoit; Leduc, Theo; Lecomte, Claude; Jelsch, Christian

2017-08-01

A database describing the electron density of common chemical groups using combinations of real and virtual spherical atoms is proposed, as an alternative to the multipolar atom modelling of the molecular charge density. Theoretical structure factors were computed from periodic density functional theory calculations on 38 crystal structures of small molecules and the charge density was subsequently refined using a density model based on real spherical atoms and additional dummy charges on the covalent bonds and on electron lone-pair sites. The electron-density parameters of real and dummy atoms present in a similar chemical environment were averaged on all the molecules studied to build a database of transferable spherical atoms. Compared with the now-popular databases of transferable multipolar parameters, the spherical charge modelling needs fewer parameters to describe the molecular electron density and can be more easily incorporated in molecular modelling software for the computation of electrostatic properties. The construction method of the database is described. In order to analyse to what extent this modelling method can be used to derive meaningful molecular properties, it has been applied to the urea molecule and to biotin/streptavidin, a protein/ligand complex.

Adsorption structures and energetics of molecules on metal surfaces: Bridging experiment and theory

NASA Astrophysics Data System (ADS)

Maurer, Reinhard J.; Ruiz, Victor G.; Camarillo-Cisneros, Javier; Liu, Wei; Ferri, Nicola; Reuter, Karsten; Tkatchenko, Alexandre

2016-05-01

Adsorption geometry and stability of organic molecules on surfaces are key parameters that determine the observable properties and functions of hybrid inorganic/organic systems (HIOSs). Despite many recent advances in precise experimental characterization and improvements in first-principles electronic structure methods, reliable databases of structures and energetics for large adsorbed molecules are largely amiss. In this review, we present such a database for a range of molecules adsorbed on metal single-crystal surfaces. The systems we analyze include noble-gas atoms, conjugated aromatic molecules, carbon nanostructures, and heteroaromatic compounds adsorbed on five different metal surfaces. The overall objective is to establish a diverse benchmark dataset that enables an assessment of current and future electronic structure methods, and motivates further experimental studies that provide ever more reliable data. Specifically, the benchmark structures and energetics from experiment are here compared with the recently developed van der Waals (vdW) inclusive density-functional theory (DFT) method, DFT + vdWsurf. In comparison to 23 adsorption heights and 17 adsorption energies from experiment we find a mean average deviation of 0.06 Å and 0.16 eV, respectively. This confirms the DFT + vdWsurf method as an accurate and efficient approach to treat HIOSs. A detailed discussion identifies remaining challenges to be addressed in future development of electronic structure methods, for which the here presented benchmark database may serve as an important reference.

Challenges of the information age: the impact of false discovery on pathway identification.

PubMed

Rog, Colin J; Chekuri, Srinivasa C; Edgerton, Mary E

2012-11-21

Pathways with members that have known relevance to a disease are used to support hypotheses generated from analyses of gene expression and proteomic studies. Using cancer as an example, the pitfalls of searching pathways databases as support for genes and proteins that could represent false discoveries are explored. The frequency with which networks could be generated from 100 instances each of randomly selected five and ten genes sets as input to MetaCore, a commercial pathways database, was measured. A PubMed search enumerated cancer-related literature published for any gene in the networks. Using three, two, and one maximum intervening step between input genes to populate the network, networks were generated with frequencies of 97%, 77%, and 7% using ten gene sets and 73%, 27%, and 1% using five gene sets. PubMed reported an average of 4225 cancer-related articles per network gene. This can be attributed to the richly populated pathways databases and the interest in the molecular basis of cancer. As information sources become enriched, they are more likely to generate plausible mechanisms for false discoveries.

Predicting the points of interaction of small molecules in the NF-κB pathway

PubMed Central

2011-01-01

Background The similarity property principle has been used extensively in drug discovery to identify small compounds that interact with specific drug targets. Here we show it can be applied to identify the interactions of small molecules within the NF-κB signalling pathway. Results Clusters that contain compounds with a predominant interaction within the pathway were created, which were then used to predict the interaction of compounds not included in the clustering analysis. Conclusions The technique successfully predicted the points of interactions of compounds that are known to interact with the NF-κB pathway. The method was also shown to be successful when compounds for which the interaction points were unknown were included in the clustering analysis. PMID:21342508

Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

PubMed

Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

2017-08-01

This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

Whole-genome expression analyses of type 2 diabetes in human skin reveal altered immune function and burden of infection.

PubMed

Wu, Chun; Chen, Xiaopan; Shu, Jing; Lee, Chun-Ting

2017-05-23

Skin disorders are among most common complications associated with type 2 diabetes mellitus (T2DM). Although T2DM patients are known to have increased risk of infections and other T2DM-related skin disorders, their molecular mechanisms are largely unknown. This study aims to identify dysregulated genes and gene networks that are associated with T2DM in human skin. We compared the expression profiles of 56,318 transcribed genes on 74 T2DM cases and 148 gender- age-, and race-matched non-diabetes controls from the Genotype-Tissue Expression (GTEx) database. RNA-Sequencing data indicates that diabetic skin is characterized by increased expression of genes that are related to immune responses (CCL20, CXCL9, CXCL10, CXCL11, CXCL13, and CCL18), JAK/STAT signaling pathway (JAK3, STAT1, and STAT2), tumor necrosis factor superfamily (TNFSF10 and TNFSF15), and infectious disease pathways (OAS1, OAS2, OAS3, and IFIH1). Genes in cell adhesion molecules pathway (NCAM1 and L1CAM) and collagen family (PCOLCE2 and COL9A3) are downregulated, suggesting structural changes in the skin of T2DM. For the first time, to the best of our knowledge, this pioneer analytic study reports comprehensive unbiased gene expression changes and dysregulated pathways in the non-diseased skin of T2DM patients. This comprehensive understanding derived from whole-genome expression profiles could advance our knowledge in determining molecular targets for the prevention and treatment of T2DM-associated skin disorders.

Gene expression profiles of fin regeneration in loach (Paramisgurnus dabryanu).

PubMed

Li, Li; He, Jingya; Wang, Linlin; Chen, Weihua; Chang, Zhongjie

2017-11-01

Teleost fins can regenerate accurate position-matched structure and function after amputation. However, we still lack systematic transcriptional profiling and methodologies to understand the molecular basis of fin regeneration. After histological analysis, we established a suppression subtraction hybridization library containing 418 distinct sequences expressed differentially during the process of blastema formation and differentiation in caudal fin regeneration. Genome ontology and comparative analysis of differential distribution of our data and the reference zebrafish genome showed notable subcategories, including multi-organism processes, response to stimuli, extracellular matrix, antioxidant activity, and cell junction function. KEGG pathway analysis allowed the effective identification of relevant genes in those pathways involved in tissue morphogenesis and regeneration, including tight junction, cell adhesion molecules, mTOR and Jak-STAT signaling pathway. From relevant function subcategories and signaling pathways, 78 clones were examined for further Southern-blot hybridization. Then, 17 genes were chosen and characterized using semi-quantitative PCR. Then 4 candidate genes were identified, including F11r, Mmp9, Agr2 and one without a match to any database. After real-time quantitative PCR, the results showed obvious expression changes in different periods of caudal fin regeneration. We can assume that the 4 candidates, likely valuable genes associated with fin regeneration, deserve additional attention. Thus, our study demonstrated how to investigate the transcript profiles with an emphasis on bioinformatics intervention and how to identify potential genes related to fin regeneration processes. The results also provide a foundation or knowledge for further research into genes and molecular mechanisms of fin regeneration. Copyright © 2017 Elsevier B.V. All rights reserved.

Pathway Distiller - multisource biological pathway consolidation

PubMed Central

2012-01-01

Background One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. Methods After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. Results We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. Conclusions By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments. PMID:23134636

Pathway Distiller - multisource biological pathway consolidation.

PubMed

Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong

2012-01-01

One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.

Endocytic pathways downregulate the L1-type cell adhesion molecule neuroglian to promote dendrite pruning in Drosophila.

PubMed

Zhang, Heng; Wang, Yan; Wong, Jack Jing Lin; Lim, Kah-Leong; Liou, Yih-Cherng; Wang, Hongyan; Yu, Fengwei

2014-08-25

Pruning of unnecessary axons and/or dendrites is crucial for maturation of the nervous system. However, little is known about cell adhesion molecules (CAMs) that control neuronal pruning. In Drosophila, dendritic arborization neurons, ddaCs, selectively prune their larval dendrites. Here, we report that Rab5/ESCRT-mediated endocytic pathways are critical for dendrite pruning. Loss of Rab5 or ESCRT function leads to robust accumulation of the L1-type CAM Neuroglian (Nrg) on enlarged endosomes in ddaC neurons. Nrg is localized on endosomes in wild-type ddaC neurons and downregulated prior to dendrite pruning. Overexpression of Nrg alone is sufficient to inhibit dendrite pruning, whereas removal of Nrg causes precocious dendrite pruning. Epistasis experiments indicate that Rab5 and ESCRT restrain the inhibitory role of Nrg during dendrite pruning. Thus, this study demonstrates the cell-surface molecule that controls dendrite pruning and defines an important mechanism whereby sensory neurons, via endolysosomal pathway, downregulate the cell-surface molecule to trigger dendrite pruning. Copyright © 2014 Elsevier Inc. All rights reserved.

Ab initio study on the 1:2 reaction of CO 2 with dimethylamine

NASA Astrophysics Data System (ADS)

Jamróz, MichałH.; Dobrowolski, Jan Cz.; Borowiak, Marek A.

1997-02-01

The reaction between CO 2 and the dimethylamine molecule in the presence of a second dimethylamine molecule is modeled by the ab initio RHF/3-21G method. Starting from the most stable 1:2 complex, the most effective reaction pathway turned out to be proton transfer between amine molecules followed by immediate proton transfer from one of the amine molecules to the CO 2 moiety. The activation barrier for this pathway (9.54 kcal mol -1 with respect to the 1:2 complex) is within the range of activation energy values found in kinetic studies for similar reactions with different hydroxylamines (from 9.2 to 13.0 kcal mol -1). The reaction product is the cyclic hydrogen bonded complex of dimethylcarbamic acid with dimethylamine.

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis.

PubMed

Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu

2003-11-07

To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s).

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis

PubMed Central

Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu

2003-01-01

Background To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. Results We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. Conclusion PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s). PMID:14604444

A computational platform to maintain and migrate manual functional annotations for BioCyc databases.

PubMed

Walsh, Jesse R; Sen, Taner Z; Dickerson, Julie A

2014-10-12

BioCyc databases are an important resource for information on biological pathways and genomic data. Such databases represent the accumulation of biological data, some of which has been manually curated from literature. An essential feature of these databases is the continuing data integration as new knowledge is discovered. As functional annotations are improved, scalable methods are needed for curators to manage annotations without detailed knowledge of the specific design of the BioCyc database. We have developed CycTools, a software tool which allows curators to maintain functional annotations in a model organism database. This tool builds on existing software to improve and simplify annotation data imports of user provided data into BioCyc databases. Additionally, CycTools automatically resolves synonyms and alternate identifiers contained within the database into the appropriate internal identifiers. Automating steps in the manual data entry process can improve curation efforts for major biological databases. The functionality of CycTools is demonstrated by transferring GO term annotations from MaizeCyc to matching proteins in CornCyc, both maize metabolic pathway databases available at MaizeGDB, and by creating strain specific databases for metabolic engineering.

The structure and dipole moment of globular proteins in solution and crystalline states: use of NMR and X-ray databases for the numerical calculation of dipole moment.

PubMed

Takashima, S

2001-04-05

The large dipole moment of globular proteins has been well known because of the detailed studies using dielectric relaxation and electro-optical methods. The search for the origin of these dipolemoments, however, must be based on the detailed knowledge on protein structure with atomic resolutions. At present, we have two sources of information on the structure of protein molecules: (1) x-ray databases obtained in crystalline state; (2) NMR databases obtained in solution state. While x-ray databases consist of only one model, NMR databases, because of the fluctuation of the protein folding in solution, consist of a number of models, thus enabling the computation of dipole moment repeated for all these models. The aim of this work, using these databases, is the detailed investigation on the interdependence between the structure and dipole moment of protein molecules. The dipole moment of protein molecules has roughly two components: one dipole moment is due to surface charges and the other, core dipole moment, is due to polar groups such as N--H and C==O bonds. The computation of surface charge dipole moment consists of two steps: (A) calculation of the pK shifts of charged groups for electrostatic interactions and (B) calculation of the dipole moment using the pK corrected for electrostatic shifts. The dipole moments of several proteins were computed using both NMR and x-ray databases. The dipole moments of these two sets of calculations are, with a few exceptions, in good agreement with one another and also with measured dipole moments.

Proposing Novel MAO-B Hit Inhibitors Using Multidimensional Molecular Modeling Approaches and Application of Binary QSAR Models for Prediction of Their Therapeutic Activity, Pharmacokinetic and Toxicity Properties.

PubMed

Is, Yusuf Serhat; Durdagi, Serdar; Aksoydan, Busecan; Yurtsever, Mine

2018-05-07

Monoamine oxidase (MAO) enzymes MAO-A and MAO-B play a critical role in the metabolism of monoamine neurotransmitters. Hence, MAO inhibitors are very important for the treatment of several neurodegenerative diseases such as Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS). In this study, 256 750 molecules from Otava Green Chemical Collection were virtually screened for their binding activities as MAO-B inhibitors. Two hit molecules were identified after applying different filters such as high docking scores and selectivity to MAO-B, desired pharmacokinetic profile predictions with binary quantitative structure-activity relationship (QSAR) models. Therapeutic activity prediction as well as pharmacokinetic and toxicity profiles were investigated using MetaCore/MetaDrug platform which is based on a manually curated database of molecular interactions, molecular pathways, gene-disease associations, chemical metabolism, and toxicity information. Particular therapeutic activity and toxic effect predictions are based on the ChemTree ability to correlate structural descriptors to that property using recursive partitioning algorithm. Molecular dynamics (MD) simulations were also performed to make more detailed assessments beyond docking studies. All these calculations were made not only to determine if studied molecules possess the potential to be a MAO-B inhibitor but also to find out whether they carry MAO-B selectivity versus MAO-A. The evaluation of docking results and pharmacokinetic profile predictions together with the MD simulations enabled us to identify one hit molecule (ligand 1, Otava ID: 3463218) which displayed higher selectivity toward MAO-B than a positive control selegiline which is a commercially used drug for PD therapeutic purposes.

The role of oxidative stress in the development of alcoholic liver disease.

PubMed

Galicia-Moreno, M; Gutiérrez-Reyes, G

2014-01-01

Alcohol is the most accepted addictive substance worldwide and its consumption is related to multiple health, economic, and social problems. The liver is the organ in charge of ethanol metabolism and it is susceptible to alcohol's toxic effects. To provide a detailed review of the role of oxidative stress in alcoholic liver disease and the mechanisms of damage involved, along with current information on the hepatoprotective effectiveness of the molecules that have been studied. A search of the PubMed database was conducted using the following keywords oxidative stress, alcoholic liver damage, alcoholic cirrhosis, and antioxidants. There was no time limit for gathering all available information on the subject at hand. According to the literature reviewed, oxidative stress plays an important role in the pathogenesis of alcoholic liver damage. Molecules such as reactive oxygen species (ROS) and reactive nitrogen species (RNS), formed during ethanol metabolism, structurally and functionally modify organic molecules. Consequently, biologic processes are altered and hepatocytes are sensitized to the action of cytokines like tumor necrosis factor-α, as well as to the action of endotoxins, activating signaling pathways such as those controlled by nuclear factor kappa B, extracellular signal regulated kinases, and mitogen activated protein kinase. Oxidative stress plays an important role in the development of liver damage resulting from alcohol consumption. The molecules that have currently displayed a hepatoprotective effect in preclinical and clinical trials must be studied further so that their effectiveness can be confirmed and they can possibly be used as adjuvant treatments for this disease. Copyright © 2014 Asociación Mexicana de Gastroenterología. Published by Masson Doyma México S.A. All rights reserved.

Simulations of polymorphic icosahedral shells assembling around many cargo molecules

NASA Astrophysics Data System (ADS)

Mohajerani, Farzaneh; Perlmutter, Jason; Hagan, Michael

Bacterial microcompartments (BMCs) are large icosahedral shells that sequester the enzymes and reactants responsible for particular metabolic pathways in bacteria. Although different BMCs vary in size and encapsulate different cargoes, they are constructed from similar pentameric and hexameric shell proteins. Despite recent groundbreaking experiments which visualized the formation of individual BMCs, the detailed assembly pathways and the factors which control shell size remain unclear. In this talk, we describe theoretical and computational models that describe the dynamical encapsulation of hundreds of cargo molecules by self-assembling icosahedral shells. We present phase diagrams and analysis of dynamical simulation trajectories showing how the thermodynamics, assembly pathways, and emergent structures depend on the interactions among shell proteins and cargo molecules. Our model suggests a mechanism for controlling insertion of the 12 pentamers required for a closed shell topology, and the relationship between assembly pathway and BMC size polydispersity. In addition to elucidating how native BMCs assemble,our results establish principles for reengineering BMCs or viral capsids as customizable nanoreactors that can assemble around a programmable set of enzymes and reactants. Supported by NIH R01GM108021 and Brandeis MRSEC DMR-1420382.

The inherent dynamics of a molecular liquid: geodesic pathways through the potential energy landscape of a liquid of linear molecules.

PubMed

Jacobson, Daniel; Stratt, Richard M

2014-05-07

Because the geodesic pathways that a liquid follows through its potential energy landscape govern its slow, diffusive motion, we suggest that these pathways are logical candidates for the title of a liquid's "inherent dynamics." Like their namesake "inherent structures," these objects are simply features of the system's potential energy surface and thus provide views of the system's structural evolution unobstructed by thermal kinetic energy. This paper shows how these geodesic pathways can be computed for a liquid of linear molecules, allowing us to see precisely how such molecular liquids mix rotational and translational degrees of freedom into their dynamics. The ratio of translational to rotational components of the geodesic path lengths, for example, is significantly larger than would be expected on equipartition grounds, with a value that scales with the molecular aspect ratio. These and other features of the geodesics are consistent with a picture in which molecular reorientation adiabatically follows translation-molecules largely thread their way through narrow channels available in the potential energy landscape.

The inherent dynamics of a molecular liquid: Geodesic pathways through the potential energy landscape of a liquid of linear molecules

NASA Astrophysics Data System (ADS)

Jacobson, Daniel; Stratt, Richard M.

2014-05-01

Because the geodesic pathways that a liquid follows through its potential energy landscape govern its slow, diffusive motion, we suggest that these pathways are logical candidates for the title of a liquid's "inherent dynamics." Like their namesake "inherent structures," these objects are simply features of the system's potential energy surface and thus provide views of the system's structural evolution unobstructed by thermal kinetic energy. This paper shows how these geodesic pathways can be computed for a liquid of linear molecules, allowing us to see precisely how such molecular liquids mix rotational and translational degrees of freedom into their dynamics. The ratio of translational to rotational components of the geodesic path lengths, for example, is significantly larger than would be expected on equipartition grounds, with a value that scales with the molecular aspect ratio. These and other features of the geodesics are consistent with a picture in which molecular reorientation adiabatically follows translation—molecules largely thread their way through narrow channels available in the potential energy landscape.

EcoCyc: a comprehensive database resource for Escherichia coli

PubMed Central

Keseler, Ingrid M.; Collado-Vides, Julio; Gama-Castro, Socorro; Ingraham, John; Paley, Suzanne; Paulsen, Ian T.; Peralta-Gil, Martín; Karp, Peter D.

2005-01-01

The EcoCyc database (http://EcoCyc.org/) is a comprehensive source of information on the biology of the prototypical model organism Escherichia coli K12. The mission for EcoCyc is to contain both computable descriptions of, and detailed comments describing, all genes, proteins, pathways and molecular interactions in E.coli. Through ongoing manual curation, extensive information such as summary comments, regulatory information, literature citations and evidence types has been extracted from 8862 publications and added to Version 8.5 of the EcoCyc database. The EcoCyc database can be accessed through a World Wide Web interface, while the downloadable Pathway Tools software and data files enable computational exploration of the data and provide enhanced querying capabilities that web interfaces cannot support. For example, EcoCyc contains carefully curated information that can be used as training sets for bioinformatics prediction of entities such as promoters, operons, genetic networks, transcription factor binding sites, metabolic pathways, functionally related genes, protein complexes and protein–ligand interactions. PMID:15608210

Nutritional metabolomics: Progress in addressing complexity in diet and health

PubMed Central

Jones, Dean P.; Park, Youngja; Ziegler, Thomas R.

2013-01-01

Nutritional metabolomics is rapidly maturing to use small molecule chemical profiling to support integration of diet and nutrition in complex biosystems research. These developments are critical to facilitate transition of nutritional sciences from population-based to individual-based criteria for nutritional research, assessment and management. This review addresses progress in making these approaches manageable for nutrition research. Important concept developments concerning the exposome, predictive health and complex pathobiology, serve to emphasize the central role of diet and nutrition in integrated biosystems models of health and disease. Improved analytic tools and databases for targeted and non-targeted metabolic profiling, along with bioinformatics, pathway mapping and computational modeling, are now used for nutrition research on diet, metabolism, microbiome and health associations. These new developments enable metabolome-wide association studies (MWAS) and provide a foundation for nutritional metabolomics, along with genomics, epigenomics and health phenotyping, to support integrated models required for personalized diet and nutrition forecasting. PMID:22540256

Metabolic profiling of Alzheimer's disease brains

NASA Astrophysics Data System (ADS)

Inoue, Koichi; Tsutsui, Haruhito; Akatsu, Hiroyasu; Hashizume, Yoshio; Matsukawa, Noriyuki; Yamamoto, Takayuki; Toyo'Oka, Toshimasa

2013-08-01

Alzheimer's disease (AD) is an irreversible, progressive brain disease and can be definitively diagnosed after death through an examination of senile plaques and neurofibrillary tangles in several brain regions. It is to be expected that changes in the concentration and/or localization of low-molecular-weight molecules are linked to the pathological changes that occur in AD, and determining their identity would provide valuable information regarding AD processes. Here, we propose definitive brain metabolic profiling using ultra-performance liquid chromatography coupled with electrospray time-of-flight mass spectrometry analysis. The acquired data were subjected to principal components analysis to differentiate the frontal and parietal lobes of the AD/Control groups. Significant differences in the levels of spermine and spermidine were identified using S-plot, mass spectra, databases and standards. Based on the investigation of the polyamine metabolite pathway, these data establish that the downstream metabolites of ornithine are increased, potentially implicating ornithine decarboxylase activity in AD pathology.

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

Using Multiorder Time-Correlation Functions (TCFs) To Elucidate Biomolecular Reaction Pathways from Microsecond Single-Molecule Fluorescence Experiments.

PubMed

Phelps, Carey; Israels, Brett; Marsh, Morgan C; von Hippel, Peter H; Marcus, Andrew H

2016-12-29

Recent advances in single-molecule fluorescence imaging have made it possible to perform measurements on microsecond time scales. Such experiments have the potential to reveal detailed information about the conformational changes in biological macromolecules, including the reaction pathways and dynamics of the rearrangements involved in processes, such as sequence-specific DNA "breathing" and the assembly of protein-nucleic acid complexes. Because microsecond-resolved single-molecule trajectories often involve "sparse" data, that is, they contain relatively few data points per unit time, they cannot be easily analyzed using the standard protocols that were developed for single-molecule experiments carried out with tens-of-millisecond time resolution and high "data density." Here, we describe a generalized approach, based on time-correlation functions, to obtain kinetic information from microsecond-resolved single-molecule fluorescence measurements. This approach can be used to identify short-lived intermediates that lie on reaction pathways connecting relatively long-lived reactant and product states. As a concrete illustration of the potential of this methodology for analyzing specific macromolecular systems, we accompany the theoretical presentation with the description of a specific biologically relevant example drawn from studies of reaction mechanisms of the assembly of the single-stranded DNA binding protein of the T4 bacteriophage replication complex onto a model DNA replication fork.

dEMBF: A Comprehensive Database of Enzymes of Microalgal Biofuel Feedstock.

PubMed

Misra, Namrata; Panda, Prasanna Kumar; Parida, Bikram Kumar; Mishra, Barada Kanta

2016-01-01

Microalgae have attracted wide attention as one of the most versatile renewable feedstocks for production of biofuel. To develop genetically engineered high lipid yielding algal strains, a thorough understanding of the lipid biosynthetic pathway and the underpinning enzymes is essential. In this work, we have systematically mined the genomes of fifteen diverse algal species belonging to Chlorophyta, Heterokontophyta, Rhodophyta, and Haptophyta, to identify and annotate the putative enzymes of lipid metabolic pathway. Consequently, we have also developed a database, dEMBF (Database of Enzymes of Microalgal Biofuel Feedstock), which catalogues the complete list of identified enzymes along with their computed annotation details including length, hydrophobicity, amino acid composition, subcellular location, gene ontology, KEGG pathway, orthologous group, Pfam domain, intron-exon organization, transmembrane topology, and secondary/tertiary structural data. Furthermore, to facilitate functional and evolutionary study of these enzymes, a collection of built-in applications for BLAST search, motif identification, sequence and phylogenetic analysis have been seamlessly integrated into the database. dEMBF is the first database that brings together all enzymes responsible for lipid synthesis from available algal genomes, and provides an integrative platform for enzyme inquiry and analysis. This database will be extremely useful for algal biofuel research. It can be accessed at http://bbprof.immt.res.in/embf.

dEMBF: A Comprehensive Database of Enzymes of Microalgal Biofuel Feedstock

PubMed Central

Misra, Namrata; Panda, Prasanna Kumar; Parida, Bikram Kumar; Mishra, Barada Kanta

2016-01-01

Microalgae have attracted wide attention as one of the most versatile renewable feedstocks for production of biofuel. To develop genetically engineered high lipid yielding algal strains, a thorough understanding of the lipid biosynthetic pathway and the underpinning enzymes is essential. In this work, we have systematically mined the genomes of fifteen diverse algal species belonging to Chlorophyta, Heterokontophyta, Rhodophyta, and Haptophyta, to identify and annotate the putative enzymes of lipid metabolic pathway. Consequently, we have also developed a database, dEMBF (Database of Enzymes of Microalgal Biofuel Feedstock), which catalogues the complete list of identified enzymes along with their computed annotation details including length, hydrophobicity, amino acid composition, subcellular location, gene ontology, KEGG pathway, orthologous group, Pfam domain, intron-exon organization, transmembrane topology, and secondary/tertiary structural data. Furthermore, to facilitate functional and evolutionary study of these enzymes, a collection of built-in applications for BLAST search, motif identification, sequence and phylogenetic analysis have been seamlessly integrated into the database. dEMBF is the first database that brings together all enzymes responsible for lipid synthesis from available algal genomes, and provides an integrative platform for enzyme inquiry and analysis. This database will be extremely useful for algal biofuel research. It can be accessed at http://bbprof.immt.res.in/embf. PMID:26727469

A pathway to bone: signaling molecules and transcription factors involved in chondrocyte development and maturation

PubMed Central

Kozhemyakina, Elena; Lassar, Andrew B.; Zelzer, Elazar

2015-01-01

Decades of work have identified the signaling pathways that regulate the differentiation of chondrocytes during bone formation, from their initial induction from mesenchymal progenitor cells to their terminal maturation into hypertrophic chondrocytes. Here, we review how multiple signaling molecules, mechanical signals and morphological cell features are integrated to activate a set of key transcription factors that determine and regulate the genetic program that induces chondrogenesis and chondrocyte differentiation. Moreover, we describe recent findings regarding the roles of several signaling pathways in modulating the proliferation and maturation of chondrocytes in the growth plate, which is the ‘engine’ of bone elongation. PMID:25715393

Small molecule mimics of DFTamP1, a database designed anti-Staphylococcal peptide

PubMed Central

Dong, Yuxiang; Lushnikova, Tamara; Golla, Radha M.; Wang, Xiaofang; Wang, Guangshun

2017-01-01

Antimicrobial peptides (AMPs) are important templates for developing new antimicrobial agents. Previously, we developed a database filtering technology that enabled us to design a potent anti-Staphylococcal peptide DFTamP1. Using this same design approach, we now report the discovery of a new class of bis-indole diimidazolines as AMP small molecule mimics. The best compound killed multiple S. aureus clinical strains in both planktonic and biofilm forms. The compound appeared to target bacterial membranes with antimicrobial activity and membrane permeation ability similar to daptomycin. PMID:28011203

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

PubMed

Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

Using Bioinformatic Approaches to Identify Pathways Targeted by Human Leukemogens

PubMed Central

Thomas, Reuben; Phuong, Jimmy; McHale, Cliona M.; Zhang, Luoping

2012-01-01

We have applied bioinformatic approaches to identify pathways common to chemical leukemogens and to determine whether leukemogens could be distinguished from non-leukemogenic carcinogens. From all known and probable carcinogens classified by IARC and NTP, we identified 35 carcinogens that were associated with leukemia risk in human studies and 16 non-leukemogenic carcinogens. Using data on gene/protein targets available in the Comparative Toxicogenomics Database (CTD) for 29 of the leukemogens and 11 of the non-leukemogenic carcinogens, we analyzed for enrichment of all 250 human biochemical pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The top pathways targeted by the leukemogens included metabolism of xenobiotics by cytochrome P450, glutathione metabolism, neurotrophin signaling pathway, apoptosis, MAPK signaling, Toll-like receptor signaling and various cancer pathways. The 29 leukemogens formed 18 distinct clusters comprising 1 to 3 chemicals that did not correlate with known mechanism of action or with structural similarity as determined by 2D Tanimoto coefficients in the PubChem database. Unsupervised clustering and one-class support vector machines, based on the pathway data, were unable to distinguish the 29 leukemogens from 11 non-leukemogenic known and probable IARC carcinogens. However, using two-class random forests to estimate leukemogen and non-leukemogen patterns, we estimated a 76% chance of distinguishing a random leukemogen/non-leukemogen pair from each other. PMID:22851955

Assembly of a novel biosynthetic pathway for production of the plant flavonoid fisetin in Escherichia coli.

PubMed

Stahlhut, Steen G; Siedler, Solvej; Malla, Sailesh; Harrison, Scott J; Maury, Jérôme; Neves, Ana Rute; Forster, Jochen

2015-09-01

Plant secondary metabolites are an underutilized pool of bioactive molecules for applications in the food, pharma and nutritional industries. One such molecule is fisetin, which is present in many fruits and vegetables and has several potential health benefits, including anti-cancer, anti-viral and anti-aging activity. Moreover, fisetin has recently been shown to prevent Alzheimer's disease in mice and to prevent complications associated with diabetes type I. Thus far the biosynthetic pathway of fisetin in plants remains elusive. Here, we present the heterologous assembly of a novel fisetin pathway in Escherichia coli. We propose a novel biosynthetic pathway from the amino acid, tyrosine, utilizing nine heterologous enzymes. The pathway proceeds via the synthesis of two flavanones never produced in microorganisms before--garbanzol and resokaempferol. We show for the first time a functional biosynthetic pathway and establish E. coli as a microbial platform strain for the production of fisetin and related flavonols. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Critical Role of the Sphingolipid Pathway in Stroke: a Review of Current Utility and Potential Therapeutic Targets.

PubMed

Sun, Na; Keep, Richard F; Hua, Ya; Xi, Guohua

2016-10-01

Sphingolipids are a series of cell membrane-derived lipids which act as signaling molecules and play a critical role in cell death and survival, proliferation, recognition, and migration. Sphingosine-1-phosphate acts as a key signaling molecule and regulates lymphocyte trafficking, glial cell activation, vasoconstriction, endothelial barrier function, and neuronal death pathways which plays a critical role in numerous neurological conditions. Stroke is a second leading cause of death all over the world and effective therapies are still in great demand, including ischemic stroke and hemorrhagic stroke as well as poststroke repair. Significantly, sphingolipid activities change after stroke and correlate with stroke outcome, which has promoted efforts to testify whether the sphingolipid pathway could be a novel therapeutic target in stroke. The sphingolipid metabolic pathway, the connection between the pathway and stroke, as well as therapeutic interventions to manipulate the pathway to reduce stroke-induced brain injury are discussed in this review.

[Cell signaling pathways interaction in cellular proliferation: Potential target for therapeutic interventionism].

PubMed

Valdespino-Gómez, Víctor Manuel; Valdespino-Castillo, Patricia Margarita; Valdespino-Castillo, Víctor Edmundo

2015-01-01

Nowadays, cellular physiology is best understood by analysing their interacting molecular components. Proteins are the major components of the cells. Different proteins are organised in the form of functional clusters, pathways or networks. These molecules are ordered in clusters of receptor molecules of extracellular signals, transducers, sensors and biological response effectors. The identification of these intracellular signaling pathways in different cellular types has required a long journey of experimental work. More than 300 intracellular signaling pathways have been identified in human cells. They participate in cell homeostasis processes for structural and functional maintenance. Some of them participate simultaneously or in a nearly-consecutive progression to generate a cellular phenotypic change. In this review, an analysis is performed on the main intracellular signaling pathways that take part in the cellular proliferation process, and the potential use of some components of these pathways as target for therapeutic interventionism are also underlined. Copyright © 2015 Academia Mexicana de Cirugía A.C. Published by Masson Doyma México S.A. All rights reserved.

Mechanisms for the inversion of chirality: global reaction route mapping of stereochemical pathways in a probable chiral extraterrestrial molecule, 2-aminopropionitrile.

PubMed

Kaur, Ramanpreet; Vikas

2015-02-21

2-Aminopropionitrile (APN), a probable candidate as a chiral astrophysical molecule, is a precursor to amino-acid alanine. Stereochemical pathways in 2-APN are explored using Global Reaction Route Mapping (GRRM) method employing high-level quantum-mechanical computations. Besides predicting the conventional mechanism for chiral inversion that proceeds through an achiral intermediate, a counterintuitive flipping mechanism is revealed for 2-APN through chiral intermediates explored using the GRRM. The feasibility of the proposed stereochemical pathways, in terms of the Gibbs free-energy change, is analyzed at the temperature conditions akin to the interstellar medium. Notably, the stereoinversion in 2-APN is observed to be more feasible than the dissociation of 2-APN and intermediates involved along the stereochemical pathways, and the flipping barrier is observed to be as low as 3.68 kJ/mol along one of the pathways. The pathways proposed for the inversion of chirality in 2-APN may provide significant insight into the extraterrestrial origin of life.

Elucidating Turnover Pathways of Bioactive Small Molecules by Isotopomer Analysis: The Persistent Organic Pollutant DDT

PubMed Central

Ehlers, Ina; Betson, Tatiana R.; Vetter, Walter; Schleucher, Jürgen

2014-01-01

The persistent organic pollutant DDT (1,1,1-trichloro-2,2-bis(4-chlorophenyl)ethane) is still indispensable in the fight against malaria, although DDT and related compounds pose toxicological hazards. Technical DDT contains the dichloro congener DDD (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethyl]benzene) as by-product, but DDD is also formed by reductive degradation of DDT in the environment. To differentiate between DDD formation pathways, we applied deuterium NMR spectroscopy to measure intramolecular deuterium distributions (2H isotopomer abundances) of DDT and DDD. DDD formed in the technical DDT synthesis was strongly deuterium-enriched at one intramolecular position, which we traced back to 2H/1H fractionation of a chlorination step in the technical synthesis. In contrast, DDD formed by reductive degradation was strongly depleted at the same position, which was due to the incorporation of 2H-depleted hydride equivalents during reductive degradation. Thus, intramolecular isotope distributions give mechanistic information on reaction pathways, and explain a puzzling difference in the whole-molecule 2H/1H ratio between DDT and DDD. In general, our results highlight that intramolecular isotope distributions are essential to interpret whole-molecule isotope ratios. Intramolecular isotope information allows distinguishing pathways of DDD formation, which is important to identify polluters or to assess DDT turnover in the environment. Because intramolecular isotope data directly reflect isotope fractionation of individual chemical reactions, they are broadly applicable to elucidate transformation pathways of small bioactive molecules in chemistry, physiology and environmental science. PMID:25350380

Mechano-chemical pathways to H2O and CO2 splitting

NASA Astrophysics Data System (ADS)

Vedadi, Mohammad H.; Haas, Stephan

2011-10-01

The shock-induced collapse of CO2-filled nanobubbles is investigated using molecular dynamics simulations based on a reactive force field. The energetic nanojet and high-pressure water hammer shock formed during and after collapse of the nanobubble trigger mechano-chemical H2O-CO2 reactions, some of which lead to splitting of water and formation of O2 molecules. The dominant pathways through which splitting of water molecules occur are identified.

Cinnamon, a promising prospect towards Alzheimer's disease.

PubMed

Momtaz, Saeideh; Hassani, Shokoufeh; Khan, Fazlullah; Ziaee, Mojtaba; Abdollahi, Mohammad

2018-04-01

Over the last decades, an exponential increase of efforts concerning the treatment of Alzheimer's disease (AD) has been practiced. Phytochemicals preparations have a millenary background to combat various pathological conditions. Various cinnamon species and their biologically active ingredients have renewed the interest towards the treatment of patients with mild-to-moderate AD through the inhibition of tau protein aggregation and prevention of the formation and accumulation of amyloid-β peptides into the neurotoxic oligomeric inclusions, both of which are considered to be the AD trademarks. In this review, we presented comprehensive data on the interactions of a number of cinnamon polyphenols (PPs) with oxidative stress and pro-inflammatory signaling pathways in the brain. In addition, we discussed the potential association between AD and diabetes mellitus (DM), vis-à-vis the effluence of cinnamon PPs. Further, an upcoming prospect of AD epigenetic pathophysiological conditions and cinnamon has been sighted. Data was retrieved from the scientific databases such as PubMed database of the National Library of Medicine, Scopus and Google Scholar without any time limitation. The extract of cinnamon efficiently inhibits tau accumulations, Aβ aggregation and toxicity in vivo and in vitro models. Indeed, cinnamon possesses neuroprotective effects interfering multiple oxidative stress and pro-inflammatory pathways. Besides, cinnamon modulates endothelial functions and attenuates the vascular cell adhesion molecules. Cinnamon PPs may induce AD epigenetic modifications. Cinnamon and in particular, cinnamaldehyde seem to be effective and safe approaches for treatment and prevention of AD onset and/or progression. However, further molecular and translational research studies as well as prolonged clinical trials are required to establish the therapeutic safety and efficacy in different cinnamon spp. Copyright © 2017 Elsevier Ltd. All rights reserved.

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology

PubMed Central

Latendresse, Mario; Paley, Suzanne M.; Krummenacker, Markus; Ong, Quang D.; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M.; Caspi, Ron

2016-01-01

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. PMID:26454094

Role of Chemical Reactivity and Transition State Modeling for Virtual Screening.

PubMed

Karthikeyan, Muthukumarasamy; Vyas, Renu; Tambe, Sanjeev S; Radhamohan, Deepthi; Kulkarni, Bhaskar D

2015-01-01

Every drug discovery research program involves synthesis of a novel and potential drug molecule utilizing atom efficient, economical and environment friendly synthetic strategies. The current work focuses on the role of the reactivity based fingerprints of compounds as filters for virtual screening using a tool ChemScore. A reactant-like (RLS) and a product- like (PLS) score can be predicted for a given compound using the binary fingerprints derived from the numerous known organic reactions which capture the molecule-molecule interactions in the form of addition, substitution, rearrangement, elimination and isomerization reactions. The reaction fingerprints were applied to large databases in biology and chemistry, namely ChEMBL, KEGG, HMDB, DSSTox, and the Drug Bank database. A large network of 1113 synthetic reactions was constructed to visualize and ascertain the reactant product mappings in the chemical reaction space. The cumulative reaction fingerprints were computed for 4000 molecules belonging to 29 therapeutic classes of compounds, and these were found capable of discriminating between the cognition disorder related and anti-allergy compounds with reasonable accuracy of 75% and AUC 0.8. In this study, the transition state based fingerprints were also developed and used effectively for virtual screening in drug related databases. The methodology presented here provides an efficient handle for the rapid scoring of molecular libraries for virtual screening.

From 20th century metabolic wall charts to 21st century systems biology: database of mammalian metabolic enzymes

PubMed Central

Corcoran, Callan C.; Grady, Cameron R.; Pisitkun, Trairak; Parulekar, Jaya

2017-01-01

The organization of the mammalian genome into gene subsets corresponding to specific functional classes has provided key tools for systems biology research. Here, we have created a web-accessible resource called the Mammalian Metabolic Enzyme Database (https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/MetabolicEnzymeDatabase.html) keyed to the biochemical reactions represented on iconic metabolic pathway wall charts created in the previous century. Overall, we have mapped 1,647 genes to these pathways, representing ~7 percent of the protein-coding genome. To illustrate the use of the database, we apply it to the area of kidney physiology. In so doing, we have created an additional database (Database of Metabolic Enzymes in Kidney Tubule Segments: https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/), mapping mRNA abundance measurements (mined from RNA-Seq studies) for all metabolic enzymes to each of 14 renal tubule segments. We carry out bioinformatics analysis of the enzyme expression pattern among renal tubule segments and mine various data sources to identify vasopressin-regulated metabolic enzymes in the renal collecting duct. PMID:27974320

LeishCyc: a guide to building a metabolic pathway database and visualization of metabolomic data.

PubMed

Saunders, Eleanor C; MacRae, James I; Naderer, Thomas; Ng, Milica; McConville, Malcolm J; Likić, Vladimir A

2012-01-01

The complexity of the metabolic networks in even the simplest organisms has raised new challenges in organizing metabolic information. To address this, specialized computer frameworks have been developed to capture, manage, and visualize metabolic knowledge. The leading databases of metabolic information are those organized under the umbrella of the BioCyc project, which consists of the reference database MetaCyc, and a number of pathway/genome databases (PGDBs) each focussed on a specific organism. A number of PGDBs have been developed for bacterial, fungal, and protozoan pathogens, greatly facilitating dissection of the metabolic potential of these organisms and the identification of new drug targets. Leishmania are protozoan parasites belonging to the family Trypanosomatidae that cause a broad spectrum of diseases in humans. In this work we use the LeishCyc database, the BioCyc database for Leishmania major, to describe how to build a BioCyc database from genomic sequences and associated annotations. By using metabolomic data generated in our group, we show how such databases can be utilized to elucidate specific changes in parasite metabolism.

Crystallography Open Database – an open-access collection of crystal structures

PubMed Central

Gražulis, Saulius; Chateigner, Daniel; Downs, Robert T.; Yokochi, A. F. T.; Quirós, Miguel; Lutterotti, Luca; Manakova, Elena; Butkus, Justas; Moeck, Peter; Le Bail, Armel

2009-01-01

The Crystallography Open Database (COD), which is a project that aims to gather all available inorganic, metal–organic and small organic molecule structural data in one database, is described. The database adopts an open-access model. The COD currently contains ∼80 000 entries in crystallographic information file format, with nearly full coverage of the International Union of Crystallography publications, and is growing in size and quality. PMID:22477773

Building an R&D chemical registration system.

PubMed

Martin, Elyette; Monge, Aurélien; Duret, Jacques-Antoine; Gualandi, Federico; Peitsch, Manuel C; Pospisil, Pavel

2012-05-31

Small molecule chemistry is of central importance to a number of R&D companies in diverse areas such as the pharmaceutical, nutraceutical, food flavoring, and cosmeceutical industries. In order to store and manage thousands of chemical compounds in such an environment, we have built a state-of-the-art master chemical database with unique structure identifiers. Here, we present the concept and methodology we used to build the system that we call the Unique Compound Database (UCD). In the UCD, each molecule is registered only once (uniqueness), structures with alternative representations are entered in a uniform way (normalization), and the chemical structure drawings are recognizable to chemists and to a cartridge. In brief, structural molecules are entered as neutral entities which can be associated with a salt. The salts are listed in a dictionary and bound to the molecule with the appropriate stoichiometric coefficient in an entity called "substance". The substances are associated with batches. Once a molecule is registered, some properties (e.g., ADMET prediction, IUPAC name, chemical properties) are calculated automatically. The UCD has both automated and manual data controls. Moreover, the UCD concept enables the management of user errors in the structure entry by reassigning or archiving the batches. It also allows updating of the records to include newly discovered properties of individual structures. As our research spans a wide variety of scientific fields, the database enables registration of mixtures of compounds, enantiomers, tautomers, and compounds with unknown stereochemistries.

SuperSweet—a resource on natural and artificial sweetening agents

PubMed Central

Ahmed, Jessica; Preissner, Saskia; Dunkel, Mathias; Worth, Catherine L.; Eckert, Andreas; Preissner, Robert

2011-01-01

A vast number of sweet tasting molecules are known, encompassing small compounds, carbohydrates, d-amino acids and large proteins. Carbohydrates play a particularly big role in human diet. The replacement of sugars in food with artificial sweeteners is common and is a general approach to prevent cavities, obesity and associated diseases such as diabetes and hyperlipidemia. Knowledge about the molecular basis of taste may reveal new strategies to overcome diet-induced diseases. In this context, the design of safe, low-calorie sweeteners is particularly important. Here, we provide a comprehensive collection of carbohydrates, artificial sweeteners and other sweet tasting agents like proteins and peptides. Additionally, structural information and properties such as number of calories, therapeutic annotations and a sweetness-index are stored in SuperSweet. Currently, the database consists of more than 8000 sweet molecules. Moreover, the database provides a modeled 3D structure of the sweet taste receptor and binding poses of the small sweet molecules. These binding poses provide hints for the design of new sweeteners. A user-friendly graphical interface allows similarity searching, visualization of docked sweeteners into the receptor etc. A sweetener classification tree and browsing features allow quick requests to be made to the database. The database is freely available at: http://bioinformatics.charite.de/sweet/. PMID:20952410

SuperSweet--a resource on natural and artificial sweetening agents.

PubMed

Ahmed, Jessica; Preissner, Saskia; Dunkel, Mathias; Worth, Catherine L; Eckert, Andreas; Preissner, Robert

2011-01-01

A vast number of sweet tasting molecules are known, encompassing small compounds, carbohydrates, d-amino acids and large proteins. Carbohydrates play a particularly big role in human diet. The replacement of sugars in food with artificial sweeteners is common and is a general approach to prevent cavities, obesity and associated diseases such as diabetes and hyperlipidemia. Knowledge about the molecular basis of taste may reveal new strategies to overcome diet-induced diseases. In this context, the design of safe, low-calorie sweeteners is particularly important. Here, we provide a comprehensive collection of carbohydrates, artificial sweeteners and other sweet tasting agents like proteins and peptides. Additionally, structural information and properties such as number of calories, therapeutic annotations and a sweetness-index are stored in SuperSweet. Currently, the database consists of more than 8000 sweet molecules. Moreover, the database provides a modeled 3D structure of the sweet taste receptor and binding poses of the small sweet molecules. These binding poses provide hints for the design of new sweeteners. A user-friendly graphical interface allows similarity searching, visualization of docked sweeteners into the receptor etc. A sweetener classification tree and browsing features allow quick requests to be made to the database. The database is freely available at: http://bioinformatics.charite.de/sweet/.

Computational Modeling as a Design Tool in Microelectronics Manufacturing

NASA Technical Reports Server (NTRS)

Meyyappan, Meyya; Arnold, James O. (Technical Monitor)

1997-01-01

Plans to introduce pilot lines or fabs for 300 mm processing are in progress. The IC technology is simultaneously moving towards 0.25/0.18 micron. The convergence of these two trends places unprecedented stringent demands on processes and equipments. More than ever, computational modeling is called upon to play a complementary role in equipment and process design. The pace in hardware/process development needs a matching pace in software development: an aggressive move towards developing "virtual reactors" is desirable and essential to reduce design cycle and costs. This goal has three elements: reactor scale model, feature level model, and database of physical/chemical properties. With these elements coupled, the complete model should function as a design aid in a CAD environment. This talk would aim at the description of various elements. At the reactor level, continuum, DSMC(or particle) and hybrid models will be discussed and compared using examples of plasma and thermal process simulations. In microtopography evolution, approaches such as level set methods compete with conventional geometric models. Regardless of the approach, the reliance on empricism is to be eliminated through coupling to reactor model and computational surface science. This coupling poses challenging issues of orders of magnitude variation in length and time scales. Finally, database development has fallen behind; current situation is rapidly aggravated by the ever newer chemistries emerging to meet process metrics. The virtual reactor would be a useless concept without an accompanying reliable database that consists of: thermal reaction pathways and rate constants, electron-molecule cross sections, thermochemical properties, transport properties, and finally, surface data on the interaction of radicals, atoms and ions with various surfaces. Large scale computational chemistry efforts are critical as experiments alone cannot meet database needs due to the difficulties associated with such controlled experiments and costs.

Ligand solvation in molecular docking.

PubMed

Shoichet, B K; Leach, A R; Kuntz, I D

1999-01-01

Solvation plays an important role in ligand-protein association and has a strong impact on comparisons of binding energies for dissimilar molecules. When databases of such molecules are screened for complementarity to receptors of known structure, as often occurs in structure-based inhibitor discovery, failure to consider ligand solvation often leads to putative ligands that are too highly charged or too large. To correct for the different charge states and sizes of the ligands, we calculated electrostatic and non-polar solvation free energies for molecules in a widely used molecular database, the Available Chemicals Directory (ACD). A modified Born equation treatment was used to calculate the electrostatic component of ligand solvation. The non-polar component of ligand solvation was calculated based on the surface area of the ligand and parameters derived from the hydration energies of apolar ligands. These solvation energies were subtracted from the ligand-receptor interaction energies. We tested the usefulness of these corrections by screening the ACD for molecules that complemented three proteins of known structure, using a molecular docking program. Correcting for ligand solvation improved the rankings of known ligands and discriminated against molecules with inappropriate charge states and sizes.

Mutations and Deregulation of Ras/Raf/MEK/ERK and PI3K/PTEN/Akt/mTOR Cascades Which Alter Therapy Response

PubMed Central

McCubrey, James A.; Steelman, Linda S.; Chappell, William H.; Abrams, Stephen L.; Montalto, Giuseppe; Cervello, Melchiorre; Nicoletti, Ferdinando; Fagone, Paolo; Malaponte, Grazia; Mazzarino, Maria C.; Candido, Saverio; Libra, Massimo; Bäsecke, Jörg; Mijatovic, Sanja; Maksimovic-Ivanic, Danijela; Milella, Michele; Tafuri, Agostino; Cocco, Lucio; Evangelisti, Camilla; Chiarini, Francesca; Martelli, Alberto M.

2012-01-01

The Ras/Raf/MEK/ERK and PI3K/PTEN/Akt/mTOR cascades are often activated by genetic alterations in upstream signaling molecules such as receptor tyrosine kinases (RTK). Certain components of these pathways, RAS, NF1, BRAF, MEK1, DUSP5, PP2A, PIK3CA, PIK3R1, PIK3R4, PIK3R5, IRS4, AKT, NFKB1, MTOR, PTEN, TSC1, and TSC2 may also be activated/inactivated by mutations or epigenetic silencing. Upstream mutations in one signaling pathway or even in downstream components of the same pathway can alter the sensitivity of the cells to certain small molecule inhibitors. These pathways have profound effects on proliferative, apoptotic and differentiation pathways. Dysregulation of components of these cascades can contribute to: resistance to other pathway inhibitors, chemotherapeutic drug resistance, premature aging as well as other diseases. This review will first describe these pathways and discuss how genetic mutations and epigenetic alterations can result in resistance to various inhibitors. PMID:23006971

KEGGtranslator: visualizing and converting the KEGG PATHWAY database to various formats.

PubMed

Wrzodek, Clemens; Dräger, Andreas; Zell, Andreas

2011-08-15

The KEGG PATHWAY database provides a widely used service for metabolic and nonmetabolic pathways. It contains manually drawn pathway maps with information about the genes, reactions and relations contained therein. To store these pathways, KEGG uses KGML, a proprietary XML-format. Parsers and translators are needed to process the pathway maps for usage in other applications and algorithms. We have developed KEGGtranslator, an easy-to-use stand-alone application that can visualize and convert KGML formatted XML-files into multiple output formats. Unlike other translators, KEGGtranslator supports a plethora of output formats, is able to augment the information in translated documents (e.g. MIRIAM annotations) beyond the scope of the KGML document, and amends missing components to fragmentary reactions within the pathway to allow simulations on those. KEGGtranslator is freely available as a Java(™) Web Start application and for download at http://www.cogsys.cs.uni-tuebingen.de/software/KEGGtranslator/. KGML files can be downloaded from within the application. clemens.wrzodek@uni-tuebingen.de Supplementary data are available at Bioinformatics online.

HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

PubMed

Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

2015-04-01

The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.

Consensus and conflict cards for metabolic pathway databases

PubMed Central

2013-01-01

Background The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. Results We introduce the concept of Consensus and Conflict Cards (C2Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C2CardsHuman, as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. Conclusions C2Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C2Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement. PMID:23803311

Consensus and conflict cards for metabolic pathway databases.

PubMed

Stobbe, Miranda D; Swertz, Morris A; Thiele, Ines; Rengaw, Trebor; van Kampen, Antoine H C; Moerland, Perry D

2013-06-26

The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. We introduce the concept of Consensus and Conflict Cards (C₂Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C₂Cards(Human), as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. C₂Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C₂Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement.

Observing the conformation of individual SNARE proteins inside live cells

NASA Astrophysics Data System (ADS)

Weninger, Keith

2010-10-01

Protein conformational dynamics are directly linked to function in many instances. Within living cells, protein dynamics are rarely synchronized so observing ensemble-averaged behaviors can hide details of signaling pathways. Here we present an approach using single molecule fluorescence resonance energy transfer (FRET) to observe the conformation of individual SNARE proteins as they fold to enter the SNARE complex in living cells. Proteins were recombinantly expressed, labeled with small-molecule fluorescent dyes and microinjected for in vivo imaging and tracking using total internal reflection microscopy. Observing single molecules avoids the difficulties of averaging over unsynchronized ensembles. Our approach is easily generalized to a wide variety of proteins in many cellular signaling pathways.

Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

PubMed Central

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-01-01

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259

Real-time ligand binding pocket database search using local surface descriptors.

PubMed

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-07-01

Because of the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two-dimensional pseudo-Zernike moments or the three-dimensional Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark studies employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed.

Chembank | Office of Cancer Genomics

Cancer.gov

Funded in large part by the Initiative for Chemical Genetics (ICG), Chembank is an interactive database for small molecules. It contains data from hundreds of biomedically relevant small molecule screens that involved hundreds-of-thousands of compounds. Chembank also provides analysis tools to facilitate data mining.

Platelet-derived growth factor receptor mediates activation of ras through different signaling pathways in different cell types.

PubMed Central

Satoh, T; Fantl, W J; Escobedo, J A; Williams, L T; Kaziro, Y

1993-01-01

A series of pieces of evidence have shown that Ras protein acts as a transducer of the platelet-derived growth factor (PDGF) receptor-mediated signaling pathway: (i) formation of Ras.GTP is detected immediately on PDGF stimulation, and (ii) a dominant inhibitory mutant Ras, as well as a neutralizing anti-Ras antibody, can interfere with PDGF-induced responses. On the other hand, several signal transducing molecules including phosphatidylinositol 3-kinase (PI3-K), GTPase-activating protein (GAP), and phospholipase C gamma (PLC gamma) bind directly to the PDGF receptor and become tyrosine phosphorylated. Recently, it was shown that specific phosphorylated tyrosines of the PDGF receptor are responsible for interaction between the receptor and each signaling molecule. However, the roles of these signaling molecules have not been elucidated, and it remains unclear which molecules are implicated in the Ras pathway. In this study, we measured Ras activation in cell lines expressing mutant PDGF receptors that are deficient in coupling with specific molecules. In fibroblast CHO cells, a mutant receptor (Y708F/Y719F [PI3-K-binding sites]) was unable to stimulate Ras, whereas another mutant (Y739F [the GAP-binding site]) could do so, suggesting an indispensable role of PI3-K or a protein that binds to the same sites as PI3-K for PDGF-stimulated Ras activation. By contrast, both of the above mutants were capable of stimulating Ras protein in a pro-B-cell line, BaF3. Furthermore, a mutant receptor (Y977F/Y989F [PLC gamma-binding sites]) could fully activate Ras, and the direct activation of protein kinase C and calcium mobilization had almost no effect on the GDP/GTP state of Ras in this cell line. These results suggest that, in the pro-B-cell transfectants, each of the above pathways (PI3-K, GAP, and PLC gamma) can be eliminated without a loss of Ras activation. It remains unclear whether another unknown essential pathway which regulates Ras protein exists within BaF3 cells. Therefore, it is likely that several different PDGF receptor-mediated signaling pathways function upstream of Ras, and the extent of the contribution of each pathway for the regulation of Ras may differ among different cell types. Images PMID:8388543

Towards the identification and quantification of candidate metabolites of tebuconazole fungicide.

NASA Astrophysics Data System (ADS)

El Azhari, Najoi; Dermou, Eftychia; Botteri, Lucio; Lucini, Luigi; Karas, Panagiotis; Karpouzas, Dimitris; Tsiamis, George; Martin-Laurent, Fabrice; Trevisan, Marco; Rossi, Riccardo; Ferrari, Federico

2017-04-01

Tebuconazole belongs to the family of triazole fungicides, used for crop protection and human health applications. In the environment, the dissipation of the parent molecule leads to the formation of metabolites that are of unknown identity or toxicity. In order to identify and determine the putative identity of those metabolites and their po- tential toxicity, a quadrupole time-of-flight (Q-TOF) approach is often used. Q-SAR ap- proaches help to predict their toxicity by comparing them to a known database of mole- cules with known properties. All together the information on the candidate by-products may help to select relevant sub-set of metabolites for further quantification by LC or GC coupled with MS. It is thereby possible to select putative toxic compounds for further quanti- fication using chemical analysis. Previous work allowed the identification of potential metabolites of tebuconazole. Triazole, triazolyl acetic acid and p-chlorophenol were suspected to result from the decomposition of tebuconazole. Tebuconazole degradation kinetics was followed for 125 days by quanti- fying the dissipation of the parent molecule and the emergence of the three candidate metabolites by LC/MS for tebuconazole, triazol and triazolyl acetate and by GC/MS for p- chlorophenol. The data allowed the proposition of several metabolic pathways.

Mechanisms and time-resolved dynamics for trihydrogen cation (H 3 +) formation from organic molecules in strong laser fields

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

Ekanayake, Nagitha; Nairat, Muath; Kaderiya, Balram

Strong-field laser-matter interactions often lead to exotic chemical reactions. Trihydrogen cation formation from organic molecules is one such case that requires multiple bonds to break and form. Here, we present evidence for the existence of two different reaction pathways for H 3 + formation from organic molecules irradiated by a strong-field laser. Assignment of the two pathways was accomplished through analysis of femtosecond time-resolved strong-field ionization and photoion-photoion coincidence measurements carried out on methanol isotopomers, ethylene glycol, and acetone. Ab initio molecular dynamics simulations suggest the formation occurs via two steps: the initial formation of a neutral hydrogen molecule, followedmore » by the abstraction of a proton from the remaining CHOH 2+ fragment by the roaming H 2 molecule. This reaction has similarities to the H 2+H 2 + mechanism leading to formation of H 3 + in the universe. These exotic chemical reaction mechanisms, involving roaming H 2 molecules, are found to occur in the ~100 fs timescale. Roaming molecule reactions may help to explain unlikely chemical processes, involving dissociation and formation of multiple chemical bonds, occurring under strong laser fields.« less

Mechanisms and time-resolved dynamics for trihydrogen cation (H 3 +) formation from organic molecules in strong laser fields

DOE PAGES

Ekanayake, Nagitha; Nairat, Muath; Kaderiya, Balram; ...

2017-07-05

Strong-field laser-matter interactions often lead to exotic chemical reactions. Trihydrogen cation formation from organic molecules is one such case that requires multiple bonds to break and form. Here, we present evidence for the existence of two different reaction pathways for H 3 + formation from organic molecules irradiated by a strong-field laser. Assignment of the two pathways was accomplished through analysis of femtosecond time-resolved strong-field ionization and photoion-photoion coincidence measurements carried out on methanol isotopomers, ethylene glycol, and acetone. Ab initio molecular dynamics simulations suggest the formation occurs via two steps: the initial formation of a neutral hydrogen molecule, followedmore » by the abstraction of a proton from the remaining CHOH 2+ fragment by the roaming H 2 molecule. This reaction has similarities to the H 2+H 2 + mechanism leading to formation of H 3 + in the universe. These exotic chemical reaction mechanisms, involving roaming H 2 molecules, are found to occur in the ~100 fs timescale. Roaming molecule reactions may help to explain unlikely chemical processes, involving dissociation and formation of multiple chemical bonds, occurring under strong laser fields.« less

A novel method to identify pathways associated with renal cell carcinoma based on a gene co-expression network

PubMed Central

RUAN, XIYUN; LI, HONGYUN; LIU, BO; CHEN, JIE; ZHANG, SHIBAO; SUN, ZEQIANG; LIU, SHUANGQING; SUN, FAHAI; LIU, QINGYONG

2015-01-01

The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson’s correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson’s correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425

Effect of Ring Strain on the Charge Transport of a Robust Norbornadiene–Quadricyclane-Based Molecular Photoswitch

PubMed Central

2017-01-01

Integrating functional molecules into single-molecule devices is a key step toward the realization of future computing machines based on the smallest possible components. In this context, photoswitching molecules that can make a transition between high and low conductivity in response to light are attractive candidates. Here we present the synthesis and conductance properties of a new type of robust molecular photothermal switch based on the norbornadiene (NB)–quadricyclane (QC) system. The transport through the molecule in the ON state is dominated by a pathway through the π-conjugated system, which is no longer available when the system is switched to the OFF state. Interestingly, in the OFF state we find that the same pathway contributes only 12% to the transport properties. We attribute this observation to the strained tetrahedral geometry of the QC. These results challenge the prevailing assumption that current will simply flow through the shortest through-bond path in a molecule. PMID:28408968

The coffee diterpene kahweol inhibits tumor necrosis factor-{alpha}-induced expression of cell adhesion molecules in human endothelial cells

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

Kim, Hyung Gyun; Kim, Ji Young; Hwang, Yong Pil

2006-12-15

Endothelial cells produce adhesion molecules after being stimulated with various inflammatory cytokines. These adhesion molecules play an important role in the development of atherogenesis. Recent studies have highlighted the chemoprotective and anti-inflammatory effects of kahweol, a coffee-specific diterpene. This study examined the effects of kahweol on the cytokine-induced monocyte/human endothelial cell interaction, which is a crucial early event in atherogenesis. Kahweol inhibited the adhesion of TNF{alpha}-induced monocytes to endothelial cells and suppressed the TNF{alpha}-induced protein and mRNA expression of the cell adhesion molecules, VCAM-1 and ICAM-1. Furthermore, kahweol inhibited the TNF{alpha}-induced JAK2-PI3K/Akt-NF-{kappa}B activation pathway in these cells. Overall, kahweol hasmore » anti-inflammatory and anti-atherosclerotic activities, which occurs partly by down-regulating the pathway that affects the expression and interaction of the cell adhesion molecules on endothelial cells.« less

Analysis of commercial and public bioactivity databases.

PubMed

Tiikkainen, Pekka; Franke, Lutz

2012-02-27

Activity data for small molecules are invaluable in chemoinformatics. Various bioactivity databases exist containing detailed information of target proteins and quantitative binding data for small molecules extracted from journals and patents. In the current work, we have merged several public and commercial bioactivity databases into one bioactivity metabase. The molecular presentation, target information, and activity data of the vendor databases were standardized. The main motivation of the work was to create a single relational database which allows fast and simple data retrieval by in-house scientists. Second, we wanted to know the amount of overlap between databases by commercial and public vendors to see whether the former contain data complementing the latter. Third, we quantified the degree of inconsistency between data sources by comparing data points derived from the same scientific article cited by more than one vendor. We found that each data source contains unique data which is due to different scientific articles cited by the vendors. When comparing data derived from the same article we found that inconsistencies between the vendors are common. In conclusion, using databases of different vendors is still useful since the data overlap is not complete. It should be noted that this can be partially explained by the inconsistencies and errors in the source data.

The formation of urea in space. I. Ion-molecule, neutral-neutral, and radical gas-phase reactions

NASA Astrophysics Data System (ADS)

Brigiano, Flavio Siro; Jeanvoine, Yannick; Largo, Antonio; Spezia, Riccardo

2018-02-01

Context. Many organic molecules have been observed in the interstellar medium thanks to advances in radioastronomy, and very recently the presence of urea was also suggested. While those molecules were observed, it is not clear what the mechanisms responsible to their formation are. In fact, if gas-phase reactions are responsible, they should occur through barrierless mechanisms (or with very low barriers). In the past, mechanisms for the formation of different organic molecules were studied, providing only in a few cases energetic conditions favorable to a synthesis at very low temperature. A particularly intriguing class of such molecules are those containing one N-C-O peptide bond, which could be a building block for the formation of biological molecules. Urea is a particular case because two nitrogen atoms are linked to the C-O moiety. Thus, motivated also by the recent tentative observation of urea, we have considered the synthetic pathways responsible to its formation. Aims: We have studied the possibility of forming urea in the gas phase via different kinds of bi-molecular reactions: ion-molecule, neutral, and radical. In particular we have focused on the activation energy of these reactions in order to find possible reactants that could be responsible for to barrierless (or very low energy) pathways. Methods: We have used very accurate, highly correlated quantum chemistry calculations to locate and characterize the reaction pathways in terms of minima and transition states connecting reactants to products. Results: Most of the reactions considered have an activation energy that is too high; but the ion-molecule reaction between NH2OHNH2OH2+ and formamide is not too high. These reactants could be responsible not only for the formation of urea but also of isocyanic acid, which is an organic molecule also observed in the interstellar medium.

Does the Loss of Stromal Caveolin-1 Remodel the Tumor Microenvironment by Activating Src-Mediated PEAK1 and PI3K Pathways

DTIC Science & Technology

2016-09-01

Inhibition of MAP kinase pathway prevents plasma protrusions Next we used a selective inhibitor of MAP kinases , PD98059, to address whether we can...from human patients harbor AKT1 and that AKT1 kinase activity is sustained in these particles, nominating them as active signaling platforms...with the extracellular matrix (ECM) and extracellular molecules (2). Though many classic extracellular signaling molecules (e.g., hormones, peptide

Novel insights into systemic autoimmune rheumatic diseases using shared molecular signatures and an integrative analysis.

PubMed

Hudson, Marie; Bernatsky, Sasha; Colmegna, Ines; Lora, Maximilien; Pastinen, Tomi; Klein Oros, Kathleen; Greenwood, Celia M T

2017-06-03

We undertook this study to identify DNA methylation signatures of three systemic autoimmune rheumatic diseases (SARDs), namely rheumatoid arthritis, systemic lupus erythematosus, and systemic sclerosis, compared to healthy controls. Using a careful design to minimize confounding, we restricted our study to subjects with incident disease and performed our analyses on purified CD4 + T cells, key effector cells in SARD. We identified differentially methylated (using the Illumina Infinium HumanMethylation450 BeadChip array) and expressed (using the Illumina TruSeq stranded RNA-seq protocol) sites between cases and controls, and investigated the biological significance of this SARD signature using gene annotation databases. We recruited 13 seropositive rheumatoid arthritis, 19 systemic sclerosis, 12 systemic lupus erythematosus subjects, and 8 healthy controls. We identified 33 genes that were both differentially methylated and expressed (26 over- and 7 under-expressed) in SARD cases versus controls. The most highly overexpressed gene was CD1C (log fold change in expression = 1.85, adjusted P value = 0.009). In functional analysis (Ingenuity Pathway Analysis), the top network identified was lipid metabolism, molecular transport, small molecule biochemistry. The top canonical pathways included the mitochondrial L-carnitine shuttle pathway (P = 5E-03) and PTEN signaling (P = 8E-03). The top upstream regulator was HNF4A (P = 3E-05). This novel SARD signature contributes to ongoing work to further our understanding of the molecular mechanisms underlying SARD and provides novel targets of interest.

BiKEGG: a COBRA toolbox extension for bridging the BiGG and KEGG databases.

PubMed

Jamialahmadi, Oveis; Motamedian, Ehsan; Hashemi-Najafabadi, Sameereh

2016-10-18

Development of an interface tool between the Biochemical, Genetic and Genomic (BiGG) and KEGG databases is necessary for simultaneous access to the features of both databases. For this purpose, we present the BiKEGG toolbox, an open source COBRA toolbox extension providing a set of functions to infer the reaction correspondences between the KEGG reaction identifiers and those in the BiGG knowledgebase using a combination of manual verification and computational methods. Inferred reaction correspondences using this approach are supported by evidence from the literature, which provides a higher number of reconciled reactions between these two databases compared to the MetaNetX and MetRxn databases. This set of equivalent reactions is then used to automatically superimpose the predicted fluxes using COBRA methods on classical KEGG pathway maps or to create a customized metabolic map based on the KEGG global metabolic pathway, and to find the corresponding reactions in BiGG based on the genome annotation of an organism in the KEGG database. Customized metabolic maps can be created for a set of pathways of interest, for the whole KEGG global map or exclusively for all pathways for which there exists at least one flux carrying reaction. This flexibility in visualization enables BiKEGG to indicate reaction directionality as well as to visualize the reaction fluxes for different static or dynamic conditions in an animated manner. BiKEGG allows the user to export (1) the output visualized metabolic maps to various standard image formats or save them as a video or animated GIF file, and (2) the equivalent reactions for an organism as an Excel spreadsheet.

Attosecond Coherent Control of the Photo-Dissociation of Oxygen Molecules

NASA Astrophysics Data System (ADS)

Sturm, Felix; Ray, Dipanwita; Wright, Travis; Shivaram, Niranjan; Bocharova, Irina; Slaughter, Daniel; Ranitovic, Predrag; Belkacem, Ali; Weber, Thorsten

2016-05-01

Attosecond Coherent Control has emerged in recent years as a technique to manipulate the absorption and ionization in atoms as well as the dissociation of molecules on an attosecond time scale. Single attosecond pulses and attosecond pulse trains (APTs) can coherently excite multiple electronic states. The electronic and nuclear wave packets can then be coupled with a second pulse forming multiple interfering quantum pathways. We have built a high flux extreme ultraviolet (XUV) light source delivering APTs based on HHG that allows to selectively excite neutral and ion states in molecules. Our beamline provides spectral selectivity and attosecond interferometric control of the pulses. In the study presented here, we use APTs, generated by High Harmonic Generation in a high flux extreme ultraviolet light source, to ionize highly excited states of oxygen molecules. We identify the ionization/dissociation pathways revealing vibrational structure with ultra-high resolution ion 3D-momentum imaging spectroscopy. Furthermore, we introduce a delay between IR pulses and XUV/IR pulses to constructively or destructively interfere the ionization and dissociation pathways, thus, enabling the manipulation of both the O2+and the O+ ion yields with attosecond precision. Supported by DOE under Contract No. DE-AC02-05CH11231.

The care pathway: concepts and theories: an introduction.

PubMed

Schrijvers, Guus; van Hoorn, Arjan; Huiskes, Nicolette

2012-01-01

This article addresses first the definition of a (care) pathway, and then follows a description of theories since the 1950s. It ends with a discussion of theoretical advantages and disadvantages of care pathways for patients and professionals. The objective of this paper is to provide a theoretical base for empirical studies on care pathways. The knowledge for this chapter is based on several books on pathways, which we found by searching in the digital encyclopedia Wikipedia. Although this is not usual in scientific publications, this method was used because books are not searchable by databases as Pubmed. From 2005, we performed a literature search on Pubmed and other literature databases, and with the keywords integrated care pathway, clinical pathway, critical pathway, theory, research, and evaluation. One of the inspirational sources was the website of the European Pathway Association (EPA) and its journal International Journal of Care Pathways. The authors visited several sites for this paper. These are mentioned as illustration of a concept or theory. Most of them have English websites with more information. The URLs of these websites are not mentioned in this paper as a reference, because the content of them changes fast, sometimes every day.

The care pathway: concepts and theories: an introduction

PubMed Central

Schrijvers, Guus; van Hoorn, Arjan; Huiskes, Nicolette

2012-01-01

This article addresses first the definition of a (care) pathway, and then follows a description of theories since the 1950s. It ends with a discussion of theoretical advantages and disadvantages of care pathways for patients and professionals. The objective of this paper is to provide a theoretical base for empirical studies on care pathways. The knowledge for this chapter is based on several books on pathways, which we found by searching in the digital encyclopedia Wikipedia. Although this is not usual in scientific publications, this method was used because books are not searchable by databases as Pubmed. From 2005, we performed a literature search on Pubmed and other literature databases, and with the keywords integrated care pathway, clinical pathway, critical pathway, theory, research, and evaluation. One of the inspirational sources was the website of the European Pathway Association (EPA) and its journal International Journal of Care Pathways. The authors visited several sites for this paper. These are mentioned as illustration of a concept or theory. Most of them have English websites with more information. The URLs of these websites are not mentioned in this paper as a reference, because the content of them changes fast, sometimes every day. PMID:23593066

Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology

PubMed Central

Paley, Suzanne M.; Krummenacker, Markus; Latendresse, Mario; Dale, Joseph M.; Lee, Thomas J.; Kaipa, Pallavi; Gilham, Fred; Spaulding, Aaron; Popescu, Liviu; Altman, Tomer; Paulsen, Ian; Keseler, Ingrid M.; Caspi, Ron

2010-01-01

Pathway Tools is a production-quality software environment for creating a type of model-organism database called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc integrates the evolving understanding of the genes, proteins, metabolic network and regulatory network of an organism. This article provides an overview of Pathway Tools capabilities. The software performs multiple computational inferences including prediction of metabolic pathways, prediction of metabolic pathway hole fillers and prediction of operons. It enables interactive editing of PGDBs by DB curators. It supports web publishing of PGDBs, and provides a large number of query and visualization tools. The software also supports comparative analyses of PGDBs, and provides several systems biology analyses of PGDBs including reachability analysis of metabolic networks, and interactive tracing of metabolites through a metabolic network. More than 800 PGDBs have been created using Pathway Tools by scientists around the world, many of which are curated DBs for important model organisms. Those PGDBs can be exchanged using a peer-to-peer DB sharing system called the PGDB Registry. PMID:19955237

A geographically-diverse collection of 418 human gut microbiome pathway genome databases

PubMed Central

Hahn, Aria S.; Altman, Tomer; Konwar, Kishori M.; Hanson, Niels W.; Kim, Dongjae; Relman, David A.; Dill, David L.; Hallam, Steven J.

2017-01-01

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools. PMID:28398290

Informatics for Metabolomics.

PubMed

Kusonmano, Kanthida; Vongsangnak, Wanwipa; Chumnanpuen, Pramote

2016-01-01

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

Computational exploration of the chemical structure space of possible reverse tricarboxylic acid cycle constituents.

PubMed

Meringer, Markus; Cleaves, H James

2017-12-13

The reverse tricarboxylic acid (rTCA) cycle has been explored from various standpoints as an idealized primordial metabolic cycle. Its simplicity and apparent ubiquity in diverse organisms across the tree of life have been used to argue for its antiquity and its optimality. In 2000 it was proposed that chemoinformatics approaches support some of these views. Specifically, defined queries of the Beilstein database showed that the molecules of the rTCA are heavily represented in such compound databases. We explore here the chemical structure "space," e.g. the set of organic compounds which possesses some minimal set of defining characteristics, of the rTCA cycle's intermediates using an exhaustive structure generation method. The rTCA's chemical space as defined by the original criteria and explored by our method is some six to seven times larger than originally considered. Acknowledging that each assumption in what is a defining criterion making the rTCA cycle special limits possible generative outcomes, there are many unrealized compounds which fulfill these criteria. That these compounds are unrealized could be due to evolutionary frozen accidents or optimization, though this optimization may also be for systems-level reasons, e.g., the way the pathway and its elements interface with other aspects of metabolism.

Exploration of natural product ingredients as inhibitors of human HMG-CoA reductase through structure-based virtual screening.

PubMed

Lin, Shih-Hung; Huang, Kao-Jean; Weng, Ching-Feng; Shiuan, David

2015-01-01

Cholesterol plays an important role in living cells. However, a very high level of cholesterol may lead to atherosclerosis. HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase is the key enzyme in the cholesterol biosynthesis pathway, and the statin-like drugs are inhibitors of human HMG-CoA reductase (hHMGR). The present study aimed to virtually screen for potential hHMGR inhibitors from natural product to discover hypolipidemic drug candidates with fewer side effects and lesser toxicities. We used the 3D structure 1HWK from the PDB (Protein Data Bank) database of hHMGR as the target to screen for the strongly bound compounds from the traditional Chinese medicine database. Many interesting molecules including polyphenolic compounds, polisubstituted heterocyclics, and linear lipophilic alcohols were identified and their ADMET (absorption, disrtibution, metabolism, excretion, toxicity) properties were predicted. Finally, four compounds were obtained for the in vitro validation experiments. The results indicated that curcumin and salvianolic acid C can effectively inhibit hHMGR, with IC50 (half maximal inhibitory concentration) values of 4.3 µM and 8 µM, respectively. The present study also demonstrated the feasibility of discovering new drug candidates through structure-based virtual screening.

Design and engineering of photosynthetic light-harvesting and electron transfer using length, time, and energy scales.

PubMed

Noy, Dror; Moser, Christopher C; Dutton, P Leslie

2006-02-01

Decades of research on the physical processes and chemical reaction-pathways in photosynthetic enzymes have resulted in an extensive database of kinetic information. Recently, this database has been augmented by a variety of high and medium resolution crystal structures of key photosynthetic enzymes that now include the two photosystems (PSI and PSII) of oxygenic photosynthetic organisms. Here, we examine the currently available structural and functional information from an engineer's point of view with the long-term goal of reproducing the key features of natural photosystems in de novo designed and custom-built molecular solar energy conversion devices. We find that the basic physics of the transfer processes, namely, the time constraints imposed by the rates of incoming photon flux and the various decay processes allow for a large degree of tolerance in the engineering parameters. Moreover, we find that the requirements to guarantee energy and electron transfer rates that yield high efficiency in natural photosystems are largely met by control of distance between chromophores and redox cofactors. Thus, for projected de novo designed constructions, the control of spatial organization of cofactor molecules within a dense array is initially given priority. Nevertheless, constructions accommodating dense arrays of different cofactors, some well within 1 nm from each other, still presents a significant challenge for protein design.

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks

PubMed Central

Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways. PMID:29049295

A Model of an Integrated Immune System Pathway in Homo sapiens and Its Interaction with Superantigen Producing Expression Regulatory Pathway in Staphylococcus aureus: Comparing Behavior of Pathogen Perturbed and Unperturbed Pathway

PubMed Central

Tomar, Namrata; De, Rajat K.

2013-01-01

Response of an immune system to a pathogen attack depends on the balance between the host immune defense and the virulence of the pathogen. Investigation of molecular interactions between the proteins of a host and a pathogen helps in identifying the pathogenic proteins. It is necessary to understand the dynamics of a normally behaved host system to evaluate the capacity of its immune system upon pathogen attack. In this study, we have compared the behavior of an unperturbed and pathogen perturbed host system. Moreover, we have developed a formalism under Flux Balance Analysis (FBA) for the optimization of conflicting objective functions. We have constructed an integrated pathway system, which includes Staphylococcal Superantigen (SAg) expression regulatory pathway and TCR signaling pathway of Homo sapiens. We have implemented the method on this pathway system and observed the behavior of host signaling molecules upon pathogen attack. The entire study has been divided into six different cases, based on the perturbed/unperturbed conditions. In other words, we have investigated unperturbed and pathogen perturbed human TCR signaling pathway, with different combinations of optimization of concentrations of regulatory and signaling molecules. One of these cases has aimed at finding out whether minimization of the toxin production in a pathogen leads to the change in the concentration levels of the proteins coded by TCR signaling pathway genes in the infected host. Based on the computed results, we have hypothesized that the balance between TCR signaling inhibitory and stimulatory molecules can keep TCR signaling system into resting/stimulating state, depending upon the perturbation. The proposed integrated host-pathogen interaction pathway model has accurately reflected the experimental evidences, which we have used for validation purpose. The significance of this kind of investigation lies in revealing the susceptible interaction points that can take back the Staphylococcal Enterotoxin (SE)-challenged system within the range of normal behavior. PMID:24324645

Computational active site analysis of molecular pathways to improve functional classification of enzymes.

PubMed

Ozyurt, A Sinem; Selby, Thomas L

2008-07-01

This study describes a method to computationally assess the function of homologous enzymes through small molecule binding interaction energy. Three experimentally determined X-ray structures and four enzyme models from ornithine cyclo-deaminase, alanine dehydrogenase, and mu-crystallin were used in combination with nine small molecules to derive a function score (FS) for each enzyme-model combination. While energy values varied for a single molecule-enzyme combination due to differences in the active sites, we observe that the binding energies for the entire pathway were proportional for each set of small molecules investigated. This proportionality of energies for a reaction pathway appears to be dependent on the amino acids in the active site and their direct interactions with the small molecules, which allows a function score (FS) to be calculated to assess the specificity of each enzyme. Potential of mean force (PMF) calculations were used to obtain the energies, and the resulting FS values demonstrate that a measurement of function may be obtained using differences between these PMF values. Additionally, limitations of this method are discussed based on: (a) larger substrates with significant conformational flexibility; (b) low homology enzymes; and (c) open active sites. This method should be useful in accurately predicting specificity for single enzymes that have multiple steps in their reactions and in high throughput computational methods to accurately annotate uncharacterized proteins based on active site interaction analysis. 2008 Wiley-Liss, Inc.

FXIa and platelet polyphosphate as therapeutic targets during human blood clotting on collagen/tissue factor surfaces under flow

PubMed Central

Zhu, Shu; Travers, Richard J.; Morrissey, James H.

2015-01-01

Factor XIIa (FXIIa) and factor XIa (FXIa) contribute to thrombosis in animal models, whereas platelet-derived polyphosphate (polyP) may potentiate contact or thrombin-feedback pathways. The significance of these mediators in human blood under thrombotic flow conditions on tissue factor (TF) –bearing surfaces remains inadequately resolved. Human blood (corn trypsin inhibitor treated [4 μg/mL]) was tested by microfluidic assay for clotting on collagen/TF at TF surface concentration ([TF]wall) from ∼0.1 to 2 molecules per μm2. Anti-FXI antibodies (14E11 and O1A6) or polyP-binding protein (PPXbd) were used to block FXIIa-dependent FXI activation, FXIa-dependent factor IX (FIX) activation, or platelet-derived polyP, respectively. Fibrin formation was sensitive to 14E11 at 0 to 0.1 molecules per µm2 and sensitive to O1A6 at 0 to 0.2 molecules per µm2. However, neither antibody reduced fibrin generation at ∼2 molecules per µm2 when the extrinsic pathway became dominant. Interestingly, PPXbd reduced fibrin generation at low [TF]wall (0.1 molecules per µm2) but not at zero or high [TF]wall, suggesting a role for polyP distinct from FXIIa activation and requiring low extrinsic pathway participation. Regardless of [TF]wall, PPXbd enhanced fibrin sensitivity to tissue plasminogen activator and promoted clot retraction during fibrinolysis concomitant with an observed PPXbd-mediated reduction of fibrin fiber diameter. This is the first detection of endogenous polyP function in human blood under thrombotic flow conditions. When triggered by low [TF]wall, thrombosis may be druggable by contact pathway inhibition, although thrombolytic susceptibility may benefit from polyP antagonism regardless of [TF]wall. PMID:26136249

Transcriptome exploration of the sex pheromone gland of Lutzomyia longipalpis (Diptera: Psychodidae: Phlebotominae).

PubMed

González-Caballero, Natalia; Valenzuela, Jesus G; Ribeiro, José M C; Cuervo, Patricia; Brazil, Reginaldo P

2013-03-07

Molecules involved in pheromone biosynthesis may represent alternative targets for insect population control. This may be particularly useful in managing the reproduction of Lutzomyia longipalpis, the main vector of the protozoan parasite Leishmania infantum in Latin America. Besides the chemical identity of the major components of the L. longipalpis sex pheromone, there is no information regarding the molecular biology behind its production. To understand this process, obtaining information on which genes are expressed in the pheromone gland is essential. In this study we used a transcriptomic approach to explore the pheromone gland and adjacent abdominal tergites in order to obtain substantial general sequence information. We used a laboratory-reared L. longipalpis (one spot, 9-Methyl GermacreneB) population, captured in Lapinha Cave, state of Minas Gerais, Brazil for this analysis. From a total of 3,547 cDNA clones, 2,502 high quality sequences from the pheromone gland and adjacent tissues were obtained and assembled into 1,387 contigs. Through blast searches of public databases, a group of transcripts encoding proteins potentially involved in the production of terpenoid precursors were identified in the 4th abdominal tergite, the segment containing the pheromone gland. Among them, protein-coding transcripts for four enzymes of the mevalonate pathway such as 3-hydroxyl-3-methyl glutaryl CoA reductase, phosphomevalonate kinase, diphosphomevalonate descarboxylase, and isopentenyl pyrophosphate isomerase were identified. Moreover, transcripts coding for farnesyl diphosphate synthase and NADP+ dependent farnesol dehydrogenase were also found in the same tergite. Additionally, genes potentially involved in pheromone transportation were identified from the three abdominal tergites analyzed. This study constitutes the first transcriptomic analysis exploring the repertoire of genes expressed in the tissue containing the L. longipalpis pheromone gland as well as the flanking tissues. Using a comparative approach, a set of molecules potentially present in the mevalonate pathway emerge as interesting subjects for further study regarding their association to pheromone biosynthesis. The sequences presented here may be used as a reference set for future research on pheromone production or other characteristics of pheromone communication in this insect. Moreover, some matches for transcripts of unknown function may provide fertile ground of an in-depth study of pheromone-gland specific molecules.

An algorithm to identify functional groups in organic molecules.

PubMed

Ertl, Peter

2017-06-07

The concept of functional groups forms a basis of organic chemistry, medicinal chemistry, toxicity assessment, spectroscopy and also chemical nomenclature. All current software systems to identify functional groups are based on a predefined list of substructures. We are not aware of any program that can identify all functional groups in a molecule automatically. The algorithm presented in this article is an attempt to solve this scientific challenge. An algorithm to identify functional groups in a molecule based on iterative marching through its atoms is described. The procedure is illustrated by extracting functional groups from the bioactive portion of the ChEMBL database, resulting in identification of 3080 unique functional groups. A new algorithm to identify all functional groups in organic molecules is presented. The algorithm is relatively simple and full details with examples are provided, therefore implementation in any cheminformatics toolkit should be relatively easy. The new method allows the analysis of functional groups in large chemical databases in a way that was not possible using previous approaches. Graphical abstract .

Using the gini coefficient to measure the chemical diversity of small-molecule libraries.

PubMed

Weidlich, Iwona E; Filippov, Igor V

2016-08-15

Modern databases of small organic molecules contain tens of millions of structures. The size of theoretically available chemistry is even larger. However, despite the large amount of chemical information, the "big data" moment for chemistry has not yet provided the corresponding payoff of cheaper computer-predicted medicine or robust machine-learning models for the determination of efficacy and toxicity. Here, we present a study of the diversity of chemical datasets using a measure that is commonly used in socioeconomic studies. We demonstrate the use of this diversity measure on several datasets that were constructed to contain various congeneric subsets of molecules as well as randomly selected molecules. We also apply our method to a number of well-known databases that are frequently used for structure-activity relationship modeling. Our results show the poor diversity of the common sources of potential lead compounds compared to actual known drugs. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

QSAR modeling and chemical space analysis of antimalarial compounds

NASA Astrophysics Data System (ADS)

Sidorov, Pavel; Viira, Birgit; Davioud-Charvet, Elisabeth; Maran, Uko; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2017-05-01

Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including 3000 molecules tested in one or several of 17 anti- Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.

QSAR modeling and chemical space analysis of antimalarial compounds.

PubMed

Sidorov, Pavel; Viira, Birgit; Davioud-Charvet, Elisabeth; Maran, Uko; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2017-05-01

Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including ~3000 molecules tested in one or several of 17 anti-Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.

Computational multiscale modeling in protein--ligand docking.

PubMed

Taufer, Michela; Armen, Roger; Chen, Jianhan; Teller, Patricia; Brooks, Charles

2009-01-01

In biological systems, the binding of small molecule ligands to proteins is a crucial process for almost every aspect of biochemistry and molecular biology. Enzymes are proteins that function by catalyzing specific biochemical reactions that convert reactants into products. Complex organisms are typically composed of cells in which thousands of enzymes participate in complex and interconnected biochemical pathways. Some enzymes serve as sequential steps in specific pathways (such as energy metabolism), while others function to regulate entire pathways and cellular functions [1]. Small molecule ligands can be designed to bind to a specific enzyme and inhibit the biochemical reaction. Inhibiting the activity of key enzymes may result in the entire biochemical pathways being turned on or off [2], [3]. Many small molecule drugs marketed today function in this generic way as enzyme inhibitors. If research identifies a specific enzyme as being crucial to the progress of disease, then this enzyme may be targeted with an inhibitor, which may slow down or reverse the progress of disease. In this way, enzymes are targeted from specific pathogens (e.g., virus, bacteria, fungi) for infectious diseases [4], [5], and human enzymes are targeted for noninfectious diseases such as cardiovascular disease, cancer, diabetes, and neurodegenerative diseases [6].

Text mining for metabolic pathways, signaling cascades, and protein networks.

PubMed

Hoffmann, Robert; Krallinger, Martin; Andres, Eduardo; Tamames, Javier; Blaschke, Christian; Valencia, Alfonso

2005-05-10

The complexity of the information stored in databases and publications on metabolic and signaling pathways, the high throughput of experimental data, and the growing number of publications make it imperative to provide systems to help the researcher navigate through these interrelated information resources. Text-mining methods have started to play a key role in the creation and maintenance of links between the information stored in biological databases and its original sources in the literature. These links will be extremely useful for database updating and curation, especially if a number of technical problems can be solved satisfactorily, including the identification of protein and gene names (entities in general) and the characterization of their types of interactions. The first generation of openly accessible text-mining systems, such as iHOP (Information Hyperlinked over Proteins), provides additional functions to facilitate the reconstruction of protein interaction networks, combine database and text information, and support the scientist in the formulation of novel hypotheses. The next challenge is the generation of comprehensive information regarding the general function of signaling pathways and protein interaction networks.

Many-molecule encapsulation by an icosahedral shell

PubMed Central

Perlmutter, Jason D; Mohajerani, Farzaneh; Hagan, Michael F

2016-01-01

We computationally study how an icosahedral shell assembles around hundreds of molecules. Such a process occurs during the formation of the carboxysome, a bacterial microcompartment that assembles around many copies of the enzymes ribulose 1,5-bisphosphate carboxylase/ oxygenase and carbonic anhydrase to facilitate carbon fixation in cyanobacteria. Our simulations identify two classes of assembly pathways leading to encapsulation of many-molecule cargoes. In one, shell assembly proceeds concomitantly with cargo condensation. In the other, the cargo first forms a dense globule; then, shell proteins assemble around and bud from the condensed cargo complex. Although the model is simplified, the simulations predict intermediates and closure mechanisms not accessible in experiments, and show how assembly can be tuned between these two pathways by modulating protein interactions. In addition to elucidating assembly pathways and critical control parameters for microcompartment assembly, our results may guide the reengineering of viruses as nanoreactors that self-assemble around their reactants. DOI: http://dx.doi.org/10.7554/eLife.14078.001 PMID:27166515

Morphological Transformation between Nanocoils and Nanoribbons via Defragmentation Structural Rearrangement or Fragmentation-recombination Mechanism

NASA Astrophysics Data System (ADS)

Zhang, Yibin; Zheng, Yingxuan; Xiong, Wei; Peng, Cheng; Zhang, Yifan; Duan, Ran; Che, Yanke; Zhao, Jincai

2016-06-01

Kinetic control over the assembly pathways towards novel metastable functional materials or far-from-equilibrium systems has been much less studied compared to the thermodynamic equilibrium self-assembly. Herein, we report the distinct morphological transformation between nanocoils and nanoribbons in the self-assembly of unsymmetric perylene diimide (PDI) molecules. We demonstrate that the morphological transformation of the kinetically trapped assemblies into the thermodynamically stable forms proceeds via two distinct mechanisms, i.e., a direct structural rearrangement (molecule 1 or 2) and a fragmentation-recombination mechanism (molecule 4), respectively. The subtle interplay of the steric hindrance of the bulky substituents and the flexibility of the linker structure between the bulky moiety and the perylene core was demonstrated to enable the effective modulation of the energetic landscape of the assemblies and thus modulation of the assembly pathways. Herein, our work presents a new approach to control the self-assembly pathways and thereby can be used to achieve novel far-from-equilibrium systems.

Cytidine derivatives as IspF inhibitors of Burkolderia pseudomallei

PubMed Central

Zhang, Zheng; Jakkaraju, Sriram; Blain, Joy; Gogol, Kenneth; Zhao, Lei; Hartley, Robert C.; Karlsson, Courtney A.; Staker, Bart L.; Stewart, Lance J.; Myler, Peter J.; Clare, Michael; Begley, Darren W.; Horn, James R.; Hagen, Timothy J

2013-01-01

Published biological data suggest that the methyl erythritol phosphate (MEP) pathway, a non-mevalonate isoprenoid biosynthetic pathway, is essential for certain bacteria and other infectious disease organisms. One highly conserved enzyme in the MEP pathway is 2C-methyl-D-erythritol 2,4-cyclodiphosphate synthase (IspF). Fragment-bound complexes of IspF from Burkholderia pseudomallei were used to design and synthesize a series of molecules linking the cytidine moiety to different zinc pocket fragment binders. Testing by surface plasmon resonance (SPR) found one molecule in the series to possess binding affinity equal to that of cytidine diphosphate, despite lacking any metal-coordinating phosphate groups. Close inspection of the SPR data suggest different binding stoichiometries between IspF and test compounds. Crystallographic analysis shows important variations between the binding mode of one synthesized compound and the pose of the bound fragment from which it was designed. The binding modes of these molecules add to our structural knowledge base for IspF and suggest future refinements in this compound series. PMID:24157367

A whole organism screen identifies novel regulators of fat storage

PubMed Central

Lemieux, George A.; Liu, Jason; Mayer, Nasima; Bainton, Roland J.; Ashrafi, Kaveh; Werb, Zena

2011-01-01

The regulation of energy homeostasis integrates diverse biological processes ranging from behavior to metabolism and is linked fundamentally to numerous disease states. To identify new molecules that can bypass homeostatic compensatory mechanisms of energy balance in intact animals, we screened for small molecule modulators of C. elegans fat content. We report on several molecules that modulate fat storage without obvious deleterious effects on feeding, growth, and reproduction. A subset of these compounds also altered fat storage in mammalian and insect cell culture. We found that one of the newly identified compounds exerts its effects in C. elegans through a pathway that requires novel functions of an AMP-activated kinase catalytic subunit and a transcription factor previously unassociated with fat regulation. Thus, our strategy identifies small molecules that are effective within the context of intact animals and reveals relationships between new pathways that operate across phyla to influence energy homeostasis. PMID:21390037

Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile.

PubMed

Long, Jin; Liu, Zhe; Wu, Xingda; Xu, Yuanhong; Ge, Chunlin

2016-05-01

The present study aimed to screen for potential genes and subnetworks associated with pancreatic cancer (PC) using the gene expression profile. The expression profile GSE 16515 was downloaded from the Gene Expression Omnibus database, which included 36 PC tissue samples and 16 normal samples. Limma package in R language was used to screen differentially expressed genes (DEGs), which were grouped as up‑ and downregulated genes. Then, PFSNet was applied to perform subnetwork analysis for all the DEGs. Moreover, Gene Ontology (GO) and REACTOME pathway enrichment analysis of up‑ and downregulated genes was performed, followed by protein‑protein interaction (PPI) network construction using Search Tool for the Retrieval of Interacting Genes Search Tool for the Retrieval of Interacting Genes. In total, 1,989 DEGs including 1,461 up‑ and 528 downregulated genes were screened out. Subnetworks including pancreatic cancer in PC tissue samples and intercellular adhesion in normal samples were identified, respectively. A total of 8 significant REACTOME pathways for upregulated DEGs, such as hemostasis and cell cycle, mitotic were identified. Moreover, 4 significant REACTOME pathways for downregulated DEGs, including regulation of β‑cell development and transmembrane transport of small molecules were screened out. Additionally, DEGs with high connectivity degrees, such as CCNA2 (cyclin A2) and PBK (PDZ binding kinase), of the module in the protein‑protein interaction network were mainly enriched with cell‑division cycle. CCNA2 and PBK of the module and their relative pathway cell‑division cycle, and two subnetworks (pancreatic cancer and intercellular adhesion subnetworks) may be pivotal for further understanding of the molecular mechanism of PC.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data

PubMed Central

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/ PMID:26363020

Hydrocarbon Spectral Database

National Institute of Standards and Technology Data Gateway

SRD 115 Hydrocarbon Spectral Database (Web, free access)   All of the rotational spectral lines observed and reported in the open literature for 91 hydrocarbon molecules have been tabulated. The isotopic molecular species, assigned quantum numbers, observed frequency, estimated measurement uncertainty and reference are given for each transition reported.

Diatomic Spectral Database

National Institute of Standards and Technology Data Gateway

SRD 114 Diatomic Spectral Database (Web, free access)   All of the rotational spectral lines observed and reported in the open literature for 121 diatomic molecules have been tabulated. The isotopic molecular species, assigned quantum numbers, observed frequency, estimated measurement uncertainty, and reference are given for each transition reported.

Triatomic Spectral Database

National Institute of Standards and Technology Data Gateway

SRD 117 Triatomic Spectral Database (Web, free access)   All of the rotational spectral lines observed and reported in the open literature for 55 triatomic molecules have been tabulated. The isotopic molecular species, assigned quantum numbers, observed frequency, estimated measurement uncertainty and reference are given for each transition reported.

Chemical Space: Big Data Challenge for Molecular Diversity.

PubMed

Awale, Mahendra; Visini, Ricardo; Probst, Daniel; Arús-Pous, Josep; Reymond, Jean-Louis

2017-10-25

Chemical space describes all possible molecules as well as multi-dimensional conceptual spaces representing the structural diversity of these molecules. Part of this chemical space is available in public databases ranging from thousands to billions of compounds. Exploiting these databases for drug discovery represents a typical big data problem limited by computational power, data storage and data access capacity. Here we review recent developments of our laboratory, including progress in the chemical universe databases (GDB) and the fragment subset FDB-17, tools for ligand-based virtual screening by nearest neighbor searches, such as our multi-fingerprint browser for the ZINC database to select purchasable screening compounds, and their application to discover potent and selective inhibitors for calcium channel TRPV6 and Aurora A kinase, the polypharmacology browser (PPB) for predicting off-target effects, and finally interactive 3D-chemical space visualization using our online tools WebDrugCS and WebMolCS. All resources described in this paper are available for public use at www.gdb.unibe.ch.

[Construction of chemical information database based on optical structure recognition technique].

PubMed

Lv, C Y; Li, M N; Zhang, L R; Liu, Z M

2018-04-18

To create a protocol that could be used to construct chemical information database from scientific literature quickly and automatically. Scientific literature, patents and technical reports from different chemical disciplines were collected and stored in PDF format as fundamental datasets. Chemical structures were transformed from published documents and images to machine-readable data by using the name conversion technology and optical structure recognition tool CLiDE. In the process of molecular structure information extraction, Markush structures were enumerated into well-defined monomer molecules by means of QueryTools in molecule editor ChemDraw. Document management software EndNote X8 was applied to acquire bibliographical references involving title, author, journal and year of publication. Text mining toolkit ChemDataExtractor was adopted to retrieve information that could be used to populate structured chemical database from figures, tables, and textual paragraphs. After this step, detailed manual revision and annotation were conducted in order to ensure the accuracy and completeness of the data. In addition to the literature data, computing simulation platform Pipeline Pilot 7.5 was utilized to calculate the physical and chemical properties and predict molecular attributes. Furthermore, open database ChEMBL was linked to fetch known bioactivities, such as indications and targets. After information extraction and data expansion, five separate metadata files were generated, including molecular structure data file, molecular information, bibliographical references, predictable attributes and known bioactivities. Canonical simplified molecular input line entry specification as primary key, metadata files were associated through common key nodes including molecular number and PDF number to construct an integrated chemical information database. A reasonable construction protocol of chemical information database was created successfully. A total of 174 research articles and 25 reviews published in Marine Drugs from January 2015 to June 2016 collected as essential data source, and an elementary marine natural product database named PKU-MNPD was built in accordance with this protocol, which contained 3 262 molecules and 19 821 records. This data aggregation protocol is of great help for the chemical information database construction in accuracy, comprehensiveness and efficiency based on original documents. The structured chemical information database can facilitate the access to medical intelligence and accelerate the transformation of scientific research achievements.

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

Karp, Peter D.

Pathway Tools is a systems-biology software package written by SRI International (SRI) that produces Pathway/Genome Databases (PGDBs) for organisms with a sequenced genome. Pathway Tools also provides a wide range of capabilities for analyzing predicted metabolic networks and user-generated omics data. More than 5,000 academic, industrial, and government groups have licensed Pathway Tools. This user community includes researchers at all three DOE bioenergy centers, as well as academic and industrial metabolic engineering (ME) groups. An integral part of the Pathway Tools software is MetaCyc, a large, multiorganism database of metabolic pathways and enzymes that SRI and its academic collaborators manuallymore » curate. This project included two main goals: I. Enhance the MetaCyc content of bioenergy-related enzymes and pathways. II. Develop computational tools for engineering metabolic pathways that satisfy specified design goals, in particular for bioenergy-related pathways. In part I, SRI proposed to significantly expand the coverage of bioenergy-related metabolic information in MetaCyc, followed by the generation of organism-specific PGDBs for all energy-relevant organisms sequenced at the DOE Joint Genome Institute (JGI). Part I objectives included: 1: Expand the content of MetaCyc to include bioenergy-related enzymes and pathways. 2: Enhance the Pathway Tools software to enable display of complex polymer degradation processes. 3: Create new PGDBs for the energy-related organisms sequenced by JGI, update existing PGDBs with new MetaCyc content, and make these data available to JBEI via the BioCyc website. In part II, SRI proposed to develop an efficient computational tool for the engineering of metabolic pathways. Part II objectives included: 4: Develop computational tools for generating metabolic pathways that satisfy specified design goals, enabling users to specify parameters such as starting and ending compounds, and preferred or disallowed intermediate compounds. The pathways were to be generated using metabolic reactions from a reference database (DB). 5: Develop computational tools for ranking the pathways generated in objective (4) according to their optimality. The ranking criteria include stoichiometric yield, the number and cost of additional inputs and the cofactor compounds required by the pathway, pathway length, and pathway energetics. 6: Develop tools for visualizing generated pathways to facilitate the evaluation of a large space of generated pathways.« less

Cryptotanshinone inhibits oxidized LDL-induced adhesion molecule expression via ROS dependent NF-κB pathways

PubMed Central

Zhao, Wenwen; Wu, Chuanhong; Chen, Xiuping

2016-01-01

ABSTRACT Adhesion molecules, such as intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1), and E-selectin, play important roles in the initial stage of atherosclerosis. Cryptotanshinone (CPT), a natural compound isolated from Salvia miltiorrhiza Bunge, exhibits anti-atherosclerotic activity although the underlying mechanisms remain elusive. In this study, the protective effect of CPT against oxidized low-density lipoprotein (ox-LDL)-induced adhesion molecule expression was investigated in human umbilical vein endothelial cells. Ox-LDL significantly induced ICAM-1, VCAM-1, and E-selectin expression at the mRNA and protein levels but reduced eNOS phosphorylation and NO generation, which were reversed by CPT pretreatment. Sodium nitroprusside, a NO donor, N-acetyl-L-cysteine (NAC), a reactive oxygen species (ROS) scavenger, and BAY117082, a NF-κB inhibitor, inhibited ox-LDL-induced ICAM-1, VCAM-1, and E-selectin expression. Ox-LDL-induced ROS production was significantly inhibited by CPT and NAC. Furthermore, ox-LDL activated the NF-κB signaling pathway by inducing phosphorylation of IKKβ and IκBα, promoting the interaction of IKKβ and IκBα, and increasing p65 nuclear translocation, which were significantly inhibited by CPT. In addition, CPT, NAC, and BAY117082 inhibited ox-LDL-induced membrane expression of ICAM-1, VCAM-1, E-selectin, and endothelial–monocyte adhesion and restored eNOS phosphorylation and NO generation. Results suggested that CPT inhibited ox-LDL-induced adhesion molecule expression by decreasing ROS and inhibiting the NF-κB pathways, which provides new insight into the anti-atherosclerotic mechanism of CPT. PMID:26647279

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology.

PubMed

Karp, Peter D; Latendresse, Mario; Paley, Suzanne M; Krummenacker, Markus; Ong, Quang D; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M; Caspi, Ron

2016-09-01

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Metabolic pathway reconstruction of eugenol to vanillin bioconversion in Aspergillus niger

PubMed Central

Srivastava, Suchita; Luqman, Suaib; Khan, Feroz; Chanotiya, Chandan S; Darokar, Mahendra P

2010-01-01

Identification of missing genes or proteins participating in the metabolic pathways as enzymes are of great interest. One such class of pathway is involved in the eugenol to vanillin bioconversion. Our goal is to develop an integral approach for identifying the topology of a reference or known pathway in other organism. We successfully identify the missing enzymes and then reconstruct the vanillin biosynthetic pathway in Aspergillus niger. The procedure combines enzyme sequence similarity searched through BLAST homology search and orthologs detection through COG & KEGG databases. Conservation of protein domains and motifs was searched through CDD, PFAM & PROSITE databases. Predictions regarding how proteins act in pathway were validated experimentally and also compared with reported data. The bioconversion of vanillin was screened on UV-TLC plates and later confirmed through GC and GC-MS techniques. We applied a procedure for identifying missing enzymes on the basis of conserved functional motifs and later reconstruct the metabolic pathway in target organism. Using the vanillin biosynthetic pathway of Pseudomonas fluorescens as a case study, we indicate how this approach can be used to reconstruct the reference pathway in A. niger and later results were experimentally validated through chromatography and spectroscopy techniques. PMID:20978605

NemaPath: online exploration of KEGG-based metabolic pathways for nematodes

PubMed Central

Wylie, Todd; Martin, John; Abubucker, Sahar; Yin, Yong; Messina, David; Wang, Zhengyuan; McCarter, James P; Mitreva, Makedonka

2008-01-01

Background Nematode.net is a web-accessible resource for investigating gene sequences from parasitic and free-living nematode genomes. Beyond the well-characterized model nematode C. elegans, over 500,000 expressed sequence tags (ESTs) and nearly 600,000 genome survey sequences (GSSs) have been generated from 36 nematode species as part of the Parasitic Nematode Genomics Program undertaken by the Genome Center at Washington University School of Medicine. However, these sequencing data are not present in most publicly available protein databases, which only include sequences in Swiss-Prot. Swiss-Prot, in turn, relies on GenBank/Embl/DDJP for predicted proteins from complete genomes or full-length proteins. Description Here we present the NemaPath pathway server, a web-based pathway-level visualization tool for navigating putative metabolic pathways for over 30 nematode species, including 27 parasites. The NemaPath approach consists of two parts: 1) a backend tool to align and evaluate nematode genomic sequences (curated EST contigs) against the annotated Kyoto Encyclopedia of Genes and Genomes (KEGG) protein database; 2) a web viewing application that displays annotated KEGG pathway maps based on desired confidence levels of primary sequence similarity as defined by a user. NemaPath also provides cross-referenced access to nematode genome information provided by other tools available on Nematode.net, including: detailed NemaGene EST cluster information; putative translations; GBrowse EST cluster views; links from nematode data to external databases for corresponding synonymous C. elegans counterparts, subject matches in KEGG's gene database, and also KEGG Ontology (KO) identification. Conclusion The NemaPath server hosts metabolic pathway mappings for 30 nematode species and is available on the World Wide Web at . The nematode source sequences used for the metabolic pathway mappings are available via FTP , as provided by the Genome Center at Washington University School of Medicine. PMID:18983679

Glioma-Associated Oncogene Homolog Inhibitors Have the Potential of Suppressing Cancer Stem Cells of Breast Cancer.

PubMed

Jeng, Kuo-Shyang; Jeng, Chi-Juei; Sheen, I-Shyan; Wu, Szu-Hua; Lu, Ssu-Jung; Wang, Chih-Hsuan; Chang, Chiung-Fang

2018-05-05

Overexpression of Sonic Hedgehog signaling (Shh) pathway molecules is associated with invasiveness and recurrence in breast carcinoma. Therefore, inhibition of the Shh pathway downstream molecule Glioma-associated Oncogene Homolog (Gli) was investigated for its ability to reduce progression and invasiveness of patient-derived breast cancer cells and cell lines. Human primary breast cancer T2 cells with high expression of Shh signaling pathway molecules were compared with breast cancer line MDA-MB-231 cells. The therapeutic effects of Gli inhibitors were examined in terms of the cell proliferation, apoptosis, cancer stem cells, cell migration and gene expression. Blockade of the Shh signaling pathway could reduce cell proliferation and migration only in MDA-MB-231 cells. Hh pathway inhibitor-1 (HPI-1) increased the percentages of late apoptotic cells in MDA-MB-231 cells and early apoptotic cells in T2 cells. It reduced Bcl2 expression for cell proliferation and increased Bim expression for apoptosis. In addition, Gli inhibitor HPI-1 decreased significantly the percentages of cancer stem cells in T2 cells. HPI-1 worked more effectively than GANT-58 against breast carcinoma cells. In conclusion, HPI-1 could inhibit cell proliferation, reduce cell invasion and decrease cancer stem cell population in breast cancer cells. To target Gli-1 could be a potential strategy to suppress breast cancer stem cells.

Chemical genetic screen identifies lithocholic acid as an anti-aging compound that extends yeast chronological life span in a TOR-independent manner, by modulating housekeeping longevity assurance processes.

PubMed

Goldberg, Alexander A; Richard, Vincent R; Kyryakov, Pavlo; Bourque, Simon D; Beach, Adam; Burstein, Michelle T; Glebov, Anastasia; Koupaki, Olivia; Boukh-Viner, Tatiana; Gregg, Christopher; Juneau, Mylène; English, Ann M; Thomas, David Y; Titorenko, Vladimir I

2010-07-01

In chronologically aging yeast, longevity can be extended by administering a caloric restriction (CR) diet or some small molecules. These life-extending interventions target the adaptable target of rapamycin (TOR) and cAMP/protein kinase A (cAMP/PKA) signaling pathways that are under the stringent control of calorie availability. We designed a chemical genetic screen for small molecules that increase the chronological life span of yeast under CR by targeting lipid metabolism and modulating housekeeping longevity pathways that regulate longevity irrespective of the number of available calories. Our screen identifies lithocholic acid (LCA) as one of such molecules. We reveal two mechanisms underlying the life-extending effect of LCA in chronologically aging yeast. One mechanism operates in a calorie availability-independent fashion and involves the LCA-governed modulation of housekeeping longevity assurance pathways that do not overlap with the adaptable TOR and cAMP/PKA pathways. The other mechanism extends yeast longevity under non-CR conditions and consists in LCA-driven unmasking of the previously unknown anti-aging potential of PKA. We provide evidence that LCA modulates housekeeping longevity assurance pathways by suppressing lipid-induced necrosis, attenuating mitochondrial fragmentation, altering oxidation-reduction processes in mitochondria, enhancing resistance to oxidative and thermal stresses, suppressing mitochondria-controlled apoptosis, and enhancing stability of nuclear and mitochondrial DNA.

Nanotubule and Tour Molecule Based Molecular Electronics: Suggestion for a Hybrid Approach

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Saini, Subhash (Technical Monitor)

1998-01-01

Recent experimental and theoretical attempts and results indicate two distinct broad pathways towards future molecular electronic devices and architectures. The first is the approach via Tour type ladder molecules and their junctions which can be fabricated with solution phase chemical approaches. Second are fullerenes or nanotubules and their junctions which may have better conductance, switching and amplifying characteristics but can not be made through well controlled and defined chemical means. A hybrid approach combining the two pathways to take advantage of the characteristics of both is suggested. Dimension and scale of such devices would be somewhere in between isolated molecule and nanotubule based devices but it maybe possible to use self-assembly towards larger functional and logicalunits.

The Anisakis Transcriptome Provides a Resource for Fundamental and Applied Studies on Allergy-Causing Parasites.

PubMed

Baird, Fiona J; Su, Xiaopei; Aibinu, Ibukun; Nolan, Matthew J; Sugiyama, Hiromu; Otranto, Domenico; Lopata, Andreas L; Cantacessi, Cinzia

2016-07-01

Food-borne nematodes of the genus Anisakis are responsible for a wide range of illnesses (= anisakiasis), from self-limiting gastrointestinal forms to severe systemic allergic reactions, which are often misdiagnosed and under-reported. In order to enhance and refine current diagnostic tools for anisakiasis, knowledge of the whole spectrum of parasite molecules transcribed and expressed by this parasite, including those acting as potential allergens, is necessary. In this study, we employ high-throughput (Illumina) sequencing and bioinformatics to characterise the transcriptomes of two Anisakis species, A. simplex and A. pegreffii, and utilize this resource to compile lists of potential allergens from these parasites. A total of ~65,000,000 reads were generated from cDNA libraries for each species, and assembled into ~34,000 transcripts (= Unigenes); ~18,000 peptides were predicted from each cDNA library and classified based on homology searches, protein motifs and gene ontology and biological pathway mapping. Using comparative analyses with sequence data available in public databases, 36 (A. simplex) and 29 (A. pegreffii) putative allergens were identified, including sequences encoding 'novel' Anisakis allergenic proteins (i.e. cyclophilins and ABA-1 domain containing proteins). This study represents a first step towards providing the research community with a curated dataset to use as a molecular resource for future investigations of the biology of Anisakis, including molecules putatively acting as allergens, using functional genomics, proteomics and immunological tools. Ultimately, an improved knowledge of the biological functions of these molecules in the parasite, as well as of their immunogenic properties, will assist the development of comprehensive, reliable and robust diagnostic tools.

From 20th century metabolic wall charts to 21st century systems biology: database of mammalian metabolic enzymes.

PubMed

Corcoran, Callan C; Grady, Cameron R; Pisitkun, Trairak; Parulekar, Jaya; Knepper, Mark A

2017-03-01

The organization of the mammalian genome into gene subsets corresponding to specific functional classes has provided key tools for systems biology research. Here, we have created a web-accessible resource called the Mammalian Metabolic Enzyme Database ( https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/MetabolicEnzymeDatabase.html) keyed to the biochemical reactions represented on iconic metabolic pathway wall charts created in the previous century. Overall, we have mapped 1,647 genes to these pathways, representing ~7 percent of the protein-coding genome. To illustrate the use of the database, we apply it to the area of kidney physiology. In so doing, we have created an additional database ( Database of Metabolic Enzymes in Kidney Tubule Segments: https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/), mapping mRNA abundance measurements (mined from RNA-Seq studies) for all metabolic enzymes to each of 14 renal tubule segments. We carry out bioinformatics analysis of the enzyme expression pattern among renal tubule segments and mine various data sources to identify vasopressin-regulated metabolic enzymes in the renal collecting duct. Copyright © 2017 the American Physiological Society.

Electron-Impact Ionization Cross Section Database

National Institute of Standards and Technology Data Gateway

SRD 107 Electron-Impact Ionization Cross Section Database (Web, free access)   This is a database primarily of total ionization cross sections of molecules by electron impact. The database also includes cross sections for a small number of atoms and energy distributions of ejected electrons for H, He, and H2. The cross sections were calculated using the Binary-Encounter-Bethe (BEB) model, which combines the Mott cross section with the high-incident energy behavior of the Bethe cross section. Selected experimental data are included.

T-cell costimulatory pathways in allograft rejection and tolerance.

PubMed

Rothstein, David M; Sayegh, Mohamed H

2003-12-01

The destiny of activated T cells is critical to the ultimate fate of immune response. After encountering antigen, naïve T cells receive signal 1 through the T-cell receptor (TCR)-major histocompatibility complex (MHC) plus antigenic peptide complex and signal 2 through "positive" costimulatory molecules leading to full activation. "Negative" T-cell costimulatory pathways, on the other hand, function to downregulate immune responses. The purpose of this article is to review the current state of knowledge and recent advances in our understanding of the functions of the positive and negative T-cell costimulatory pathways in alloimmune responses. Specifically, we discuss the functions of the CD28:B7 and the tumor necrosis factor receptor (TNFR):tumor necrosis factor (TNF) family of molecules in allograft rejection and tolerance. We address the following important questions: are T-cell costimulatory pathways merely redundant or do they provide distinct and unique functions? What are the important and unique interactions between the various pathways? And, what are the effects and mechanisms of targeting of these pathways in different types and patterns of allograft rejection and tolerance models?

Mechanisms for the inversion of chirality: Global reaction route mapping of stereochemical pathways in a probable chiral extraterrestrial molecule, 2-aminopropionitrile

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

Kaur, Ramanpreet; Vikas, E-mail: qlabspu@pu.ac.in, E-mail: qlabspu@yahoo.com

2015-02-21

2-Aminopropionitrile (APN), a probable candidate as a chiral astrophysical molecule, is a precursor to amino-acid alanine. Stereochemical pathways in 2-APN are explored using Global Reaction Route Mapping (GRRM) method employing high-level quantum-mechanical computations. Besides predicting the conventional mechanism for chiral inversion that proceeds through an achiral intermediate, a counterintuitive flipping mechanism is revealed for 2-APN through chiral intermediates explored using the GRRM. The feasibility of the proposed stereochemical pathways, in terms of the Gibbs free-energy change, is analyzed at the temperature conditions akin to the interstellar medium. Notably, the stereoinversion in 2-APN is observed to be more feasible than themore » dissociation of 2-APN and intermediates involved along the stereochemical pathways, and the flipping barrier is observed to be as low as 3.68 kJ/mol along one of the pathways. The pathways proposed for the inversion of chirality in 2-APN may provide significant insight into the extraterrestrial origin of life.« less

YMDB 2.0: a significantly expanded version of the yeast metabolome database.

PubMed

Ramirez-Gaona, Miguel; Marcu, Ana; Pon, Allison; Guo, An Chi; Sajed, Tanvir; Wishart, Noah A; Karu, Naama; Djoumbou Feunang, Yannick; Arndt, David; Wishart, David S

2017-01-04

YMDB or the Yeast Metabolome Database (http://www.ymdb.ca/) is a comprehensive database containing extensive information on the genome and metabolome of Saccharomyces cerevisiae Initially released in 2012, the YMDB has gone through a significant expansion and a number of improvements over the past 4 years. This manuscript describes the most recent version of YMDB (YMDB 2.0). More specifically, it provides an updated description of the database that was previously described in the 2012 NAR Database Issue and it details many of the additions and improvements made to the YMDB over that time. Some of the most important changes include a 7-fold increase in the number of compounds in the database (from 2007 to 16 042), a 430-fold increase in the number of metabolic and signaling pathway diagrams (from 66 to 28 734), a 16-fold increase in the number of compounds linked to pathways (from 742 to 12 733), a 17-fold increase in the numbers of compounds with nuclear magnetic resonance or MS spectra (from 783 to 13 173) and an increase in both the number of data fields and the number of links to external databases. In addition to these database expansions, a number of improvements to YMDB's web interface and its data visualization tools have been made. These additions and improvements should greatly improve the ease, the speed and the quantity of data that can be extracted, searched or viewed within YMDB. Overall, we believe these improvements should not only improve the understanding of the metabolism of S. cerevisiae, but also allow more in-depth exploration of its extensive metabolic networks, signaling pathways and biochemistry. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Computational Thermochemistry of Jet Fuels and Rocket Propellants

NASA Technical Reports Server (NTRS)

Crawford, T. Daniel

2002-01-01

The design of new high-energy density molecules as candidates for jet and rocket fuels is an important goal of modern chemical thermodynamics. The NASA Glenn Research Center is home to a database of thermodynamic data for over 2000 compounds related to this goal, in the form of least-squares fits of heat capacities, enthalpies, and entropies as functions of temperature over the range of 300 - 6000 K. The chemical equilibrium with applications (CEA) program written and maintained by researchers at NASA Glenn over the last fifty years, makes use of this database for modeling the performance of potential rocket propellants. During its long history, the NASA Glenn database has been developed based on experimental results and data published in the scientific literature such as the standard JANAF tables. The recent development of efficient computational techniques based on quantum chemical methods provides an alternative source of information for expansion of such databases. For example, it is now possible to model dissociation or combustion reactions of small molecules to high accuracy using techniques such as coupled cluster theory or density functional theory. Unfortunately, the current applicability of reliable computational models is limited to relatively small molecules containing only around a dozen (non-hydrogen) atoms. We propose to extend the applicability of coupled cluster theory- often referred to as the 'gold standard' of quantum chemical methods- to molecules containing 30-50 non-hydrogen atoms. The centerpiece of this work is the concept of local correlation, in which the description of the electron interactions- known as electron correlation effects- are reduced to only their most important localized components. Such an advance has the potential to greatly expand the current reach of computational thermochemistry and thus to have a significant impact on the theoretical study of jet and rocket propellants.

Comparison of tumor related signaling pathways with known compounds to determine potential agents for lung adenocarcinoma.

PubMed

Xu, Song; Liu, Renwang; Da, Yurong

2018-06-05

This study compared tumor-related signaling pathways with known compounds to determine potential agents for lung adenocarcinoma (LUAD) treatment. Kyoto Encyclopedia of Genes and Genomes signaling pathway analyses were performed based on LUAD differentially expressed genes from The Cancer Genome Atlas (TCGA) project and genotype-tissue expression controls. These results were compared to various known compounds using the Connectivity Mapping dataset. The clinical significance of the hub genes identified by overlapping pathway enrichment analysis was further investigated using data mining from multiple sources. A drug-pathway network for LUAD was constructed, and molecular docking was carried out. After the integration of 57 LUAD-related pathways and 35 pathways affected by small molecules, five overlapping pathways were revealed. Among these five pathways, the p53 signaling pathway was the most significant, with CCNB1, CCNB2, CDK1, CDKN2A, and CHEK1 being identified as hub genes. The p53 signaling pathway is implicated as a risk factor for LUAD tumorigenesis and survival. A total of 88 molecules significantly inhibiting the five LUAD-related oncogenic pathways were involved in the LUAD drug-pathway network. Daunorubicin, mycophenolic acid, and pyrvinium could potentially target the hub gene CHEK1 directly. Our study highlights the critical pathways that should be targeted in the search for potential LUAD treatments, most importantly, the p53 signaling pathway. Some compounds, such as ciclopirox and AG-028671, may have potential roles for LUAD treatment but require further experimental verification. © 2018 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

Small-molecule factor D inhibitors selectively block the alternative pathway of complement in paroxysmal nocturnal hemoglobinuria and atypical hemolytic uremic syndrome.

PubMed

Yuan, Xuan; Gavriilaki, Eleni; Thanassi, Jane A; Yang, Guangwei; Baines, Andrea C; Podos, Steven D; Huang, Yongqing; Huang, Mingjun; Brodsky, Robert A

2017-03-01

Paroxysmal nocturnal hemoglobinuria and atypical hemolytic uremic syndrome are diseases of excess activation of the alternative pathway of complement that are treated with eculizumab, a humanized monoclonal antibody against the terminal complement component C5. Eculizumab must be administered intravenously, and moreover some patients with paroxysmal nocturnal hemoglobinuria on eculizumab have symptomatic extravascular hemolysis, indicating an unmet need for additional therapeutic approaches. We report the activity of two novel small-molecule inhibitors of the alternative pathway component Factor D using in vitro correlates of both paroxysmal nocturnal hemoglobinuria and atypical hemolytic uremic syndrome. Both compounds bind human Factor D with high affinity and effectively inhibit its proteolytic activity against purified Factor B in complex with C3b. When tested using the traditional Ham test with cells from paroxysmal nocturnal hemoglobinuria patients, the Factor D inhibitors significantly reduced complement-mediated hemolysis at concentrations as low as 0.01 μM. Additionally the compound ACH-4471 significantly decreased C3 fragment deposition on paroxysmal nocturnal hemoglobinuria erythrocytes, indicating a reduced potential relative to eculizumab for extravascular hemolysis. Using the recently described modified Ham test with serum from patients with atypical hemolytic uremic syndrome, the compounds reduced the alternative pathway-mediated killing of PIGA -null reagent cells, thus establishing their potential utility for this disease of alternative pathway of complement dysregulation and validating the modified Ham test as a system for pre-clinical drug development for atypical hemolytic uremic syndrome. Finally, ACH-4471 blocked alternative pathway activity when administered orally to cynomolgus monkeys. In conclusion, the small-molecule Factor D inhibitors show potential as oral therapeutics for human diseases driven by the alternative pathway of complement, including paroxysmal nocturnal hemoglobinuria and atypical hemolytic uremic syndrome. Copyright© Ferrata Storti Foundation.

Novel Evasion Mechanisms of the Classical Complement Pathway

PubMed Central

Garcia, Brandon L.; Zwarthoff, Seline A.; Rooijakkers, Suzan H. M.; Geisbrecht, Brian V.

2016-01-01

Complement is a network of soluble and cell surface-associated proteins which gives rise to a self-amplifying, yet tightly regulated system with fundamental roles in immune surveillance and clearance. Complement becomes activated on the surface of ‘non-self’ cells by one of three initiating mechanisms known as the classical, lectin, or alternative pathways. Evasion of complement function is a hallmark of invasive pathogens and hematophagous organisms. While many complement inhibition strategies hinge on hijacking activities of endogenous complement regulatory proteins, an increasing number of uniquely evolved evasion molecules have been discovered over the past decade. In this review we focus on several recent investigations which have revealed mechanistically distinct inhibitors of the classical pathway. Because the classical pathway is an important and specific mediator of various autoimmune and inflammatory disorders, in-depth knowledge of novel evasion mechanisms could direct future development of therapeutic anti-inflammatory molecules. PMID:27591336

Novel Evasion Mechanisms of the Classical Complement Pathway.

PubMed

Garcia, Brandon L; Zwarthoff, Seline A; Rooijakkers, Suzan H M; Geisbrecht, Brian V

2016-09-15

Complement is a network of soluble and cell surface-associated proteins that gives rise to a self-amplifying, yet tightly regulated system with fundamental roles in immune surveillance and clearance. Complement becomes activated on the surface of nonself cells by one of three initiating mechanisms known as the classical, lectin, and alternative pathways. Evasion of complement function is a hallmark of invasive pathogens and hematophagous organisms. Although many complement-inhibition strategies hinge on hijacking activities of endogenous complement regulatory proteins, an increasing number of uniquely evolved evasion molecules have been discovered over the past decade. In this review, we focus on several recent investigations that revealed mechanistically distinct inhibitors of the classical pathway. Because the classical pathway is an important and specific mediator of various autoimmune and inflammatory disorders, in-depth knowledge of novel evasion mechanisms could direct future development of therapeutic anti-inflammatory molecules. Copyright © 2016 by The American Association of Immunologists, Inc.

Inhibitors targeting on cell wall biosynthesis pathway of MRSA.

PubMed

Hao, Haihong; Cheng, Guyue; Dai, Menghong; Wu, Qinghua; Yuan, Zonghui

2012-11-01

Methicillin resistant Staphylococcus aureus (MRSA), widely known as a type of new superbug, has aroused world-wide concern. Cell wall biosynthesis pathway is an old but good target for the development of antibacterial agents. Peptidoglycan and wall teichoic acids (WTAs) biosynthesis are two main processes of the cell wall biosynthesis pathway (CWBP). Other than penicillin-binding proteins (PBPs), some key factors (Mur enzymes, lipid I or II precursor, etc.) in CWBP are becoming attractive molecule targets for the discovery of anti-MRSA compounds. A number of new compounds, with higher affinity for PBPs or with inhibitory activity on such molecule targets in CWBP of MRSA, have been in the pipeline recently. This review concludes recent research achievements and provides a complete picture of CWBP of MRSA, including the peptidoglycan and wall teichoic acids synthesis pathway. The potential inhibitors targeting on CWBP are subsequently presented to improve development of novel therapeutic strategies for MRSA.

Design of two-photon molecular tandem architectures for solar cells by ab initio theory

DOE PAGES

Ornso, Kristian B.; Garcia-Lastra, Juan M.; De La Torre, Gema; ...

2015-03-04

An extensive database of spectroscopic properties of molecules from ab initio calculations is used to design molecular complexes for use in tandem solar cells that convert two photons into a single electron–hole pair, thereby increasing the output voltage while covering a wider spectral range. Three different architectures are considered: the first two involve a complex consisting of two dye molecules with appropriately matched frontier orbitals, connected by a molecular diode. Optimized combinations of dye molecules are determined by taking advantage of our computational database of the structural and energetic properties of several thousand porphyrin dyes. The third design is amore » molecular analogy of the intermediate band solar cell, and involves a single dye molecule with strong intersystem crossing to ensure a long lifetime of the intermediate state. Based on the calculated energy levels and molecular orbitals, energy diagrams are presented for the individual steps in the operation of such tandem solar cells. We find that theoretical open circuit voltages of up to 1.8 V can be achieved using these tandem designs. Questions about the practical implementation of prototypical devices, such as the synthesis of the tandem molecules and potential loss mechanisms, are addressed.« less

Recognition of LPS by TLR4: Potential for Anti-Inflammatory Therapies

PubMed Central

Nijland, Reindert; Hofland, Tom; van Strijp, Jos A. G.

2014-01-01

LPS molecules of marine bacteria show structures distinct from terrestrial bacteria, due to the different environment that marine bacteria live in. Because of these different structures, lipid A molecules from marine bacteria are most often poor stimulators of the Toll-like receptor 4 (TLR4) pathway. Due to their low stimulatory potential, these lipid A molecules are suggested to be applicable as antagonists of TLR4 signaling in sepsis patients, where this immune response is amplified and unregulated. Antagonizing lipid A molecules might be used for future therapies against sepsis, therapies that currently do not exist. In this review, we will discuss these differences in lipid A structures and their recognition by the immune system. The modifications present in marine lipid A structures are described, and their potential as LPS antagonists will be discussed. Finally, since clinical trials built on antagonizing lipid A molecules have proven unsuccessful, we propose to also focus on different aspects of the TLR4 signaling pathway when searching for new potential drugs. Furthermore, we put forward the notion that bacteria probably already produce inhibitors of TLR4 signaling, making these bacterial products interesting molecules to investigate for future sepsis therapies. PMID:25056632

A new method for finding the minimum free energy pathway of ions and small molecule transportation through protein based on 3D-RISM theory and the string method

NASA Astrophysics Data System (ADS)

Yoshida, Norio

2018-05-01

A new method for finding the minimum free energy pathway (MFEP) of ions and small molecule transportation through a protein based on the three-dimensional reference interaction site model (3D-RISM) theory combined with the string method has been proposed. The 3D-RISM theory produces the distribution function, or the potential of mean force (PMF), for transporting substances around the given protein structures. By applying the string method to the PMF surface, one can readily determine the MFEP on the PMF surface. The method has been applied to consider the Na+ conduction pathway of channelrhodopsin as an example.

Aromatic sulfonation with sulfur trioxide: mechanism and kinetic model.

PubMed

Moors, Samuel L C; Deraet, Xavier; Van Assche, Guy; Geerlings, Paul; De Proft, Frank

2017-01-01

Electrophilic aromatic sulfonation of benzene with sulfur trioxide is studied with ab initio molecular dynamics simulations in gas phase, and in explicit noncomplexing (CCl 3 F) and complexing (CH 3 NO 2 ) solvent models. We investigate different possible reaction pathways, the number of SO 3 molecules participating in the reaction, and the influence of the solvent. Our simulations confirm the existence of a low-energy concerted pathway with formation of a cyclic transition state with two SO 3 molecules. Based on the simulation results, we propose a sequence of elementary reaction steps and a kinetic model compatible with experimental data. Furthermore, a new alternative reaction pathway is proposed in complexing solvent, involving two SO 3 and one CH 3 NO 2 .

Molecular scaffold analysis of natural products databases in the public domain.

PubMed

Yongye, Austin B; Waddell, Jacob; Medina-Franco, José L

2012-11-01

Natural products represent important sources of bioactive compounds in drug discovery efforts. In this work, we compiled five natural products databases available in the public domain and performed a comprehensive chemoinformatic analysis focused on the content and diversity of the scaffolds with an overview of the diversity based on molecular fingerprints. The natural products databases were compared with each other and with a set of molecules obtained from in-house combinatorial libraries, and with a general screening commercial library. It was found that publicly available natural products databases have different scaffold diversity. In contrast to the common concept that larger libraries have the largest scaffold diversity, the largest natural products collection analyzed in this work was not the most diverse. The general screening library showed, overall, the highest scaffold diversity. However, considering the most frequent scaffolds, the general reference library was the least diverse. In general, natural products databases in the public domain showed low molecule overlap. In addition to benzene and acyclic compounds, flavones, coumarins, and flavanones were identified as the most frequent molecular scaffolds across the different natural products collections. The results of this work have direct implications in the computational and experimental screening of natural product databases for drug discovery. © 2012 John Wiley & Sons A/S.

Meta-All: a system for managing metabolic pathway information.

PubMed

Weise, Stephan; Grosse, Ivo; Klukas, Christian; Koschützki, Dirk; Scholz, Uwe; Schreiber, Falk; Junker, Björn H

2006-10-23

Many attempts are being made to understand biological subjects at a systems level. A major resource for these approaches are biological databases, storing manifold information about DNA, RNA and protein sequences including their functional and structural motifs, molecular markers, mRNA expression levels, metabolite concentrations, protein-protein interactions, phenotypic traits or taxonomic relationships. The use of these databases is often hampered by the fact that they are designed for special application areas and thus lack universality. Databases on metabolic pathways, which provide an increasingly important foundation for many analyses of biochemical processes at a systems level, are no exception from the rule. Data stored in central databases such as KEGG, BRENDA or SABIO-RK is often limited to read-only access. If experimentalists want to store their own data, possibly still under investigation, there are two possibilities. They can either develop their own information system for managing that own data, which is very time-consuming and costly, or they can try to store their data in existing systems, which is often restricted. Hence, an out-of-the-box information system for managing metabolic pathway data is needed. We have designed META-ALL, an information system that allows the management of metabolic pathways, including reaction kinetics, detailed locations, environmental factors and taxonomic information. Data can be stored together with quality tags and in different parallel versions. META-ALL uses Oracle DBMS and Oracle Application Express. We provide the META-ALL information system for download and use. In this paper, we describe the database structure and give information about the tools for submitting and accessing the data. As a first application of META-ALL, we show how the information contained in a detailed kinetic model can be stored and accessed. META-ALL is a system for managing information about metabolic pathways. It facilitates the handling of pathway-related data and is designed to help biochemists and molecular biologists in their daily research. It is available on the Web at http://bic-gh.de/meta-all and can be downloaded free of charge and installed locally.

Meta-All: a system for managing metabolic pathway information

PubMed Central

Weise, Stephan; Grosse, Ivo; Klukas, Christian; Koschützki, Dirk; Scholz, Uwe; Schreiber, Falk; Junker, Björn H

2006-01-01

Background Many attempts are being made to understand biological subjects at a systems level. A major resource for these approaches are biological databases, storing manifold information about DNA, RNA and protein sequences including their functional and structural motifs, molecular markers, mRNA expression levels, metabolite concentrations, protein-protein interactions, phenotypic traits or taxonomic relationships. The use of these databases is often hampered by the fact that they are designed for special application areas and thus lack universality. Databases on metabolic pathways, which provide an increasingly important foundation for many analyses of biochemical processes at a systems level, are no exception from the rule. Data stored in central databases such as KEGG, BRENDA or SABIO-RK is often limited to read-only access. If experimentalists want to store their own data, possibly still under investigation, there are two possibilities. They can either develop their own information system for managing that own data, which is very time-consuming and costly, or they can try to store their data in existing systems, which is often restricted. Hence, an out-of-the-box information system for managing metabolic pathway data is needed. Results We have designed META-ALL, an information system that allows the management of metabolic pathways, including reaction kinetics, detailed locations, environmental factors and taxonomic information. Data can be stored together with quality tags and in different parallel versions. META-ALL uses Oracle DBMS and Oracle Application Express. We provide the META-ALL information system for download and use. In this paper, we describe the database structure and give information about the tools for submitting and accessing the data. As a first application of META-ALL, we show how the information contained in a detailed kinetic model can be stored and accessed. Conclusion META-ALL is a system for managing information about metabolic pathways. It facilitates the handling of pathway-related data and is designed to help biochemists and molecular biologists in their daily research. It is available on the Web at and can be downloaded free of charge and installed locally. PMID:17059592

Size-independent neural networks based first-principles method for accurate prediction of heat of formation of fuels

NASA Astrophysics Data System (ADS)

Yang, GuanYa; Wu, Jiang; Chen, ShuGuang; Zhou, WeiJun; Sun, Jian; Chen, GuanHua

2018-06-01

Neural network-based first-principles method for predicting heat of formation (HOF) was previously demonstrated to be able to achieve chemical accuracy in a broad spectrum of target molecules [L. H. Hu et al., J. Chem. Phys. 119, 11501 (2003)]. However, its accuracy deteriorates with the increase in molecular size. A closer inspection reveals a systematic correlation between the prediction error and the molecular size, which appears correctable by further statistical analysis, calling for a more sophisticated machine learning algorithm. Despite the apparent difference between simple and complex molecules, all the essential physical information is already present in a carefully selected set of small molecule representatives. A model that can capture the fundamental physics would be able to predict large and complex molecules from information extracted only from a small molecules database. To this end, a size-independent, multi-step multi-variable linear regression-neural network-B3LYP method is developed in this work, which successfully improves the overall prediction accuracy by training with smaller molecules only. And in particular, the calculation errors for larger molecules are drastically reduced to the same magnitudes as those of the smaller molecules. Specifically, the method is based on a 164-molecule database that consists of molecules made of hydrogen and carbon elements. 4 molecular descriptors were selected to encode molecule's characteristics, among which raw HOF calculated from B3LYP and the molecular size are also included. Upon the size-independent machine learning correction, the mean absolute deviation (MAD) of the B3LYP/6-311+G(3df,2p)-calculated HOF is reduced from 16.58 to 1.43 kcal/mol and from 17.33 to 1.69 kcal/mol for the training and testing sets (small molecules), respectively. Furthermore, the MAD of the testing set (large molecules) is reduced from 28.75 to 1.67 kcal/mol.

PathNER: a tool for systematic identification of biological pathway mentions in the literature

PubMed Central

2013-01-01

Background Biological pathways are central to many biomedical studies and are frequently discussed in the literature. Several curated databases have been established to collate the knowledge of molecular processes constituting pathways. Yet, there has been little focus on enabling systematic detection of pathway mentions in the literature. Results We developed a tool, named PathNER (Pathway Named Entity Recognition), for the systematic identification of pathway mentions in the literature. PathNER is based on soft dictionary matching and rules, with the dictionary generated from public pathway databases. The rules utilise general pathway-specific keywords, syntactic information and gene/protein mentions. Detection results from both components are merged. On a gold-standard corpus, PathNER achieved an F1-score of 84%. To illustrate its potential, we applied PathNER on a collection of articles related to Alzheimer's disease to identify associated pathways, highlighting cases that can complement an existing manually curated knowledgebase. Conclusions In contrast to existing text-mining efforts that target the automatic reconstruction of pathway details from molecular interactions mentioned in the literature, PathNER focuses on identifying specific named pathway mentions. These mentions can be used to support large-scale curation and pathway-related systems biology applications, as demonstrated in the example of Alzheimer's disease. PathNER is implemented in Java and made freely available online at http://sourceforge.net/projects/pathner/. PMID:24555844

The volatile compound BinBase mass spectral database.

PubMed

Skogerson, Kirsten; Wohlgemuth, Gert; Barupal, Dinesh K; Fiehn, Oliver

2011-08-04

Volatile compounds comprise diverse chemical groups with wide-ranging sources and functions. These compounds originate from major pathways of secondary metabolism in many organisms and play essential roles in chemical ecology in both plant and animal kingdoms. In past decades, sampling methods and instrumentation for the analysis of complex volatile mixtures have improved; however, design and implementation of database tools to process and store the complex datasets have lagged behind. The volatile compound BinBase (vocBinBase) is an automated peak annotation and database system developed for the analysis of GC-TOF-MS data derived from complex volatile mixtures. The vocBinBase DB is an extension of the previously reported metabolite BinBase software developed to track and identify derivatized metabolites. The BinBase algorithm uses deconvoluted spectra and peak metadata (retention index, unique ion, spectral similarity, peak signal-to-noise ratio, and peak purity) from the Leco ChromaTOF software, and annotates peaks using a multi-tiered filtering system with stringent thresholds. The vocBinBase algorithm assigns the identity of compounds existing in the database. Volatile compound assignments are supported by the Adams mass spectral-retention index library, which contains over 2,000 plant-derived volatile compounds. Novel molecules that are not found within vocBinBase are automatically added using strict mass spectral and experimental criteria. Users obtain fully annotated data sheets with quantitative information for all volatile compounds for studies that may consist of thousands of chromatograms. The vocBinBase database may also be queried across different studies, comprising currently 1,537 unique mass spectra generated from 1.7 million deconvoluted mass spectra of 3,435 samples (18 species). Mass spectra with retention indices and volatile profiles are available as free download under the CC-BY agreement (http://vocbinbase.fiehnlab.ucdavis.edu). The BinBase database algorithms have been successfully modified to allow for tracking and identification of volatile compounds in complex mixtures. The database is capable of annotating large datasets (hundreds to thousands of samples) and is well-suited for between-study comparisons such as chemotaxonomy investigations. This novel volatile compound database tool is applicable to research fields spanning chemical ecology to human health. The BinBase source code is freely available at http://binbase.sourceforge.net/ under the LGPL 2.0 license agreement.

The volatile compound BinBase mass spectral database

PubMed Central

2011-01-01

Background Volatile compounds comprise diverse chemical groups with wide-ranging sources and functions. These compounds originate from major pathways of secondary metabolism in many organisms and play essential roles in chemical ecology in both plant and animal kingdoms. In past decades, sampling methods and instrumentation for the analysis of complex volatile mixtures have improved; however, design and implementation of database tools to process and store the complex datasets have lagged behind. Description The volatile compound BinBase (vocBinBase) is an automated peak annotation and database system developed for the analysis of GC-TOF-MS data derived from complex volatile mixtures. The vocBinBase DB is an extension of the previously reported metabolite BinBase software developed to track and identify derivatized metabolites. The BinBase algorithm uses deconvoluted spectra and peak metadata (retention index, unique ion, spectral similarity, peak signal-to-noise ratio, and peak purity) from the Leco ChromaTOF software, and annotates peaks using a multi-tiered filtering system with stringent thresholds. The vocBinBase algorithm assigns the identity of compounds existing in the database. Volatile compound assignments are supported by the Adams mass spectral-retention index library, which contains over 2,000 plant-derived volatile compounds. Novel molecules that are not found within vocBinBase are automatically added using strict mass spectral and experimental criteria. Users obtain fully annotated data sheets with quantitative information for all volatile compounds for studies that may consist of thousands of chromatograms. The vocBinBase database may also be queried across different studies, comprising currently 1,537 unique mass spectra generated from 1.7 million deconvoluted mass spectra of 3,435 samples (18 species). Mass spectra with retention indices and volatile profiles are available as free download under the CC-BY agreement (http://vocbinbase.fiehnlab.ucdavis.edu). Conclusions The BinBase database algorithms have been successfully modified to allow for tracking and identification of volatile compounds in complex mixtures. The database is capable of annotating large datasets (hundreds to thousands of samples) and is well-suited for between-study comparisons such as chemotaxonomy investigations. This novel volatile compound database tool is applicable to research fields spanning chemical ecology to human health. The BinBase source code is freely available at http://binbase.sourceforge.net/ under the LGPL 2.0 license agreement. PMID:21816034

CREDO: a structural interactomics database for drug discovery

PubMed Central

Schreyer, Adrian M.; Blundell, Tom L.

2013-01-01

CREDO is a unique relational database storing all pairwise atomic interactions of inter- as well as intra-molecular contacts between small molecules and macromolecules found in experimentally determined structures from the Protein Data Bank. These interactions are integrated with further chemical and biological data. The database implements useful data structures and algorithms such as cheminformatics routines to create a comprehensive analysis platform for drug discovery. The database can be accessed through a web-based interface, downloads of data sets and web services at http://www-cryst.bioc.cam.ac.uk/credo. Database URL: http://www-cryst.bioc.cam.ac.uk/credo PMID:23868908

An investigation of isomerization pathways of epoxysaccharides

NASA Astrophysics Data System (ADS)

Andrianov, V. M.; Kirillova, S. G.; Zhbankov, R. G.

1997-07-01

Direct and reverse interconversion pathways of six epoxysaccharide molecules, namely, three molecules with epoxypyranose rings: methyl 2,3-anhydro-2,3,4-trideoxy- β- D-lyxohexopyranoside, methyl 2,3-anhydro-4-deoxy- α- D, L-ribo- and - α- D, L-lyxohexopyranosides and three molecules with epoxypyranose rings: methyl 2,6-di- O-acetyl-3,4-anhydro- α- D, L-( 6,6- 2H2) derivatives of talopyranoside and galactopyranoside, and methyl 3,4-anhydro- α- D, L-allopyranoside were simulated by the Wiberg and Boyd method. This made it possible to determine all stationary and intermediate forms in which anhydropyranose rings can exist. Calculations of barrier heights for interconversion and energies of global minima have shown that conformations revealed in X-ray studies are more favorable. Most of the local minima found lie in the vicinity of the boat (B) forms, the other minima correspond to conformations possessing symmetry elements of the skew-boat (S) and twist (T) forms. The interconversion pathways of the molecules investigated are presented on the Cremer-Pople diagram. We studied the effect of various structural factors on the character of conformational transformations, heights of transition barriers, the form of the ground state, and the energy of stationary forms, and their number and location on the Cremer-Pople diagram.

The Anti-Atherosclerotic Effect of Naringin Is Associated with Reduced Expressions of Cell Adhesion Molecules and Chemokines through NF-κB Pathway.

PubMed

Hsueh, Tun-Pin; Sheen, Jer-Ming; Pang, Jong-Hwei S; Bi, Kuo-Wei; Huang, Chao-Chun; Wu, Hsiao-Ting; Huang, Sheng-Teng

2016-02-05

Naringin has been reported to have an anti-atherosclerosis effect but the underlying mechanism is not fully understood. The aim of this study is to investigate the impact of naringin on the TNF-α-induced expressions of cell adhesion molecules, chemokines and NF-κB signaling pathway in human umbilical vein endothelial cells (HUVECs). The experiments revealed that naringin, at concentrations without cytotoxicity, dose-dependently inhibited the adhesion of THP-1 monocytes to the TNF-α-stimulated HUVECs. The TNF-α-induced expressions of cell adhesion molecules, including VCAM-1, ICAM-1 and E-selectin, at both the mRNA and protein levels, were significantly suppressed by naringin in a dose dependent manner. In addition, the TNF-α-induced mRNA and protein levels of chemokines, including fractalkine/CX3CL1, MCP-1 and RANTES, were also reduced by naringin. Naringin significantly inhibited TNF-α-induced nuclear translocation of NF-κB, which resulted from the inhibited phosphorylation of IKKα/β, IκB-α and NF-κB. Altogether, we proposed that naringin modulated TNF-α-induced expressions of cell adhesion molecules and chemokines through the inhibition of TNF-α-induced activation of IKK/NF-κB signaling pathway to exert the anti-atherosclerotic effect.

Chemical methodology as a source of small-molecule checkpoint inhibitors and heat shock protein 70 (Hsp70) modulators.

PubMed

Huryn, Donna M; Brodsky, Jeffrey L; Brummond, Kay M; Chambers, Peter G; Eyer, Benjamin; Ireland, Alex W; Kawasumi, Masaoki; Laporte, Matthew G; Lloyd, Kayla; Manteau, Baptiste; Nghiem, Paul; Quade, Bettina; Seguin, Sandlin P; Wipf, Peter

2011-04-26

Unique chemical methodology enables the synthesis of innovative and diverse scaffolds and chemotypes and allows access to previously unexplored "chemical space." Compound collections based on such new synthetic methods can provide small-molecule probes of proteins and/or pathways whose functions are not fully understood. We describe the identification, characterization, and evolution of two such probes. In one example, a pathway-based screen for DNA damage checkpoint inhibitors identified a compound, MARPIN (ATM and ATR pathway inhibitor) that sensitizes p53-deficient cells to DNA-damaging agents. Modification of the small molecule and generation of an immobilized probe were used to selectively bind putative protein target(s) responsible for the observed activity. The second example describes a focused library approach that relied on tandem multicomponent reaction methodologies to afford a series of modulators of the heat shock protein 70 (Hsp70) molecular chaperone. The synthesis of libraries based on the structure of MAL3-101 generated a collection of chemotypes, each modulating Hsp70 function, but exhibiting divergent pharmacological activities. For example, probes that compromise the replication of a disease-associated polyomavirus were identified. These projects highlight the importance of chemical methodology development as a source of small-molecule probes and as a drug discovery starting point.

Chemical methodology as a source of small-molecule checkpoint inhibitors and heat shock protein 70 (Hsp70) modulators

PubMed Central

Huryn, Donna M.; Brodsky, Jeffrey L.; Brummond, Kay M.; Chambers, Peter G.; Eyer, Benjamin; Ireland, Alex W.; Kawasumi, Masaoki; LaPorte, Matthew G.; Lloyd, Kayla; Manteau, Baptiste; Nghiem, Paul; Quade, Bettina; Seguin, Sandlin P.; Wipf, Peter

2011-01-01

Unique chemical methodology enables the synthesis of innovative and diverse scaffolds and chemotypes and allows access to previously unexplored “chemical space.” Compound collections based on such new synthetic methods can provide small-molecule probes of proteins and/or pathways whose functions are not fully understood. We describe the identification, characterization, and evolution of two such probes. In one example, a pathway-based screen for DNA damage checkpoint inhibitors identified a compound, MARPIN (ATM and ATR pathway inhibitor) that sensitizes p53-deficient cells to DNA-damaging agents. Modification of the small molecule and generation of an immobilized probe were used to selectively bind putative protein target(s) responsible for the observed activity. The second example describes a focused library approach that relied on tandem multicomponent reaction methodologies to afford a series of modulators of the heat shock protein 70 (Hsp70) molecular chaperone. The synthesis of libraries based on the structure of MAL3-101 generated a collection of chemotypes, each modulating Hsp70 function, but exhibiting divergent pharmacological activities. For example, probes that compromise the replication of a disease-associated polyomavirus were identified. These projects highlight the importance of chemical methodology development as a source of small-molecule probes and as a drug discovery starting point. PMID:21502524

Predicting Protein Relationships to Human Pathways through a Relational Learning Approach Based on Simple Sequence Features.

PubMed

García-Jiménez, Beatriz; Pons, Tirso; Sanchis, Araceli; Valencia, Alfonso

2014-01-01

Biological pathways are important elements of systems biology and in the past decade, an increasing number of pathway databases have been set up to document the growing understanding of complex cellular processes. Although more genome-sequence data are becoming available, a large fraction of it remains functionally uncharacterized. Thus, it is important to be able to predict the mapping of poorly annotated proteins to original pathway models. We have developed a Relational Learning-based Extension (RLE) system to investigate pathway membership through a function prediction approach that mainly relies on combinations of simple properties attributed to each protein. RLE searches for proteins with molecular similarities to specific pathway components. Using RLE, we associated 383 uncharacterized proteins to 28 pre-defined human Reactome pathways, demonstrating relative confidence after proper evaluation. Indeed, in specific cases manual inspection of the database annotations and the related literature supported the proposed classifications. Examples of possible additional components of the Electron transport system, Telomere maintenance and Integrin cell surface interactions pathways are discussed in detail. All the human predicted proteins in the 2009 and 2012 releases 30 and 40 of Reactome are available at http://rle.bioinfo.cnio.es.

Chemistry at molecular junctions: Rotation and dissociation of O2 on the Ag(110) surface induced by a scanning tunneling microscope.

PubMed

Roy, Sharani; Mujica, Vladimiro; Ratner, Mark A

2013-08-21

The scanning tunneling microscope (STM) is a fascinating tool used to perform chemical processes at the single-molecule level, including bond formation, bond breaking, and even chemical reactions. Hahn and Ho [J. Chem. Phys. 123, 214702 (2005)] performed controlled rotations and dissociations of single O2 molecules chemisorbed on the Ag(110) surface at precise bias voltages using STM. These threshold voltages were dependent on the direction of the bias voltage and the initial orientation of the chemisorbed molecule. They also observed an interesting voltage-direction-dependent and orientation-dependent pathway selectivity suggestive of mode-selective chemistry at molecular junctions, such that in one case the molecule underwent direct dissociation, whereas in the other case it underwent rotation-mediated dissociation. We present a detailed, first-principles-based theoretical study to investigate the mechanism of the tunneling-induced O2 dynamics, including the origin of the observed threshold voltages, the pathway dependence, and the rate of O2 dissociation. Results show a direct correspondence between the observed threshold voltage for a process and the activation energy for that process. The pathway selectivity arises from a competition between the voltage-modified barrier heights for rotation and dissociation, and the coupling strength of the tunneling electrons to the rotational and vibrational modes of the adsorbed molecule. Finally, we explore the "dipole" and "resonance" mechanisms of inelastic electron tunneling to elucidate the energy transfer between the tunneling electrons and chemisorbed O2.

From Databases to Modelling of Functional Pathways

PubMed Central

2004-01-01

This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell. PMID:18629070

From databases to modelling of functional pathways.

PubMed

Nasi, Sergio

2004-01-01

This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell.

AOP-DB: A database resource for the exploration of Adverse Outcome Pathways through integrated association networks.

EPA Science Inventory

The Adverse Outcome Pathway (AOP) framework describes the progression of a toxicity pathway from molecular perturbation to population-level outcome in a series of measurable, mechanistic responses. The controlled, computer-readable vocabulary that defines an AOP has the ability t...

THE E2/FRB PATHWAY REGULATION OF DNA REPLICATION AND PROTEIN BIOSYNTHESIS

EPA Science Inventory

The E2F/Rb pathway plays a pivotal role in the control of cell cycle progression and regulates the expression of genes required for Gl/S transition. Our study examines the genomic response in Drosophila embryos after overexpression and mutation of E2F/Rb pathway molecules. Hierar...

In silico database screening of potential targets and pathways of compounds contained in plants used for psoriasis vulgaris.

PubMed

May, Brian H; Deng, Shiqiang; Zhang, Anthony L; Lu, Chuanjian; Xue, Charlie C L

2015-09-01

Reviews and meta-analyses of clinical trials identified plants used as traditional medicines (TMs) that show promise for psoriasis. These include Rehmannia glutinosa, Camptotheca acuminata, Indigo naturalis and Salvia miltiorrhiza. Compounds contained in these TMs have shown activities of relevance to psoriasis in experimental models. To further investigate the likely mechanisms of action of the multiple compounds in these TMs, we undertook a computer-based in silico investigation of the proteins known to be regulated by these compounds and their associated biological pathways. The proteins reportedly regulated by compounds in these four TMs were identified using the HIT (Herbal Ingredients' Targets) database. The resultant data were entered into the PANTHER (Protein ANnotation THrough Evolutionary Relationship) database to identify the pathways in which the proteins could be involved. The study identified 237 compounds in the TMs and these retrieved 287 proteins from HIT. These proteins identified 59 pathways in PANTHER with most proteins being located in the Apoptosis, Angiogenesis, Inflammation mediated by chemokine and cytokine, Gonadotropin releasing hormone receptor, and/or Interleukin signaling pathways. All four TMs contained compounds that had regulating effects on Apoptosis regulator BAX, Apoptosis regulator Bcl-2, Caspase-3, Tumor necrosis factor (TNF) or Prostaglandin G/H synthase 2 (COX2). The main proteins and pathways are primarily related to inflammation, proliferation and angiogenesis which are all processes involved in psoriasis. Experimental studies have reported that certain compounds from these TMs can regulate the expression of proteins involved in each of these pathways.

Metabolomics analysis: Finding out metabolic building blocks

PubMed Central

2017-01-01

In this paper we propose a new methodology for the analysis of metabolic networks. We use the notion of strongly connected components of a graph, called in this context metabolic building blocks. Every strongly connected component is contracted to a single node in such a way that the resulting graph is a directed acyclic graph, called a metabolic DAG, with a considerably reduced number of nodes. The property of being a directed acyclic graph brings out a background graph topology that reveals the connectivity of the metabolic network, as well as bridges, isolated nodes and cut nodes. Altogether, it becomes a key information for the discovery of functional metabolic relations. Our methodology has been applied to the glycolysis and the purine metabolic pathways for all organisms in the KEGG database, although it is general enough to work on any database. As expected, using the metabolic DAGs formalism, a considerable reduction on the size of the metabolic networks has been obtained, specially in the case of the purine pathway due to its relative larger size. As a proof of concept, from the information captured by a metabolic DAG and its corresponding metabolic building blocks, we obtain the core of the glycolysis pathway and the core of the purine metabolism pathway and detect some essential metabolic building blocks that reveal the key reactions in both pathways. Finally, the application of our methodology to the glycolysis pathway and the purine metabolism pathway reproduce the tree of life for the whole set of the organisms represented in the KEGG database which supports the utility of this research. PMID:28493998

Database and Related Activities in Japan

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

Murakami, Izumi; Kato, Daiji; Kato, Masatoshi

2011-05-11

We have constructed and made available atomic and molecular (AM) numerical databases on collision processes such as electron-impact excitation and ionization, recombination and charge transfer of atoms and molecules relevant for plasma physics, fusion research, astrophysics, applied-science plasma, and other related areas. The retrievable data is freely accessible via the internet. We also work on atomic data evaluation and constructing collisional-radiative models for spectroscopic plasma diagnostics. Recently we have worked on Fe ions and W ions theoretically and experimentally. The atomic data and collisional-radiative models for these ions are examined and applied to laboratory plasmas. A visible M1 transition ofmore » W{sup 26+} ion is identified at 389.41 nm by EBIT experiments and theoretical calculations. We have small non-retrievable databases in addition to our main database. Recently we evaluated photo-absorption cross sections for 9 atoms and 23 molecules and we present them as a new database. We established a new association ''Forum of Atomic and Molecular Data and Their Applications'' to exchange information among AM data producers, data providers and data users in Japan and we hope this will help to encourage AM data activities in Japan.« less

Database and Related Activities in Japan

NASA Astrophysics Data System (ADS)

Murakami, Izumi; Kato, Daiji; Kato, Masatoshi; Sakaue, Hiroyuki A.; Kato, Takako; Ding, Xiaobin; Morita, Shigeru; Kitajima, Masashi; Koike, Fumihiro; Nakamura, Nobuyuki; Sakamoto, Naoki; Sasaki, Akira; Skobelev, Igor; Tsuchida, Hidetsugu; Ulantsev, Artemiy; Watanabe, Tetsuya; Yamamoto, Norimasa

2011-05-01

We have constructed and made available atomic and molecular (AM) numerical databases on collision processes such as electron-impact excitation and ionization, recombination and charge transfer of atoms and molecules relevant for plasma physics, fusion research, astrophysics, applied-science plasma, and other related areas. The retrievable data is freely accessible via the internet. We also work on atomic data evaluation and constructing collisional-radiative models for spectroscopic plasma diagnostics. Recently we have worked on Fe ions and W ions theoretically and experimentally. The atomic data and collisional-radiative models for these ions are examined and applied to laboratory plasmas. A visible M1 transition of W26+ ion is identified at 389.41 nm by EBIT experiments and theoretical calculations. We have small non-retrievable databases in addition to our main database. Recently we evaluated photo-absorption cross sections for 9 atoms and 23 molecules and we present them as a new database. We established a new association "Forum of Atomic and Molecular Data and Their Applications" to exchange information among AM data producers, data providers and data users in Japan and we hope this will help to encourage AM data activities in Japan.

Collisional excitation of molecules in dense interstellar clouds

NASA Technical Reports Server (NTRS)

Green, S.

1985-01-01

State transitions which permit the identification of the molecular species in dense interstellar clouds are reviewed, along with the techniques used to calculate the transition energies, the database on known molecular transitions and the accuracy of the values. The transition energies cannot be measured directly and therefore must be modeled analytically. Scattering theory is used to determine the intermolecular forces on the basis of quantum mechanics. The nuclear motions can also be modeled with classical mechanics. Sample rate constants are provided for molecular systems known to inhabit dense interstellar clouds. The values serve as a database for interpreting microwave and RF astrophysical data on the transitions undergone by interstellar molecules.

Quantitative Proteomics Reveals Temporal Proteomic Changes in Signaling Pathways during BV2 Mouse Microglial Cell Activation.

PubMed

Woo, Jongmin; Han, Dohyun; Wang, Joseph Injae; Park, Joonho; Kim, Hyunsoo; Kim, Youngsoo

2017-09-01

The development of systematic proteomic quantification techniques in systems biology research has enabled one to perform an in-depth analysis of cellular systems. We have developed a systematic proteomic approach that encompasses the spectrum from global to targeted analysis on a single platform. We have applied this technique to an activated microglia cell system to examine changes in the intracellular and extracellular proteomes. Microglia become activated when their homeostatic microenvironment is disrupted. There are varying degrees of microglial activation, and we chose to focus on the proinflammatory reactive state that is induced by exposure to such stimuli as lipopolysaccharide (LPS) and interferon-gamma (IFN-γ). Using an improved shotgun proteomics approach, we identified 5497 proteins in the whole-cell proteome and 4938 proteins in the secretome that were associated with the activation of BV2 mouse microglia by LPS or IFN-γ. Of the differentially expressed proteins in stimulated microglia, we classified pathways that were related to immune-inflammatory responses and metabolism. Our label-free parallel reaction monitoring (PRM) approach made it possible to comprehensively measure the hyper-multiplex quantitative value of each protein by high-resolution mass spectrometry. Over 450 peptides that corresponded to pathway proteins and direct or indirect interactors via the STRING database were quantified by label-free PRM in a single run. Moreover, we performed a longitudinal quantification of secreted proteins during microglial activation, in which neurotoxic molecules that mediate neuronal cell loss in the brain are released. These data suggest that latent pathways that are associated with neurodegenerative diseases can be discovered by constructing and analyzing a pathway network model of proteins. Furthermore, this systematic quantification platform has tremendous potential for applications in large-scale targeted analyses. The proteomics data for discovery and label-free PRM analysis have been deposited to the ProteomeXchange Consortium with identifiers and , respectively.

MicroRNA-106a-5p facilitates human glioblastoma cell proliferation and invasion by targeting adenomatosis polyposis coli protein

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

Li, Dazhi; Wang, Zengliang; Chen, Zigui

The invasive behavior of glioblastoma multiforme (GBM) cells is an important reason for its poor prognosis. Tumor cells acquire an ability to digest the extracellular matrix and infiltrate the adjacent normal tissue during invasion. Restraining GBM invasion by changing effector molecules can significantly improve the patient's prognosis. MiRNAs are involved in multiple biological functions via suppressing target genes. In this study, we found that miR-106a-5p expression was high in GBM tissues and cells. The data showed an inverse correlation in GBM tissues between the levels of miR-106a-5p and adenomatosis polyposis coli (APC) mRNAs.Additionally, ectopic expression of miR-106a-5pfacilitated the invasion ofmore » GBM cells whereas inhibition of miR-106a-5p expression weakened the invasive ability. Numerous transcription factors are downstream effectors of the Wnt/β-catenin pathway. Target prediction databases and luciferase data showed that APC is a new direct target of miR-106a-5p. Importantly, westernblot assays demonstrated that miR-106a-5p can reduce APC protein level and enhance target proteins of Wnt/β-catenin pathway. Thus, we hypothesize that miR-106a-5p directly targets APC, resulting in the activation of Wnt/β-catenin pathway. Our results suggest that miR-106a-5p is involved in the invasive behavior of GBM cells and by targeting APC and activating Wnt/β-catenin pathway, it provides a theoretical basis for developing potential clinical strategies. - Highlights: • miR-106a-5p is upregulated in human glioblastoma. • Upregulation of miR-106a-5p promotes glioma cell proliferation and invasion. • miR-106a-5p inactivates the Wnt/β-catenin pathway by directly targeting APC.« less

Transition model for ricin-aptamer interactions with multiple pathways and energy barriers

NASA Astrophysics Data System (ADS)

Wang, Bin; Xu, Bingqian

2014-02-01

We develop a transition model to interpret single-molecule ricin-aptamer interactions with multiple unbinding pathways and energy barriers measured by atomic force microscopy dynamic force spectroscopy. Molecular simulations establish the relationship between binding conformations and the corresponding unbinding pathways. Each unbinding pathway follows a Bell-Evans multiple-barrier model. Markov-type transition matrices are developed to analyze the redistribution of unbinding events among the pathways under different loading rates. Our study provides detailed information about complex behaviors in ricin-aptamer unbinding events.

The HITRAN2016 molecular spectroscopic database

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

Gordon, I. E.; Rothman, L. S.; Hill, C.

This paper describes the contents of the 2016 edition of the HITRAN molecular spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2012 and its updates during the intervening years. The HITRAN molecular absorption compilation is comprised of five major components: the traditional line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, infrared absorption cross-sections for molecules not yet amenable to representation in a line-by-line form, collision-induced absorption data, aerosol indices of refraction, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additionalmore » absorption phenomena, added line-shape formalisms, and validity. Moreover, molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth. Of considerable note, experimental IR cross-sections for almost 200 additional significant molecules have been added to the database.« less

PhAST: pharmacophore alignment search tool.

PubMed

Hähnke, Volker; Hofmann, Bettina; Grgat, Tomislav; Proschak, Ewgenij; Steinhilber, Dieter; Schneider, Gisbert

2009-04-15

We present a ligand-based virtual screening technique (PhAST) for rapid hit and lead structure searching in large compound databases. Molecules are represented as strings encoding the distribution of pharmacophoric features on the molecular graph. In contrast to other text-based methods using SMILES strings, we introduce a new form of text representation that describes the pharmacophore of molecules. This string representation opens the opportunity for revealing functional similarity between molecules by sequence alignment techniques in analogy to homology searching in protein or nucleic acid sequence databases. We favorably compared PhAST with other current ligand-based virtual screening methods in a retrospective analysis using the BEDROC metric. In a prospective application, PhAST identified two novel inhibitors of 5-lipoxygenase product formation with minimal experimental effort. This outcome demonstrates the applicability of PhAST to drug discovery projects and provides an innovative concept of sequence-based compound screening with substantial scaffold hopping potential. 2008 Wiley Periodicals, Inc.

PD-1/PD-L1 inhibitor screening of caffeoylquinic acid compounds using surface plasmon resonance spectroscopy.

PubMed

Han, Ya; Gao, Yaning; He, Tian; Wang, Daidong; Guo, Ning; Zhang, Xiaotian; Chen, Shizhong; Wang, Hong

2018-04-15

Following the FDA approval of three monoclonal antibodies of PD-1/PD-L1, this pathway has become a promising target for cancer treatment. Currently small-molecule inhibitors have not been extensively investigated, and appropriate screening methods for such inhibitors are urgently required. In this study, surface plasmon resonance (SPR) technology was used to evaluate the affinity and competitive inhibition of nine caffeoylquinic acid compounds (CQAs) against PD-1/PD-L1. As a result, four small molecules including 1-CQA, 3-CQA, 4-CQA and 5-CQA were determined as PD-1/PD-L1 inhibitors. This study provided an efficient method for screening small-molecule inhibitors targeting PD-1/PD-L1 pathway. Copyright © 2018. Published by Elsevier Inc.

Characterization of the Mycobacterium tuberculosis phagosome and evidence that phagosomal maturation is inhibited

PubMed Central

1995-01-01

We have used the cryosection immunogold technique to study the composition of the Mycobacterium tuberculosis phagosome. We have used quantitative immunogold staining to determine the distribution of several known markers of the endosomal-lysosomal pathway in human monocytes after ingestion of either M. tuberculosis, Legionella pneumophila, or polystyrene beads. Compared with the other phagocytic particles studied, the M. tuberculosis phagosome exhibits delayed clearance of major histocompatibility complex (MHC) class I molecules, relatively intense staining for MHC class II molecules and the endosomal marker transferrin receptor, and relatively weak staining for the lysosomal membrane glycoproteins, CD63, LAMP-1, and LAMP-2 and the lysosomal acid protease, cathepsin D. In contrast to M. tuberculosis, the L. pneumophila phagosome rapidly clears MHC class I molecules and excludes all endosomal-lysosomal markers studied. In contrast to both live M. tuberculosis and L. pneumophila phagosomes, phagosomes containing either polystyrene beads or heat-killed M. tuberculosis stain intensely for lysosomal membrane glycoproteins and cathepsin D. These findings suggest that (a) M. tuberculosis retards the maturation of its phagosome along the endosomal-lysosomal pathway and resides in a compartment with endosomal, as opposed to lysosomal, characteristics; and (b) the intraphagosomal pathway, i.e., the pathway followed by several intracellular parasites that inhibit phagosome-lysosome fusion, is heterogeneous. PMID:7807006

First-principles study of the formation of glycine-producing radicals from common interstellar species

NASA Astrophysics Data System (ADS)

Sato, Akimasa; Kitazawa, Yuya; Ochi, Toshiro; Shoji, Mitsuo; Komatsu, Yu; Kayanuma, Megumi; Aikawa, Yuri; Umemura, Masayuki; Shigeta, Yasuteru

2018-03-01

Glycine, the simplest amino acid, has been intensively searched for in molecular clouds, and the comprehensive clarification of the formation path of interstellar glycine is now imperative. Among all the possible glycine formation pathways, we focused on the radical pathways revealed by Garrod (2013). In the present study, we have precisely investigated all the chemical reaction steps related to the glycine formation processes based on state-of-the-art density functional theory (DFT) calculations. We found that two reaction pathways require small activation barriers (ΔE‡ ≤ 7.75 kJ mol-1), which demonstrates the possibility of glycine formation even at low temperatures in interstellar space if the radical species are generated. The origin of carbon and nitrogen in the glycine backbone and their combination patterns are further discussed in relation to the formation mechanisms. According to the clarification of the atomic correspondence between glycine and its potential parental molecules, it is shown that the nitrogen and two carbons in the glycine can originate in three common interstellar molecules, methanol, hydrogen cyanide, and ammonia, and that the source molecules of glycine can be described by any of their combinations. The glycine formation processes can be categorized into six patterns. Finally, we discussed two other glycine formation pathways expected from the present DFT calculation results.

Differential regulation of peripheral CD4+ T cell tolerance induced by deletion and TCR revision.

PubMed

Ali, Mohamed; Weinreich, Michael; Balcaitis, Stephanie; Cooper, Cristine J; Fink, Pamela J

2003-12-01

In Vbeta5 transgenic mice, mature Vbeta5(+)CD4(+) T cells are tolerized upon recognition of a self Ag, encoded by a defective endogenous retrovirus, whose expression is confined to the lymphoid periphery. Cells are driven by the tolerogen to enter one of two tolerance pathways, deletion or TCR revision. CD4(+) T cells entering the former pathway are rendered anergic and then eliminated. In contrast, TCR revision drives gene rearrangement at the endogenous TCR beta locus and results in the appearance of Vbeta5(-), endogenous Vbeta(+), CD4(+) T cells that are both self-tolerant and functional. An analysis of the molecules that influence each of these pathways was conducted to understand better the nature of the interactions that control tolerance induction in the lymphoid periphery. These studies reveal that deletion is efficient in reconstituted radiation chimeras and is B cell, CD28, inducible costimulatory molecule, Fas, CD4, and CD8 independent. In contrast, TCR revision is radiosensitive, B cell, CD28, and inducible costimulatory molecule dependent, Fas and CD4 influenced, and CD8 independent. Our data demonstrate the differential regulation of these two divergent tolerance pathways, despite the fact that they are both driven by the same tolerogen and restricted to mature CD4(+) T cells.

Potential Therapeutic Targets of Epithelial-Mesenchymal Transition in Melanoma

PubMed Central

Pearlman, Ross L.; de Oca, Mary Katherine Montes; Pal, Harish Chandra; Afaq, Farrukh

2017-01-01

Melanoma is a cutaneous neoplastic growth of melanocytes with great potential to invade and metastasize, especially when not treated early and effectively. Epithelial-mesenchymal transition (EMT) is the process by which melanocytes lose their epithelial characteristics and acquire mesenchymal phenotypes. Mesenchymal protein expression increases the motility, invasiveness, and metastatic potential of melanoma. Many pathways play a role in promotion of mesenchymal protein expression including RAS/RAF/MEK/ERK, PI3K/AKT/mTOR, Wnt/β-catenin, and several others. Downstream effectors of these pathways induce expression of EMT transcription factors including Snail, Slug, Twist, and Zeb that promote repression of epithelial and induction of mesenchymal character. Emerging research has demonstrated that a variety of small molecule inhibitors as well as phytochemicals can influence the progression of EMT and may even reverse the process, inducing re-expression of epithelial markers. Phytochemicals are of particular interest as supplementary treatment options because of their relatively low toxicities and anti-EMT properties. Modulation of EMT signaling pathways using synthetic small molecules and phytochemicals is a potential therapeutic strategy for reducing the aggressive progression of metastatic melanoma. In this review, we discuss the emerging pathways and transcription factor targets that regulate EMT and evaluate potential synthetic small molecules and naturally occurring compounds that may reduce metastatic melanoma progression. PMID:28131904

Inhibition of the Ras-Net (Elk-3) pathway by a novel pyrazole that affects microtubules.

PubMed

Wasylyk, Christine; Zheng, Hong; Castell, Christelle; Debussche, Laurent; Multon, Marie-Christine; Wasylyk, Bohdan

2008-03-01

Net (Elk-3/SAP-2/Erp) is a transcription factor that is phosphorylated and activated by the Ras-extracellular signal-regulated kinase (Erk) signaling pathway and is involved in wound healing, angiogenesis, and tumor growth. In a cell-based screen for small molecule inhibitors of Ras activation of Net transcriptional activity, we identified a novel pyrazole, XRP44X. XRP44X inhibits fibroblast growth factor 2 (FGF-2)-induced Net phosphorylation by the Ras-Erk signaling upstream from Ras. It also binds to the colchicine-binding site of tubulin, depolymerizes microtubules, stimulates cell membrane blebbing, and affects the morphology of the actin skeleton. Interestingly, Combretastin-A4, which produces similar effects on the cytoskeleton, also inhibits FGF-2 Ras-Net signaling. This differs from other classes of agents that target microtubules, which have either little effect (vincristine) or no effect (docetaxel and nocodazole) on the Ras-Net pathway. XRP44X inhibits various cellular properties, including cell growth, cell cycle progression, and aortal sprouting, similar to other molecules that bind to the tubulin colchicine site. XRP44X has the potentially interesting property of connecting two important pathways involved in cell transformation and may thereby represent an interesting class of molecules that could be developed for cancer treatment.

Representing metabolic pathway information: an object-oriented approach.

PubMed

Ellis, L B; Speedie, S M; McLeish, R

1998-01-01

The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD) is a website providing information and dynamic links for microbial metabolic pathways, enzyme reactions, and their substrates and products. The Compound, Organism, Reaction and Enzyme (CORE) object-oriented database management system was developed to contain and serve this information. CORE was developed using Java, an object-oriented programming language, and PSE persistent object classes from Object Design, Inc. CORE dynamically generates descriptive web pages for reactions, compounds and enzymes, and reconstructs ad hoc pathway maps starting from any UM-BBD reaction. CORE code is available from the authors upon request. CORE is accessible through the UM-BBD at: http://www. labmed.umn.edu/umbbd/index.html.

A two-step approach for mining patient treatment pathways in administrative healthcare databases.

PubMed

Najjar, Ahmed; Reinharz, Daniel; Girouard, Catherine; Gagné, Christian

2018-05-01

Clustering electronic medical records allows the discovery of information on healthcare practices. Entries in such medical records are usually composed of a succession of diagnostics or therapeutic steps. The corresponding processes are complex and heterogeneous since they depend on medical knowledge integrating clinical guidelines, the physician's individual experience, and patient data and conditions. To analyze such data, we are first proposing to cluster medical visits, consultations, and hospital stays into homogeneous groups, and then to construct higher-level patient treatment pathways over these different groups. These pathways are then also clustered to distill typical pathways, enabling interpretation of clusters by experts. This approach is evaluated on a real-world administrative database of elderly people in Québec suffering from heart failures. Copyright © 2018 Elsevier B.V. All rights reserved.

Proteome reference map and regulation network of neonatal rat cardiomyocyte

PubMed Central

Li, Zi-jian; Liu, Ning; Han, Qi-de; Zhang, You-yi

2011-01-01

Aim: To study and establish a proteome reference map and regulation network of neonatal rat cardiomyocyte. Methods: Cultured cardiomyocytes of neonatal rats were used. All proteins expressed in the cardiomyocytes were separated and identified by two-dimensional polyacrylamide gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). Biological networks and pathways of the neonatal rat cardiomyocytes were analyzed using the Ingenuity Pathway Analysis (IPA) program (www.ingenuity.com). A 2-DE database was made accessible on-line by Make2ddb package on a web server. Results: More than 1000 proteins were separated on 2D gels, and 148 proteins were identified. The identified proteins were used for the construction of an extensible markup language-based database. Biological networks and pathways were constructed to analyze the functions associate with cardiomyocyte proteins in the database. The 2-DE database of rat cardiomyocyte proteins can be accessed at http://2d.bjmu.edu.cn. Conclusion: A proteome reference map and regulation network of the neonatal rat cardiomyocytes have been established, which may serve as an international platform for storage, analysis and visualization of cardiomyocyte proteomic data. PMID:21841810

Role of insulin, adipocyte hormones, and nutrient-sensing pathways in regulating fuel metabolism and energy homeostasis: a nutritional perspective of diabetes, obesity, and cancer.

PubMed

Marshall, Stephen

2006-08-01

Traditionally, nutrients such as glucose and amino acids have been viewed as substrates for the generation of high-energy molecules and as precursors for the biosynthesis of macromolecules. However, it is now apparent that nutrients also function as signaling molecules in functionally diverse signal transduction pathways. Glucose and amino acids trigger signaling cascades that regulate various aspects of fuel and energy metabolism and control the growth, proliferation, and survival of cells. Here, we provide a functional and regulatory overview of three well-established nutrient signaling pathways-the hexosamine signaling pathway, the mTOR (mammalian target of rapamycin) signaling pathway, and the adenosine monophosphate-activated protein kinase (AMPK) signaling pathway. Nutrient signaling pathways are interconnected, coupled to insulin signaling, and linked to the release of metabolic hormones from adipose tissue. Thus, nutrient signaling pathways do not function in isolation. Rather, they appear to serve as components of a larger "metabolic regulatory network" that controls fuel and energy metabolism (at the cell, tissue, and whole-body levels) and links nutrient availability with cell growth and proliferation. Understanding the diverse roles of nutrients and delineating nutrient signaling pathways should facilitate drug discovery research and the search for novel therapeutic compounds to prevent and treat various human diseases such as diabetes, obesity, and cancer.

Water-mediated electron transfer between protein redox centers.

PubMed

Migliore, Agostino; Corni, Stefano; Felice, Rosa Di; Molinari, Elisa

2007-04-12

Recent experimental and theoretical investigations show that water molecules between or near redox partners can significantly affect their electron-transfer (ET) properties. Here we study the effects of intervening water molecules on the electron self-exchange reaction of azurin (Az), by performing a conformational sampling on the water medium and by using a newly developed ab initio method to calculate transfer integrals between molecular redox sites. We show that the insertion of water molecules at the interface between the copper active sites of Az dimers slightly increases the overall ET rate, while some favorable water conformations can considerably enhance the ET kinetics. These features are traced back to the interplay of two competing factors: the electrostatic interaction between the water and protein subsystems (mainly opposing the ET process for the water arrangements drawn from MD simulations) and the effectiveness of water in mediating ET coupling pathways. Such an interplay provides a physical basis for the found absence of correlation between the electronic couplings derived through ab initio electronic structure calculations and the related quantities obtained through the Empirical Pathways (EP) method. In fact, the latter does not account for electrostatic effects on the transfer integrals. Thus, we conclude that the water-mediated electron tunneling is not controlled by the geometry of a single physical pathway. We discuss the results in terms of the interplay between different ET pathways controlled by the conformational changes of one of the water molecules via its electrostatic influence. Finally, we examine the dynamical effects of the interfacial water and check the validity of the Condon approximation.

Experimental and theoretical study of the pyrrole cluster photochemistry: Closing the {pi}{sigma}{sup *} dissociation pathway by complexation

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

Poterya, Viktoriya; Profant, Vaclav; Farnik, Michal

Photolysis of size selected pyrrole clusters has been investigated and compared to the photolysis of an isolated pyrrole molecule. Experimentally, size distributions of different mean cluster sizes (n=3 and n>>5) have been prepared in supersonic expansions and the clusters were photolyzed at 243 and 193 nm. The kinetic energy distributions of the H photofragments have been measured. The distributions exhibit a bimodal character with fast and slow H-fragment peaks similar to the spectra of the bare molecule. However, with increasing cluster size the slow component gains intensity with respect to the fast one. A similar effect is observed with increasingmore » the excitation energy from 243 to 193 nm. Theoretical calculations at the CASSCF/CASPT2 level have been performed for bare and complexed pyrroles (pyrrole is complexed with an argon atom and with another pyrrole unit). Combination of theoretical and experimental approaches leads to the conclusion that the direct dissociative pathway along the {pi}{sigma}{sup *} potential energy surface in the N-H stretch coordinate is closed by the presence of the solvent molecule. This pathway is an important channel leading to the fast H atoms in the dissociation of the bare molecule. The solvent molecule influences significantly the electronic structure in the Rydberg-type {pi}{sigma}{sup *} state while it has little influence on the valence states. The slow channel is mostly populated by the out-of-plane deformation mode which is also not influenced by solvation. We have also studied other possible reaction channels in pyrrole clusters (hydrogen transfer, dimerization). The present study shows that more insight into the bulk behavior of biologically relevant molecules can be gained from cluster studies.« less

Network medicine in disease analysis and therapeutics.

PubMed

Chen, B; Butte, A J

2013-12-01

Two parallel trends are occurring in drug discovery. The first is that we are moving away from a symptom-based disease classification system to a system based on molecules and molecular states. The second is that we are shifting from targeting a single molecule toward targeting multiple molecules, pathways, or networks. Network medicine is an approach to understanding disease and discovering therapeutics looking at many molecules and how they interrelate, and it may play a critical role in the adoption of both trends.

Critical assessment of human metabolic pathway databases: a stepping stone for future integration

PubMed Central

2011-01-01

Background Multiple pathway databases are available that describe the human metabolic network and have proven their usefulness in many applications, ranging from the analysis and interpretation of high-throughput data to their use as a reference repository. However, so far the various human metabolic networks described by these databases have not been systematically compared and contrasted, nor has the extent to which they differ been quantified. For a researcher using these databases for particular analyses of human metabolism, it is crucial to know the extent of the differences in content and their underlying causes. Moreover, the outcomes of such a comparison are important for ongoing integration efforts. Results We compared the genes, EC numbers and reactions of five frequently used human metabolic pathway databases. The overlap is surprisingly low, especially on reaction level, where the databases agree on 3% of the 6968 reactions they have combined. Even for the well-established tricarboxylic acid cycle the databases agree on only 5 out of the 30 reactions in total. We identified the main causes for the lack of overlap. Importantly, the databases are partly complementary. Other explanations include the number of steps a conversion is described in and the number of possible alternative substrates listed. Missing metabolite identifiers and ambiguous names for metabolites also affect the comparison. Conclusions Our results show that each of the five networks compared provides us with a valuable piece of the puzzle of the complete reconstruction of the human metabolic network. To enable integration of the networks, next to a need for standardizing the metabolite names and identifiers, the conceptual differences between the databases should be resolved. Considerable manual intervention is required to reach the ultimate goal of a unified and biologically accurate model for studying the systems biology of human metabolism. Our comparison provides a stepping stone for such an endeavor. PMID:21999653

PLMItRNA, a database for mitochondrial tRNA genes and tRNAs in photosynthetic eukaryotes.

PubMed

Damiano, F; Gallerani, R; Liuni, S; Licciulli, F; Ceci, L R

2001-01-01

The PLMItRNA database for mitochondrial tRNA molecules and genes in VIRIDIPLANTAE: (green plants) [Volpetti,V., Gallerani,R., DeBenedetto,C., Liuni,S., Licciulli,F. and Ceci,L.R. (2000) Nucleic Acids Res., 28, 159-162] has been enlarged to include algae. The database now contains 436 genes and 16 tRNA entries relative to 25 higher plants, eight green algae, four red algae (RHODOPHYTAE:) and two STRAMENOPILES: The PLMItRNA database is accessible via the WWW at http://bio-www.ba.cnr.it:8000/PLMItRNA.

Experimental and Theoretical Studies on Gas-Phase Fragmentation Reactions of Protonated Methyl Benzoate: Concomitant Neutral Eliminations of Benzene, Carbon Dioxide, and Methanol

NASA Astrophysics Data System (ADS)

Xia, Hanxue; Zhang, Yong; Attygalle, Athula B.

2018-06-01

Protonated methyl benzoate, upon activation, fragments by three distinct pathways. The m/z 137 ion for the protonated species generated by helium-plasma ionization (HePI) was mass-selected and subjected to collisional activation. In one fragmentation pathway, the protonated molecule generated a product ion of m/z 59 by eliminating a molecule of benzene (Pathway I). The m/z 59 ion (generally recognized as the methoxycarbonyl cation) produced in this way, then formed a methyl carbenium ion in situ by decarboxylation, which in turn evoked an electrophilic aromatic addition reaction on the benzene ring by a termolecular process to generate the toluenium cation (Pathway II). Moreover, protonated methyl benzoate undergoes also a methanol loss (Pathway III). However, it is not a simple removal of a methanol molecule after a protonation on the methoxy group. The incipient proton migrates to the ring and randomizes to a certain degree before a subsequent transfer of one of the ring protons to the alkoxy group for the concomitant methanol elimination. The spectrum recorded from deuteronated methyl benzoate showed two peaks at m/z 105 and 106 for the benzoyl cation at a ratio of 2:1, confirming the charge-imparting proton is mobile. However, the proton transfer from the benzenium intermediate to the methoxy group for the methanol loss occurs before achieving a complete state of scrambling. [Figure not available: see fulltext.

The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice.

PubMed

Abbott, Kenneth L; Nyre, Erik T; Abrahante, Juan; Ho, Yen-Yi; Isaksson Vogel, Rachel; Starr, Timothy K

2015-01-01

Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Coherent control of the formation of cold heteronuclear molecules by photoassociation

NASA Astrophysics Data System (ADS)

de Lima, Emanuel F.

2017-01-01

We consider the formation of cold diatomic molecules in the electronic ground state by photoassociation of atoms of dissimilar species. A combination of two transition pathways from the free colliding pair of atoms to a bound vibrational level of the electronic molecular ground state is envisioned. The first pathway consists of a pump-dump scheme with two time-delayed laser pulses in the near-infrared frequency domain. The pump pulse drives the transition to a bound vibrational level of an excited electronic state, while the dump pulse transfers the population to a bound vibrational level of the electronic ground state. The second pathway takes advantage of the existing permanent dipole moment and employs a single pulse in the far-infrared domain to drive the transition from the unbound atoms directly to a bound vibrational level in the electronic ground state. We show that this scheme offers the possibility to coherently control the photoassociation yield by manipulating the relative phase and timing of the pulses. The photoassociation mechanism is illustrated for the formation of cold LiCs molecules.

A Wingless and Notch double-repression mechanism regulates G1–S transition in the Drosophila wing

PubMed Central

Herranz, Héctor; Pérez, Lidia; Martín, Francisco A; Milán, Marco

2008-01-01

The control of tissue growth and patterning is orchestrated in various multicellular tissues by the coordinated activity of the signalling molecules Wnt/Wingless (Wg) and Notch, and mutations in these pathways can cause cancer. The role of these molecules in the control of cell proliferation and the crosstalk between their corresponding pathways remain poorly understood. Crosstalk between Notch and Wg has been proposed to organize pattern and growth in the Drosophila wing primordium. Here we report that Wg and Notch act in a surprisingly linear pathway to control G1–S progression. We present evidence that these molecules exert their function by regulating the expression of the dmyc proto-oncogene and the bantam micro-RNA, which positively modulated the activity of the E2F transcription factor. Our results demonstrate that Notch acts in this cellular context as a repressor of cell-cycle progression and Wg has a permissive role in alleviating Notch-mediated repression of G1–S progression in wing cells. PMID:18451803

Arbuscular mycorrhizal fungal inoculation increases phenolic synthesis in clover roots via hydrogen peroxide, salicylic acid and nitric oxide signaling pathways.

PubMed

Zhang, Rui-Qin; Zhu, Hong-Hui; Zhao, Hai-Quan; Yao, Qing

2013-01-01

Arbuscular mycorrhizal fungi can increase the host resistance to pathogens via promoted phenolic synthesis, however, the signaling pathway responsible for it still remains unclear. In this study, in order to reveal the signaling molecules involved in this process, we inoculated Trifolium repense L. with an arbuscular mycorrhizal fungus (AMF), Glomus mosseae, and monitored the contents of phenolics and signaling molecules (hydrogen peroxide (H(2)O(2)), salicylic acid (SA), and nitric oxide (NO)) in roots, measured the activities of l-phenylalanine ammonia-lyase (PAL) and nitric oxide synthase (NOS), and the expression of pal and chs genes. Results demonstrated that AMF colonization promoted the phenolic synthesis, in parallel with the increase in related enzyme activity and gene expression. Meanwhile, the accumulation of all three signaling molecules was also up-regulated by AMF. This study suggested that AMF increased the phenolic synthesis in roots probably via signaling pathways of H(2)O(2), SA and NO in a signaling cascade. Copyright © 2012 Elsevier GmbH. All rights reserved.

Mitochondrial reactive oxygen species (ROS) as signaling molecules of intracellular pathways triggered by the cardiac renin-angiotensin II-aldosterone system (RAAS)

PubMed Central

De Giusti, V. C.; Caldiz, C. I.; Ennis, I. L.; Pérez, N. G.; Cingolani, H. E.; Aiello, E. A.

2013-01-01

Mitochondria represent major sources of basal reactive oxygen species (ROS) production of the cardiomyocyte. The role of ROS as signaling molecules that mediate different intracellular pathways has gained increasing interest among physiologists in the last years. In our lab, we have been studying the participation of mitochondrial ROS in the intracellular pathways triggered by the renin-angiotensin II-aldosterone system (RAAS) in the myocardium during the past few years. We have demonstrated that acute activation of cardiac RAAS induces mitochondrial ATP-dependent potassium channel (mitoKATP) opening with the consequent enhanced production of mitochondrial ROS. These oxidant molecules, in turn, activate membrane transporters, as sodium/hydrogen exchanger (NHE-1) and sodium/bicarbonate cotransporter (NBC) via the stimulation of the ROS-sensitive MAPK cascade. The stimulation of such effectors leads to an increase in cardiac contractility. In addition, it is feasible to suggest that a sustained enhanced production of mitochondrial ROS induced by chronic cardiac RAAS, and hence, chronic NHE-1 and NBC stimulation, would also result in the development of cardiac hypertrophy. PMID:23755021

Mitochondrial reactive oxygen species (ROS) as signaling molecules of intracellular pathways triggered by the cardiac renin-angiotensin II-aldosterone system (RAAS).

PubMed

De Giusti, V C; Caldiz, C I; Ennis, I L; Pérez, N G; Cingolani, H E; Aiello, E A

2013-01-01

Mitochondria represent major sources of basal reactive oxygen species (ROS) production of the cardiomyocyte. The role of ROS as signaling molecules that mediate different intracellular pathways has gained increasing interest among physiologists in the last years. In our lab, we have been studying the participation of mitochondrial ROS in the intracellular pathways triggered by the renin-angiotensin II-aldosterone system (RAAS) in the myocardium during the past few years. We have demonstrated that acute activation of cardiac RAAS induces mitochondrial ATP-dependent potassium channel (mitoKATP) opening with the consequent enhanced production of mitochondrial ROS. These oxidant molecules, in turn, activate membrane transporters, as sodium/hydrogen exchanger (NHE-1) and sodium/bicarbonate cotransporter (NBC) via the stimulation of the ROS-sensitive MAPK cascade. The stimulation of such effectors leads to an increase in cardiac contractility. In addition, it is feasible to suggest that a sustained enhanced production of mitochondrial ROS induced by chronic cardiac RAAS, and hence, chronic NHE-1 and NBC stimulation, would also result in the development of cardiac hypertrophy.

Genome sequence analysis of a flocculant-producing bacterium, Paenibacillus shenyangensis.

PubMed

Fu, Lili; Jiang, Binhui; Liu, Jinliang; Zhao, Xin; Liu, Qian; Hu, Xiaomin

2016-03-01

To explore the metabolic process of Paenibacillus shenyangensis that is an efficient bioflocculant-producing bacterium. The biosynthesis mechanism of bioflocculation was used to enrich the genome of Paenibacillus shenyangensis and provide a basis for molecular genetics and functional genomics analyses. According to the analysis of de novo assembly, a total of 5,501,467 bp clean reads were generated, and were assembled into 92 contigs. 4800 unigenes were predicted of which 4393 were annotated showing a specific gene function in the NCBI-Nr database. 3423 genes were found in the database of cluster of orthologous groups. Among the 168 Kyoto Encyclopedia of Genes and Genomes database, cell growth and metabolism were the main biological processes, and a potential metabolic pathway was predicted from glucose to exopolysaccharide within the starch and sucrose metabolism pathway. By using the high-throughput sequencing technology, we provide a genome analysis of Paenibacillus shenyangensis that predicts the main metabolic processes and a potential pathway of exopolysaccharide biosynthesis.

Systems biology, adverse outcome pathways, and ecotoxicology in the 21st century

EPA Science Inventory

While many definitions of systems biology exist, the majority of these contain most (if not all) of the following elements: global measurements of biological molecules to the extent technically feasible, dynamic measurements of key biological molecules to establish quantitative r...

A Single Amino Acid Substitution in the v-Eyk Intracellular Domain Results in Activation of Stat3 and Enhances Cellular Transformation

PubMed Central

Besser, Daniel; Bromberg, Jacqueline F.; Darnell, James E.; Hanafusa, Hidesaburo

1999-01-01

The receptor tyrosine kinase Eyk, a member of the Axl/Tyro3 subfamily, activates the STAT pathway and transforms cells when constitutively activated. Here, we compared the potentials of the intracellular domains of Eyk molecules derived from c-Eyk and v-Eyk to transform rat 3Y1 fibroblasts. The v-Eyk molecule induced higher numbers of transformants in soft agar and stronger activation of Stat3; levels of Stat1 activation by the two Eyk molecules were similar. A mutation in the sequence Y933VPL, present in c-Eyk, to the v-Eyk sequence Y933VPQ led to increased activation of Stat3 and increased transformation efficiency. However, altering another sequence, Y862VNT, present in both Eyk molecules to F862VNT markedly decreased transformation without impairing Stat3 activation. These results indicate that activation of Stat3 enhances transformation efficiency and cooperates with another pathway to induce transformation. PMID:9891073

Ordering and partitioning in vesicle forming block copolymer thin films

NASA Astrophysics Data System (ADS)

Parnell, Andrew; Kamata, Yohei; Jones, Richard

Cell biology routinely uses encapsulation processes to package a payload and transport it to a location where the payload can then be used. Synthetic polymer based liposomes (Polymersomes) are one possible way in which we can artificially contain a molecule of interest that is protected from its surrounding environment. Encapsulation technologies at present rely on forming a lipid vesicle and then extruding it in a solution containing the target molecule to be encapsulated. Only a small fraction is encapsulated in this process. This is because of the complex structural formation pathway in going from individual isolated amphiphilic molecules into vesicle aggregates. My talk will discuss strategies to overcome the formation pathways, by forming a block copolymer film with the target molecule and then solvent ordering prior to the formation of vesicles. By studying block copolymer thin films with neutron reflectivity and ellipsometry we are able to observe partitioning and ordering which is essential for high encapsulation efficiencies. We acknowledge funding from STFC for use of the ISIS spallation neutron source.

Interaction of Mycobacterium avium-containing phagosomes with the antigen presentation pathway.

PubMed

Ullrich, H J; Beatty, W L; Russell, D G

2000-12-01

Pathogenic mycobacteria infect macrophages where they replicate in phagosomes that minimize contact with late endosomal/lysosomal compartments. Loading of Ags to MHC class II molecules occurs in specialized compartments with late endosomal characteristics. This points to a sequestration of mycobacteria-containing phagosomes from the sites where Ags meet MHC class II molecules. Indeed, in resting macrophages MHC class II levels decreased strongly in phagosomes containing M. avium during a 4-day infection. Phagosomal MHC class II of early (4 h) infections was partly surface-derived and associated with peptide. Activation of host macrophages led to the appearance of H2-M, a chaperon of Ag loading, and to a strong increase in MHC class II molecules in phagosomes of acute (1 day) infections. Comparison with the kinetics of MHC class II acquisition by IgG-coated bead-containing phagosomes suggests that the arrest in phagosome maturation by mycobacteria limits the intersection of mycobacteria-containing phagosomes with the intracellular trafficking pathways of Ag-presenting molecules.

Multiple cell adhesion molecules shaping a complex nicotinic synapse on neurons.

PubMed

Triana-Baltzer, Gallen B; Liu, Zhaoping; Gounko, Natalia V; Berg, Darwin K

2008-09-01

Neuroligin, SynCAM, and L1-CAM are cell adhesion molecules with synaptogenic roles in glutamatergic pathways. We show here that SynCAM is expressed in the chick ciliary ganglion, embedded in a nicotinic pathway, and, as shown previously for neuroligin and L1-CAM, acts transcellularly to promote synaptic maturation on the neurons in culture. Moreover, we show that electroporation of chick embryos with dominant negative constructs disrupting any of the three molecules in vivo reduces the total amount of presynaptic SV2 overlaying the neurons expressing the constructs. Only disruption of L1-CAM and neuroligin, however, reduces the number of SV2 puncta specifically overlaying nicotinic receptor clusters. Disrupting L1-CAM and neuroligin together produces no additional decrement, indicating that they act on the same subset of synapses. SynCAM may affect synaptic maturation rather than synapse formation. The results indicate that individual neurons can express multiple synaptogenic molecules with different effects on the same class of nicotinic synapses.

Structure-based functional annotation of putative conserved proteins having lyase activity from Haemophilus influenzae.

PubMed

Shahbaaz, Mohd; Ahmad, Faizan; Imtaiyaz Hassan, Md

2015-06-01

Haemophilus influenzae is a small pleomorphic Gram-negative bacteria which causes several chronic diseases, including bacteremia, meningitis, cellulitis, epiglottitis, septic arthritis, pneumonia, and empyema. Here we extensively analyzed the sequenced genome of H. influenzae strain Rd KW20 using protein family databases, protein structure prediction, pathways and genome context methods to assign a precise function to proteins whose functions are unknown. These proteins are termed as hypothetical proteins (HPs), for which no experimental information is available. Function prediction of these proteins would surely be supportive to precisely understand the biochemical pathways and mechanism of pathogenesis of Haemophilus influenzae. During the extensive analysis of H. influenzae genome, we found the presence of eight HPs showing lyase activity. Subsequently, we modeled and analyzed three-dimensional structure of all these HPs to determine their functions more precisely. We found these HPs possess cystathionine-β-synthase, cyclase, carboxymuconolactone decarboxylase, pseudouridine synthase A and C, D-tagatose-1,6-bisphosphate aldolase and aminodeoxychorismate lyase-like features, indicating their corresponding functions in the H. influenzae. Lyases are actively involved in the regulation of biosynthesis of various hormones, metabolic pathways, signal transduction, and DNA repair. Lyases are also considered as a key player for various biological processes. These enzymes are critically essential for the survival and pathogenesis of H. influenzae and, therefore, these enzymes may be considered as a potential target for structure-based rational drug design. Our structure-function relationship analysis will be useful to search and design potential lead molecules based on the structure of these lyases, for drug design and discovery.

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org. PMID:21190573

Formation mechanism of glycolaldehyde and ethylene glycol in astrophysical ices from HCO• and •CH2OH recombination: an experimental study

NASA Astrophysics Data System (ADS)

Butscher, T.; Duvernay, F.; Theule, P.; Danger, G.; Carissan, Y.; Hagebaum-Reignier, D.; Chiavassa, T.

2015-10-01

Among all existing complex organic molecules, glycolaldehyde HOCH2CHO and ethylene glycol HOCH2CH2OH are two of the largest detected molecules in the interstellar medium. We investigate both experimentally and theoretically the low-temperature reaction pathways leading to glycolaldehyde and ethylene glycol in interstellar grains. Using infrared spectroscopy, mass spectroscopy and quantum calculations, we investigate formation pathways of glycolaldehyde and ethylene glycol based on HCO• and •CH2OH radical-radical recombinations. We also show that •CH2OH is the main intermediate radical species in the H2CO to CH3OH hydrogenation processes. We then discuss astrophysical implications of the chemical pathway we propose on the observed gas-phase ethylene glycol and glycolaldehyde.

Chemical screening platforms for autophagy drug discovery to identify therapeutic candidates for Huntington's disease and other neurodegenerative disorders.

PubMed

Sarkar, Sovan

2013-01-01

Autophagy is a cellular degradation process involved in the clearance of aggregate-prone proteins associated with neurodegenerative diseases. While the mTOR pathway has been known to be the major regulator of autophagy, recent advancements into the regulation of autophagy have identified mTOR-independent autophagy pathways that are amenable to chemical perturbations. Several chemical and genetic screens have been undertaken to identify small molecule and genetic regulators of autophagy, respectively. The small molecule autophagy enhancers offer great potential as therapeutic candidates not only for neurodegenerative diseases, but also for diverse human diseases where autophagy acts as a protective pathway. This review highlights the various chemical screening platforms for autophagy drug discovery pertinent for the treatment of neurodegenerative diseases.

Mechanisms of the epithelial-to-mesenchymal transition in sea urchin embryos

PubMed Central

Katow, Hideki

2015-01-01

Sea urchin mesenchyme is composed of the large micromere-derived spiculogenetic primary mesenchyme cells (PMC), veg2-tier macromere-derived non-spiculogenetic mesenchyme cells, the small micromere-derived germ cells, and the macro- and mesomere-derived neuronal mesenchyme cells. They are formed through the epithelial-to-mesenchymal transition (EMT) and possess multipotency, except PMCs that solely differentiate larval spicules. The process of EMT is associated with modification of epithelial cell surface property that includes loss of affinity to the apical and basal extracellular matrices, inter-epithelial cell adherens junctions and epithelial cell surface-specific proteins. These cell surface structures and molecules are endocytosed during EMT and utilized as initiators of cytoplasmic signaling pathways that often initiate protein phosphorylation to activate the gene regulatory networks. Acquisition of cell motility after EMT in these mesenchyme cells is associated with the expression of proteins such as Lefty, Snail and Seawi. Structural simplicity and genomic database of this model will further promote detailed EMT research. PMID:26716069

Visualization and Analysis of MiRNA-Targets Interactions Networks.

PubMed

León, Luis E; Calligaris, Sebastián D

2017-01-01

MicroRNAs are a class of small, noncoding RNA molecules of 21-25 nucleotides in length that regulate the gene expression by base-pairing with the target mRNAs, mainly leading to down-regulation or repression of the target genes. MicroRNAs are involved in diverse regulatory pathways in normal and pathological conditions. In this context, it is highly important to identify the targets of specific microRNA in order to understand the mechanism of its regulation and consequently its involvement in disease. However, the microRNA target identification is experimentally laborious and time-consuming. The in silico prediction of microRNA targets is an extremely useful approach because you can identify potential mRNA targets, reduce the number of possibilities and then, validate a few microRNA-mRNA interactions in an in vitro experimental model. In this chapter, we describe, in a simple way, bioinformatics guidelines to use miRWalk database and Cytoscape software for analyzing microRNA-mRNA interactions through their visualization as a network.

Norrie disease gene: characterization of deletions and possible function.

PubMed

Chen, Z Y; Battinelli, E M; Hendriks, R W; Powell, J F; Middleton-Price, H; Sims, K B; Breakefield, X O; Craig, I W

1993-05-01

Positional cloning experiments have resulted recently in the isolation of a candidate gene for Norrie disease (pseudoglioma; NDP), a severe X-linked neurodevelopmental disorder. Here we report the isolation and analysis of human genomic DNA clones encompassing the NDP gene. The gene spans 28 kb and consists of 3 exons, the first of which is entirely contained within the 5' untranslated region. Detailed analysis of genomic deletions in Norrie patients shows that they are heterogeneous, both in size and in position. By PCR analysis, we found that expression of the NDP gene was not confined to the eye or to the brain. An extensive DNA and protein sequence comparison between the human NDP gene and related genes from the database revealed homology with cysteine-rich protein-binding domains of immediate--early genes implicated in the regulation of cell proliferation. We propose that NDP is a molecule related in function to these genes and may be involved in a pathway that regulates neural cell differentiation and proliferation.

MetNetAPI: A flexible method to access and manipulate biological network data from MetNet

PubMed Central

2010-01-01

Background Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server. Results MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only. Conclusions An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad data- retrieval methods. Data retrieval can be customized to client needs and the API offers a framework to construct and manipulate user-defined networks. The design principles can be used as a template to build programmable interfaces for other biological databases. The API software and tutorials are available at http://www.metnetonline.org/api. PMID:21083943

Pathways for the Oxidation of Sarin in Urban Atmospheres

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

Gerald E. Streit; James E. Bossert; Jeffrey S. Gaffney

1998-11-01

Terrorists have threatened and carried out chemicalhiological agent attacks on targets in major cities. The nerve agent sarin figured prominently in one well-publicized incident. Vapors disseminating from open containers in a Tokyo subway caused thousands of casualties. High-resolution tracer transport modeling of agent dispersion is at hand and will be enhanced by data on reactions with components of the urban atmosphere. As a sample of the level of complexity currently attainable, we elaborate the mechanisms by which sarin can decompose in polluted air. A release scenario is outlined involving the passage of a gas-phase agent through a city locale inmore » the daytime. The atmospheric chemistry database on related organophosphorus pesticides is mined for rate and product information. The hydroxyl,radical and fine-mode particles are identified as major reactants. A review of urban air chernistry/rnicrophysics generates concentration tables for major oxidant and aerosol types in both clean and dirty environments. Organic structure-reactivity relationships yield an upper limit of 10-1' cm3 molecule-' S-* for hydrogen abstraction by hydroxyl. The associated midday loss time scale could be as little as one hour. Product distributions are difficult to define but may include nontoxic organic oxygenates, inorganic phosphorus acids, sarin-like aldehydes, and nitrates preserving cholinergic capabilities. Agent molecules will contact aerosol surfaces in on the order of minutes, with hydrolysis and side-chain oxidation as likely reaction channels.« less

Cyclophilin B Supports Myc and Mutant p53 Dependent Survival of Glioblastoma Multiforme Cells

PubMed Central

Choi, Jae Won; Schroeder, Mark A.; Sarkaria, Jann N.; Bram, Richard J.

2014-01-01

Glioblastoma multiforme (GBM) is an aggressive, treatment-refractory type of brain tumor for which effective therapeutic targets remain important to identify. Here we report that cyclophilin B (CypB), a prolyl isomerase residing in the endoplasmic reticulum (ER), provides an essential survival signal in GBM cells. Analysis of gene expression databases revealed that CypB is upregulated in many cases of malignant glioma. We found that suppression of CypB reduced cell proliferation and survival in human GBM cells in vitro and in vivo. We also found that treatment with small molecule inhibitors of cyclophilins, including the approved drug cyclosporine, greatly reduced the viability of GBM cells. Mechanistically, depletion or pharmacologic inhibition of CypB caused hyperactivation of the oncogenic RAS-MAPK pathway, induction of cellular senescence signals, and death resulting from loss of MYC, mutant p53, Chk1 and JAK/STAT3 signaling. Elevated reactive oxygen species, ER expansion and abnormal unfolded protein responses in CypB-depleted GBM cells indicated that CypB alleviates oxidative and ER stresses and coordinates stress adaptation responses. Enhanced cell survival and sustained expression of multiple oncogenic proteins downstream of CypB may thus contribute to the poor outcome of GBM tumors. Our findings link chaperone-mediated protein folding in the ER to mechanisms underlying oncogenic transformation, and they make CypB an attractive and immediately targetable molecule for GBM therapy. PMID:24272483

BioM2MetDisease: a manually curated database for associations between microRNAs, metabolites, small molecules and metabolic diseases

PubMed Central

Xu, Yanjun; Yang, Haixiu; Wu, Tan; Dong, Qun; Sun, Zeguo; Shang, Desi; Li, Feng; Xu, Yingqi; Su, Fei; Liu, Siyao

2017-01-01

Abstract BioM2MetDisease is a manually curated database that aims to provide a comprehensive and experimentally supported resource of associations between metabolic diseases and various biomolecules. Recently, metabolic diseases such as diabetes have become one of the leading threats to people’s health. Metabolic disease associated with alterations of multiple types of biomolecules such as miRNAs and metabolites. An integrated and high-quality data source that collection of metabolic disease associated biomolecules is essential for exploring the underlying molecular mechanisms and discovering novel therapeutics. Here, we developed the BioM2MetDisease database, which currently documents 2681 entries of relationships between 1147 biomolecules (miRNAs, metabolites and small molecules/drugs) and 78 metabolic diseases across 14 species. Each entry includes biomolecule category, species, biomolecule name, disease name, dysregulation pattern, experimental technique, a brief description of metabolic disease-biomolecule relationships, the reference, additional annotation information etc. BioM2MetDisease provides a user-friendly interface to explore and retrieve all data conveniently. A submission page was also offered for researchers to submit new associations between biomolecules and metabolic diseases. BioM2MetDisease provides a comprehensive resource for studying biology molecules act in metabolic diseases, and it is helpful for understanding the molecular mechanisms and developing novel therapeutics for metabolic diseases. Database URL: http://www.bio-bigdata.com/BioM2MetDisease/ PMID:28605773

The Pathway Coexpression Network: Revealing pathway relationships

PubMed Central

Tanzi, Rudolph E.

2018-01-01

A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer’s Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of global pathway relationships. Comprehensive exploration of PCxN can be performed at http://pcxn.org/. PMID:29554099

FXIa and platelet polyphosphate as therapeutic targets during human blood clotting on collagen/tissue factor surfaces under flow.

PubMed

Zhu, Shu; Travers, Richard J; Morrissey, James H; Diamond, Scott L

2015-09-17

Factor XIIa (FXIIa) and factor XIa (FXIa) contribute to thrombosis in animal models, whereas platelet-derived polyphosphate (polyP) may potentiate contact or thrombin-feedback pathways. The significance of these mediators in human blood under thrombotic flow conditions on tissue factor (TF) -bearing surfaces remains inadequately resolved. Human blood (corn trypsin inhibitor treated [4 μg/mL]) was tested by microfluidic assay for clotting on collagen/TF at TF surface concentration ([TF]wall) from ∼0.1 to 2 molecules per μm(2). Anti-FXI antibodies (14E11 and O1A6) or polyP-binding protein (PPXbd) were used to block FXIIa-dependent FXI activation, FXIa-dependent factor IX (FIX) activation, or platelet-derived polyP, respectively. Fibrin formation was sensitive to 14E11 at 0 to 0.1 molecules per µm(2) and sensitive to O1A6 at 0 to 0.2 molecules per µm(2). However, neither antibody reduced fibrin generation at ∼2 molecules per µm(2) when the extrinsic pathway became dominant. Interestingly, PPXbd reduced fibrin generation at low [TF]wall (0.1 molecules per µm(2)) but not at zero or high [TF]wall, suggesting a role for polyP distinct from FXIIa activation and requiring low extrinsic pathway participation. Regardless of [TF]wall, PPXbd enhanced fibrin sensitivity to tissue plasminogen activator and promoted clot retraction during fibrinolysis concomitant with an observed PPXbd-mediated reduction of fibrin fiber diameter. This is the first detection of endogenous polyP function in human blood under thrombotic flow conditions. When triggered by low [TF]wall, thrombosis may be druggable by contact pathway inhibition, although thrombolytic susceptibility may benefit from polyP antagonism regardless of [TF]wall. © 2015 by The American Society of Hematology.

Differential Expression of Osteo-Modulatory Molecules in Periodontal Ligament Stem Cells in Response to Modified Titanium Surfaces

PubMed Central

Kim, So Yeon; Yoo, Ji-Yeon; Ohe, Joo-Young; Lee, Jung-Woo; Moon, Ji-Hoi; Kwon, Yong-Dae; Heo, Jung Sun

2014-01-01

This study assessed differential gene expression of signaling molecules involved in osteogenic differentiation of periodontal ligament stem cells (PDLSCs) subjected to different titanium (Ti) surface types. PDLSCs were cultured on tissue culture polystyrene (TCPS), and four types of Ti discs (PT, SLA, hydrophilic PT (pmodPT), and hydrophilic SLA (modSLA)) with no osteoinductive factor and then osteogenic activity, including alkaline phosphatase (ALP) activity, mRNA expression of runt-related gene 2, osterix, FOSB, FRA1, and protein levels of osteopontin and collagen type IA, were examined. The highest osteogenic activity appeared in PDLSCs cultured on SLA, compared with the TCPS and other Ti surfaces. The role of surface properties in affecting signaling molecules to modulate PDLSC behavior was determined by examining the regulation of Wnt pathways. mRNA expression of the canonical Wnt signaling molecules, Wnt3a and β-catenin, was higher on SLA and modSLA than on smooth surfaces, but gene expression of the calcium-dependent Wnt signaling molecules Wnt5a, calmodulin, and NFATc1 was increased significantly on PT and pmodPT. Moreover, integrin α2/β1, sonic hedgehog, and Notch signaling molecules were affected differently by each surface modification. In conclusion, surface roughness and hydrophilicity can affect differential Wnt pathways and signaling molecules, targeting the osteogenic differentiation of PDLSCs. PMID:25057487

Differential expression of osteo-modulatory molecules in periodontal ligament stem cells in response to modified titanium surfaces.

PubMed

Kim, So Yeon; Yoo, Ji-Yeon; Ohe, Joo-Young; Lee, Jung-Woo; Moon, Ji-Hoi; Kwon, Yong-Dae; Heo, Jung Sun

2014-01-01

This study assessed differential gene expression of signaling molecules involved in osteogenic differentiation of periodontal ligament stem cells (PDLSCs) subjected to different titanium (Ti) surface types. PDLSCs were cultured on tissue culture polystyrene (TCPS), and four types of Ti discs (PT, SLA, hydrophilic PT (pmodPT), and hydrophilic SLA (modSLA)) with no osteoinductive factor and then osteogenic activity, including alkaline phosphatase (ALP) activity, mRNA expression of runt-related gene 2, osterix, FOSB, FRA1, and protein levels of osteopontin and collagen type IA, were examined. The highest osteogenic activity appeared in PDLSCs cultured on SLA, compared with the TCPS and other Ti surfaces. The role of surface properties in affecting signaling molecules to modulate PDLSC behavior was determined by examining the regulation of Wnt pathways. mRNA expression of the canonical Wnt signaling molecules, Wnt3a and β-catenin, was higher on SLA and modSLA than on smooth surfaces, but gene expression of the calcium-dependent Wnt signaling molecules Wnt5a, calmodulin, and NFATc1 was increased significantly on PT and pmodPT. Moreover, integrin α2/β1, sonic hedgehog, and Notch signaling molecules were affected differently by each surface modification. In conclusion, surface roughness and hydrophilicity can affect differential Wnt pathways and signaling molecules, targeting the osteogenic differentiation of PDLSCs.

Use of Direct Dynamics Simulations to Determine Unimolecular Reaction Paths and Arrhenius Parameters for Large Molecules.

PubMed

Yang, Li; Sun, Rui; Hase, William L

2011-11-08

In a previous study (J. Chem. Phys.2008, 129, 094701) it was shown that for a large molecule, with a total energy much greater than its barrier for decomposition and whose vibrational modes are harmonic oscillators, the expressions for the classical Rice-Ramsperger-Kassel-Marcus (RRKM) (i.e., RRK) and classical transition-state theory (TST) rate constants become equivalent. Using this relationship, a molecule's unimolecular rate constants versus temperature may be determined from chemical dynamics simulations of microcanonical ensembles for the molecule at different total energies. The simulation identifies the molecule's unimolecular pathways and their Arrhenius parameters. In the work presented here, this approach is used to study the thermal decomposition of CH3-NH-CH═CH-CH3, an important constituent in the polymer of cross-linked epoxy resins. Direct dynamics simulations, at the MP2/6-31+G* level of theory, were used to investigate the decomposition of microcanonical ensembles for this molecule. The Arrhenius A and Ea parameters determined from the direct dynamics simulation are in very good agreement with the TST Arrhenius parameters for the MP2/6-31+G* potential energy surface. The simulation method applied here may be particularly useful for large molecules with a multitude of decomposition pathways and whose transition states may be difficult to determine and have structures that are not readily obvious.

[Status of libraries and databases for natural products at abroad].

PubMed

Zhao, Li-Mei; Tan, Ning-Hua

2015-01-01

For natural products are one of the important sources for drug discovery, libraries and databases of natural products are significant for the development and research of natural products. At present, most of compound libraries at abroad are synthetic or combinatorial synthetic molecules, resulting to access natural products difficult; for information of natural products are scattered with different standards, it is difficult to construct convenient, comprehensive and large-scale databases for natural products. This paper reviewed the status of current accessing libraries and databases for natural products at abroad and provided some important information for the development of libraries and database for natural products.

Mapping small molecule binding data to structural domains

PubMed Central

2012-01-01

Background Large-scale bioactivity/SAR Open Data has recently become available, and this has allowed new analyses and approaches to be developed to help address the productivity and translational gaps of current drug discovery. One of the current limitations of these data is the relative sparsity of reported interactions per protein target, and complexities in establishing clear relationships between bioactivity and targets using bioinformatics tools. We detail in this paper the indexing of targets by the structural domains that bind (or are likely to bind) the ligand within a full-length protein. Specifically, we present a simple heuristic to map small molecule binding to Pfam domains. This profiling can be applied to all proteins within a genome to give some indications of the potential pharmacological modulation and regulation of all proteins. Results In this implementation of our heuristic, ligand binding to protein targets from the ChEMBL database was mapped to structural domains as defined by profiles contained within the Pfam-A database. Our mapping suggests that the majority of assay targets within the current version of the ChEMBL database bind ligands through a small number of highly prevalent domains, and conversely the majority of Pfam domains sampled by our data play no currently established role in ligand binding. Validation studies, carried out firstly against Uniprot entries with expert binding-site annotation and secondly against entries in the wwPDB repository of crystallographic protein structures, demonstrate that our simple heuristic maps ligand binding to the correct domain in about 90 percent of all assessed cases. Using the mappings obtained with our heuristic, we have assembled ligand sets associated with each Pfam domain. Conclusions Small molecule binding has been mapped to Pfam-A domains of protein targets in the ChEMBL bioactivity database. The result of this mapping is an enriched annotation of small molecule bioactivity data and a grouping of activity classes following the Pfam-A specifications of protein domains. This is valuable for data-focused approaches in drug discovery, for example when extrapolating potential targets of a small molecule with known activity against one or few targets, or in the assessment of a potential target for drug discovery or screening studies. PMID:23282026

Small Molecules Affect Human Dental Pulp Stem Cell Properties Via Multiple Signaling Pathways

PubMed Central

Al-Habib, Mey; Yu, Zongdong

2013-01-01

One fundamental issue regarding stem cells for regenerative medicine is the maintenance of stem cell stemness. The purpose of the study was to test whether small molecules can enhance stem cell properties of mesenchymal stem cells (MSCs) derived from human dental pulp (hDPSCs), which have potential for multiple clinical applications. We identified the effects of small molecules (Pluripotin (SC1), 6-bromoindirubin-3-oxime and rapamycin) on the maintenance of hDPSC properties in vitro and the mechanisms involved in exerting the effects. Primary cultures of hDPSCs were exposed to optimal concentrations of these small molecules. Treated hDPSCs were analyzed for their proliferation, the expression levels of pluripotent and MSC markers, differentiation capacities, and intracellular signaling activations. We found that small molecule treatments decreased cell proliferation and increased the expression of STRO-1, NANOG, OCT4, and SOX2, while diminishing cell differentiation into odonto/osteogenic, adipogenic, and neurogenic lineages in vitro. These effects involved Ras-GAP-, ERK1/2-, and mTOR-signaling pathways, which may preserve the cell self-renewal capacity, while suppressing differentiation. We conclude that small molecules appear to enhance the immature state of hDPSCs in culture, which may be used as a strategy for adult stem cell maintenance and extend their capacity for regenerative applications. PMID:23573877

Determining the elastic properties of aptamer-ricin single molecule multiple pathways

USDA-ARS?s Scientific Manuscript database

Ricin and an anti-ricin aptamer showed three stable binding conformations with their special chemomechanical properties. The elastic properties of the ricin-aptamer single-molecule interactions were investigated by the dynamic force spectroscopy (DFS). The worm-like-chain model and Hook’s law were ...

Electronegativity Equalization Method: Parameterization and Validation for Large Sets of Organic, Organohalogene and Organometal Molecule

PubMed Central

Vařeková, Radka Svobodová; Jiroušková, Zuzana; Vaněk, Jakub; Suchomel, Šimon; Koča, Jaroslav

2007-01-01

The Electronegativity Equalization Method (EEM) is a fast approach for charge calculation. A challenging part of the EEM is the parameterization, which is performed using ab initio charges obtained for a set of molecules. The goal of our work was to perform the EEM parameterization for selected sets of organic, organohalogen and organometal molecules. We have performed the most robust parameterization published so far. The EEM parameterization was based on 12 training sets selected from a database of predicted 3D structures (NCI DIS) and from a database of crystallographic structures (CSD). Each set contained from 2000 to 6000 molecules. We have shown that the number of molecules in the training set is very important for quality of the parameters. We have improved EEM parameters (STO-3G MPA charges) for elements that were already parameterized, specifically: C, O, N, H, S, F and Cl. The new parameters provide more accurate charges than those published previously. We have also developed new parameters for elements that were not parameterized yet, specifically for Br, I, Fe and Zn. We have also performed crossover validation of all obtained parameters using all training sets that included relevant elements and confirmed that calculated parameters provide accurate charges.

MicroRNA expression, target genes, and signaling pathways in infants with a ventricular septal defect.

PubMed

Chai, Hui; Yan, Zhaoyuan; Huang, Ke; Jiang, Yuanqing; Zhang, Lin

2018-02-01

This study aimed to systematically investigate the relationship between miRNA expression and the occurrence of ventricular septal defect (VSD), and characterize the miRNA target genes and pathways that can lead to VSD. The miRNAs that were differentially expressed in blood samples from VSD and normal infants were screened and validated by implementing miRNA microarrays and qRT-PCR. The target genes regulated by differentially expressed miRNAs were predicted using three target gene databases. The functions and signaling pathways of the target genes were enriched using the GO database and KEGG database, respectively. The transcription and protein expression of specific target genes in critical pathways were compared in the VSD and normal control groups using qRT-PCR and western blotting, respectively. Compared with the normal control group, the VSD group had 22 differentially expressed miRNAs; 19 were downregulated and three were upregulated. The 10,677 predicted target genes participated in many biological functions related to cardiac development and morphogenesis. Four target genes (mGLUR, Gq, PLC, and PKC) were involved in the PKC pathway and four (ECM, FAK, PI3 K, and PDK1) were involved in the PI3 K-Akt pathway. The transcription and protein expression of these eight target genes were significantly upregulated in the VSD group. The 22 miRNAs that were dysregulated in the VSD group were mainly downregulated, which may result in the dysregulation of several key genes and biological functions related to cardiac development. These effects could also be exerted via the upregulation of eight specific target genes, the subsequent over-activation of the PKC and PI3 K-Akt pathways, and the eventual abnormal cardiac development and VSD.

Next generation of immune checkpoint therapy in cancer: new developments and challenges.

PubMed

Marin-Acevedo, Julian A; Dholaria, Bhagirathbhai; Soyano, Aixa E; Knutson, Keith L; Chumsri, Saranya; Lou, Yanyan

2018-03-15

Immune checkpoints consist of inhibitory and stimulatory pathways that maintain self-tolerance and assist with immune response. In cancer, immune checkpoint pathways are often activated to inhibit the nascent anti-tumor immune response. Immune checkpoint therapies act by blocking or stimulating these pathways and enhance the body's immunological activity against tumors. Cytotoxic T lymphocyte-associated molecule-4 (CTLA-4), programmed cell death receptor-1 (PD-1), and programmed cell death ligand-1(PD-L1) are the most widely studied and recognized inhibitory checkpoint pathways. Drugs blocking these pathways are currently utilized for a wide variety of malignancies and have demonstrated durable clinical activities in a subset of cancer patients. This approach is rapidly extending beyond CTLA-4 and PD-1/PD-L1. New inhibitory pathways are under investigation, and drugs blocking LAG-3, TIM-3, TIGIT, VISTA, or B7/H3 are being investigated. Furthermore, agonists of stimulatory checkpoint pathways such as OX40, ICOS, GITR, 4-1BB, CD40, or molecules targeting tumor microenvironment components like IDO or TLR are under investigation. In this article, we have provided a comprehensive review of immune checkpoint pathways involved in cancer immunotherapy, and discuss their mechanisms and the therapeutic interventions currently under investigation in phase I/II clinical trials. We also reviewed the limitations, toxicities, and challenges and outline the possible future research directions.

A novel approach to select differential pathways associated with hypertrophic cardiomyopathy based on gene co‑expression analysis.

PubMed

Chen, Xiao-Min; Feng, Ming-Jun; Shen, Cai-Jie; He, Bin; Du, Xian-Feng; Yu, Yi-Bo; Liu, Jing; Chu, Hui-Min

2017-07-01

The present study was designed to develop a novel method for identifying significant pathways associated with human hypertrophic cardiomyopathy (HCM), based on gene co‑expression analysis. The microarray dataset associated with HCM (E‑GEOD‑36961) was obtained from the European Molecular Biology Laboratory‑European Bioinformatics Institute database. Informative pathways were selected based on the Reactome pathway database and screening treatments. An empirical Bayes method was utilized to construct co‑expression networks for informative pathways, and a weight value was assigned to each pathway. Differential pathways were extracted based on weight threshold, which was calculated using a random model. In order to assess whether the co‑expression method was feasible, it was compared with traditional pathway enrichment analysis of differentially expressed genes, which were identified using the significance analysis of microarrays package. A total of 1,074 informative pathways were screened out for subsequent investigations and their weight values were also obtained. According to the threshold of weight value of 0.01057, 447 differential pathways, including folding of actin by chaperonin containing T‑complex protein 1 (CCT)/T‑complex protein 1 ring complex (TRiC), purine ribonucleoside monophosphate biosynthesis and ubiquinol biosynthesis, were obtained. Compared with traditional pathway enrichment analysis, the number of pathways obtained from the co‑expression approach was increased. The results of the present study demonstrated that this method may be useful to predict marker pathways for HCM. The pathways of folding of actin by CCT/TRiC and purine ribonucleoside monophosphate biosynthesis may provide evidence of the underlying molecular mechanisms of HCM, and offer novel therapeutic directions for HCM.

Allosteric Communication Disrupted by a Small Molecule Binding to the Imidazole Glycerol Phosphate Synthase Protein-Protein Interface.

PubMed

Rivalta, Ivan; Lisi, George P; Snoeberger, Ning-Shiuan; Manley, Gregory; Loria, J Patrick; Batista, Victor S

2016-11-29

Allosteric enzymes regulate a wide range of catalytic transformations, including biosynthetic mechanisms of important human pathogens, upon binding of substrate molecules to an orthosteric (or active) site and effector ligands at distant (allosteric) sites. We find that enzymatic activity can be impaired by small molecules that bind along the allosteric pathway connecting the orthosteric and allosteric sites, without competing with endogenous ligands. Noncompetitive allosteric inhibitors disrupted allostery in the imidazole glycerol phosphate synthase (IGPS) enzyme from Thermotoga maritima as evidenced by nuclear magnetic resonance, microsecond time-scale molecular dynamics simulations, isothermal titration calorimetry, and kinetic assays. The findings are particularly relevant for the development of allosteric antibiotics, herbicides, and antifungal compounds because IGPS is absent in mammals but provides an entry point to fundamental biosynthetic pathways in plants, fungi, and bacteria.

Signalling molecules in the urothelium.

PubMed

Winder, Michael; Tobin, Gunnar; Zupančič, Daša; Romih, Rok

2014-01-01

The urothelium was long considered to be a silent barrier protecting the body from the toxic effects of urine. However, today a number of dynamic abilities of the urothelium are well recognized, including its ability to act as a sensor of the intravesical environment. During recent years several pathways of these urothelial abilities have been proposed and a major part of these pathways includes release of signalling molecules. It is now evident that the urothelium represents only one part of the sensory web. Urinary bladder signalling is finely tuned machinery of signalling molecules, acting in autocrine and paracrine manner, and their receptors are specifically distributed among different types of cells in the urinary bladder. In the present review the current knowledge of the formation, release, and signalling effects of urothelial acetylcholine, ATP, adenosine, and nitric oxide in health and disease is discussed.

Signalling Molecules in the Urothelium

PubMed Central

Winder, Michael; Tobin, Gunnar; Zupančič, Daša; Romih, Rok

2014-01-01

The urothelium was long considered to be a silent barrier protecting the body from the toxic effects of urine. However, today a number of dynamic abilities of the urothelium are well recognized, including its ability to act as a sensor of the intravesical environment. During recent years several pathways of these urothelial abilities have been proposed and a major part of these pathways includes release of signalling molecules. It is now evident that the urothelium represents only one part of the sensory web. Urinary bladder signalling is finely tuned machinery of signalling molecules, acting in autocrine and paracrine manner, and their receptors are specifically distributed among different types of cells in the urinary bladder. In the present review the current knowledge of the formation, release, and signalling effects of urothelial acetylcholine, ATP, adenosine, and nitric oxide in health and disease is discussed. PMID:25177686

Absolute Configuration from Different Multifragmentation Pathways in Light-Induced Coulomb Explosion Imaging.

PubMed

Pitzer, Martin; Kastirke, Gregor; Kunitski, Maksim; Jahnke, Till; Bauer, Tobias; Goihl, Christoph; Trinter, Florian; Schober, Carl; Henrichs, Kevin; Becht, Jasper; Zeller, Stefan; Gassert, Helena; Waitz, Markus; Kuhlins, Andreas; Sann, Hendrik; Sturm, Felix; Wiegandt, Florian; Wallauer, Robert; Schmidt, Lothar Ph H; Johnson, Allan S; Mazenauer, Manuel; Spenger, Benjamin; Marquardt, Sabrina; Marquardt, Sebastian; Schmidt-Böcking, Horst; Stohner, Jürgen; Dörner, Reinhard; Schöffler, Markus; Berger, Robert

2016-08-18

The absolute configuration of individual small molecules in the gas phase can be determined directly by light-induced Coulomb explosion imaging (CEI). Herein, this approach is demonstrated for ionization with a single X-ray photon from a synchrotron light source, leading to enhanced efficiency and faster fragmentation as compared to previous experiments with a femtosecond laser. In addition, it is shown that even incomplete fragmentation pathways of individual molecules from a racemic CHBrClF sample can give access to the absolute configuration in CEI. This leads to a significant increase of the applicability of the method as compared to the previously reported complete break-up into atomic ions and can pave the way for routine stereochemical analysis of larger chiral molecules by light-induced CEI. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Applicability of computational systems biology in toxicology.

PubMed

Kongsbak, Kristine; Hadrup, Niels; Audouze, Karine; Vinggaard, Anne Marie

2014-07-01

Systems biology as a research field has emerged within the last few decades. Systems biology, often defined as the antithesis of the reductionist approach, integrates information about individual components of a biological system. In integrative systems biology, large data sets from various sources and databases are used to model and predict effects of chemicals on, for instance, human health. In toxicology, computational systems biology enables identification of important pathways and molecules from large data sets; tasks that can be extremely laborious when performed by a classical literature search. However, computational systems biology offers more advantages than providing a high-throughput literature search; it may form the basis for establishment of hypotheses on potential links between environmental chemicals and human diseases, which would be very difficult to establish experimentally. This is possible due to the existence of comprehensive databases containing information on networks of human protein-protein interactions and protein-disease associations. Experimentally determined targets of the specific chemical of interest can be fed into these networks to obtain additional information that can be used to establish hypotheses on links between the chemical and human diseases. Such information can also be applied for designing more intelligent animal/cell experiments that can test the established hypotheses. Here, we describe how and why to apply an integrative systems biology method in the hypothesis-generating phase of toxicological research. © 2014 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

Structure-Based Characterization of Multiprotein Complexes

PubMed Central

Wiederstein, Markus; Gruber, Markus; Frank, Karl; Melo, Francisco; Sippl, Manfred J.

2014-01-01

Summary Multiprotein complexes govern virtually all cellular processes. Their 3D structures provide important clues to their biological roles, especially through structural correlations among protein molecules and complexes. The detection of such correlations generally requires comprehensive searches in databases of known protein structures by means of appropriate structure-matching techniques. Here, we present a high-speed structure search engine capable of instantly matching large protein oligomers against the complete and up-to-date database of biologically functional assemblies of protein molecules. We use this tool to reveal unseen structural correlations on the level of protein quaternary structure and demonstrate its general usefulness for efficiently exploring complex structural relationships among known protein assemblies. PMID:24954616

Bioinformatics approach reveals systematic mechanism underlying lung adenocarcinoma.

PubMed

Wu, Xiya; Zhang, Wei; Hu, Yunhua; Yi, Xianghua

2015-01-01

The purpose of this work was to explore the systematic molecular mechanism of lung adenocarcinoma and gain a deeper insight into it. Comprehensive bioinformatics methods were applied. Initially, significant differentially expressed genes (DEGs) were analyzed from the Affymetrix microarray data (GSE27262) deposited in the Gene Expression Omnibus (GEO). Subsequently, gene ontology (GO) analysis was performed using online Database for Annotation, Visualization and Integration Discovery (DAVID) software. Finally, significant pathway crosstalk was investigated based on the information derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. According to our results, the N-terminal globular domain of the type X collagen (COL10A1) gene and transmembrane protein 100 (TMEM100) gene were identified to be the most significant DEGs in tumor tissue compared with the adjacent normal tissues. The main GO categories were biological process, cellular component and molecular function. In addition, the crosstalk was significantly different between non-small cell lung cancer pathways and inositol phosphate metabolism pathway, focal adhesion signal pathway, vascular smooth muscle contraction signal pathway, peroxisome proliferator-activated receptor (PPAR) signaling pathway and calcium signaling pathway in tumor. Dysfunctional genes and pathways may play key roles in the progression and development of lung adenocarcinoma. Our data provide a systematic perspective for understanding this mechanism and may be helpful in discovering an effective treatment for lung adenocarcinoma.

Structure and photochemistry of a saccharyl thiotetrazole.

PubMed

Ismael, A; Borba, A; Henriques, M S C; Paixão, J A; Fausto, R; Cristiano, M L S

2015-01-02

The molecular structure and photochemistry of 5-thiosaccharyl-1-methyltetrazole (TSMT) were studied by means of matrix-isolation FTIR spectroscopy, X-ray crystallography, and theoretical calculations. The calculations predicted two conformers of TSMT that differ in energy by more than 15 kJ mol(-1). The infrared spectrum of TSMT isolated in solid argon was fully assigned on the basis of the spectrum calculated (O3LYP/6-311++G(3df,3pd)) for the most stable conformer. In the crystal, TSMT molecules were found to assume the same conformation as for the isolated molecule, with each molecule forming four hydrogen bonds with three neighboring molecules, leading to a network of TSMT oligomers. Upon UV (λ = 265 nm) irradiation of the matrix-isolated TSMT, two photodegradation pathways were observed, both arising from cleavage of the tetrazolyl ring. Pathway a involves cleavage of the N1-N2 and N3-N4 bonds with extrusion of N2, leading to photostable diazirine and thiocarbodiimide derivatives. The photostability of the photoproduced diazirine under the conditions used precluded its rearrangement to the nitrile imine, as reported for 5-phenyltetrazole by Bégué et al. ( J. Am. Chem. Soc. 2012 , 134 , 5339 ). Pathway b involves cleavage of the C5-N1 and N4-N3 bonds, leading to a thiocyanate and methyl azide, the latter undergoing subsequent fragmentation to give CNH.

The Anisakis Transcriptome Provides a Resource for Fundamental and Applied Studies on Allergy-Causing Parasites

PubMed Central

Baird, Fiona J.; Su, Xiaopei; Aibinu, Ibukun; Nolan, Matthew J.; Sugiyama, Hiromu; Otranto, Domenico

2016-01-01

Background Food-borne nematodes of the genus Anisakis are responsible for a wide range of illnesses (= anisakiasis), from self-limiting gastrointestinal forms to severe systemic allergic reactions, which are often misdiagnosed and under-reported. In order to enhance and refine current diagnostic tools for anisakiasis, knowledge of the whole spectrum of parasite molecules transcribed and expressed by this parasite, including those acting as potential allergens, is necessary. Methodology/Principal Findings In this study, we employ high-throughput (Illumina) sequencing and bioinformatics to characterise the transcriptomes of two Anisakis species, A. simplex and A. pegreffii, and utilize this resource to compile lists of potential allergens from these parasites. A total of ~65,000,000 reads were generated from cDNA libraries for each species, and assembled into ~34,000 transcripts (= Unigenes); ~18,000 peptides were predicted from each cDNA library and classified based on homology searches, protein motifs and gene ontology and biological pathway mapping. Using comparative analyses with sequence data available in public databases, 36 (A. simplex) and 29 (A. pegreffii) putative allergens were identified, including sequences encoding ‘novel’ Anisakis allergenic proteins (i.e. cyclophilins and ABA-1 domain containing proteins). Conclusions/Significance This study represents a first step towards providing the research community with a curated dataset to use as a molecular resource for future investigations of the biology of Anisakis, including molecules putatively acting as allergens, using functional genomics, proteomics and immunological tools. Ultimately, an improved knowledge of the biological functions of these molecules in the parasite, as well as of their immunogenic properties, will assist the development of comprehensive, reliable and robust diagnostic tools. PMID:27472517

Virtual High-Throughput Screening To Identify Novel Activin Antagonists

PubMed Central

Zhu, Jie; Mishra, Rama K.; Schiltz, Gary E.; Makanji, Yogeshwar; Scheidt, Karl A.; Mazar, Andrew P.; Woodruff, Teresa K.

2015-01-01

Activin belongs to the TGFβ superfamily, which is associated with several disease conditions, including cancer-related cachexia, preterm labor with delivery, and osteoporosis. Targeting activin and its related signaling pathways holds promise as a therapeutic approach to these diseases. A small-molecule ligand-binding groove was identified in the interface between the two activin βA subunits and was used for a virtual high-throughput in silico screening of the ZINC database to identify hits. Thirty-nine compounds without significant toxicity were tested in two well-established activin assays: FSHβ transcription and HepG2 cell apoptosis. This screening workflow resulted in two lead compounds: NUCC-474 and NUCC-555. These potential activin antagonists were then shown to inhibit activin A-mediated cell proliferation in ex vivo ovary cultures. In vivo testing showed that our most potent compound (NUCC-555) caused a dose-dependent decrease in FSH levels in ovariectomized mice. The Blitz competition binding assay confirmed target binding of NUCC-555 to the activin A:ActRII that disrupts the activin A:ActRII complex’s binding with ALK4-ECD-Fc in a dose-dependent manner. The NUCC-555 also specifically binds to activin A compared with other TGFβ superfamily member myostatin (GDF8). These data demonstrate a new in silico-based strategy for identifying small-molecule activin antagonists. Our approach is the first to identify a first-in-class small-molecule antagonist of activin binding to ALK4, which opens a completely new approach to inhibiting the activity of TGFβ receptor superfamily members. in addition, the lead compound can serve as a starting point for lead optimization toward the goal of a compound that may be effective in activin-mediated diseases. PMID:26098096

Screening and identification of potential PTP1B allosteric inhibitors using in silico and in vitro approaches.

PubMed

Shinde, Ranajit Nivrutti; Kumar, G Siva; Eqbal, Shahbaz; Sobhia, M Elizabeth

2018-01-01

Protein tyrosine phosphatase 1B (PTP1B) is a validated therapeutic target for Type 2 diabetes due to its specific role as a negative regulator of insulin signaling pathways. Discovery of active site directed PTP1B inhibitors is very challenging due to highly conserved nature of the active site and multiple charge requirements of the ligands, which makes them non-selective and non-permeable. Identification of the PTP1B allosteric site has opened up new avenues for discovering potent and selective ligands for therapeutic intervention. Interactions made by potent allosteric inhibitor in the presence of PTP1B were studied using Molecular Dynamics (MD). Computationally optimized models were used to build separate pharmacophore models of PTP1B and TCPTP, respectively. Based on the nature of interactions the target residues offered, a receptor based pharmacophore was developed. The pharmacophore considering conformational flexibility of the residues was used for the development of pharmacophore hypothesis to identify potentially active inhibitors by screening large compound databases. Two pharmacophore were successively used in the virtual screening protocol to identify potential selective and permeable inhibitors of PTP1B. Allosteric inhibition mechanism of these molecules was established using molecular docking and MD methods. The geometrical criteria values confirmed their ability to stabilize PTP1B in an open conformation. 23 molecules that were identified as potential inhibitors were screened for PTP1B inhibitory activity. After screening, 10 molecules which have good permeability values were identified as potential inhibitors of PTP1B. This study confirms that selective and permeable inhibitors can be identified by targeting allosteric site of PTP1B.

Simulating electric field interactions with polar molecules using spectroscopic databases

NASA Astrophysics Data System (ADS)

Owens, Alec; Zak, Emil J.; Chubb, Katy L.; Yurchenko, Sergei N.; Tennyson, Jonathan; Yachmenev, Andrey

2017-03-01

Ro-vibrational Stark-associated phenomena of small polyatomic molecules are modelled using extensive spectroscopic data generated as part of the ExoMol project. The external field Hamiltonian is built from the computed ro-vibrational line list of the molecule in question. The Hamiltonian we propose is general and suitable for any polar molecule in the presence of an electric field. By exploiting precomputed data, the often prohibitively expensive computations associated with high accuracy simulations of molecule-field interactions are avoided. Applications to strong terahertz field-induced ro-vibrational dynamics of PH3 and NH3, and spontaneous emission data for optoelectrical Sisyphus cooling of H2CO and CH3Cl are discussed.

Enterocyte protein tyrosine nitration in response to Eimeria infection in broilers

USDA-ARS?s Scientific Manuscript database

Activation of pathogen-sensing mechanisms in intestinal cells initiate the generation of pathway effectors that perturb normal nutritional enterocyte (ETC) functions. Among the conserved pathway mediator molecules generated are nitric oxide (NO) and superoxide anion (SOA) which are known to interac...

ACTP: A webserver for predicting potential targets and relevant pathways of autophagy-modulating compounds

PubMed Central

Ouyang, Liang; Cai, Haoyang; Liu, Bo

2016-01-01

Autophagy (macroautophagy) is well known as an evolutionarily conserved lysosomal degradation process for long-lived proteins and damaged organelles. Recently, accumulating evidence has revealed a series of small-molecule compounds that may activate or inhibit autophagy for therapeutic potential on human diseases. However, targeting autophagy for drug discovery still remains in its infancy. In this study, we developed a webserver called Autophagic Compound-Target Prediction (ACTP) (http://actp.liu-lab.com/) that could predict autophagic targets and relevant pathways for a given compound. The flexible docking of submitted small-molecule compound (s) to potential autophagic targets could be performed by backend reverse docking. The webpage would return structure-based scores and relevant pathways for each predicted target. Thus, these results provide a basis for the rapid prediction of potential targets/pathways of possible autophagy-activating or autophagy-inhibiting compounds without labor-intensive experiments. Moreover, ACTP will be helpful to shed light on identifying more novel autophagy-activating or autophagy-inhibiting compounds for future therapeutic implications. PMID:26824420

The potential signalling pathways which regulate surface changes induced by phytohormones in the potato cyst nematode (Globodera rostochiensis).

PubMed

Akhkha, A; Curtis, R; Kennedy, M; Kusel, J

2004-05-01

It has been demonstrated that the surface lipophilicity of the plant-parasitic nematode Globodera rostochiensis decreases when infective larvae are exposed to the phytohormones indole-3-acetic acid (auxin) or kinetin (cytokinin). In the present study, it was shown that inhibition of phospholipase C (PLC) or phosphatidylinositol 3 kinase (PI3-kinase) reversed the effect of phytohormones on surface lipophilicity. The signalling pathway(s) involved in surface modification were investigated using 'caged' signalling molecules and stimulators or inhibitors of different signalling enzymes. Photolysis of the 'caged' signalling molecules, NPE-caged Ins 1,4,5-P3, NITR-5/AM or caged-cAMP to liberate IP3, Ca2+ or cAMP respectively, decreased the surface lipophilicity. Activation of adenylate cyclase also decreased the surface lipophilicity. In contrast, inhibition of PI3-kinase using Wortmannin, LY-294002 or Quercetin, and inhibition of PLC using U-73122 all increased the surface lipophilicity. Two possible signalling pathways involved in phytohormone-induced surface modification are proposed.

Combining RNA interference and kinase inhibitors against cell signalling components involved in cancer

PubMed Central

O'Grady, Michael; Raha, Debasish; Hanson, Bonnie J; Bunting, Michaeline; Hanson, George T

2005-01-01

Background The transcription factor activator protein-1 (AP-1) has been implicated in a large variety of biological processes including oncogenic transformation. The tyrosine kinases of the epidermal growth factor receptor (EGFR) constitute the beginning of one signal transduction cascade leading to AP-1 activation and are known to control cell proliferation and differentiation. Drug discovery efforts targeting this receptor and other pathway components have centred on monoclonal antibodies and small molecule inhibitors. Resistance to such inhibitors has already been observed, guiding the prediction of their use in combination therapies with other targeted agents such as RNA interference (RNAi). This study examines the use of RNAi and kinase inhibitors for qualification of components involved in the EGFR/AP-1 pathway of ME180 cells, and their inhibitory effects when evaluated individually or in tandem against multiple components of this important disease-related pathway. Methods AP-1 activation was assessed using an ME180 cell line stably transfected with a beta-lactamase reporter gene under the control of AP-1 response element following epidermal growth factor (EGF) stimulation. Immunocytochemistry allowed for further quantification of small molecule inhibition on a cellular protein level. RNAi and RT-qPCR experiments were performed to assess the amount of knockdown on an mRNA level, and immunocytochemistry was used to reveal cellular protein levels for the targeted pathway components. Results Increased potency of kinase inhibitors was shown by combining RNAi directed towards EGFR and small molecule inhibitors acting at proximal or distal points in the pathway. After cellular stimulation with EGF and analysis at the level of AP-1 activation using a β-lactamase reporter gene, a 10–12 fold shift or 2.5–3 fold shift toward greater potency in the IC50 was observed for EGFR and MEK-1 inhibitors, respectively, in the presence of RNAi targeting EGFR. Conclusion EGFR pathway components were qualified as targets for inhibition of AP-1 activation using RNAi and small molecule inhibitors. The combination of these two targeted agents was shown to increase the efficacy of EGFR and MEK-1 kinase inhibitors, leading to possible implications for overcoming or preventing drug resistance, lowering effective drug doses, and providing new strategies for interrogating cellular signalling pathways. PMID:16202132

Microfibrillar associated protein 4 mfap4 genes in catfish play a novel role in innate immune responses

USDA-ARS?s Scientific Manuscript database

The lectin pathway of the complement system is characterized by two groups of soluble pattern recognition molecules, mannose-binding lectins (MBLs) and ficolins. These molecules recognize and bind carbohydrates in pathogens and activate complement leading to opsonization, leukocyte activation, and d...

MetaboLyzer: A Novel Statistical Workflow for Analyzing Post-Processed LC/MS Metabolomics Data

PubMed Central

Mak, Tytus D.; Laiakis, Evagelia C.; Goudarzi, Maryam; Fornace, Albert J.

2014-01-01

Metabolomics, the global study of small molecules in a particular system, has in the last few years risen to become a primary –omics platform for the study of metabolic processes. With the ever-increasing pool of quantitative data yielded from metabolomic research, specialized methods and tools with which to analyze and extract meaningful conclusions from these data are becoming more and more crucial. Furthermore, the depth of knowledge and expertise required to undertake a metabolomics oriented study is a daunting obstacle to investigators new to the field. As such, we have created a new statistical analysis workflow, MetaboLyzer, which aims to both simplify analysis for investigators new to metabolomics, as well as provide experienced investigators the flexibility to conduct sophisticated analysis. MetaboLyzer’s workflow is specifically tailored to the unique characteristics and idiosyncrasies of postprocessed liquid chromatography/mass spectrometry (LC/MS) based metabolomic datasets. It utilizes a wide gamut of statistical tests, procedures, and methodologies that belong to classical biostatistics, as well as several novel statistical techniques that we have developed specifically for metabolomics data. Furthermore, MetaboLyzer conducts rapid putative ion identification and putative biologically relevant analysis via incorporation of four major small molecule databases: KEGG, HMDB, Lipid Maps, and BioCyc. MetaboLyzer incorporates these aspects into a comprehensive workflow that outputs easy to understand statistically significant and potentially biologically relevant information in the form of heatmaps, volcano plots, 3D visualization plots, correlation maps, and metabolic pathway hit histograms. For demonstration purposes, a urine metabolomics data set from a previously reported radiobiology study in which samples were collected from mice exposed to gamma radiation was analyzed. MetaboLyzer was able to identify 243 statistically significant ions out of a total of 1942. Numerous putative metabolites and pathways were found to be biologically significant from the putative ion identification workflow. PMID:24266674

Discovering relationships between nuclear receptor signaling pathways, genes, and tissues in Transcriptomine.

PubMed

Becnel, Lauren B; Ochsner, Scott A; Darlington, Yolanda F; McOwiti, Apollo; Kankanamge, Wasula H; Dehart, Michael; Naumov, Alexey; McKenna, Neil J

2017-04-25

We previously developed a web tool, Transcriptomine, to explore expression profiling data sets involving small-molecule or genetic manipulations of nuclear receptor signaling pathways. We describe advances in biocuration, query interface design, and data visualization that enhance the discovery of uncharacterized biology in these pathways using this tool. Transcriptomine currently contains about 45 million data points encompassing more than 2000 experiments in a reference library of nearly 550 data sets retrieved from public archives and systematically curated. To make the underlying data points more accessible to bench biologists, we classified experimental small molecules and gene manipulations into signaling pathways and experimental tissues and cell lines into physiological systems and organs. Incorporation of these mappings into Transcriptomine enables the user to readily evaluate tissue-specific regulation of gene expression by nuclear receptor signaling pathways. Data points from animal and cell model experiments and from clinical data sets elucidate the roles of nuclear receptor pathways in gene expression events accompanying various normal and pathological cellular processes. In addition, data sets targeting non-nuclear receptor signaling pathways highlight transcriptional cross-talk between nuclear receptors and other signaling pathways. We demonstrate with specific examples how data points that exist in isolation in individual data sets validate each other when connected and made accessible to the user in a single interface. In summary, Transcriptomine allows bench biologists to routinely develop research hypotheses, validate experimental data, or model relationships between signaling pathways, genes, and tissues. Copyright © 2017, American Association for the Advancement of Science.

Reconstruction of metabolic pathways by combining probabilistic graphical model-based and knowledge-based methods

PubMed Central

2014-01-01

Automatic reconstruction of metabolic pathways for an organism from genomics and transcriptomics data has been a challenging and important problem in bioinformatics. Traditionally, known reference pathways can be mapped into an organism-specific ones based on its genome annotation and protein homology. However, this simple knowledge-based mapping method might produce incomplete pathways and generally cannot predict unknown new relations and reactions. In contrast, ab initio metabolic network construction methods can predict novel reactions and interactions, but its accuracy tends to be low leading to a lot of false positives. Here we combine existing pathway knowledge and a new ab initio Bayesian probabilistic graphical model together in a novel fashion to improve automatic reconstruction of metabolic networks. Specifically, we built a knowledge database containing known, individual gene / protein interactions and metabolic reactions extracted from existing reference pathways. Known reactions and interactions were then used as constraints for Bayesian network learning methods to predict metabolic pathways. Using individual reactions and interactions extracted from different pathways of many organisms to guide pathway construction is new and improves both the coverage and accuracy of metabolic pathway construction. We applied this probabilistic knowledge-based approach to construct the metabolic networks from yeast gene expression data and compared its results with 62 known metabolic networks in the KEGG database. The experiment showed that the method improved the coverage of metabolic network construction over the traditional reference pathway mapping method and was more accurate than pure ab initio methods. PMID:25374614

Structator: fast index-based search for RNA sequence-structure patterns

PubMed Central

2011-01-01

Background The secondary structure of RNA molecules is intimately related to their function and often more conserved than the sequence. Hence, the important task of searching databases for RNAs requires to match sequence-structure patterns. Unfortunately, current tools for this task have, in the best case, a running time that is only linear in the size of sequence databases. Furthermore, established index data structures for fast sequence matching, like suffix trees or arrays, cannot benefit from the complementarity constraints introduced by the secondary structure of RNAs. Results We present a novel method and readily applicable software for time efficient matching of RNA sequence-structure patterns in sequence databases. Our approach is based on affix arrays, a recently introduced index data structure, preprocessed from the target database. Affix arrays support bidirectional pattern search, which is required for efficiently handling the structural constraints of the pattern. Structural patterns like stem-loops can be matched inside out, such that the loop region is matched first and then the pairing bases on the boundaries are matched consecutively. This allows to exploit base pairing information for search space reduction and leads to an expected running time that is sublinear in the size of the sequence database. The incorporation of a new chaining approach in the search of RNA sequence-structure patterns enables the description of molecules folding into complex secondary structures with multiple ordered patterns. The chaining approach removes spurious matches from the set of intermediate results, in particular of patterns with little specificity. In benchmark experiments on the Rfam database, our method runs up to two orders of magnitude faster than previous methods. Conclusions The presented method's sublinear expected running time makes it well suited for RNA sequence-structure pattern matching in large sequence databases. RNA molecules containing several stem-loop substructures can be described by multiple sequence-structure patterns and their matches are efficiently handled by a novel chaining method. Beyond our algorithmic contributions, we provide with Structator a complete and robust open-source software solution for index-based search of RNA sequence-structure patterns. The Structator software is available at http://www.zbh.uni-hamburg.de/Structator. PMID:21619640

Stereoselective virtual screening of the ZINC database using atom pair 3D-fingerprints.

PubMed

Awale, Mahendra; Jin, Xian; Reymond, Jean-Louis

2015-01-01

Tools to explore large compound databases in search for analogs of query molecules provide a strategically important support in drug discovery to help identify available analogs of any given reference or hit compound by ligand based virtual screening (LBVS). We recently showed that large databases can be formatted for very fast searching with various 2D-fingerprints using the city-block distance as similarity measure, in particular a 2D-atom pair fingerprint (APfp) and the related category extended atom pair fingerprint (Xfp) which efficiently encode molecular shape and pharmacophores, but do not perceive stereochemistry. Here we investigated related 3D-atom pair fingerprints to enable rapid stereoselective searches in the ZINC database (23.2 million 3D structures). Molecular fingerprints counting atom pairs at increasing through-space distance intervals were designed using either all atoms (16-bit 3DAPfp) or different atom categories (80-bit 3DXfp). These 3D-fingerprints retrieved molecular shape and pharmacophore analogs (defined by OpenEye ROCS scoring functions) of 110,000 compounds from the Cambridge Structural Database with equal or better accuracy than the 2D-fingerprints APfp and Xfp, and showed comparable performance in recovering actives from decoys in the DUD database. LBVS by 3DXfp or 3DAPfp similarity was stereoselective and gave very different analogs when starting from different diastereomers of the same chiral drug. Results were also different from LBVS with the parent 2D-fingerprints Xfp or APfp. 3D- and 2D-fingerprints also gave very different results in LBVS of folded molecules where through-space distances between atom pairs are much shorter than topological distances. 3DAPfp and 3DXfp are suitable for stereoselective searches for shape and pharmacophore analogs of query molecules in large databases. Web-browsers for searching ZINC by 3DAPfp and 3DXfp similarity are accessible at www.gdb.unibe.ch and should provide useful assistance to drug discovery projects. Graphical abstractAtom pair fingerprints based on through-space distances (3DAPfp) provide better shape encoding than atom pair fingerprints based on topological distances (APfp) as measured by the recovery of ROCS shape analogs by fp similarity.

Omentin inhibits TNF-{alpha}-induced expression of adhesion molecules in endothelial cells via ERK/NF-{kappa}B pathway

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

Zhong, Xia, E-mail: zhongxia1977@126.com; Li, Xiaonan; Liu, Fuli

2012-08-24

Highlights: Black-Right-Pointing-Pointer Omentin inhibited TNF-{alpha}-induced adhesion of THP-1 cells to HUVECs. Black-Right-Pointing-Pointer Omentin reduces expression of ICAM-1 and VCAM-1 induced by TNF-{alpha} in HUVECs. Black-Right-Pointing-Pointer Omentin inhibits TNF-{alpha}-induced ERK and NF-{kappa}B activation in HUVECs. Black-Right-Pointing-Pointer Omentin supreeses TNF-{alpha}-induced expression of ICAM-1 and VCAM-1 via ERK/NF-{kappa}B pathway. -- Abstract: In the present study, we investigated whether omentin affected the expression of intracellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) in tumor necrosis factor-{alpha} (TNF-{alpha}) induced human umbilical vein endothelial cells (HUVECs). Our data showed that omentin decreased TNF-{alpha}-induced expression of ICAM-1 and VCAM-1 in HUVECs. In addition, omentin inhibitedmore » TNF-{alpha}-induced adhesion of THP-1 cells to HUVECs. Further, we found that omentin inhibited TNF-{alpha}-activated signal pathway of nuclear factor-{kappa}B (NF-{kappa}B) by preventing NF-{kappa}B inhibitory protein (I{kappa}B{alpha}) degradation and NF-{kappa}B/DNA binding activity. Omentin pretreatment significantly inhibited TNF-{alpha}-induced ERK activity and ERK phosphorylation in HUVECs. Pretreatment with PD98059 suppressed TNF-{alpha}-induced NF-{kappa}B activity. Omentin, NF-kB inhibitor (BAY11-7082) and ERK inhibitor (PD98059) reduced the up-regulation of ICAM-1 and VCAM-1 induced by TNF-{alpha}. These results suggest that omentin may inhibit TNF-{alpha}-induced expression of adhesion molecules in endothelial cells via blocking ERK/NF-{kappa}B pathway.« less

Knowledge representation in metabolic pathway databases.

PubMed

Stobbe, Miranda D; Jansen, Gerbert A; Moerland, Perry D; van Kampen, Antoine H C

2014-05-01

The accurate representation of all aspects of a metabolic network in a structured format, such that it can be used for a wide variety of computational analyses, is a challenge faced by a growing number of researchers. Analysis of five major metabolic pathway databases reveals that each database has made widely different choices to address this challenge, including how to deal with knowledge that is uncertain or missing. In concise overviews, we show how concepts such as compartments, enzymatic complexes and the direction of reactions are represented in each database. Importantly, also concepts which a database does not represent are described. Which aspects of the metabolic network need to be available in a structured format and to what detail differs per application. For example, for in silico phenotype prediction, a detailed representation of gene-protein-reaction relations and the compartmentalization of the network is essential. Our analysis also shows that current databases are still limited in capturing all details of the biology of the metabolic network, further illustrated with a detailed analysis of three metabolic processes. Finally, we conclude that the conceptual differences between the databases, which make knowledge exchange and integration a challenge, have not been resolved, so far, by the exchange formats in which knowledge representation is standardized.

Entamoeba histolytica: construction and applications of subgenomic databases.

PubMed

Hofer, Margit; Duchêne, Michael

2005-07-01

Knowledge about the influence of environmental stress such as the action of chemotherapeutic agents on gene expression in Entamoeba histolytica is limited. We plan to use oligonucleotide microarray hybridization to approach these questions. As the basis for our array, sequence data from the genome project carried out by the Institute for Genomic Research (TIGR) and the Sanger Institute were used to annotate parts of the parasite genome. Three subgenomic databases containing enzymes, cytoskeleton genes, and stress genes were compiled with the help of the ExPASy proteomics website and the BLAST servers at the two genome project sites. The known sequences from reference species, mostly human and Escherichia coli, were searched against TIGR and Sanger E. histolytica sequence contigs and the homologs were copied into a Microsoft Access database. In a similar way, two additional databases of cytoskeletal genes and stress genes were generated. Metabolic pathways could be assembled from our enzyme database, but sometimes they were incomplete as is the case for the sterol biosynthesis pathway. The raw databases contained a significant number of duplicate entries which were merged to obtain curated non-redundant databases. This procedure revealed that some E. histolytica genes may have several putative functions. Representative examples such as the case of the delta-aminolevulinate synthase/serine palmitoyltransferase are discussed.

Incorporating Virtual Reactions into a Logic-based Ligand-based Virtual Screening Method to Discover New Leads

PubMed Central

Reynolds, Christopher R; Muggleton, Stephen H; Sternberg, Michael J E

2015-01-01

The use of virtual screening has become increasingly central to the drug development pipeline, with ligand-based virtual screening used to screen databases of compounds to predict their bioactivity against a target. These databases can only represent a small fraction of chemical space, and this paper describes a method of exploring synthetic space by applying virtual reactions to promising compounds within a database, and generating focussed libraries of predicted derivatives. A ligand-based virtual screening tool Investigational Novel Drug Discovery by Example (INDDEx) is used as the basis for a system of virtual reactions. The use of virtual reactions is estimated to open up a potential space of 1.21×1012 potential molecules. A de novo design algorithm known as Partial Logical-Rule Reactant Selection (PLoRRS) is introduced and incorporated into the INDDEx methodology. PLoRRS uses logical rules from the INDDEx model to select reactants for the de novo generation of potentially active products. The PLoRRS method is found to increase significantly the likelihood of retrieving molecules similar to known actives with a p-value of 0.016. Case studies demonstrate that the virtual reactions produce molecules highly similar to known actives, including known blockbuster drugs. PMID:26583052

Identification of potential genomic biomarkers of hepatotoxicity caused by reactive metabolites of N-methylformamide: Application of stable isotope labeled compounds in toxicogenomic studies.

PubMed

Mutlib, Abdul; Jiang, Ping; Atherton, Jim; Obert, Leslie; Kostrubsky, Seva; Madore, Steven; Nelson, Sidney

2006-10-01

The inability to predict if a metabolically bioactivated compound will cause toxicity in later stages of drug development or post-marketing is of serious concern. One approach for improving the predictive success of compound toxicity has been to compare the gene expression profile in preclinical models dosed with novel compounds to a gene expression database generated from compounds with known toxicity. While this guilt-by-association approach can be useful, it is often difficult to elucidate gene expression changes that may be related to the generation of reactive metabolites. In an effort to address this issue, we compared the gene expression profiles obtained from animals treated with a soft-electrophile-producing hepatotoxic compound against corresponding deuterium labeled analogues resistant to metabolic processing. Our aim was to identify a subset of potential biomarker genes for hepatotoxicity caused by soft-electrophile-producing compounds. The current study utilized a known hepatotoxic compound N-methylformamide (NMF) and its two analogues labeled with deuterium at different positions to block metabolic oxidation at the formyl (d(1)) and methyl (d(3)) moieties. Groups of mice were dosed with each compound, and their livers were harvested at different time intervals. RNA was prepared and analyzed on Affymetrix GeneChip arrays. RNA transcripts showing statistically significant changes were identified, and selected changes were confirmed using TaqMan RT-PCR. Serum clinical chemistry and histopathologic evaluations were performed on selected samples as well. The data set generated from the different groups of animals enabled us to determine which gene expression changes were attributed to the bioactivating pathway. We were able to selectively modulate the metabolism of NMF by labeling various positions of the molecule with a stable isotope, allowing us to monitor gene changes specifically due to a particular metabolic pathway. Two groups of genes were identified, which were associated with the metabolism of a certain part of the NMF molecule. The metabolic pathway leading to the production of reactive methyl isocyanate resulted in distinct expression patterns that correlated with histopathologic findings. There was a clear correlation between the expression of certain genes involved in the cell cycle/apoptosis and inflammatory pathways and the presence of reactive metabolite. These genes may serve as potential genomic biomarkers of hepatotoxicity induced by soft-electrophile-producing compounds. However, the robustness of these potential genomic biomarkers will need to be validated using other hepatotoxicants (both soft- and hard-electrophile-producing agents) and compounds known to cause idiosyncratic liver toxicity before being adopted into the drug discovery screening process.

DG-AMMOS: a new tool to generate 3d conformation of small molecules using distance geometry and automated molecular mechanics optimization for in silico screening.

PubMed

Lagorce, David; Pencheva, Tania; Villoutreix, Bruno O; Miteva, Maria A

2009-11-13

Discovery of new bioactive molecules that could enter drug discovery programs or that could serve as chemical probes is a very complex and costly endeavor. Structure-based and ligand-based in silico screening approaches are nowadays extensively used to complement experimental screening approaches in order to increase the effectiveness of the process and facilitating the screening of thousands or millions of small molecules against a biomolecular target. Both in silico screening methods require as input a suitable chemical compound collection and most often the 3D structure of the small molecules has to be generated since compounds are usually delivered in 1D SMILES, CANSMILES or in 2D SDF formats. Here, we describe the new open source program DG-AMMOS which allows the generation of the 3D conformation of small molecules using Distance Geometry and their energy minimization via Automated Molecular Mechanics Optimization. The program is validated on the Astex dataset, the ChemBridge Diversity database and on a number of small molecules with known crystal structures extracted from the Cambridge Structural Database. A comparison with the free program Balloon and the well-known commercial program Omega generating the 3D of small molecules is carried out. The results show that the new free program DG-AMMOS is a very efficient 3D structure generator engine. DG-AMMOS provides fast, automated and reliable access to the generation of 3D conformation of small molecules and facilitates the preparation of a compound collection prior to high-throughput virtual screening computations. The validation of DG-AMMOS on several different datasets proves that generated structures are generally of equal quality or sometimes better than structures obtained by other tested methods.

TAK-242 treatment ameliorates liver ischemia/reperfusion injury by inhibiting TLR4 signaling pathway in a swine model of Maastricht-category-III cardiac death.

PubMed

Shao, Zigong; Jiao, Baoping; Liu, Tingting; Cheng, Ying; Liu, Hao; Liu, Yongfeng

2016-12-01

This study aims to test the effects of TAK-242 on liver transplant viability in a model of swine Maastricht-category-III cardiac death. A swine DCD Maastricht-III model of cardiac death was established, and TAK-242 was administered prior to the induction of cardiac death. The protein and mRNA level of TLR4 signaling pathway molecules and cytokines that are important in mediating immune and inflammatory responses were assessed at different time points following the induction of cardiac death. After induction of cardiac death, both the mRNA and protein levels of key molecules (TLR4, TRAF6, NF-ϰB, ICAM-1, MCP-1 and MPO), TNF-α and IL-6 increased significantly. Infusion of TAK-242 1h before induction of cardiac death blocked the increase of immune and inflammatory response molecules. However, the increase of TLR4 level was not affected by infusion of TAK-242. Histology study showed that infusion of TAK-242 protect liver tissue from damage during cardiac death. These results indicates that TLR4 signaling pathway may contribute to ischemia/reperfusion injury in the liver grafts, and blocking TLR4 pathway with TAk-242 may reduce TLR4-mediated tissue damage. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Network modeling of kinase inhibitor polypharmacology reveals pathways targeted in chemical screens

PubMed Central

Ursu, Oana; Gosline, Sara J. C.; Beeharry, Neil; Fink, Lauren; Bhattacharjee, Vikram; Huang, Shao-shan Carol; Zhou, Yan; Yen, Tim; Fraenkel, Ernest

2017-01-01

Small molecule screens are widely used to prioritize pharmaceutical development. However, determining the pathways targeted by these molecules is challenging, since the compounds are often promiscuous. We present a network strategy that takes into account the polypharmacology of small molecules in order to generate hypotheses for their broader mode of action. We report a screen for kinase inhibitors that increase the efficacy of gemcitabine, the first-line chemotherapy for pancreatic cancer. Eight kinase inhibitors emerge that are known to affect 201 kinases, of which only three kinases have been previously identified as modifiers of gemcitabine toxicity. In this work, we use the SAMNet algorithm to identify pathways linking these kinases and genetic modifiers of gemcitabine toxicity with transcriptional and epigenetic changes induced by gemcitabine that we measure using DNaseI-seq and RNA-seq. SAMNet uses a constrained optimization algorithm to connect genes from these complementary datasets through a small set of protein-protein and protein-DNA interactions. The resulting network recapitulates known pathways including DNA repair, cell proliferation and the epithelial-to-mesenchymal transition. We use the network to predict genes with important roles in the gemcitabine response, including six that have already been shown to modify gemcitabine efficacy in pancreatic cancer and ten novel candidates. Our work reveals the important role of polypharmacology in the activity of these chemosensitizing agents. PMID:29023490

Chemical genomics: characterizing target pathways for bioactive compounds using the endomembrane trafficking network.

PubMed

Rodriguez-Furlán, Cecilia; Hicks, Glenn R; Norambuena, Lorena

2014-01-01

The plant endomembrane trafficking system is a highly complex set of processes. This complexity presents a challenge for its study. Classical plant genetics often struggles with loss-of-function lethality and gene redundancy. Chemical genomics allows overcoming many of these issues by using small molecules of natural or synthetic origin to inhibit specific trafficking proteins thereby affecting the processes in a tunable and reversible manner. Bioactive chemicals identified by high-throughput phenotype screens must be characterized in detail starting with understanding of the specific trafficking pathways affected. Here, we describe approaches to characterize bioactive compounds that perturb vesicle trafficking. This should equip researchers with practical knowledge on how to identify endomembrane-specific trafficking pathways that may be perturbed by specific compounds and will help to eventually identify molecular targets for these small molecules.

Fundamental Pathways for the Adsorption and Transport of Hydrogen on TiO2 Surfaces: Origin for Effective Sensing at about Room Temperature.

PubMed

Wang, Zhuo; Xia, Xiaohong; Guo, Meilan; Shao, Guosheng

2016-12-28

Effective detection of hydrogen at lowered temperature is highly desirable in promoting safety in using this abundant gas as a clean energy source. Through first-principle calculations in the framework of density functional theory, we find that the high-energy (002) surface for rutile TiO 2 is significantly more effective in adsorbing hydrogen atoms through dissociating hydrogen molecules. The pathways for the dissociation of hydrogen molecules and sequential migration of hydrogen atoms are identified through searching along various transitional states. Pathways of low potential barriers indicate promise for hydrogen sensing, even close to room temperature. This has been proven through sensors made of thin films of well-aligned rutile nanorods, wherein the high-energy (002) surface dictates the top surface of the active layer of the sensors.

Systematization of the protein sequence diversity in enzymes related to secondary metabolic pathways in plants, in the context of big data biology inspired by the KNApSAcK motorcycle database.

PubMed

Ikeda, Shun; Abe, Takashi; Nakamura, Yukiko; Kibinge, Nelson; Hirai Morita, Aki; Nakatani, Atsushi; Ono, Naoaki; Ikemura, Toshimichi; Nakamura, Kensuke; Altaf-Ul-Amin, Md; Kanaya, Shigehiko

2013-05-01

Biology is increasingly becoming a data-intensive science with the recent progress of the omics fields, e.g. genomics, transcriptomics, proteomics and metabolomics. The species-metabolite relationship database, KNApSAcK Core, has been widely utilized and cited in metabolomics research, and chronological analysis of that research work has helped to reveal recent trends in metabolomics research. To meet the needs of these trends, the KNApSAcK database has been extended by incorporating a secondary metabolic pathway database called Motorcycle DB. We examined the enzyme sequence diversity related to secondary metabolism by means of batch-learning self-organizing maps (BL-SOMs). Initially, we constructed a map by using a big data matrix consisting of the frequencies of all possible dipeptides in the protein sequence segments of plants and bacteria. The enzyme sequence diversity of the secondary metabolic pathways was examined by identifying clusters of segments associated with certain enzyme groups in the resulting map. The extent of diversity of 15 secondary metabolic enzyme groups is discussed. Data-intensive approaches such as BL-SOM applied to big data matrices are needed for systematizing protein sequences. Handling big data has become an inevitable part of biology.

Comprehensive coverage of cardiovascular disease data in the disease portals at the Rat Genome Database.

PubMed

Wang, Shur-Jen; Laulederkind, Stanley J F; Hayman, G Thomas; Petri, Victoria; Smith, Jennifer R; Tutaj, Marek; Nigam, Rajni; Dwinell, Melinda R; Shimoyama, Mary

2016-08-01

Cardiovascular diseases are complex diseases caused by a combination of genetic and environmental factors. To facilitate progress in complex disease research, the Rat Genome Database (RGD) provides the community with a disease portal where genome objects and biological data related to cardiovascular diseases are systematically organized. The purpose of this study is to present biocuration at RGD, including disease, genetic, and pathway data. The RGD curation team uses controlled vocabularies/ontologies to organize data curated from the published literature or imported from disease and pathway databases. These organized annotations are associated with genes, strains, and quantitative trait loci (QTLs), thus linking functional annotations to genome objects. Screen shots from the web pages are used to demonstrate the organization of annotations at RGD. The human cardiovascular disease genes identified by annotations were grouped according to data sources and their annotation profiles were compared by in-house tools and other enrichment tools available to the public. The analysis results show that the imported cardiovascular disease genes from ClinVar and OMIM are functionally different from the RGD manually curated genes in terms of pathway and Gene Ontology annotations. The inclusion of disease genes from other databases enriches the collection of disease genes not only in quantity but also in quality. Copyright © 2016 the American Physiological Society.

The systematic annotation of the three main GPCR families in Reactome.

PubMed

Jassal, Bijay; Jupe, Steven; Caudy, Michael; Birney, Ewan; Stein, Lincoln; Hermjakob, Henning; D'Eustachio, Peter

2010-07-29

Reactome is an open-source, freely available database of human biological pathways and processes. A major goal of our work is to provide an integrated view of cellular signalling processes that spans from ligand-receptor interactions to molecular readouts at the level of metabolic and transcriptional events. To this end, we have built the first catalogue of all human G protein-coupled receptors (GPCRs) known to bind endogenous or natural ligands. The UniProt database has records for 797 proteins classified as GPCRs and sorted into families A/1, B/2 and C/3 on the basis of amino acid sequence. To these records we have added details from the IUPHAR database and our own manual curation of relevant literature to create reactions in which 563 GPCRs bind ligands and also interact with specific G-proteins to initiate signalling cascades. We believe the remaining 234 GPCRs are true orphans. The Reactome GPCR pathway can be viewed as a detailed interactive diagram and can be exported in many forms. It provides a template for the orthology-based inference of GPCR reactions for diverse model organism species, and can be overlaid with protein-protein interaction and gene expression datasets to facilitate overrepresentation studies and other forms of pathway analysis. Database URL: http://www.reactome.org.

Progranulin protects vascular endothelium against atherosclerotic inflammatory reaction via Akt/eNOS and nuclear factor-κB pathways.

PubMed

Hwang, Hwan-Jin; Jung, Tae Woo; Hong, Ho Cheol; Choi, Hae Yoon; Seo, Ji-A; Kim, Sin Gon; Kim, Nan Hee; Choi, Kyung Mook; Choi, Dong Seop; Baik, Sei Hyun; Yoo, Hye Jin

2013-01-01

Atherosclerosis is considered a chronic inflammatory disease, initiated by activation and dysfunction of the endothelium. Recently, progranulin has been regarded as an important modulator of inflammatory processes; however, the role for prgranulin in regulating inflammation in vascular endothelial cells has not been described. Signaling pathways mediated by progranulin were analyzed in human umbilical vein endothelial cells (HUVECs) treated with progranulin. Progranulin significantly induced Akt and endothelial nitric oxide synthase (eNOS) phosphorylation in HUVECs, an effect that was blocked with Akt inhibitor. Furthermore, nitric oxide (NO) level, the end product of Akt/eNOS pathway, was significantly upregulated after progranulin treatment. Next, we showed that progranulin efficiently inhibited lipopolysaccharide (LPS)-mediated pro-inflammatory signaling. LPS-induced phosphorylation of IκB and nuclear factor-κB (NF-κB) levels decreased after progranulin treatment. Also, progranulin blocked translocation of NF-κB from the cytosol to the nucleus. In addition, progranulin significantly reduced the expression of vascular cell adhesion molecule-1 (VCAM-1) and intercellular adhesion molecule-1 (ICAM-1) by inhibiting binding of NF- κB to their promoter regions and blocked attachment of monocytes to HUVECs. Progranulin also significantly reduced the expression of tumor necrosis factor receptor-α (TNF-α) and monocyte chemo-attractant protein-1 (MCP-1), the crucial inflammatory molecules known to aggravate atherosclerosis. Progranulin efficiently inhibited LPS-mediated pro-inflammatory signaling in endothelial cells through activation of the Akt/eNOS pathway and attenuation of the NF-κB pathway, suggesting its protective roles in vascular endothelium against inflammatory reaction underlying atherosclerosis.

Databases for Microbiologists

DOE PAGES

Zhulin, Igor B.

2015-05-26

Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. Finally, the purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.

Databases for Microbiologists

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

Zhulin, Igor B.

Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. Finally, the purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.

Databases for Microbiologists

PubMed Central

2015-01-01

Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. The purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists. PMID:26013493

The University of Minnesota Biocatalysis/Biodegradation Database: specialized metabolism for functional genomics.

PubMed Central

Ellis, L B; Hershberger, C D; Wackett, L P

1999-01-01

The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://www.labmed.umn.edu/umbbd/i nde x.html) first became available on the web in 1995 to provide information on microbial biocatalytic reactions of, and biodegradation pathways for, organic chemical compounds, especially those produced by man. Its goal is to become a representative database of biodegradation, spanning the diversity of known microbial metabolic routes, organic functional groups, and environmental conditions under which biodegradation occurs. The database can be used to enhance understanding of basic biochemistry, biocatalysis leading to speciality chemical manufacture, and biodegradation of environmental pollutants. It is also a resource for functional genomics, since it contains information on enzymes and genes involved in specialized metabolism not found in intermediary metabolism databases, and thus can assist in assigning functions to genes homologous to such less common genes. With information on >400 reactions and compounds, it is poised to become a resource for prediction of microbial biodegradation pathways for compounds it does not contain, a process complementary to predicting the functions of new classes of microbial genes. PMID:9847233

Reverse screening methods to search for the protein targets of chemopreventive compounds

NASA Astrophysics Data System (ADS)

Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan

2018-05-01

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.

Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds.

PubMed

Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan

2018-01-01

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.

Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds

PubMed Central

Huang, Hongbin; Zhang, Guigui; Zhou, Yuquan; Lin, Chenru; Chen, Suling; Lin, Yutong; Mai, Shangkang; Huang, Zunnan

2018-01-01

This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction. PMID:29868550

An "EAR" on environmental surveillance and monitoring: A ...

EPA Pesticide Factsheets

Current environmental monitoring approaches focus primarily on chemical occurrence. However, based on chemical concentration alone, it can be difficult to identify which compounds may be of toxicological concern for prioritization for further monitoring or management. This can be problematic because toxicological characterization is lacking for many emerging contaminants. New sources of high throughput screening data like the ToxCast™ database, which contains data for over 9,000 compounds screened through up to 1,100 assays, are now available. Integrated analysis of chemical occurrence data with HTS data offers new opportunities to prioritize chemicals, sites, or biological effects for further investigation based on concentrations detected in the environment linked to relative potencies in pathway-based bioassays. As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast™ effects database were used to calculate exposure-activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast™ database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Biological pathways were then linked to adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts. Anthropogenic contaminants are frequently reported in environm

Psmir: a database of potential associations between small molecules and miRNAs.

PubMed

Meng, Fanlin; Wang, Jing; Dai, Enyu; Yang, Feng; Chen, Xiaowen; Wang, Shuyuan; Yu, Xuexin; Liu, Dianming; Jiang, Wei

2016-01-13

miRNAs are key post-transcriptional regulators of many essential biological processes, and their dysregulation has been validated in almost all human cancers. Restoring aberrantly expressed miRNAs might be a novel therapeutics. Recently, many studies have demonstrated that small molecular compounds can affect miRNA expression. Thus, prediction of associations between small molecules and miRNAs is important for investigation of miRNA-targeted drugs. Here, we analyzed 39 miRNA-perturbed gene expression profiles, and then calculated the similarity of transcription responses between miRNA perturbation and drug treatment to predict drug-miRNA associations. At the significance level of 0.05, we obtained 6501 candidate associations between 1295 small molecules and 25 miRNAs, which included 624 FDA approved drugs. Finally, we constructed the Psmir database to store all potential associations and the related materials. In a word, Psmir served as a valuable resource for dissecting the biological significance in small molecules' effects on miRNA expression, which will facilitate developing novel potential therapeutic targets or treatments for human cancers. Psmir is supported by all major browsers, and is freely available at http://www.bio-bigdata.com/Psmir/.

Transcriptome exploration of the sex pheromone gland of Lutzomyia longipalpis (Diptera: Psychodidae: Phlebotominae)

PubMed Central

2013-01-01

Background Molecules involved in pheromone biosynthesis may represent alternative targets for insect population control. This may be particularly useful in managing the reproduction of Lutzomyia longipalpis, the main vector of the protozoan parasite Leishmania infantum in Latin America. Besides the chemical identity of the major components of the L. longipalpis sex pheromone, there is no information regarding the molecular biology behind its production. To understand this process, obtaining information on which genes are expressed in the pheromone gland is essential. Methods In this study we used a transcriptomic approach to explore the pheromone gland and adjacent abdominal tergites in order to obtain substantial general sequence information. We used a laboratory-reared L. longipalpis (one spot, 9-Methyl GermacreneB) population, captured in Lapinha Cave, state of Minas Gerais, Brazil for this analysis. Results From a total of 3,547 cDNA clones, 2,502 high quality sequences from the pheromone gland and adjacent tissues were obtained and assembled into 1,387 contigs. Through blast searches of public databases, a group of transcripts encoding proteins potentially involved in the production of terpenoid precursors were identified in the 4th abdominal tergite, the segment containing the pheromone gland. Among them, protein-coding transcripts for four enzymes of the mevalonate pathway such as 3-hydroxyl-3-methyl glutaryl CoA reductase, phosphomevalonate kinase, diphosphomevalonate descarboxylase, and isopentenyl pyrophosphate isomerase were identified. Moreover, transcripts coding for farnesyl diphosphate synthase and NADP+ dependent farnesol dehydrogenase were also found in the same tergite. Additionally, genes potentially involved in pheromone transportation were identified from the three abdominal tergites analyzed. Conclusion This study constitutes the first transcriptomic analysis exploring the repertoire of genes expressed in the tissue containing the L. longipalpis pheromone gland as well as the flanking tissues. Using a comparative approach, a set of molecules potentially present in the mevalonate pathway emerge as interesting subjects for further study regarding their association to pheromone biosynthesis. The sequences presented here may be used as a reference set for future research on pheromone production or other characteristics of pheromone communication in this insect. Moreover, some matches for transcripts of unknown function may provide fertile ground of an in-depth study of pheromone-gland specific molecules. PMID:23497448

Highlights of the HITRAN2016 database

NASA Astrophysics Data System (ADS)

Gordon, I.; Rothman, L. S.; Hill, C.; Kochanov, R. V.; Tan, Y.

2016-12-01

The HITRAN2016 database will be released just before the AGU meeting. It is a titanic effort of world-wide collaboration between experimentalists, theoreticians and atmospheric scientists, who measure, calculate and validate the HITRAN data. The line-by-line lists for almost all of the HITRAN molecules were updated in comparison with the previous compilation HITRAN2012 [1] that has been in use, along with some intermediate updates, since 2012. The extent of the updates ranges from updating a few lines of certain molecules to complete replacements of the lists and introduction of additional isotopologues. Many more vibrational bands were added to the database, extending the spectral coverage and completeness of the datasets. For several molecules, including H2O, CO2 and CH4, the extent of the updates is so complex that separate task groups were assembled to make strategic decisions about the choices of sources for various parameters in different spectral regions. The amount of parameters has also been significantly increased, now incorporating, for instance, non-Voigt line profiles [2]; broadening by gases other than air and "self" [3]; and other phenomena, including line mixing. In addition, the amount of cross-sectional sets in the database has increased dramatically and includes many recent experiments as well as adaptation of the existing databases that were not in HITRAN previously (for instance the PNNL database [4]). The HITRAN2016 edition takes full advantage of the new structure and interface available at www.hitran.org [5] and the HITRAN Application Programming Interface [6]. This poster will provide a summary of the updates, emphasizing details of some of the most important or dramatic improvements. The users of the database will have an opportunity to discuss the updates relevant to their research and request a demonstration on how to work with the database. This work is supported by the NASA PATM (NNX13AI59G), PDART (NNX16AG51G) and AURA (NNX14AI55G) programs. References[1] L.S. Rothman et al, JQSRT 130, 4 (2013). [2] P. Wcisło et al., JQSRT 177, 75 (2016). [3] J. S. Wilzewski et al., JQSRT 168, 193 (2016). [4] S.W. Sharpe et al, Appl Spectrosc 58, 1452 (2004). [5] C. Hill et al, JQSRT 177, 4 (2016). [6] R.V. Kochanov et al, JQSRT 177, 15 (2016).

FAST TRACK COMMUNICATION: Attosecond correlation dynamics during electron tunnelling from molecules

NASA Astrophysics Data System (ADS)

Walters, Zachary B.; Smirnova, Olga

2010-08-01

In this communication, we present an analytical theory of strong-field ionization of molecules, which takes into account the rearrangement of multiple interacting electrons during the ionization process. We show that such rearrangement offers an alternative pathway to the ionization of orbitals more deeply bound than the highest occupied molecular orbital. This pathway is not subject to the full exponential suppression characteristic of direct tunnel ionization from the deeper orbitals. The departing electron produces an 'attosecond correlation pulse' which controls the rearrangement during the tunnelling process. The shape and duration of this pulse are determined by the electronic structure of the relevant states, molecular orientation and laser parameters.

The invertebrate Caenorhabditis elegans biosynthesizes ascorbate

PubMed Central

Patananan, Alexander N.; Budenholzer, Lauren M.; Pedraza, Maria E.; Torres, Eric R.; Adler, Lital N.; Clarke, Steven G.

2015-01-01

L-ascorbate, commonly known as vitamin C, serves as an antioxidant and cofactor essential for many biological processes. Distinct ascorbate biosynthetic pathways have been established for animals and plants, but little is known about the presence or synthesis of this molecule in invertebrate species. We have investigated ascorbate metabolism in the nematode Caenorhabditis elegans, where this molecule would be expected to play roles in oxidative stress resistance and as cofactor in collagen and neurotransmitter synthesis. Using high-performance liquid chromatography and gas-chromatography mass spectrometry, we determined that ascorbate is present at low amounts in the egg stage, L1 larvae, and mixed animal populations, with the egg stage containing the highest concentrations. Incubating C. elegans with precursor molecules necessary for ascorbate synthesis in plants and animals did not significantly alter ascorbate levels. Furthermore, bioinformatic analyses did not support the presence in C. elegans of either the plant or the animal biosynthetic pathway. However, we observed the complete 13C-labeling of ascorbate when C. elegans was grown with 13C-labeled Escherichia coli as a food source. These results support the hypothesis that ascorbate biosynthesis in invertebrates may proceed by a novel pathway and lay the foundation for a broader understanding of its biological role. PMID:25668719

Exogenous adenosine 5'-phosphoramidate behaves as a signal molecule in plants; it augments metabolism of phenylpropanoids and salicylic acid in Arabidopsis thaliana seedlings.

PubMed

Pietrowska-Borek, Małgorzata; Nuc, Katarzyna; Guranowski, Andrzej

2015-09-01

Cells contain various congeners of the canonical nucleotides. Some of these accumulate in cells under stress and may function as signal molecules. Their cellular levels are enzymatically controlled. Previously, we demonstrated a signaling function for diadenosine polyphosphates and cyclic nucleotides in Arabidopsis thaliana and grape, Vitis vinifera. These compounds increased the expression of genes for and the specific activity of enzymes of phenylpropanoid pathways resulting in the accumulation of certain products of these pathways. Here, we show that adenosine 5'-phosphoramidate, whose level can be controlled by HIT-family proteins, induced similar effects. This natural nucleotide, when added to A. thaliana seedlings, activated the genes for phenylalanine:ammonia lyase, 4-coumarate:coenzyme A ligase, cinnamate-4-hydroxylase, chalcone synthase, cinnamoyl-coenzyme A:NADP oxidoreductase and isochorismate synthase, which encode proteins catalyzing key reactions of phenylpropanoid pathways, and caused accumulation of lignins, anthocyanins and salicylic acid. Adenosine 5'-phosphofluoridate, a synthetic congener of adenosine 5'-phosphoramidate, behaved similarly. The results allow us to postulate that adenosine 5'-phosphoramidate should be considered as a novel signaling molecule. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Autism Spectrum Disorders and Drug Addiction: Common Pathways, Common Molecules, Distinct Disorders?

PubMed

Rothwell, Patrick E

2016-01-01

Autism spectrum disorders (ASDs) and drug addiction do not share substantial comorbidity or obvious similarities in etiology or symptomatology. It is thus surprising that a number of recent studies implicate overlapping neural circuits and molecular signaling pathways in both disorders. The purpose of this review is to highlight this emerging intersection and consider implications for understanding the pathophysiology of these seemingly distinct disorders. One area of overlap involves neural circuits and neuromodulatory systems in the striatum and basal ganglia, which play an established role in addiction and reward but are increasingly implicated in clinical and preclinical studies of ASDs. A second area of overlap relates to molecules like Fragile X mental retardation protein (FMRP) and methyl CpG-binding protein-2 (MECP2), which are best known for their contribution to the pathogenesis of syndromic ASDs, but have recently been shown to regulate behavioral and neurobiological responses to addictive drug exposure. These shared pathways and molecules point to common dimensions of behavioral dysfunction, including the repetition of behavioral patterns and aberrant reward processing. The synthesis of knowledge gained through parallel investigations of ASDs and addiction may inspire the design of new therapeutic interventions to correct common elements of striatal dysfunction.

Autism Spectrum Disorders and Drug Addiction: Common Pathways, Common Molecules, Distinct Disorders?

PubMed Central

Rothwell, Patrick E.

2016-01-01

Autism spectrum disorders (ASDs) and drug addiction do not share substantial comorbidity or obvious similarities in etiology or symptomatology. It is thus surprising that a number of recent studies implicate overlapping neural circuits and molecular signaling pathways in both disorders. The purpose of this review is to highlight this emerging intersection and consider implications for understanding the pathophysiology of these seemingly distinct disorders. One area of overlap involves neural circuits and neuromodulatory systems in the striatum and basal ganglia, which play an established role in addiction and reward but are increasingly implicated in clinical and preclinical studies of ASDs. A second area of overlap relates to molecules like Fragile X mental retardation protein (FMRP) and methyl CpG-binding protein-2 (MECP2), which are best known for their contribution to the pathogenesis of syndromic ASDs, but have recently been shown to regulate behavioral and neurobiological responses to addictive drug exposure. These shared pathways and molecules point to common dimensions of behavioral dysfunction, including the repetition of behavioral patterns and aberrant reward processing. The synthesis of knowledge gained through parallel investigations of ASDs and addiction may inspire the design of new therapeutic interventions to correct common elements of striatal dysfunction. PMID:26903789

Revealing the favorable dissociation pathway of type II kinase inhibitors via enhanced sampling simulations and two-end-state calculations.

PubMed

Sun, Huiyong; Tian, Sheng; Zhou, Shunye; Li, Youyong; Li, Dan; Xu, Lei; Shen, Mingyun; Pan, Peichen; Hou, Tingjun

2015-02-13

How does a type II inhibitor bind to/unbind from a kinase target is still a confusing question because the small molecule occupies both the ATP pocket and the allosteric pocket of the kinase binding site. Here, by using enhanced sampling simulations (umbrella sampling, US) and two-end-state free energy calculations (MM/GSBA), we systemically studied the dissociation processes of two distinct small molecules escaping from the binding pocket of p38 MAP kinase through the allosteric channel and the ATP channel. The results show that the unbinding pathways along the allosteric channel have much lower PMF depths than those along the ATP channel, suggesting that the allosteric channel is more favorable for the dissociations of the two inhibitors and thereby supporting the general understanding that the largest channel of a target is usually the entry/exit pathway for the binding/dissociation of small molecules. Interestingly, the MM/GBSA approach yielded similar PMF profiles compared with those based on US, a much time consuming approach, indicating that for a general study, such as detecting the important transition state of a ligand binding/unbinding process, MM/GBSA may be a feasible choice.

Virtual Exploration of the Ring Systems Chemical Universe.

PubMed

Visini, Ricardo; Arús-Pous, Josep; Awale, Mahendra; Reymond, Jean-Louis

2017-11-27

Here, we explore the chemical space of all virtually possible organic molecules focusing on ring systems, which represent the cyclic cores of organic molecules obtained by removing all acyclic bonds and converting all remaining atoms to carbon. This approach circumvents the combinatorial explosion encountered when enumerating the molecules themselves. We report the chemical universe database GDB4c containing 916 130 ring systems up to four saturated or aromatic rings and maximum ring size of 14 atoms and GDB4c3D containing the corresponding 6 555 929 stereoisomers. Almost all (98.6%) of these ring systems are unknown and represent chiral 3D-shaped macrocycles containing small rings and quaternary centers reminiscent of polycyclic natural products. We envision that GDB4c can serve to select new ring systems from which to design analogs of such natural products. The database is available for download at www.gdb.unibe.ch together with interactive visualization and search tools as a resource for molecular design.

Inorganic bromine in organic molecular crystals: Database survey and four case studies

NASA Astrophysics Data System (ADS)

Nemec, Vinko; Lisac, Katarina; Stilinović, Vladimir; Cinčić, Dominik

2017-01-01

We present a Cambridge Structural Database and experimental study of multicomponent molecular crystals containing bromine. The CSD study covers supramolecular behaviour of bromide and tribromide anions as well as halogen bonded dibromine molecules in crystal structures of organic salts and cocrystals, and a study of the geometries and complexities in polybromide anion systems. In addition, we present four case studies of organic structures with bromide, tribromide and polybromide anions as well as the neutral dibromine molecule. These include the first observed crystal with diprotonated phenazine, a double salt of phenazinium bromide and tribromide, a cocrystal of 4-methoxypyridine with the neutral dibromine molecule as a halogen bond donor, as well as bis(4-methoxypyridine)bromonium polybromide. Structural features of the four case studies are in the most part consistent with the statistically prevalent behaviour indicated by the CSD study for given bromine species, although they do exhibit some unorthodox structural features and in that indicate possible supramolecular causes for aberrations from the statistically most abundant (and presumably most favourable) geometries.

Cyclophilin C Participates in the US2-Mediated Degradation of Major Histocompatibility Complex Class I Molecules.

PubMed

Chapman, Daniel C; Stocki, Pawel; Williams, David B

2015-01-01

Human cytomegalovirus uses a variety of mechanisms to evade immune recognition through major histocompatibility complex class I molecules. One mechanism mediated by the immunoevasin protein US2 causes rapid disposal of newly synthesized class I molecules by the endoplasmic reticulum-associated degradation pathway. Although several components of this degradation pathway have been identified, there are still questions concerning how US2 targets class I molecules for degradation. In this study we identify cyclophilin C, a peptidyl prolyl isomerase of the endoplasmic reticulum, as a component of US2-mediated immune evasion. Cyclophilin C could be co-isolated with US2 and with the class I molecule HLA-A2. Furthermore, it was required at a particular expression level since depletion or overexpression of cyclophilin C impaired the degradation of class I molecules. To better characterize the involvement of cyclophilin C in class I degradation, we used LC-MS/MS to detect US2-interacting proteins that were influenced by cyclophilin C expression levels. We identified malectin, PDIA6, and TMEM33 as proteins that increased in association with US2 upon cyclophilin C knockdown. In subsequent validation all were shown to play a functional role in US2 degradation of class I molecules. This was specific to US2 rather than general ER-associated degradation since depletion of these proteins did not impede the degradation of a misfolded substrate, the null Hong Kong variant of α1-antitrypsin.

Cyclophilin C Participates in the US2-Mediated Degradation of Major Histocompatibility Complex Class I Molecules

PubMed Central

Chapman, Daniel C.; Stocki, Pawel; Williams, David B.

2015-01-01

Human cytomegalovirus uses a variety of mechanisms to evade immune recognition through major histocompatibility complex class I molecules. One mechanism mediated by the immunoevasin protein US2 causes rapid disposal of newly synthesized class I molecules by the endoplasmic reticulum-associated degradation pathway. Although several components of this degradation pathway have been identified, there are still questions concerning how US2 targets class I molecules for degradation. In this study we identify cyclophilin C, a peptidyl prolyl isomerase of the endoplasmic reticulum, as a component of US2-mediated immune evasion. Cyclophilin C could be co-isolated with US2 and with the class I molecule HLA-A2. Furthermore, it was required at a particular expression level since depletion or overexpression of cyclophilin C impaired the degradation of class I molecules. To better characterize the involvement of cyclophilin C in class I degradation, we used LC-MS/MS to detect US2-interacting proteins that were influenced by cyclophilin C expression levels. We identified malectin, PDIA6, and TMEM33 as proteins that increased in association with US2 upon cyclophilin C knockdown. In subsequent validation all were shown to play a functional role in US2 degradation of class I molecules. This was specific to US2 rather than general ER-associated degradation since depletion of these proteins did not impede the degradation of a misfolded substrate, the null Hong Kong variant of α1-antitrypsin. PMID:26691022

Molecular Genetic Characterization of Terreic Acid Pathway in Aspergillus terreus

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

Guo, Chun-Jun; Sun, Wei-wen; Bruno, Kenneth S.

Terreic acid is a natural product derived from 6-methylsalicylic acid (6-MSA). A compact gene cluster for its biosynthesis was characterized. Isolation of the intermediates and shunt products from the mutant strains, in combined with bioinformatic analyses, allowed us to propose a biosynthetic pathway for terreic acid. Lastly, defining the pathway and the genes involved will facilitate the engineering of this molecule with interesting antimicrobial and antitumor bioactivities.

Molecular Genetic Characterization of Terreic Acid Pathway in Aspergillus terreus

DOE PAGES

Guo, Chun-Jun; Sun, Wei-wen; Bruno, Kenneth S.; ...

2014-09-29

Terreic acid is a natural product derived from 6-methylsalicylic acid (6-MSA). A compact gene cluster for its biosynthesis was characterized. Isolation of the intermediates and shunt products from the mutant strains, in combined with bioinformatic analyses, allowed us to propose a biosynthetic pathway for terreic acid. Lastly, defining the pathway and the genes involved will facilitate the engineering of this molecule with interesting antimicrobial and antitumor bioactivities.

Alkaline hydrolysis of ethylene phosphate: an ab initio study by supermolecule model and polarizable continuum approach.

PubMed

Xia, Futing; Zhu, Hua

2011-09-01

The alkaline hydrolysis reaction of ethylene phosphate (EP) has been investigated using a supermolecule model, in which several explicit water molecules are included. The structures and single-point energies for all of the stationary points are calculated in the gas phase and in solution at the B3LYP/6-31++G(df,p) and MP2/6-311++G(df,2p) levels. The effect of water bulk solvent is introduced by the polarizable continuum model (PCM). Water attack and hydroxide attack pathways are taken into account for the alkaline hydrolysis of EP. An associative mechanism is observed for both of the two pathways with a kinetically insignificant intermediate. The water attack pathway involves a water molecule attacking and a proton transfer from the attacking water to the hydroxide in the first step, followed by an endocyclic bond cleavage to the leaving group. While in the first step of the hydroxide attack pathway the nucleophile is the hydroxide anion. The calculated barriers in aqueous solution for the water attack and hydroxide attack pathways are all about 22 kcal/mol. The excellent agreement between the calculated and observed values demonstrates that both of the two pathways are possible for the alkaline hydrolysis of EP. Copyright © 2011 Wiley Periodicals, Inc.