Recent Developments in Toxico-Cheminformatics; Supporting ...

EPA Pesticide Factsheets

EPA's National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction through the harnessing of legacy toxicity data, creation of data linkages, and generation of new high-content and high-thoughput screening data. In association with EPA's ToxCast, ToxRefDB, and ACToR projects, the DSSTox project provides cheminformatics support and, in addition, is improving public access to quality structure-annotated chemical toxicity information in less summarized forms than traditionally employed in SAR modeling, and in ways that facilitate data-mining and data read-across. The latest DSSTox version of the Carcinogenic Potency Database file (CPDBAS) illustrates ways in which various summary definitions of carcinogenic activity can be employed in modeling and data mining. DSSTox Structure-Browser provides structure searchability across all published DSSTox toxicity-related inventory, and is enabling linkages between previously isolated toxicity data resources associated with environmental and industrial chemicals. The public DSSTox inventory also has been integrated into PubChem, allowing a user to take full advantage of PubChem structure-activity and bioassay clustering features. Phase I of the ToxCast project is generating high-throughput screening data from several hundred biochemical and cell-based assays for a set of 320 chemicals, mostly pesticide actives with rich toxicology profiles. Incorporating

Lipid prodrug nanocarriers in cancer therapy.

PubMed

Mura, Simona; Bui, Duc Trung; Couvreur, Patrick; Nicolas, Julien

2015-06-28

Application of nanotechnology in the medical field (i.e., nanomedicine) plays an important role in the development of novel drug delivery methods. Nanoscale drug delivery systems can indeed be customized with specific functionalities in order to improve the efficacy of the treatments. However, despite the progresses of the last decades, nanomedicines still face important obstacles related to: (i) the physico-chemical properties of the drug moieties which may reduce the total amount of loaded drug; (ii) the rapid and uncontrolled release (i.e., burst release) of the encapsulated drug after administration and (iii) the instability of the drug in biological media where a fast transformation into inactive metabolites can occur. As an alternative strategy to alleviate these drawbacks, the prodrug approach has found wide application. The covalent modification of a drug molecule into an inactive precursor from which the drug will be freed after administration offers several benefits such as: (i) a sustained drug release (mediated by chemical or enzymatic hydrolysis of the linkage between the drug-moiety and its promoiety); (ii) an increase of the drug chemical stability and solubility and, (iii) a reduced toxicity before the metabolization occurs. Lipids have been widely used as building blocks for the design of various prodrugs. Interestingly enough, these lipid-derivatized drugs can be delivered through a nanoparticulate form due to their ability to self-assemble and/or to be incorporated into lipid/polymer matrices. Among the several prodrugs developed so far, this review will focus on the main achievements in the field of lipid-based prodrug nanocarriers designed to improve the efficacy of anticancer drugs. Gemcitabine (Pubchem CID: 60750); 5-fluorouracil (Pubchem CID: 3385); Doxorubicin (Pubchem CID: 31703); Docetaxel (Pubchem CID: 148124); Methotrexate (Pubchem CID: 126941); Paclitaxel (Pubchem CID: 36314). Copyright © 2015 Elsevier B.V. All rights reserved.

Trainable structure-activity relationship model for virtual screening of CYP3A4 inhibition.

PubMed

Didziapetris, Remigijus; Dapkunas, Justas; Sazonovas, Andrius; Japertas, Pranas

2010-11-01

A new structure-activity relationship model predicting the probability for a compound to inhibit human cytochrome P450 3A4 has been developed using data for >800 compounds from various literature sources and tested on PubChem screening data. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling methodology has been used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain. For compounds within this domain the statistical results of the final model approach the data consistency between experimental data from literature and PubChem datasets with the overall accuracy of 89%. However, the original model is applicable only for less than a half of PubChem database. Since the similarity correction procedure of GALAS modeling method allows straightforward model training, the possibility to expand the applicability domain has been investigated. Experimental data from PubChem dataset served as an example of in-house high-throughput screening data. The model successfully adapted itself to both data classified using the same and different IC₅₀ threshold compared with the training set. In addition, adjustment of the CYP3A4 inhibition model to compounds with a novel chemical scaffold has been demonstrated. The reported GALAS model is proposed as a useful tool for virtual screening of compounds for possible drug-drug interactions even prior to the actual synthesis.

New Toxico-Cheminformatics & Computational Toxicology ...

EPA Pesticide Factsheets

EPA’s National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction. The DSSTox project is improving public access to quality structure-annotated chemical toxicity information in less summarized forms than traditionally employed in SAR modeling, and in ways that facilitate data-mining, and data read-across. The DSSTox Structure-Browser provides structure searchability across all published DSSTox toxicity-related inventory, and is enabling linkages between previously isolated toxicity data resources. As of early March 2008, the public DSSTox inventory has been integrated into PubChem, allowing a user to take full advantage of PubChem structure-activity and bioassay clustering features. The most recent DSSTox version of the Carcinogenic Potency Database file (CPDBAS) illustrates ways in which various summary definitions of carcinogenic activity can be employed in modeling and data mining. Phase I of the ToxCastTM project is generating high-throughput screening data from several hundred biochemical and cell-based assays for a set of 320 chemicals, mostly pesticide actives, with rich toxicology profiles. Incorporating and expanding traditional SAR concepts into this new high-throughput and data-rich world pose conceptual and practical challenges, but also holds great promise for improving predictive capabilities.

MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics.

PubMed

Jeffryes, James G; Colastani, Ricardo L; Elbadawi-Sidhu, Mona; Kind, Tobias; Niehaus, Thomas D; Broadbelt, Linda J; Hanson, Andrew D; Fiehn, Oliver; Tyo, Keith E J; Henry, Christopher S

2015-01-01

In spite of its great promise, metabolomics has proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography-mass spectrometry (LC-MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases. Here we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likely to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC-MS accurate mass data enabled the identity of an unknown peak to be confidently predicted. MINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. Furthermore, MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures. Graphical abstractMINE database construction and access methods. The process of constructing a MINE database from the curated source databases is depicted on the left. The methods for accessing the database are shown on the right.

EPA Project Updates: DSSTox and ToxCast Generating New ...

EPA Pesticide Factsheets

EPAs National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction. The DSSTox project is improving public access to quality structure-annotated chemical toxicity information in less summarized forms than traditionally employed in SAR modeling, and in ways that facilitate data-mining, and data read-across. The DSSTox Structure-Browser, launched in September 2007, provides structure searchability across all published DSSTox toxicity-related inventory, and is enabling linkages between previously isolated toxicity data resources. As of early March 2008, the public DSSTox inventory as been integrated into PubChem, allowing a user to take full advantage of PubChem structure-activity and bioassay clustering features. The most recent DSSTox version of Carcinogenic Potency Database file (CPDBAS) illustrates ways in which various summary definitions of carcinogenic activity can be employed in modeling and data mining. Phase I of the ToxCast project is generating high-throughput screening data from several hundred biochemical and cell-based assays for a set of 320 chemicals, mostly pesticide actives, with rich toxicology profiles. Incorporating and expanding traditional SAR Concepts into this new high-throughput and data-rich would pose conceptual and practical challenges, but also holds great promise for improving predictive capabilities. EPA's National Center for Computational Toxicology is bu

Quantitative assessment of the expanding complementarity between public and commercial databases of bioactive compounds.

PubMed

Southan, Christopher; Várkonyi, Péter; Muresan, Sorel

2009-07-06

Since 2004 public cheminformatic databases and their collective functionality for exploring relationships between compounds, protein sequences, literature and assay data have advanced dramatically. In parallel, commercial sources that extract and curate such relationships from journals and patents have also been expanding. This work updates a previous comparative study of databases chosen because of their bioactive content, availability of downloads and facility to select informative subsets. Where they could be calculated, extracted compounds-per-journal article were in the range of 12 to 19 but compound-per-protein counts increased with document numbers. Chemical structure filtration to facilitate standardised comparisons typically reduced source counts by between 5% and 30%. The pair-wise overlaps between 23 databases and subsets were determined, as well as changes between 2006 and 2008. While all compound sets have increased, PubChem has doubled to 14.2 million. The 2008 comparison matrix shows not only overlap but also unique content across all sources. Many of the detailed differences could be attributed to individual strategies for data selection and extraction. While there was a big increase in patent-derived structures entering PubChem since 2006, GVKBIO contains over 0.8 million unique structures from this source. Venn diagrams showed extensive overlap between compounds extracted by independent expert curation from journals by GVKBIO, WOMBAT (both commercial) and BindingDB (public) but each included unique content. In contrast, the approved drug collections from GVKBIO, MDDR (commercial) and DrugBank (public) showed surprisingly low overlap. Aggregating all commercial sources established that while 1 million compounds overlapped with PubChem 1.2 million did not. On the basis of chemical structure content per se public sources have covered an increasing proportion of commercial databases over the last two years. However, commercial products included in this study provide links between compounds and information from patents and journals at a larger scale than current public efforts. They also continue to capture a significant proportion of unique content. Our results thus demonstrate not only an encouraging overall expansion of data-supported bioactive chemical space but also that both commercial and public sources are complementary for its exploration.

CHEMICAL STRUCTURE INDEXING OF TOXICITY DATA ON ...

EPA Pesticide Factsheets

Standardized chemical structure annotation of public toxicity databases and information resources is playing an increasingly important role in the 'flattening' and integration of diverse sets of biological activity data on the Internet. This review discusses public initiatives that are accelerating the pace of this transformation, with particular reference to toxicology-related chemical information. Chemical content annotators, structure locator services, large structure/data aggregator web sites, structure browsers, International Union of Pure and Applied Chemistry (IUPAC) International Chemical Identifier (InChI) codes, toxicity data models and public chemical/biological activity profiling initiatives are all playing a role in overcoming barriers to the integration of toxicity data, and are bringing researchers closer to the reality of a mineable chemical Semantic Web. An example of this integration of data is provided by the collaboration among researchers involved with the Distributed Structure-Searchable Toxicity (DSSTox) project, the Carcinogenic Potency Project, projects at the National Cancer Institute and the PubChem database. Standardizing chemical structure annotation of public toxicity databases

Distributed chemical computing using ChemStar: an open source java remote method invocation architecture applied to large scale molecular data from PubChem.

PubMed

Karthikeyan, M; Krishnan, S; Pandey, Anil Kumar; Bender, Andreas; Tropsha, Alexander

2008-04-01

We present the application of a Java remote method invocation (RMI) based open source architecture to distributed chemical computing. This architecture was previously employed for distributed data harvesting of chemical information from the Internet via the Google application programming interface (API; ChemXtreme). Due to its open source character and its flexibility, the underlying server/client framework can be quickly adopted to virtually every computational task that can be parallelized. Here, we present the server/client communication framework as well as an application to distributed computing of chemical properties on a large scale (currently the size of PubChem; about 18 million compounds), using both the Marvin toolkit as well as the open source JOELib package. As an application, for this set of compounds, the agreement of log P and TPSA between the packages was compared. Outliers were found to be mostly non-druglike compounds and differences could usually be explained by differences in the underlying algorithms. ChemStar is the first open source distributed chemical computing environment built on Java RMI, which is also easily adaptable to user demands due to its "plug-in architecture". The complete source codes as well as calculated properties along with links to PubChem resources are available on the Internet via a graphical user interface at http://moltable.ncl.res.in/chemstar/.

Scrubchem: Building Bioactivity Datasets from Pubchem ...

EPA Pesticide Factsheets

The PubChem Bioassay database is a non-curated public repository with data from 64 sources, including: ChEMBL, BindingDb, DrugBank, EPA Tox21, NIH Molecular Libraries Screening Program, and various other academic, government, and industrial contributors. Methods for extracting this public data into quality datasets, useable for analytical research, presents several big-data challenges for which we have designed manageable solutions. According to our preliminary work, there are approximately 549 million bioactivity values and related meta-data within PubChem that can be mapped to over 10,000 biological targets. However, this data is not ready for use in data-driven research, mainly due to lack of structured annotations.We used a pragmatic approach that provides increasing access to bioactivity values in the PubChem Bioassay database. This included restructuring of individual PubChem Bioassay files into a relational database (ScrubChem). ScrubChem contains all primary PubChem Bioassay data that was: reparsed; error-corrected (when applicable); enriched with additional data links from other NCBI databases; and improved by adding key biological and assay annotations derived from logic-based language processing rules. The utility of ScrubChem and the curation process were illustrated using an example bioactivity dataset for the androgen receptor protein. This initial work serves as a trial ground for establishing the technical framework for accessing, integrating, cu

Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data.

PubMed

Kim, Marlene Thai; Huang, Ruili; Sedykh, Alexander; Wang, Wenyi; Xia, Menghang; Zhu, Hao

2016-05-01

Hepatotoxicity accounts for a substantial number of drugs being withdrawn from the market. Using traditional animal models to detect hepatotoxicity is expensive and time-consuming. Alternative in vitro methods, in particular cell-based high-throughput screening (HTS) studies, have provided the research community with a large amount of data from toxicity assays. Among the various assays used to screen potential toxicants is the antioxidant response element beta lactamase reporter gene assay (ARE-bla), which identifies chemicals that have the potential to induce oxidative stress and was used to test > 10,000 compounds from the Tox21 program. The ARE-bla computational model and HTS data from a big data source (PubChem) were used to profile environmental and pharmaceutical compounds with hepatotoxicity data. Quantitative structure-activity relationship (QSAR) models were developed based on ARE-bla data. The models predicted the potential oxidative stress response for known liver toxicants when no ARE-bla data were available. Liver toxicants were used as probe compounds to search PubChem Bioassay and generate a response profile, which contained thousands of bioassays (> 10 million data points). By ranking the in vitro-in vivo correlations (IVIVCs), the most relevant bioassay(s) related to hepatotoxicity were identified. The liver toxicants profile contained the ARE-bla and relevant PubChem assays. Potential toxicophores for well-known toxicants were created by identifying chemical features that existed only in compounds with high IVIVCs. Profiling chemical IVIVCs created an opportunity to fully explore the source-to-outcome continuum of modern experimental toxicology using cheminformatics approaches and big data sources. Kim MT, Huang R, Sedykh A, Wang W, Xia M, Zhu H. 2016. Mechanism profiling of hepatotoxicity caused by oxidative stress using antioxidant response element reporter gene assay models and big data. Environ Health Perspect 124:634-641; http://dx.doi.org/10.1289/ehp.1509763.

PubChem3D: conformer ensemble accuracy

PubMed Central

2013-01-01

Background PubChem is a free and publicly available resource containing substance descriptions and their associated biological activity information. PubChem3D is an extension to PubChem containing computationally-derived three-dimensional (3-D) structures of small molecules. All the tools and services that are a part of PubChem3D rely upon the quality of the 3-D conformer models. Construction of the conformer models currently available in PubChem3D involves a clustering stage to sample the conformational space spanned by the molecule. While this stage allows one to downsize the conformer models to more manageable size, it may result in a loss of the ability to reproduce experimentally determined “bioactive” conformations, for example, found for PDB ligands. This study examines the extent of this accuracy loss and considers its effect on the 3-D similarity analysis of molecules. Results The conformer models consisting of up to 100,000 conformers per compound were generated for 47,123 small molecules whose structures were experimentally determined, and the conformers in each conformer model were clustered to reduce the size of the conformer model to a maximum of 500 conformers per molecule. The accuracy of the conformer models before and after clustering was evaluated using five different measures: root-mean-square distance (RMSD), shape-optimized shape-Tanimoto (STST-opt) and combo-Tanimoto (ComboTST-opt), and color-optimized color-Tanimoto (CTCT-opt) and combo-Tanimoto (ComboTCT-opt). On average, the effect of clustering decreased the conformer model accuracy, increasing the conformer ensemble’s RMSD to the bioactive conformer (by 0.18 ± 0.12 Å), and decreasing the STST-opt, ComboTST-opt, CTCT-opt, and ComboTCT-opt scores (by 0.04 ± 0.03, 0.16 ± 0.09, 0.09 ± 0.05, and 0.15 ± 0.09, respectively). Conclusion This study shows the RMSD accuracy performance of the PubChem3D conformer models is operating as designed. In addition, the effect of PubChem3D sampling on 3-D similarity measures shows that there is a linear degradation of average accuracy with respect to molecular size and flexibility. Generally speaking, one can likely expect the worst-case minimum accuracy of 90% or more of the PubChem3D ensembles to be 0.75, 1.09, 0.43, and 1.13, in terms of STST-opt, ComboTST-opt, CTCT-opt, and ComboTCT-opt, respectively. This expected accuracy improves linearly as the molecule becomes smaller or less flexible. PMID:23289532

Biophenols: Enzymes (β-secretase, Cholinesterases, histone deacetylase and tyrosinase) inhibitors from olive (Olea europaea L.).

PubMed

Omar, Syed Haris; Scott, Christopher J; Hamlin, Adam S; Obied, Hassan K

2018-07-01

The focus of this study was on inhibition of enzymes involved in the pathogenesis Alzheimer's disease (AD) including prime amyloid beta (Aβ) producing enzyme (β-secretase: BACE-1) and disease progression enzymes including acetylcholinesterase (AChE), butyrylcholinesterase (BChE), histone deacetylase (HDAC), and tyrosinase along with the catecholamine L-DOPA, by using olive biophenols. Here we report the strongest inhibition of BACE-1 from rutin (IC 50 : 3.8 nM) followed by verbascoside (IC 50 : 6.3 nM) and olive fruit extract (IC 50 : 18 ng), respectively. Olive biophenol, quercetin exhibited strongest enzyme inhibitory activity against tyrosinase (IC 50 : 10.73 μM), BChE (IC 50 : 19.08 μM), AChE (IC 50 : 55.44 μM), and HDAC (IC 50 : 105.1 μM) enzymes. Furthermore, olive biophenol verbascoside (IC 50 : 188.6 μM), and hydroxytyrosol extreme extract (IC 50 : 66.22 μg) were showed the highest levels of inhibition against the HDAC enzyme. Neuroprotective capacity against levodopa-induced toxicity in neuroblastoma (SH-SY5Y) cells of olive biophenols were assessed, where rutin indicated the highest neuroprotection (74%), followed by caffeic acid (73%), and extract hydroxytyrosol extreme (97%), respectively. To the best of our knowledge, this is the first in vitro report on the enzymes inhibitory activity of olive biophenols. Taken together, our in vitro results data suggest that olive biophenols could be a promising natural inhibitor, which may reduce the enzyme-induced toxicity associated with the oxidative stress involved in the progression of AD. Acetylthiocholine iodide (PubChem CID: 74629); S-Butyrylthiocholine chloride (PubChem CID: 3015121); Caffeic acid (PubChem CID: 689043); Dimethyl sulfoxide (DMSO) (PubChem: 679); L-3,4-Dihydroxyphenylalanine (L-DOPA) (PubChem CID: 6047); 5,5'-Dithiobis (2-nitrobenzoic acid) (DTNB) (PubChem CID: 6254); Epigallocatechin gallate (EGCG) (PubChem CID: 65064); Ethylenediamine tetraacetic acid (EDTA) (PubChem CID: 6049); Galantamine hydrobromide (PubChem CID: 121587); l-Glutamine (PubChem CID: 5961); Hydroxytyrosol (PubChem CID: 82755); Kojic acid (PubChem CID: 3840); Luteolin (PubChem CID: 5280445); Oleuropein (PubChem CID: 5281544); Penicillin-streptomycin (PubChem CID: 131715954); Quercetin (PubChem CID: 5280343); Rutin (PubChem CID: 5280805); Tris-HCl buffer (PubChem: 93573); Trypan blue (PubChem: 9562061). Copyright © 2018 Elsevier B.V. All rights reserved.

Parallel Worlds of Public and Commercial Bioactive Chemistry Data

PubMed Central

2014-01-01

The availability of structures and linked bioactivity data in databases is powerfully enabling for drug discovery and chemical biology. However, we now review some confounding issues with the divergent expansions of public and commercial sources of chemical structures. These are associated with not only expanding patent extraction but also increasingly large vendor collections amassed via different selection criteria between SciFinder from Chemical Abstracts Service (CAS) and major public sources such as PubChem, ChemSpider, UniChem, and others. These increasingly massive collections may include both real and virtual compounds, as well as so-called prophetic compounds from patents. We address a range of issues raised by the challenges faced resolving the NIH probe compounds. In addition we highlight the confounding of prior-art searching by virtual compounds that could impact the composition of matter patentability of a new medicinal chemistry lead. Finally, we propose some potential solutions. PMID:25415348

B2-kinin receptors in the dorsal periaqueductal gray are implicated in the panicolytic-like effect of opiorphin.

PubMed

Sestile, Caio César; Maraschin, Jhonatan Christian; Rangel, Marcel Pereira; Santana, Rosangela Getirana; Zangrossi, Hélio; Graeff, Frederico Guilherme; Audi, Elisabeth Aparecida

2017-10-03

Reported results have shown that the pentapeptide opiorphin inhibits oligopeptidases that degrade brain neuropeptides, and has analgesic and antidepressant effects in experimental animals, without either tolerance or dependency after chronic administration. In a previous study we showed that opiorphin has a panicolytic-like effect in the dorsal periaqueductal gray (dPAG) electrical stimulation test (EST), mediated by the μ-opioid receptor (MOR). This study further analyzes the mechanism of opiorphin panicolytic action, using the EST and drug injection inside the dPAG. The obtained results showed that blockade of the 5-HT 1A receptors with WAY-100635 did not change the escape-impairing effect of opiorphin, and combined injection of sub-effective doses of opiorphin and the 5-HT 1A -agonist 8-OH-DPAT did not have a significant anti-escape effect. In contrast, the anti-escape effect of opiorphin was antagonized by pretreatment with the kinin B2 receptor blocker HOE-140, and association of sub-effective doses of opiorphin and bradykinin caused a significant anti-escape effect. The anti-escape effect of bradykinin was not affected by previous administration of WAY-100635. Therefore, the anti-escape effect of opiorphin in the dPAG seems to be mediated by endogenous bradykinin, acting on kinin B2 receptors, which previous results have shown to interact synergistically with MOR in the dPAG to restrain escape in two animal models of panic. Chemical compounds: Opiorphin (PubChem CID: 25195667); WAY100635 maleate salt (PubChem CID: 11957721); 8-OH-DPAT hydrobromide (PubChem CID: 6917794); Bradykinin (PubChem CID: 439201); HOE-140 (Icatibant) (PubChem CID: 6918173). Copyright © 2017 Elsevier Inc. All rights reserved.

Large-scale annotation of small-molecule libraries using public databases.

PubMed

Zhou, Yingyao; Zhou, Bin; Chen, Kaisheng; Yan, S Frank; King, Frederick J; Jiang, Shumei; Winzeler, Elizabeth A

2007-01-01

While many large publicly accessible databases provide excellent annotation for biological macromolecules, the same is not true for small chemical compounds. Commercial data sources also fail to encompass an annotation interface for large numbers of compounds and tend to be cost prohibitive to be widely available to biomedical researchers. Therefore, using annotation information for the selection of lead compounds from a modern day high-throughput screening (HTS) campaign presently occurs only under a very limited scale. The recent rapid expansion of the NIH PubChem database provides an opportunity to link existing biological databases with compound catalogs and provides relevant information that potentially could improve the information garnered from large-scale screening efforts. Using the 2.5 million compound collection at the Genomics Institute of the Novartis Research Foundation (GNF) as a model, we determined that approximately 4% of the library contained compounds with potential annotation in such databases as PubChem and the World Drug Index (WDI) as well as related databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and ChemIDplus. Furthermore, the exact structure match analysis showed 32% of GNF compounds can be linked to third party databases via PubChem. We also showed annotations such as MeSH (medical subject headings) terms can be applied to in-house HTS databases in identifying signature biological inhibition profiles of interest as well as expediting the assay validation process. The automated annotation of thousands of screening hits in batch is becoming feasible and has the potential to play an essential role in the hit-to-lead decision making process.

Predicting hepatotoxicity using ToxCast in vitro bioactivity and ...

EPA Pesticide Factsheets

Background: The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. We represented chemicals based on bioactivity and chemical structure descriptors then used supervised machine learning to predict their hepatotoxic effects.Results: A set of 677 chemicals were represented by 711 in vitro bioactivity descriptors (from ToxCast assays), 4,376 chemical structure descriptors (from QikProp, OpenBabel, PADEL, and PubChem), and three hepatotoxicity categories (from animal studies). Hepatotoxicants were defined by rat liver histopathology observed after chronic chemical testing and grouped into hypertrophy (161), injury (101) and proliferative lesions (99). Classifiers were built using six machine learning algorithms: linear discriminant analysis (LDA), Naïve Bayes (NB), support vector classification (SVM), classification and regression trees (CART), k-nearest neighbors (KNN) and an ensemble of classifiers (ENSMB). Classifiers of hepatotoxicity were built using chemical structure, ToxCast bioactivity, and a hybrid representation. Predictive performance was evaluated using 10-fold cross-validation testing and in-loop, filter-based, feature subset selection. Hybrid classifiers had the best balanced accuracy for predicting hypertrophy (0.78±0.08), injury (0.73±0.10) and proliferative lesions (0.72±0.09). Though chemical and bioactivity class

A Crowdsourcing Evaluation of the NIH Chemical Probes

PubMed Central

Oprea, Tudor I.; Bologa, Cristian G.; Boyer, Scott; Curpan, Ramona F.; Glen, Robert C.; Hopkins, Andrew L.; Lipinski, Christopher A.; Marshall, Garland R.; Martin, Yvonne C.; Ostopovici-Halip, Liliana; Rishton, Gilbert; Ursu, Oleg; Vaz, Roy J.; Waller, Chris; Waldmann, Herbert; Sklar, Larry A.

2013-01-01

Between 2004 and 2008, the NIH molecular libraries and imaging initiative (MLI) pilot phase funded ten high-throughput Screening Centers, resulting in the deposition of 691 assays into PubChem and the nomination of 64 chemical probes. We crowdsourced the MLI output to 11 experts, who expressed medium or high levels of confidence in 48 of these 64 probes. PMID:19536101

Recent Developments in Toxico-Cheminformatics: A New ...

EPA Pesticide Factsheets

Efforts to improve public access to chemical toxicity information resources, coupled with new high-throughput screening (HTS) data and efforts to systematize legacy toxicity studies, have the potential to significantly improve predictive capabilities in toxicology. Important recent developments include: 1) large and growing public resources that link chemical structures to biological activity and toxicity data in searchable format, and that offer more nuanced and varied representations of activity; 2) standardized relational data models that capture relevant details of chemical treatment and effects of published in vivo experiments; and 3) the generation of large amounts of new data from public efforts that are employing HTS technologies to probe a wide range of bioactivity and cellular processes across large swaths of chemical space. Most recently, EPA’s DSSTox project has published several new EPA chemical data inventories (IRIS, HPV, ToxCast) and added an on-line capability for structure (substructure or similarity)-searching through all or parts of the published DSSTox data files. These efforts are, for the first time in many cases, opening up a structure-paved two-way highway between previously inaccessible or isolated public chemical data repositories and large public resources, such as PubChem. In addition, public initiatives (such as ToxML) are developing systematized data models of toxicity study areas, and introducing standardized templates, contr

Toxico-Cheminformatics: New and Expanding Public ...

EPA Pesticide Factsheets

High-throughput screening (HTS) technologies, along with efforts to improve public access to chemical toxicity information resources and to systematize older toxicity studies, have the potential to significantly improve information gathering efforts for chemical assessments and predictive capabilities in toxicology. Important developments include: 1) large and growing public resources that link chemical structures to biological activity and toxicity data in searchable format, and that offer more nuanced and varied representations of activity; 2) standardized relational data models that capture relevant details of chemical treatment and effects of published in vivo experiments; and 3) the generation of large amounts of new data from public efforts that are employing HTS technologies to probe a wide range of bioactivity and cellular processes across large swaths of chemical space. By annotating toxicity data with associated chemical structure information, these efforts link data across diverse study domains (e.g., ‘omics’, HTS, traditional toxicity studies), toxicity domains (carcinogenicity, developmental toxicity, neurotoxicity, immunotoxicity, etc) and database sources (EPA, FDA, NCI, DSSTox, PubChem, GEO, ArrayExpress, etc.). Public initiatives are developing systematized data models of toxicity study areas and introducing standardized templates, controlled vocabularies, hierarchical organization, and powerful relational searching capability across capt

Dynamics of Chemical Degradation in Water Using Photocatalytic Reactions in an Ultraviolet Light Emitting Diode Reactor

DTIC Science & Technology

2017-09-14

one such study, AOPs were investigated for the removal of organophosphorus pesticides in wastewater by selecting and optimizing oxidation processes...micropollutants (primarily pharmaceuticals, personal care products, and pesticides ) in four 64 different river water sources (Colorado River, Passaic...the National Institutes of Health PubChem data repository (National Institutes of Health 2016). Additional chemical properties were also selected for

PubChem promiscuity: a web resource for gathering compound promiscuity data from PubChem.

PubMed

Canny, Stephanie A; Cruz, Yasel; Southern, Mark R; Griffin, Patrick R

2012-01-01

Promiscuity counts allow for a better understanding of a compound's assay activity profile and drug potential. Although PubChem contains a vast amount of compound and assay data, it currently does not have a convenient or efficient method to obtain in-depth promiscuity counts for compounds. PubChem promiscuity fills this gap. It is a Java servlet that uses NCBI Entrez (eUtils) web services to interact with PubChem and provide promiscuity counts in a variety of categories along with compound descriptors, including PAINS-based functional group detection. http://chemutils.florida.scripps.edu/pcpromiscuity southern@scripps.edu

PubChem promiscuity: a web resource for gathering compound promiscuity data from PubChem

PubMed Central

Canny, Stephanie A.; Cruz, Yasel; Southern, Mark R.; Griffin, Patrick R.

2012-01-01

Summary: Promiscuity counts allow for a better understanding of a compound's assay activity profile and drug potential. Although PubChem contains a vast amount of compound and assay data, it currently does not have a convenient or efficient method to obtain in-depth promiscuity counts for compounds. PubChem promiscuity fills this gap. It is a Java servlet that uses NCBI Entrez (eUtils) web services to interact with PubChem and provide promiscuity counts in a variety of categories along with compound descriptors, including PAINS-based functional group detection. Availability: http://chemutils.florida.scripps.edu/pcpromiscuity Contact: southern@scripps.edu PMID:22084255

Estimation of the size of drug-like chemical space based on GDB-17 data.

PubMed

Polishchuk, P G; Madzhidov, T I; Varnek, A

2013-08-01

The goal of this paper is to estimate the number of realistic drug-like molecules which could ever be synthesized. Unlike previous studies based on exhaustive enumeration of molecular graphs or on combinatorial enumeration preselected fragments, we used results of constrained graphs enumeration by Reymond to establish a correlation between the number of generated structures (M) and the number of heavy atoms (N): logM = 0.584 × N × logN + 0.356. The number of atoms limiting drug-like chemical space of molecules which follow Lipinsky's rules (N = 36) has been obtained from the analysis of the PubChem database. This results in M ≈ 10³³ which is in between the numbers estimated by Ertl (10²³) and by Bohacek (10⁶⁰).

Gas Chromatography-Tandem Mass Spectrometry of Lignin Pyrolyzates with Dopant-Assisted Atmospheric Pressure Chemical Ionization and Molecular Structure Search with CSI:FingerID

NASA Astrophysics Data System (ADS)

Larson, Evan A.; Hutchinson, Carolyn P.; Lee, Young Jin

2018-06-01

Dopant-assisted atmospheric pressure chemical ionization (dAPCI) is a soft ionization method rarely used for gas chromatography-mass spectrometry (GC-MS). The current study combines GC-dAPCI with tandem mass spectrometry (MS/MS) for analysis of a complex mixture such as lignin pyrolysis analysis. To identify the structures of volatile lignin pyrolysis products, collision-induced dissociation (CID) MS/MS using a quadrupole time-of-flight mass spectrometer (QTOFMS) and pseudo MS/MS through in-source collision-induced dissociation (ISCID) using a single stage TOFMS are utilized. To overcome the lack of MS/MS database, Compound Structure Identification (CSI):FingerID is used to interpret CID spectra and predict best matched structures from PubChem library. With this approach, a total of 59 compounds were positively identified in comparison to only 22 in NIST database search of GC-EI-MS dataset. This study demonstrates the effectiveness of GC-dAPCI-MS/MS to overcome the limitations of traditional GC-EI-MS analysis when EI-MS database is not sufficient. [Figure not available: see fulltext.

Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening

NASA Astrophysics Data System (ADS)

Hsieh, Jui-Hua; Wang, Xiang S.; Teotico, Denise; Golbraikh, Alexander; Tropsha, Alexander

2008-09-01

The use of inaccurate scoring functions in docking algorithms may result in the selection of compounds with high predicted binding affinity that nevertheless are known experimentally not to bind to the target receptor. Such falsely predicted binders have been termed `binding decoys'. We posed a question as to whether true binders and decoys could be distinguished based only on their structural chemical descriptors using approaches commonly used in ligand based drug design. We have applied the k-Nearest Neighbor ( kNN) classification QSAR approach to a dataset of compounds characterized as binders or binding decoys of AmpC beta-lactamase. Models were subjected to rigorous internal and external validation as part of our standard workflow and a special QSAR modeling scheme was employed that took into account the imbalanced ratio of inhibitors to non-binders (1:4) in this dataset. 342 predictive models were obtained with correct classification rate (CCR) for both training and test sets as high as 0.90 or higher. The prediction accuracy was as high as 100% (CCR = 1.00) for the external validation set composed of 10 compounds (5 true binders and 5 decoys) selected randomly from the original dataset. For an additional external set of 50 known non-binders, we have achieved the CCR of 0.87 using very conservative model applicability domain threshold. The validated binary kNN QSAR models were further employed for mining the NCGC AmpC screening dataset (69653 compounds). The consensus prediction of 64 compounds identified as screening hits in the AmpC PubChem assay disagreed with their annotation in PubChem but was in agreement with the results of secondary assays. At the same time, 15 compounds were identified as potential binders contrary to their annotation in PubChem. Five of them were tested experimentally and showed inhibitory activities in millimolar range with the highest binding constant Ki of 135 μM. Our studies suggest that validated QSAR models could complement structure based docking and scoring approaches in identifying promising hits by virtual screening of molecular libraries.

Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data

PubMed Central

Kim, Marlene Thai; Huang, Ruili; Sedykh, Alexander; Wang, Wenyi; Xia, Menghang; Zhu, Hao

2015-01-01

Background: Hepatotoxicity accounts for a substantial number of drugs being withdrawn from the market. Using traditional animal models to detect hepatotoxicity is expensive and time-consuming. Alternative in vitro methods, in particular cell-based high-throughput screening (HTS) studies, have provided the research community with a large amount of data from toxicity assays. Among the various assays used to screen potential toxicants is the antioxidant response element beta lactamase reporter gene assay (ARE-bla), which identifies chemicals that have the potential to induce oxidative stress and was used to test > 10,000 compounds from the Tox21 program. Objective: The ARE-bla computational model and HTS data from a big data source (PubChem) were used to profile environmental and pharmaceutical compounds with hepatotoxicity data. Methods: Quantitative structure–activity relationship (QSAR) models were developed based on ARE-bla data. The models predicted the potential oxidative stress response for known liver toxicants when no ARE-bla data were available. Liver toxicants were used as probe compounds to search PubChem Bioassay and generate a response profile, which contained thousands of bioassays (> 10 million data points). By ranking the in vitro–in vivo correlations (IVIVCs), the most relevant bioassay(s) related to hepatotoxicity were identified. Results: The liver toxicants profile contained the ARE-bla and relevant PubChem assays. Potential toxicophores for well-known toxicants were created by identifying chemical features that existed only in compounds with high IVIVCs. Conclusion: Profiling chemical IVIVCs created an opportunity to fully explore the source-to-outcome continuum of modern experimental toxicology using cheminformatics approaches and big data sources. Citation: Kim MT, Huang R, Sedykh A, Wang W, Xia M, Zhu H. 2016. Mechanism profiling of hepatotoxicity caused by oxidative stress using antioxidant response element reporter gene assay models and big data. Environ Health Perspect 124:634–641; http://dx.doi.org/10.1289/ehp.1509763 PMID:26383846

Ultrasound improves chemical reduction of natural contaminant microbiota and Salmonella enterica subsp. enterica on strawberries.

PubMed

do Rosário, Denes Kaic Alves; da Silva Mutz, Yhan; Peixoto, Jaqueline Moreira Curtis; Oliveira, Syllas Borburema Silva; de Carvalho, Raquel Vieira; Carneiro, Joel Camilo Souza; de São José, Jackline Freitas Brilhante; Bernardes, Patrícia Campos

2017-01-16

New sanitization methods have been evaluated to improve food safety and food quality and to replace chlorine compounds. However, these new methods can lead to physicochemical and sensory changes in fruits and vegetables. The present study evaluated the effects of acetic acid, peracetic acid, and sodium dodecylbenzenesulfonate isolated or combined with 5min of ultrasound treatment (40kHz, 500W) on strawberry quality over 9days of storage at 8°C. The strawberry natural contaminant microbiota (molds and yeasts, mesophilic aerobic and lactic acid bacteria), physicochemical quality (pH, total titratable acidity, total soluble solids, vitamin C, and color), sensory quality (triangle test) and inactivation of Salmonella enterica subsp. enterica intentionally inoculated onto strawberries were analyzed. Ultrasound increased the effect of all chemical compounds in the reduction of aerobic mesophilic, molds and yeasts. The best treatment for those groups of microorganisms was ultrasound combined with peracetic acid (US+PA) that reduced 1.8 and 2.0logcfu/g during 9days of storage. Bactericidal effect of peracetic acid was also improved by ultrasound inactivation of S. enterica, reaching a decimal reduction of 2.1logcfu/g. Moreover, synergistic effects were observed in contaminant natural microbiota inactivation for all tested compounds during storage, without any major physicochemical or sensory alteration to the strawberries. Therefore, ultrasound treatment can improve the effect of sanitizers that are substitutes of chlorine compounds without altering the quality of strawberries during storage. Acetic acid (PubChem CID: 176); Peracetic acid (PubChem CID: 6585); Sodium dodecylbenzenesulfonate (PubChem CID: 18372154). Copyright © 2016 Elsevier B.V. All rights reserved.

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

Artichoke (Cynara cardunculus L. var. scolymus) waste as a natural source of carbonyl trapping and antiglycative agents.

PubMed

Maietta, Mariarosa; Colombo, Raffaella; Lavecchia, Roberto; Sorrenti, Milena; Zuorro, Antonio; Papetti, Adele

2017-10-01

The role of polyphenolic compounds extractable from artichoke solid wastes in the formation of advanced glycation end products (AGEs) was studied. Outer bracts and stems were extracted using different water-ethanol mixtures and HPLC-DAD analyses indicated aqueous and hydro-alcoholic 20:80 stem extracts as the richest in polyphenols. The samples were characterized in their phenolic composition (using mass spectrometry) and antioxidant capacity. Antiglycative capacity was evaluated by in vitro BSA-sugars (glucose, fructose, and ribose) and BSA-methylglyoxal (MGO) tests, formation of Amadori products assay, direct glyoxal (GO) and MGO trapping capacity. Results indicated both extracts as effective inhibitors of fructosamine formation and antiglycative agents. In particular, aqueous extract showed the best activity in the systems containing glucose and fructose, differently from ethanolic extract, that was demonstrated able to better inhibit AGEs formation when ribose or MGO act as precursors. Ethanolic extract was also shown to be able to trap MGO and GO, with efficiency increasing after 24hours of incubation time. These activities are partially correlated with the antioxidant effect of the extract, as demonstrated by the scavenger capacity against ABTS cation and DPPH stable radicals; this relationship is evident when the model system, containing protein incubated with ribose or MGO, is considered. The different activities of the tested extracts could probably be ascribed to the different composition in chlorogenic acids (CQAs), being aqueous extract richer in 1-CQA, 3-CQA, and 1,3-di-CQA, and ethanolic extract in 5-CQA, caffeic acid, 1,5-di-CQA. These findings support further investigations to study the stability of the different CQAs in simil-physiological conditions and the feasibility of artichoke waste as antiglycative agents in food or pharmacological preparations. 5-caffeoylquinic acid (PubChem CID 5280633); 3-caffeoylquinic acid (PubChem CID 1794427); 1-caffeoylquinic acid (PubChem CID 10155076); 1,3-di-caffeoylquinic acid (PubChem CID 24720973); 1,5 - di-caffeoylquinic acid (PubChem CID 122685); caffeic acid (PubChem CID 689043); apigenin-7-glucuronide (PubChem CID 5319484); methylglyoxal PubChem CID (880); aminoguanidine hydrochloride (PubChem CID 2734687). Copyright © 2017 Elsevier Ltd. All rights reserved.

Rational design of protamine nanocapsules as antigen delivery carriers.

PubMed

González-Aramundiz, José Vicente; Presas, Elena; Dalmau-Mena, Inmaculada; Martínez-Pulgarín, Susana; Alonso, Covadonga; Escribano, José M; Alonso, María J; Csaba, Noemi Stefánia

2017-01-10

Current challenges in global immunization indicate the demand for new delivery strategies, which could be applied to the development of new vaccines against emerging diseases, as well as to improve safety and efficacy of currently existing vaccine formulations. Here, we report a novel antigen nanocarrier consisting of an oily core and a protamine shell, further stabilized with pegylated surfactants. These nanocarriers, named protamine nanocapsules, were rationally designed to promote the intracellular delivery of antigens to immunocompetent cells and to trigger an efficient and long-lasting immune response. Protamine nanocapsules have nanometric size, positive zeta potential and high association capacity for H1N1 influenza hemagglutinin, a protein that was used here as a model antigen. The new formulation shows an attractive stability profile both, as an aqueous suspension or a freeze-dried powder formulation. In vitro studies showed that protamine nanocapsules were efficiently internalized by macrophages without eliciting significant toxicity. In vivo studies indicate that antigen-loaded nanocapsules trigger immune responses comparable to those achieved with alum, even when using significantly lower antigen doses, thus indicating their adjuvant properties. These promising in vivo data, alongside with their versatility for the loading of different antigens and oily immunomodulators and their excellent stability profile, make these nanocapsules a promising platform for the delivery of antigens. Protamine sulphate (PubChem SID: 7849283), Sodium Cholate (PubChem CID: 23668194), Miglyol (PubChem CID: 53471835), α tocopherol (PubChem CID: 14985), Tween® 20(PubChem CID: 443314), Tween® 80(PubChem CID: 5281955), TPGS (PubChem CID: 71406). Copyright © 2016 Elsevier B.V. All rights reserved.

Treatment with sodium nitroprusside improves the endothelial function in aortic rings with endothelial dysfunction.

PubMed

Buzinari, Tereza Cristina; Oishi, Jorge Camargo; De Moraes, Thiago Francisco; Vatanabe, Izabela Pereira; Selistre-de-Araújo, Heloisa Sobreiro; Pestana, Cezar Rangel; Rodrigues, Gerson Jhonatan

2017-07-15

Verify if sodium nitroprusside (SNP) is able to improve endothelial function and if this effect is independent of nitric oxide (NO) release of the compound. Normotensive (2K) and hypertensive (2K-1C) wistar rats were used. Intact endothelium aortas were placed in a myograph and incubated with SNP: 0.1nM; 1nM or 10nM during 30min. Cumulative concentration-effect curves for acetylcholine (Ach) were realized to measure the relaxing capacity. Intracellular NO were measured (by DAF-2DA probe) in HUVEC treated with SNP 0.1nM or DETA/NO 0.1μM. The detection of intracellular superoxide radical (O 2 •- ) was obtained by using DHE probe. Treatment of 2K-1C aortic rings with SNP (0.1; 1.0 and 10nM) improved endothelium dependent relaxation induced by acetylcholine. This improvement induced by SNP was verified at the concentration of 0.1nM, which does not release NO, suggesting that this effect was not induced due to NO release by SNP compound. Besides, we show that the cell treatment with 0.1nM of SNP decreased the fluorescence intensity to DHE in cells stimulated with angiotensin II. These results indicate that SNP decreases the concentration of O 2 •- in HUVEC cells. The SNP at a concentration that does not release NO inside the cells is able to attenuate endothelial dysfunction. Acetylcholine (Ach) (PubChem CID:6060); angiotensin II human (Ang II) (PubChem CID: 16211177); diethylenetriamine/nitric oxide (DETA-NO) (PubChem CID 4518); dihydroethidium (DHE) (PubChem CID: 128682); phenylephrine (Phe) (PubChem CID: 5284443); sodium nitroprusside (SNP) (PubChem CID: 11963579); Thiazolyl Blue Tetrazolium Bromide (MTT) (PubChem CID: 64965); 4,5-diaminofluorescein diacetate (DAF-2DA); 4-hidroxy-Tempo (Tempol) (PubChem CID: 137994), were purchased from Sigma-Aldrich (St. Louis, MO, USA). Copyright © 2017 Elsevier B.V. All rights reserved.

Benchmarking Ligand-Based Virtual High-Throughput Screening with the PubChem Database

PubMed Central

Butkiewicz, Mariusz; Lowe, Edward W.; Mueller, Ralf; Mendenhall, Jeffrey L.; Teixeira, Pedro L.; Weaver, C. David; Meiler, Jens

2013-01-01

With the rapidly increasing availability of High-Throughput Screening (HTS) data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD) have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR) models are built using Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Decision Trees (DTs), and Kohonen networks (KNs). Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS) and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed. PMID:23299552

A Systematic Evaluation of Analogs for the Read-across ...

EPA Pesticide Factsheets

Read-across is a data gap filling technique widely used within category and analog approaches to predict a biological property for a target data-poor chemical using known information from similar (source analog) chemical(s). Potential source analogs are typically identified based on structural similarity. Although much guidance has been published for read-across, practical guiding principles for the identification and evaluation of the scientific validity of source analogs, which is a critical step in deriving a robust read-across prediction, remains largely lacking.This case study explores the extent to which 3 structure descriptor sets (Pubchem, Chemotyper and MoSS) and their combinations are able to identify valid analogs for reading across Estrogen Receptor (ER) activity for a specific class of chemicals: hindered phenols. For each target chemical, two sets of analogs (hindered and non-hindered phenols) were selected using each descriptor set with two cut-offs: (1). Minimum Tanimoto similarity (range 0.1 - 0.9), and (2). Closest N analogs (range 1 - 10). Each target-analog pair was then evaluated for its agreement with measured ER binding and agonism. Subsequently, the analogs were filtered using physchem properties (LogKow & Molecular Volume) and the resultant agreement between each target-analog pair was evaluated. The data set comprised 462 hindered phenols and 296 non-hindered phenols. The results demonstrate that: (1). The concordance in ER activity r

A Systematic Evaluation of Analogs and Automated Read ...

EPA Pesticide Factsheets

Read-across is a data gap filling technique widely used within category and analog approaches to predict a biological property for a data-poor (target) chemical using known information from similar (source analog) chemical(s). Potential source analogs are typically identified based on structural similarity. Although much guidance has been published for read-across, practical principles for the identification and evaluation of the scientific validity of source analogs remains lacking. This case study explores how well 3 structure descriptor sets (Pubchem, Chemotyper and MoSS) are able to identify analogs for read-across and predict Estrogen Receptor (ER) binding activity for a specific class of chemicals: hindered phenols. For each target chemical, analogs were selected using each descriptor set with two cut-offs: (1) Minimum Tanimoto similarity (range 0.1 - 0.9), and (2) Closest N analogs (range 1 - 10). Each target-analog pair was then evaluated for its agreement with measured ER binding and agonism. The analogs were subsequently filtered using: (1) physchem properties (LogKow & Molecular Volume), and (2) number of literature sources as a marker for the quality of the experimental data. A majority vote prediction was made for each target phenol by reading-across from the closest N analogs. The data set comprised 462 hindered phenols and 257 non-hindered phenols. The results demonstrate that: (1) The concordance in ER activity rises with increasing similarity,

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.

Ranking the selectivity of PubChem screening hits by activity-based protein profiling: MMP13 as a case study.

PubMed

Nakai, Ryuichiro; Salisbury, Cleo M; Rosen, Hugh; Cravatt, Benjamin F

2009-02-01

High-throughput screening (HTS) has become an integral part of academic and industrial efforts aimed at developing new chemical probes and drugs. These screens typically generate several 'hits', or lead active compounds, that must be prioritized for follow-up medicinal chemistry studies. Among primary considerations for ranking lead compounds is selectivity for the intended target, especially among mechanistically related proteins. Here, we show how the chemical proteomic technology activity-based protein profiling (ABPP) can serve as a universal assay to rank HTS hits based on their selectivity across many members of an enzyme superfamily. As a case study, four metalloproteinase-13 (MMP13) inhibitors of similar potency originating from a publically supported HTS and reported in PubChem were tested by ABPP for selectivity against a panel of 27 diverse metalloproteases. The inhibitors could be readily separated into two groups: (1) those that were active against several metalloproteases and (2) those that showed high selectivity for MMP13. The latter set of inhibitors was thereby designated as more suitable for future medicinal chemistry optimization. We anticipate that ABPP will find general utility as a platform to rank the selectivity of lead compounds emerging from HTS assays for a wide variety of enzymes.

A Virtual Screening Approach for the Identification of High Affinity Small Molecules Targeting BCR-ABL1 Inhibitors for the Treatment of Chronic Myeloid Leukemia.

PubMed

Sharda, Saphy; Sarmandal, Palash; Cherukommu, Shirisha; Dindhoria, Kiran; Yadav, Manisha; Bandaru, Srinivas; Sharma, Anudeep; Sakhi, Aditi; Vyas, Tanmay; Hussain, Tajamul; Nayarisseri, Anuraj; Singh, Sanjeev Kumar

2017-01-01

CML originates due to reciprocal translocation in Philadelphia chromosome leading to the formation of fusion product BCR-ABL which constitutively activates tyrosine kinase signaling pathways eventually leading to abnormal proliferation of granulocytic cells. As a therapeutic strategy, BCR-ABL inhibitors have been clinically approved which terminates its phosphorylation activity and retards cancer progression. However, a number of patients develop resistance to inhibitors which demand for the discovery of new inhibitors. Given the drawbacks of present inhibitors, by high throughput virtual screening approaches, present study pursues to identify high affinity compounds targeting BCR-ABL1 anticipated to have safer pharmacological profiles. Five established BCR-ABL inhibitors formed the query compounds for identification of structurally similar compounds by Tanimoto coefficient based linear fingerprint search with a threshold of 95% against PubChemdatabase. Assisted by MolDock algorithm all compounds were docked against BCR-ABL protein in order to retrieve high affinity compounds. The parents and similars were further tested for their ADMET propertiesand bioactivity. Rebastinib formed higher affinity inhibitor than rest of the four established compound investigated in the study. Interestingly, Rebastinib similar compound with Pubchem ID: 67254402 was also shown to have highest affinity than other similars including the similars of respective five parents. In terms of ADMET properties Pubchem ID: 67254402 had appreciable ADMET profile and bioactivity. However, Rebastinib still stood as the best inhibitor in terms of binding affinity and ADMET properties than Pubchem ID: 67254402. Nevertheless, owing to the similar pharmacological properties with Rebastinib, Pubchem ID: 67254402 can be expected to form potential BCR-ABL inhibitor. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A semantic web ontology for small molecules and their biological targets.

PubMed

Choi, Jooyoung; Davis, Melissa J; Newman, Andrew F; Ragan, Mark A

2010-05-24

A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.

A search map for organic additives and solvents applicable in high-voltage rechargeable batteries.

PubMed

Park, Min Sik; Park, Insun; Kang, Yoon-Sok; Im, Dongmin; Doo, Seok-Gwang

2016-09-29

Chemical databases store information such as molecular formulas, chemical structures, and the physical and chemical properties of compounds. Although the massive databases of organic compounds exist, the search of target materials is constrained by a lack of physical and chemical properties necessary for specific applications. With increasing interest in the development of energy storage systems such as high-voltage rechargeable batteries, it is critical to find new electrolytes efficiently. Here we build a search map to screen organic additives and solvents with novel core and functional groups, and thus establish a database of electrolytes to identify the most promising electrolyte for high-voltage rechargeable batteries. This search map is generated from MAssive Molecular Map BUilder (MAMMBU) by combining a high-throughput quantum chemical simulation with an artificial neural network algorithm. MAMMBU is designed for predicting the oxidation and reduction potentials of organic compounds existing in the massive organic compound database, PubChem. We develop a search map composed of ∼1 000 000 redox potentials and elucidate the quantitative relationship between the redox potentials and functional groups. Finally, we screen a quinoxaline compound for an anode additive and apply it to electrolytes and improve the capacity retention from 64.3% to 80.8% near 200 cycles for a lithium ion battery in experiments.

Scrubchem: Building Bioactivity Datasets from Pubchem Bioassay Data (SOT)

EPA Science Inventory

The PubChem Bioassay database is a non-curated public repository with data from 64 sources, including: ChEMBL, BindingDb, DrugBank, EPA Tox21, NIH Molecular Libraries Screening Program, and various other academic, government, and industrial contributors. Methods for extracting th...

Prognosis and survival analysis of paraquat poisoned patients based on improved HPLC-UV method.

PubMed

Hong, Guangliang; Hu, Lufeng; Tang, Yahui; Zhang, Tao; Kang, Xiaowen; Zhao, Guangju; Lu, Zhongqiu

2016-01-01

Paraquat (PQ) has caused deaths of numerous people around the world. In order to assess the lethal plasma concentration, the patients who acquired acute PQ intoxication were analyzed by plasma concentration monitoring. The plasma PQ concentrations were determined by high performance liquid chromatography (HPLC) which used 5-bromopyrimidine as internal standard and trichloroacetic acid-methanol (1:9) as protein precipitant. The liver, kidney and coagulation function were determined by automatic biochemical analyzer. According to plasma PQ concentration, 90 patients were divided into four groups: trace PQ group (<50ng/mL), low PQ group (<1000ng/mL), medium PQ group (1000-5000ng/mL) and high PQ group (>5000ng/mL). The clinical data from the four groups was statistically analyzed. The results showed the developed HPLC methods exhibited a high degree of accuracy and good linearity within 50-25000ng/mL (R=0.9998). The Spearman's correlation analysis showed PQ concentration had a strong relationship to total bilirubin, direct bilirubin, aspartic transaminase, urea nitrogen, prothrombin time, prothrombin activity, and international normalized ratio (P<0.01). The cured or survival PQ poisoned patients among the trace PQ group, the low PQ group, the medium PQ group, and the high PQ group were 19/19 (100%), 19/21 (90.47%), 11/25 (44.0%), and 0/25 (0%) respectively. The mean hospital days were (10.37±8.04), (18.76±12.06), (16.76±14.44), and (4.04±5.41) days respectively. The Cox regression analysis indicated that plasma PQ concentration was highly related to prognosis (P<0.05). In conclusion, no patient presenting with a PQ concentration over 5000ng/mL survived. The plasma PQ level is related to liver, kidney and coagulation function, which can be used as an important clinical index to judge the prognosis of PQ poisoned patients. Paraquat (PubChem CID: 15938), 5-bromopyrimidine (PubChem CID: 78344), acetonitrile (PubChem CID: 6342), sodium dihydrogen phosphate (PubChem CID: 23672064), sodium heptanesulfonate (PubChem CID: 23672332), methylprednisolone (PubChem CID: 6741), cyclophosphamide (PubChem CID: 2907). Copyright © 2016. Published by Elsevier Inc.

Automatic Compound Annotation from Mass Spectrometry Data Using MAGMa

PubMed Central

Ridder, Lars; van der Hooft, Justin J. J.; Verhoeven, Stefan

2014-01-01

The MAGMa software for automatic annotation of mass spectrometry based fragmentation data was applied to 16 MS/MS datasets of the CASMI 2013 contest. Eight solutions were submitted in category 1 (molecular formula assignments) and twelve in category 2 (molecular structure assignment). The MS/MS peaks of each challenge were matched with in silico generated substructures of candidate molecules from PubChem, resulting in penalty scores that were used for candidate ranking. In 6 of the 12 submitted solutions in category 2, the correct chemical structure obtained the best score, whereas 3 molecules were ranked outside the top 5. All top ranked molecular formulas submitted in category 1 were correct. In addition, we present MAGMa results generated retrospectively for the remaining challenges. Successful application of the MAGMa algorithm required inclusion of the relevant candidate molecules, application of the appropriate mass tolerance and a sufficient degree of in silico fragmentation of the candidate molecules. Furthermore, the effect of the exhaustiveness of the candidate lists and limitations of substructure based scoring are discussed. PMID:26819876

Automatic Compound Annotation from Mass Spectrometry Data Using MAGMa.

PubMed

Ridder, Lars; van der Hooft, Justin J J; Verhoeven, Stefan

2014-01-01

The MAGMa software for automatic annotation of mass spectrometry based fragmentation data was applied to 16 MS/MS datasets of the CASMI 2013 contest. Eight solutions were submitted in category 1 (molecular formula assignments) and twelve in category 2 (molecular structure assignment). The MS/MS peaks of each challenge were matched with in silico generated substructures of candidate molecules from PubChem, resulting in penalty scores that were used for candidate ranking. In 6 of the 12 submitted solutions in category 2, the correct chemical structure obtained the best score, whereas 3 molecules were ranked outside the top 5. All top ranked molecular formulas submitted in category 1 were correct. In addition, we present MAGMa results generated retrospectively for the remaining challenges. Successful application of the MAGMa algorithm required inclusion of the relevant candidate molecules, application of the appropriate mass tolerance and a sufficient degree of in silico fragmentation of the candidate molecules. Furthermore, the effect of the exhaustiveness of the candidate lists and limitations of substructure based scoring are discussed.

Communication and re-use of chemical information in bioscience

PubMed Central

Murray-Rust, Peter; Mitchell, John BO; Rzepa, Henry S

2005-01-01

The current methods of publishing chemical information in bioscience articles are analysed. Using 3 papers as use-cases, it is shown that conventional methods using human procedures, including cut-and-paste are time-consuming and introduce errors. The meaning of chemical terms and the identity of compounds is often ambiguous. valuable experimental data such as spectra and computational results are almost always omitted. We describe an Open XML architecture at proof-of-concept which addresses these concerns. Compounds are identified through explicit connection tables or links to persistent Open resources such as PubChem. It is argued that if publishers adopt these tools and protocols, then the quality and quantity of chemical information available to bioscientists will increase and the authors, publishers and readers will find the process cost-effective. PMID:16026614

Use of in Vitro HTS-Derived Concentration-Response Data as ...

EPA Pesticide Factsheets

Background: Quantitative high-throughput screening (qHTS) assays are increasingly being employed to inform chemical hazard identification. Hundreds of chemicals have been tested in dozens of cell lines across extensive concentration ranges by the National Toxicology Program in collaboration with the NIH Chemical Genomics Center. Objectives: To test a hypothesis that dose-response data points of the qHTS assays can serve as biological descriptors of assayed chemicals and, when combined with conventional chemical descriptors, may improve the accuracy of Quantitative Structure-Activity Relationship (QSAR) models applied to prediction of in vivo toxicity endpoints. Methods and Results: The cell viability qHTS concentration-response data for 1,408 substances assayed in 13 cell lines were obtained from PubChem; for a subset of these compounds rodent acute toxicity LD50 data were also available. The classification k Nearest Neighbor and Random Forest QSAR methods were employed for modeling LD50 data using either chemical descriptors alone (conventional models) or in combination with biological descriptors derived from the concentration-response qHTS data (hybrid models). Critical to our approach was the use of a novel noise-filtering algorithm to treat qHTS data. We show that both the external classification accuracy and coverage (i.e., fraction of compounds in the external set that fall within the applicability domain) of the hybrid QSAR models was superior to convent

Mapping of the Available Chemical Space versus the Chemical Universe of Lead-Like Compounds.

PubMed

Lin, Arkadii; Horvath, Dragos; Afonina, Valentina; Marcou, Gilles; Reymond, Jean-Louis; Varnek, Alexandre

2018-03-20

This is, to our knowledge, the most comprehensive analysis to date based on generative topographic mapping (GTM) of fragment-like chemical space (40 million molecules with no more than 17 heavy atoms, both from the theoretically enumerated GDB-17 and real-world PubChem/ChEMBL databases). The challenge was to prove that a robust map of fragment-like chemical space can actually be built, in spite of a limited (≪10 5 ) maximal number of compounds ("frame set") usable for fitting the GTM manifold. An evolutionary map building strategy has been updated with a "coverage check" step, which discards manifolds failing to accommodate compounds outside the frame set. The evolved map has a good propensity to separate actives from inactives for more than 20 external structure-activity sets. It was proven to properly accommodate the entire collection of 40 m compounds. Next, it served as a library comparison tool to highlight biases of real-world molecules (PubChem and ChEMBL) versus the universe of all possible species represented by FDB-17, a fragment-like subset of GDB-17 containing 10 million molecules. Specific patterns, proper to some libraries and absent from others (diversity holes), were highlighted. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Carcinogenicity and Mutagenicity Data: New Initiatives to ...

EPA Pesticide Factsheets

Currents models for prediction of chemical carcinogenicity and mutagenicity rely upon a relatively small number of publicly available data resources, where the data being modeled are highly summarized and aggregated representations of the actual experimental results. A number of new initiatives are underway to improve access to existing public carcinogenicity and mutagenicity data for use in modeling, as well as to encourage new approaches to the use of data in modeling. Rodent bioassay results from the NIEHS National Toxicology Program (NTP) and the Berkeley Carcinogenic Potency Database (CPDB) have provided the largest public data resources for building carcinogenicity prediction models to date. However, relatively few and limited representations of these data have actually informed existing models. Initiatives, such as EPA's DSSTox Database Network, offer elaborated and quality reviewed presentations of the CPDB and expanded data linkages and coverage of chemical space for carcinogenicity and mutagenicity. In particular the latest published DSSTox CPDBAS structure-data file includes a number of species-specific and summary activity fields, including a species-specific normalized score for carcinogenic potency (TD50) and various weighted summary activities. These data are being incorporated into PubChem to provide broad

In silico design and screening of hypothetical MOF-74 analogs and their experimental synthesis

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

Witman, Matthew; Ling, Sanliang; Anderson, Samantha

Here, we present the in silico design of metal-organic frameworks (MOFs) exhibiting 1-dimensional rod topologies. We then introduce an algorithm for construction of this family of MOF topologies, and illustrate its application for enumerating MOF-74-type analogs. Furthermore, we perform a broad search for new linkers that satisfy the topological requirements of MOF-74 and consider the largest database of known chemical space for organic compounds, the PubChem database. Our in silico crystal assembly, when combined with dispersion-corrected density functional theory (DFT) calculations, is demonstrated to generate a hypothetical library of open-metal site containing MOF-74 analogs in the 1-D rod topology frommore » which we can simulate the adsorption behavior of CO 2 . We conclude that these hypothetical structures have synthesizable potential through computational identification and experimental validation of a novel MOF-74 analog, Mg 2 (olsalazine).« less

In silico design and screening of hypothetical MOF-74 analogs and their experimental synthesis

DOE PAGES

Witman, Matthew; Ling, Sanliang; Anderson, Samantha; ...

2016-06-21

Here, we present the in silico design of metal-organic frameworks (MOFs) exhibiting 1-dimensional rod topologies. We then introduce an algorithm for construction of this family of MOF topologies, and illustrate its application for enumerating MOF-74-type analogs. Furthermore, we perform a broad search for new linkers that satisfy the topological requirements of MOF-74 and consider the largest database of known chemical space for organic compounds, the PubChem database. Our in silico crystal assembly, when combined with dispersion-corrected density functional theory (DFT) calculations, is demonstrated to generate a hypothetical library of open-metal site containing MOF-74 analogs in the 1-D rod topology frommore » which we can simulate the adsorption behavior of CO 2 . We conclude that these hypothetical structures have synthesizable potential through computational identification and experimental validation of a novel MOF-74 analog, Mg 2 (olsalazine).« less

ScrubChem: Cleaning of PubChem Bioassay Data to Create Diverse and Massive Bioactivity Datasets for Use in Modeling Applications (SOT)

EPA Science Inventory

The PubChem Bioassay database is a non-curated public repository with bioactivity data from 64 sources, including: ChEMBL, BindingDb, DrugBank, Tox21, NIH Molecular Libraries Screening Program, and various academic, government, and industrial contributors. However, this data is d...

PubChem3D: Shape compatibility filtering using molecular shape quadrupoles

PubMed Central

2011-01-01

Background PubChem provides a 3-D neighboring relationship, which involves finding the maximal shape overlap between two static compound 3-D conformations, a computationally intensive step. It is highly desirable to avoid this overlap computation, especially if it can be determined with certainty that a conformer pair cannot meet the criteria to be a 3-D neighbor. As such, PubChem employs a series of pre-filters, based on the concept of volume, to remove approximately 65% of all conformer neighbor pairs prior to shape overlap optimization. Given that molecular volume, a somewhat vague concept, is rather effective, it leads one to wonder: can the existing PubChem 3-D neighboring relationship, which consists of billions of shape similar conformer pairs from tens of millions of unique small molecules, be used to identify additional shape descriptor relationships? Or, put more specifically, can one place an upper bound on shape similarity using other "fuzzy" shape-like concepts like length, width, and height? Results Using a basis set of 4.18 billion 3-D neighbor pairs identified from single conformer per compound neighboring of 17.1 million molecules, shape descriptors were computed for all conformers. These steric shape descriptors included several forms of molecular volume and shape quadrupoles, which essentially embody the length, width, and height of a conformer. For a given 3-D neighbor conformer pair, the volume and each quadrupole component (Qx, Qy, and Qz) were binned and their frequency of occurrence was examined. Per molecular volume type, this effectively produced three different maps, one per quadrupole component (Qx, Qy, and Qz), of allowed values for the similarity metric, shape Tanimoto (ST) ≥ 0.8. The efficiency of these relationships (in terms of true positive, true negative, false positive and false negative) as a function of ST threshold was determined in a test run of 13.2 billion conformer pairs not previously considered by the 3-D neighbor set. At an ST ≥ 0.8, a filtering efficiency of 40.4% of true negatives was achieved with only 32 false negatives out of 24 million true positives, when applying the separate Qx, Qy, and Qz maps in a series (Qxyz). This efficiency increased linearly as a function of ST threshold in the range 0.8-0.99. The Qx filter was consistently the most efficient followed by Qy and then by Qz. Use of a monopole volume showed the best overall performance, followed by the self-overlap volume and then by the analytic volume. Application of the monopole-based Qxyz filter in a "real world" test of 3-D neighboring of 4,218 chemicals of biomedical interest against 26.1 million molecules in PubChem reduced the total CPU cost of neighboring by between 24-38% and, if used as the initial filter, removed from consideration 48.3% of all conformer pairs at almost negligible computational overhead. Conclusion Basic shape descriptors, such as those embodied by size, length, width, and height, can be highly effective in identifying shape incompatible compound conformer pairs. When performing a 3-D search using a shape similarity cut-off, computation can be avoided by identifying conformer pairs that cannot meet the result criteria. Applying this methodology as a filter for PubChem 3-D neighboring computation, an improvement of 31% was realized, increasing the average conformer pair throughput from 154,000 to 202,000 per second per CPU core. PMID:21774809

Development and Validation of a High Throughput Screen for Compounds with Antiviral Activity Against Encephalitic Alphaviruses

DTIC Science & Technology

2010-09-15

viruses , including West Nile virus (WNV) 7 (PubChem AID: 1635), respiratory syncytial virus (PubChem AID: 2440...such as West Nile virus assay with a threshold value of 3.42%. D. Single Dose experiment with Arbo virus ...compounds. RESULT 1. Hit compounds nomination A. Arbo virus hits (1) SMR000372439 and SMR000058373 : Informatics analysis discovered

Characterizing the Diversity and Biological Relevance of the MLPCN Assay Manifold and Screening Set

PubMed Central

Zhang, Jintao; Lushington, Gerald H.; Huan, Jun

2011-01-01

The NIH Molecular Libraries Initiative (MLI), launched in 2004 with initial goals of identifying chemical probes for characterizing gene function and druggability, has produced PubChem, a chemical genomics knowledgebase for fostering translation of basic research into new therapeutic strategies. This paper assesses progress toward these goals by evaluating MLI target novelty and propensity for undergoing biochemically or therapeutically relevant modulations and the degree of chemical diversity and biogenic bias inherent in the MLI screening set. Our analyses suggest that while MLI target selection has not yet been fully optimized for biochemical diversity, it covers biologically interesting pathway space that complements established drug targets. We find the MLI screening set to be chemically diverse and to have greater biogenic bias than comparable collections of commercially available compounds. Biogenic enhancements such as incorporation of more metabolite-like chemotypes are suggested. PMID:21568288

Chemotion ELN: an Open Source electronic lab notebook for chemists in academia.

PubMed

Tremouilhac, Pierre; Nguyen, An; Huang, Yu-Chieh; Kotov, Serhii; Lütjohann, Dominic Sebastian; Hübsch, Florian; Jung, Nicole; Bräse, Stefan

2017-09-25

The development of an electronic lab notebook (ELN) for researchers working in the field of chemical sciences is presented. The web based application is available as an Open Source software that offers modern solutions for chemical researchers. The Chemotion ELN is equipped with the basic functionalities necessary for the acquisition and processing of chemical data, in particular the work with molecular structures and calculations based on molecular properties. The ELN supports planning, description, storage, and management for the routine work of organic chemists. It also provides tools for communicating and sharing the recorded research data among colleagues. Meeting the requirements of a state of the art research infrastructure, the ELN allows the search for molecules and reactions not only within the user's data but also in conventional external sources as provided by SciFinder and PubChem. The presented development makes allowance for the growing dependency of scientific activity on the availability of digital information by providing Open Source instruments to record and reuse research data. The current version of the ELN has been using for over half of a year in our chemistry research group, serves as a common infrastructure for chemistry research and enables chemistry researchers to build their own databases of digital information as a prerequisite for the detailed, systematic investigation and evaluation of chemical reactions and mechanisms.

Avogadro: an advanced semantic chemical editor, visualization, and analysis platform

PubMed Central

2012-01-01

Background The Avogadro project has developed an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible, high quality rendering, and a powerful plugin architecture. Typical uses include building molecular structures, formatting input files, and analyzing output of a wide variety of computational chemistry packages. By using the CML file format as its native document type, Avogadro seeks to enhance the semantic accessibility of chemical data types. Results The work presented here details the Avogadro library, which is a framework providing a code library and application programming interface (API) with three-dimensional visualization capabilities; and has direct applications to research and education in the fields of chemistry, physics, materials science, and biology. The Avogadro application provides a rich graphical interface using dynamically loaded plugins through the library itself. The application and library can each be extended by implementing a plugin module in C++ or Python to explore different visualization techniques, build/manipulate molecular structures, and interact with other programs. We describe some example extensions, one which uses a genetic algorithm to find stable crystal structures, and one which interfaces with the PackMol program to create packed, solvated structures for molecular dynamics simulations. The 1.0 release series of Avogadro is the main focus of the results discussed here. Conclusions Avogadro offers a semantic chemical builder and platform for visualization and analysis. For users, it offers an easy-to-use builder, integrated support for downloading from common databases such as PubChem and the Protein Data Bank, extracting chemical data from a wide variety of formats, including computational chemistry output, and native, semantic support for the CML file format. For developers, it can be easily extended via a powerful plugin mechanism to support new features in organic chemistry, inorganic complexes, drug design, materials, biomolecules, and simulations. Avogadro is freely available under an open-source license from http://avogadro.openmolecules.net. PMID:22889332

Avogadro: an advanced semantic chemical editor, visualization, and analysis platform.

PubMed

Hanwell, Marcus D; Curtis, Donald E; Lonie, David C; Vandermeersch, Tim; Zurek, Eva; Hutchison, Geoffrey R

2012-08-13

The Avogadro project has developed an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible, high quality rendering, and a powerful plugin architecture. Typical uses include building molecular structures, formatting input files, and analyzing output of a wide variety of computational chemistry packages. By using the CML file format as its native document type, Avogadro seeks to enhance the semantic accessibility of chemical data types. The work presented here details the Avogadro library, which is a framework providing a code library and application programming interface (API) with three-dimensional visualization capabilities; and has direct applications to research and education in the fields of chemistry, physics, materials science, and biology. The Avogadro application provides a rich graphical interface using dynamically loaded plugins through the library itself. The application and library can each be extended by implementing a plugin module in C++ or Python to explore different visualization techniques, build/manipulate molecular structures, and interact with other programs. We describe some example extensions, one which uses a genetic algorithm to find stable crystal structures, and one which interfaces with the PackMol program to create packed, solvated structures for molecular dynamics simulations. The 1.0 release series of Avogadro is the main focus of the results discussed here. Avogadro offers a semantic chemical builder and platform for visualization and analysis. For users, it offers an easy-to-use builder, integrated support for downloading from common databases such as PubChem and the Protein Data Bank, extracting chemical data from a wide variety of formats, including computational chemistry output, and native, semantic support for the CML file format. For developers, it can be easily extended via a powerful plugin mechanism to support new features in organic chemistry, inorganic complexes, drug design, materials, biomolecules, and simulations. Avogadro is freely available under an open-source license from http://avogadro.openmolecules.net.

Chemical-Gene Interactions from ToxCast Bioactivity Data ...

EPA Pesticide Factsheets

Characterizing the effects of chemicals in biological systems is often summarized by chemical-gene interactions, which have sparse coverage in the literature. The ToxCast chemical screening program has produced bioactivity data for nearly 2000 chemicals and over 450 gene targets. To evaluate the information gained from the ToxCast project, a ToxCast bioactivity network was created comprising ToxCast chemical-gene interactions based on assay data and compared to a chemical-gene association network from literature. The literature network was compiled from PubMed articles, excluding ToxCast publications, mapped to genes and chemicals. Genes were identified by curated associations available from NCBI while chemicals were identified by PubChem submissions. The frequencies of chemical-gene associations from the literature network were log-scaled and then compared to the ToxCast bioactivity network. In total, 140 times more chemical-gene associations were present in the ToxCast network in comparison to the literature-derived network highlighting the vast increase in chemical-gene interactions putatively elucidated by the ToxCast research program. There were 165 associations found in the literature network that were reproduced by ToxCast bioactivity data, and 336 associations in the literature network were not reproduced by the ToxCast bioactivity network. The literature network relies on the assumption that chemical-gene associations represent a true chemical-gene inte

Fast 3D shape screening of large chemical databases through alignment-recycling

PubMed Central

Fontaine, Fabien; Bolton, Evan; Borodina, Yulia; Bryant, Stephen H

2007-01-01

Background Large chemical databases require fast, efficient, and simple ways of looking for similar structures. Although such tasks are now fairly well resolved for graph-based similarity queries, they remain an issue for 3D approaches, particularly for those based on 3D shape overlays. Inspired by a recent technique developed to compare molecular shapes, we designed a hybrid methodology, alignment-recycling, that enables efficient retrieval and alignment of structures with similar 3D shapes. Results Using a dataset of more than one million PubChem compounds of limited size (< 28 heavy atoms) and flexibility (< 6 rotatable bonds), we obtained a set of a few thousand diverse structures covering entirely the 3D shape space of the conformers of the dataset. Transformation matrices gathered from the overlays between these diverse structures and the 3D conformer dataset allowed us to drastically (100-fold) reduce the CPU time required for shape overlay. The alignment-recycling heuristic produces results consistent with de novo alignment calculation, with better than 80% hit list overlap on average. Conclusion Overlay-based 3D methods are computationally demanding when searching large databases. Alignment-recycling reduces the CPU time to perform shape similarity searches by breaking the alignment problem into three steps: selection of diverse shapes to describe the database shape-space; overlay of the database conformers to the diverse shapes; and non-optimized overlay of query and database conformers using common reference shapes. The precomputation, required by the first two steps, is a significant cost of the method; however, once performed, querying is two orders of magnitude faster. Extensions and variations of this methodology, for example, to handle more flexible and larger small-molecules are discussed. PMID:17880744

Global QSAR modeling of logP values of phenethylamines acting as adrenergic alpha-1 receptor agonists.

PubMed

Yadav, Mukesh; Joshi, Shobha; Nayarisseri, Anuraj; Jain, Anuja; Hussain, Aabid; Dubey, Tushar

2013-06-01

Global QSAR models predict biological response of molecular structures which are generic in particular class. A global QSAR dataset admits structural features derived from larger chemical space, intricate to model but more applicable in medicinal chemistry. The present work is global in either sense of structural diversity in QSAR dataset or large number of descriptor input. Forty phenethylamine structure derivatives were selected from a large pool (904) of similar phenethylamines available in Pubchem database. LogP values of selected candidates were collected from physical properties database (PHYSPROP) determined in identical set of conditions. Attempts to model logP value have produced significant QSAR models. MLR aided linear one-variable and two-variable QSAR models with their respective R(2) (0.866, 0.937), R(2)A (0.862, 0.932), F-stat (181.936, 199.812) and Standard Error (0.365, 0.255) are statistically fit and found predictive after internal validation and external validation. The descriptors chosen after improvisation and optimization reveal mechanistic part of work in terms of Verhaar model of Fish base-line toxicity from MLOGP, i.e. (BLTF96) and 3D-MoRSE -signal 15 /unweighted molecular descriptor calculated by summing atom weights viewed by a different angular scattering function (Mor15u) are crucial in regulation of logP values of phenethylamines.

MATCH: An Atom- Typing Toolset for Molecular Mechanics Force Fields

PubMed Central

Yesselman, Joseph D.; Price, Daniel J.; Knight, Jennifer L.; Brooks, Charles L.

2011-01-01

We introduce a toolset of program libraries collectively titled MATCH (Multipurpose Atom-Typer for CHARMM) for the automated assignment of atom types and force field parameters for molecular mechanics simulation of organic molecules. The toolset includes utilities for the conversion from multiple chemical structure file formats into a molecular graph. A general chemical pattern-matching engine using this graph has been implemented whereby assignment of molecular mechanics atom types, charges and force field parameters is achieved by comparison against a customizable list of chemical fragments. While initially designed to complement the CHARMM simulation package and force fields by generating the necessary input topology and atom-type data files, MATCH can be expanded to any force field and program, and has core functionality that makes it extendable to other applications such as fragment-based property prediction. In the present work, we demonstrate the accurate construction of atomic parameters of molecules within each force field included in CHARMM36 through exhaustive cross validation studies illustrating that bond increment rules derived from one force field can be transferred to another. In addition, using leave-one-out substitution it is shown that it is also possible to substitute missing intra and intermolecular parameters with ones included in a force field to complete the parameterization of novel molecules. Finally, to demonstrate the robustness of MATCH and the coverage of chemical space offered by the recent CHARMM CGENFF force field (Vanommeslaeghe, et al., JCC., 2010, 31, 671–690), one million molecules from the PubChem database of small molecules are typed, parameterized and minimized. PMID:22042689

GPU Accelerated Chemical Similarity Calculation for Compound Library Comparison

PubMed Central

Ma, Chao; Wang, Lirong; Xie, Xiang-Qun

2012-01-01

Chemical similarity calculation plays an important role in compound library design, virtual screening, and “lead” optimization. In this manuscript, we present a novel GPU-accelerated algorithm for all-vs-all Tanimoto matrix calculation and nearest neighbor search. By taking advantage of multi-core GPU architecture and CUDA parallel programming technology, the algorithm is up to 39 times superior to the existing commercial software that runs on CPUs. Because of the utilization of intrinsic GPU instructions, this approach is nearly 10 times faster than existing GPU-accelerated sparse vector algorithm, when Unity fingerprints are used for Tanimoto calculation. The GPU program that implements this new method takes about 20 minutes to complete the calculation of Tanimoto coefficients between 32M PubChem compounds and 10K Active Probes compounds, i.e., 324G Tanimoto coefficients, on a 128-CUDA-core GPU. PMID:21692447

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

Computational and in vitro insights on snake venom phospholipase A2 inhibitor of phytocompound ikshusterol3-O-glucoside of Clematis gouriana Roxb. ex DC.

PubMed

Muthusamy, Karthikeyan; Chinnasamy, Sathishkumar; Nagarajan, Subbiah; Sivaraman, Thirunavukkarasu

2017-12-14

Ikshusterol3-O-glucoside was isolated from Clematis gouriana Roxb. ex DC. root. A structure of the isolated compound was determined on the basis of various spectroscopic interpretations (UV, NMR, FTIR, and GC-MS-EI). This structure was submitted in the PubChem compound database (SID 249494133). SID 249494133 was carried out by density functional theory calculation to observe the chemical stability and electrostatic potential of this compound. The absorption, distribution, metabolism, and excretion property of this compound was predicted to evaluate the drug likeness and toxicity. In addition, molecular docking, quantum polarized ligand docking, prime MMGBSA calculation, and induced fit docking were performed to predict the binding status of SID 249494133 with the active site of phospholipase A 2 (PLA 2 ) (PDB ID: 1A3D). The stability of the compound in the active site of PLA 2 was carried out using molecular dynamics simulation. Further, the anti-venom activity of the compound was assessed using the PLA 2 assay against Naja naja (Indian cobra) crude venom. The results strongly show that Ikshusterol3-O-glucoside has a potent snake-venom neutralizing capacity and it might be a potential molecule for the therapeutic treatment for snakebites.

DPubChem: a web tool for QSAR modeling and high-throughput virtual screening.

PubMed

Soufan, Othman; Ba-Alawi, Wail; Magana-Mora, Arturo; Essack, Magbubah; Bajic, Vladimir B

2018-06-14

High-throughput screening (HTS) performs the experimental testing of a large number of chemical compounds aiming to identify those active in the considered assay. Alternatively, faster and cheaper methods of large-scale virtual screening are performed computationally through quantitative structure-activity relationship (QSAR) models. However, the vast amount of available HTS heterogeneous data and the imbalanced ratio of active to inactive compounds in an assay make this a challenging problem. Although different QSAR models have been proposed, they have certain limitations, e.g., high false positive rates, complicated user interface, and limited utilization options. Therefore, we developed DPubChem, a novel web tool for deriving QSAR models that implement the state-of-the-art machine-learning techniques to enhance the precision of the models and enable efficient analyses of experiments from PubChem BioAssay database. DPubChem also has a simple interface that provides various options to users. DPubChem predicted active compounds for 300 datasets with an average geometric mean and F 1 score of 76.68% and 76.53%, respectively. Furthermore, DPubChem builds interaction networks that highlight novel predicted links between chemical compounds and biological assays. Using such a network, DPubChem successfully suggested a novel drug for the Niemann-Pick type C disease. DPubChem is freely available at www.cbrc.kaust.edu.sa/dpubchem .

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

ProCarDB: a database of bacterial carotenoids.

PubMed

Nupur, L N U; Vats, Asheema; Dhanda, Sandeep Kumar; Raghava, Gajendra P S; Pinnaka, Anil Kumar; Kumar, Ashwani

2016-05-26

Carotenoids have important functions in bacteria, ranging from harvesting light energy to neutralizing oxidants and acting as virulence factors. However, information pertaining to the carotenoids is scattered throughout the literature. Furthermore, information about the genes/proteins involved in the biosynthesis of carotenoids has tremendously increased in the post-genomic era. A web server providing the information about microbial carotenoids in a structured manner is required and will be a valuable resource for the scientific community working with microbial carotenoids. Here, we have created a manually curated, open access, comprehensive compilation of bacterial carotenoids named as ProCarDB- Prokaryotic Carotenoid Database. ProCarDB includes 304 unique carotenoids arising from 50 biosynthetic pathways distributed among 611 prokaryotes. ProCarDB provides important information on carotenoids, such as 2D and 3D structures, molecular weight, molecular formula, SMILES, InChI, InChIKey, IUPAC name, KEGG Id, PubChem Id, and ChEBI Id. The database also provides NMR data, UV-vis absorption data, IR data, MS data and HPLC data that play key roles in the identification of carotenoids. An important feature of this database is the extension of biosynthetic pathways from the literature and through the presence of the genes/enzymes in different organisms. The information contained in the database was mined from published literature and databases such as KEGG, PubChem, ChEBI, LipidBank, LPSN, and Uniprot. The database integrates user-friendly browsing and searching with carotenoid analysis tools to help the user. We believe that this database will serve as a major information centre for researchers working on bacterial carotenoids.

Dual-mechanism gastroretentive drug delivery system loaded with an amorphous solid dispersion prepared by hot-melt extrusion.

PubMed

Vo, Anh Q; Feng, Xin; Pimparade, Manjeet; Ye, Xinyou; Kim, Dong Wuk; Martin, Scott T; Repka, Michael A

2017-05-01

In the present study, we aimed to prepare a gastroretentive drug delivery system that would be both highly resistant to gastric emptying via multiple mechanisms and would also potentially induce in situ supersaturation. The bioadhesive floating pellets, loaded with an amorphous solid dispersion, were prepared in a single step of hot-melt extrusion technology. Hydroxypropyl cellulose (Klucel™ MF) and hypromellose (Benecel™ K15M) were used as matrix-forming polymers, and felodipine was used as the model drug. The foam pellets were fabricated based on the expansion of CO 2 , which was generated from sodium bicarbonate during the melt-extrusion process. A 2 n full factorial experimental design was utilized to investigate the effects of formulation compositions to the pellet properties. The melt-extrusion process transformed the crystalline felodipine into an amorphous state that was dispersed and "frozen" in the polymer matrix. All formulations showed high porosity and were able to float immediately, without lag time, on top of gastric fluid, and maintained their buoyancy over 12h. The pellet-specific floating force, which could be as high as 4800μN/g, increased significantly during the first hour, and was relatively stable until 9h. The sodium bicarbonate percentage was found to be most significantly effect to the floating force. The ex vivo bioadhesion force of the pellets to porcine stomach mucosa was approximately 5mN/pellet, which was more than five times higher than the gravitation force of the pellet saturated with water. Drug release was well controlled up to 12h in the sink condition of 0.5% sodium lauryl sulphate in 0.1N HCl. The dissolution at 1, 3, 5, and 8h were 5-12%, 25-45%, 55-80%, and ≥75% respectively for all 11 formulations. In biorelevant dissolution medium, a supersaturated solution was formed, and the concentration was maintained at around 2μg/mL, approximately 10-folds higher than that of the pure felodipine. All input factors significantly affected dissolution in the first 3h, but afterwards, only drug load and hypromellose (HPMC) content had significant effects. The prepared drug delivery system has great potential in overcoming low and fluctuating bioavailability of poorly soluble drugs. Felodipine (PubChem CID: 3333); hypromellose (PubChem CID: 57503849), hydroxypropyl cellulose (PubChem CID: 71306830), sodium bicarbonate (PubChem CID: 516892); sodium carbonate (PubChem CID: 10340). Copyright © 2017 Elsevier B.V. All rights reserved.

LeadMine: a grammar and dictionary driven approach to entity recognition.

PubMed

Lowe, Daniel M; Sayle, Roger A

2015-01-01

Chemical entity recognition has traditionally been performed by machine learning approaches. Here we describe an approach using grammars and dictionaries. This approach has the advantage that the entities found can be directly related to a given grammar or dictionary, which allows the type of an entity to be known and, if an entity is misannotated, indicates which resource should be corrected. As recognition is driven by what is expected, if spelling errors occur, they can be corrected. Correcting such errors is highly useful when attempting to lookup an entity in a database or, in the case of chemical names, converting them to structures. Our system uses a mixture of expertly curated grammars and dictionaries, as well as dictionaries automatically derived from public resources. We show that the heuristics developed to filter our dictionary of trivial chemical names (from PubChem) yields a better performing dictionary than the previously published Jochem dictionary. Our final system performs post-processing steps to modify the boundaries of entities and to detect abbreviations. These steps are shown to significantly improve performance (2.6% and 4.0% F1-score respectively). Our complete system, with incremental post-BioCreative workshop improvements, achieves 89.9% precision and 85.4% recall (87.6% F1-score) on the CHEMDNER test set. Grammar and dictionary approaches can produce results at least as good as the current state of the art in machine learning approaches. While machine learning approaches are commonly thought of as "black box" systems, our approach directly links the output entities to the input dictionaries and grammars. Our approach also allows correction of errors in detected entities, which can assist with entity resolution.

LeadMine: a grammar and dictionary driven approach to entity recognition

PubMed Central

2015-01-01

Background Chemical entity recognition has traditionally been performed by machine learning approaches. Here we describe an approach using grammars and dictionaries. This approach has the advantage that the entities found can be directly related to a given grammar or dictionary, which allows the type of an entity to be known and, if an entity is misannotated, indicates which resource should be corrected. As recognition is driven by what is expected, if spelling errors occur, they can be corrected. Correcting such errors is highly useful when attempting to lookup an entity in a database or, in the case of chemical names, converting them to structures. Results Our system uses a mixture of expertly curated grammars and dictionaries, as well as dictionaries automatically derived from public resources. We show that the heuristics developed to filter our dictionary of trivial chemical names (from PubChem) yields a better performing dictionary than the previously published Jochem dictionary. Our final system performs post-processing steps to modify the boundaries of entities and to detect abbreviations. These steps are shown to significantly improve performance (2.6% and 4.0% F1-score respectively). Our complete system, with incremental post-BioCreative workshop improvements, achieves 89.9% precision and 85.4% recall (87.6% F1-score) on the CHEMDNER test set. Conclusions Grammar and dictionary approaches can produce results at least as good as the current state of the art in machine learning approaches. While machine learning approaches are commonly thought of as "black box" systems, our approach directly links the output entities to the input dictionaries and grammars. Our approach also allows correction of errors in detected entities, which can assist with entity resolution. PMID:25810776

Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

PubMed

Ribay, Kathryn; Kim, Marlene T; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

2016-03-01

Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR models, particularly for the activity cliffs that induce prediction errors. The results of this study indicate that the response profile of chemicals from public data provides useful information for modeling and evaluation purposes. The public big data resources should be considered along with chemical structure information when predicting new compounds, such as unknown ERα binding agents.

InChI in the wild: an assessment of InChIKey searching in Google

PubMed Central

2013-01-01

While chemical databases can be queried using the InChI string and InChIKey (IK) the latter was designed for open-web searching. It is becoming increasingly effective for this since more sources enhance crawling of their websites by the Googlebot and consequent IK indexing. Searchers who use Google as an adjunct to database access may be less familiar with the advantages of using the IK as explored in this review. As an example, the IK for atorvastatin retrieves ~200 low-redundancy links from a Google search in 0.3 of a second. These include most major databases and a very low false-positive rate. Results encompass less familiar but potentially useful sources and can be extended to isomer capture by using just the skeleton layer of the IK. Google Advanced Search can be used to filter large result sets. Image searching with the IK is also effective and complementary to open-web queries. Results can be particularly useful for less-common structures as exemplified by a major metabolite of atorvastatin giving only three hits. Testing also demonstrated document-to-document and document-to-database joins via structure matching. The necessary generation of an IK from chemical names can be accomplished using open tools and resources for patents, papers, abstracts or other text sources. Active global sharing of local IK-linked information can be accomplished via surfacing in open laboratory notebooks, blogs, Twitter, figshare and other routes. While information-rich chemistry (e.g. approved drugs) can exhibit swamping and redundancy effects, the much smaller IK result sets for link-poor structures become a transformative first-pass option. The IK indexing has therefore turned Google into a de-facto open global chemical information hub by merging links to most significant sources, including over 50 million PubChem and ChemSpider records. The simplicity, specificity and speed of matching make it a useful option for biologists or others less familiar with chemical searching. However, compared to rigorously maintained major databases, users need to be circumspect about the consistency of Google results and provenance of retrieved links. In addition, community engagement may be necessary to ameliorate possible future degradation of utility. PMID:23399051

Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

PubMed

Fang, Xingang; Bagui, Sikha; Bagui, Subhash

2017-08-01

The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular descriptors developed to encode useful chemical information representing the characteristics of molecules, descriptor selection is an essential step in building an optimal quantitative structural-activity relationship (QSAR) model. For the development of a systematic descriptor selection strategy, we need the understanding of the relationship between: (i) the descriptor selection; (ii) the choice of the machine learning model; and (iii) the characteristics of the target bio-molecule. In this work, we employed the Signature descriptor to generate a dataset on the Human kallikrein 5 (hK 5) inhibition confirmatory assay data and compared multiple classification models including logistic regression, support vector machine, random forest and k-nearest neighbor. Under optimal conditions, the logistic regression model provided extremely high overall accuracy (98%) and precision (90%), with good sensitivity (65%) in the cross validation test. In testing the primary HTS screening data with more than 200K molecular structures, the logistic regression model exhibited the capability of eliminating more than 99.9% of the inactive structures. As part of our exploration of the descriptor-model-target relationship, the excellent predictive performance of the combination of the Signature descriptor and the logistic regression model on the assay data of the Human kallikrein 5 (hK 5) target suggested a feasible descriptor/model selection strategy on similar targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

MetaMapR: pathway independent metabolomic network analysis incorporating unknowns.

PubMed

Grapov, Dmitry; Wanichthanarak, Kwanjeera; Fiehn, Oliver

2015-08-15

Metabolic network mapping is a widely used approach for integration of metabolomic experimental results with biological domain knowledge. However, current approaches can be limited by biochemical domain or pathway knowledge which results in sparse disconnected graphs for real world metabolomic experiments. MetaMapR integrates enzymatic transformations with metabolite structural similarity, mass spectral similarity and empirical associations to generate richly connected metabolic networks. This open source, web-based or desktop software, written in the R programming language, leverages KEGG and PubChem databases to derive associations between metabolites even in cases where biochemical domain or molecular annotations are unknown. Network calculation is enhanced through an interface to the Chemical Translation System, which allows metabolite identifier translation between >200 common biochemical databases. Analysis results are presented as interactive visualizations or can be exported as high-quality graphics and numerical tables which can be imported into common network analysis and visualization tools. Freely available at http://dgrapov.github.io/MetaMapR/. Requires R and a modern web browser. Installation instructions, tutorials and application examples are available at http://dgrapov.github.io/MetaMapR/. ofiehn@ucdavis.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Dendrobium officinale Kimura et Migo: A Review on Its Ethnopharmacology, Phytochemistry, Pharmacology, and Industrialization

PubMed Central

Tang, Hanxiao; Zhao, Tianwen; Sheng, Yunjie; Zheng, Ting; Fu, Lingzhu

2017-01-01

Ethnopharmacological Relevance. Dendrobii Officinalis Caulis, the stems of Dendrobium officinale Kimura et Migo, as a tonic herb in Chinese materia medica and health food in folk, has been utilized for the treatment of yin-deficiency diseases for decades. Methods. Information for analysis of Dendrobium officinale Kimura et Migo was obtained from libraries and Internet scientific databases such as PubMed, Web of Science, Google Scholar, ScienceDirect, Wiley InterScience, Ingenta, Embase, CNKI, and PubChem. Results. Over the past decades, about 190 compounds have been isolated from Dendrobium officinale Kimura et Migo. Its wide modern pharmacological actions in hepatoprotective effect, anticancer effect, hypoglycemic effect, antifatigue effect, gastric ulcer protective effect, and so on were reported. This may mainly attribute to the major and bioactive components: polysaccharides. However, other small molecule components require further study. Conclusions. Due to the lack of systematic data of Dendrobium officinale, it is important to explore its ingredient-function relationships with modern pharmacology. Recently, studies on the chemical constituents of Dendrobium officinale concentrated in crude polysaccharides and its structure-activity relationships remain scant. Further research is required to determine the Dendrobium officinale toxicological action and pharmacological mechanisms of other pure ingredients and crude extracts. In addition, investigation is needed for better quality control and novel drug or product development. PMID:28386292

MMpI: A WideRange of Available Compounds of Matrix Metalloproteinase Inhibitors

PubMed Central

Muvva, Charuvaka; Patra, Sanjukta; Venkatesan, Subramanian

2016-01-01

Matrix metalloproteinases (MMPs) are a family of zinc-dependent proteinases involved in the regulation of the extracellular signaling and structural matrix environment of cells and tissues. MMPs are considered as promising targets for the treatment of many diseases. Therefore, creation of database on the inhibitors of MMP would definitely accelerate the research activities in this area due to its implication in above-mentioned diseases and associated limitations in the first and second generation inhibitors. In this communication, we report the development of a new MMpI database which provides resourceful information for all researchers working in this field. It is a web-accessible, unique resource that contains detailed information on the inhibitors of MMP including small molecules, peptides and MMP Drug Leads. The database contains entries of ~3000 inhibitors including ~72 MMP Drug Leads and ~73 peptide based inhibitors. This database provides the detailed molecular and structural details which are necessary for the drug discovery and development. The MMpI database contains physical properties, 2D and 3D structures (mol2 and pdb format files) of inhibitors of MMP. Other data fields are hyperlinked to PubChem, ChEMBL, BindingDB, DrugBank, PDB, MEROPS and PubMed. The database has extensive searching facility with MMpI ID, IUPAC name, chemical structure and with the title of research article. The MMP inhibitors provided in MMpI database are optimized using Python-based Hierarchical Environment for Integrated Xtallography (Phenix) software. MMpI Database is unique and it is the only public database that contains and provides the complete information on the inhibitors of MMP. Database URL: http://clri.res.in/subramanian/databases/mmpi/index.php. PMID:27509041

2P2IHUNTER: a tool for filtering orthosteric protein–protein interaction modulators via a dedicated support vector machine

PubMed Central

Hamon, Véronique; Bourgeas, Raphael; Ducrot, Pierre; Theret, Isabelle; Xuereb, Laura; Basse, Marie Jeanne; Brunel, Jean Michel; Combes, Sebastien; Morelli, Xavier; Roche, Philippe

2014-01-01

Over the last 10 years, protein–protein interactions (PPIs) have shown increasing potential as new therapeutic targets. As a consequence, PPIs are today the most screened target class in high-throughput screening (HTS). The development of broad chemical libraries dedicated to these particular targets is essential; however, the chemical space associated with this ‘high-hanging fruit’ is still under debate. Here, we analyse the properties of 40 non-redundant small molecules present in the 2P2I database (http://2p2idb.cnrs-mrs.fr/) to define a general profile of orthosteric inhibitors and propose an original protocol to filter general screening libraries using a support vector machine (SVM) with 11 standard Dragon molecular descriptors. The filtering protocol has been validated using external datasets from PubChem BioAssay and results from in-house screening campaigns. This external blind validation demonstrated the ability of the SVM model to reduce the size of the filtered chemical library by eliminating up to 96% of the compounds as well as enhancing the proportion of active compounds by up to a factor of 8. We believe that the resulting chemical space identified in this paper will provide the scientific community with a concrete support to search for PPI inhibitors during HTS campaigns. PMID:24196694

An Informatics Approach to Evaluating Combined Chemical Exposures from Consumer Products: A Case Study of Asthma-Associated Chemicals and Potential Endocrine Disruptors.

PubMed

Gabb, Henry A; Blake, Catherine

2016-08-01

Simultaneous or sequential exposure to multiple environmental stressors can affect chemical toxicity. Cumulative risk assessments consider multiple stressors but it is impractical to test every chemical combination to which people are exposed. New methods are needed to prioritize chemical combinations based on their prevalence and possible health impacts. We introduce an informatics approach that uses publicly available data to identify chemicals that co-occur in consumer products, which account for a significant proportion of overall chemical load. Fifty-five asthma-associated and endocrine disrupting chemicals (target chemicals) were selected. A database of 38,975 distinct consumer products and 32,231 distinct ingredient names was created from online sources, and PubChem and the Unified Medical Language System were used to resolve synonymous ingredient names. Synonymous ingredient names are different names for the same chemical (e.g., vitamin E and tocopherol). Nearly one-third of the products (11,688 products, 30%) contained ≥ 1 target chemical and 5,229 products (13%) contained > 1. Of the 55 target chemicals, 31 (56%) appear in ≥ 1 product and 19 (35%) appear under more than one name. The most frequent three-way chemical combination (2-phenoxyethanol, methyl paraben, and ethyl paraben) appears in 1,059 products. Further work is needed to assess combined chemical exposures related to the use of multiple products. The informatics approach increased the number of products considered in a traditional analysis by two orders of magnitude, but missing/incomplete product labels can limit the effectiveness of this approach. Such an approach must resolve synonymy to ensure that chemicals of interest are not missed. Commonly occurring chemical combinations can be used to prioritize cumulative toxicology risk assessments. Gabb HA, Blake C. 2016. An informatics approach to evaluating combined chemical exposures from consumer products: a case study of asthma-associated chemicals and potential endocrine disruptors. Environ Health Perspect 124:1155-1165; http://dx.doi.org/10.1289/ehp.1510529.

Discovery of novel Pim-1 kinase inhibitors by a hierarchical multistage virtual screening approach based on SVM model, pharmacophore, and molecular docking.

PubMed

Ren, Ji-Xia; Li, Lin-Li; Zheng, Ren-Lin; Xie, Huan-Zhang; Cao, Zhi-Xing; Feng, Shan; Pan, You-Li; Chen, Xin; Wei, Yu-Quan; Yang, Sheng-Yong

2011-06-27

In this investigation, we describe the discovery of novel potent Pim-1 inhibitors by employing a proposed hierarchical multistage virtual screening (VS) approach, which is based on support vector machine-based (SVM-based VS or SB-VS), pharmacophore-based VS (PB-VS), and docking-based VS (DB-VS) methods. In this approach, the three VS methods are applied in an increasing order of complexity so that the first filter (SB-VS) is fast and simple, while successive ones (PB-VS and DB-VS) are more time-consuming but are applied only to a small subset of the entire database. Evaluation of this approach indicates that it can be used to screen a large chemical library rapidly with a high hit rate and a high enrichment factor. This approach was then applied to screen several large chemical libraries, including PubChem, Specs, and Enamine as well as an in-house database. From the final hits, 47 compounds were selected for further in vitro Pim-1 inhibitory assay, and 15 compounds show nanomolar level or low micromolar inhibition potency against Pim-1. In particular, four of them were found to have new scaffolds which have potential for the chemical development of Pim-1 inhibitors.

Docking analysis of verteporfin with YAP WW domain.

PubMed

Kandoussi, Ilham; Lakhlili, Wiame; Taoufik, Jamal; Ibrahimi, Azeddine

2017-01-01

The YAP oncogene is a known cancer target. Therefore, it is of interest to understand the molecular docking interaction of verteporfin (a derivative of benzo-porphyrin) with the WW domain of YAP (clinically used for photo-dynamic therapy in macular degeneration) as a potential WW domain-ligand modulator by inhibition. A homology protein SWISS MODEL of the human YAP protein was constructed to dock (using AutoDock vina) with the PubChem verteporfin structure for interaction analysis. The docking result shows the possibilities of verteporfin interaction with the oncogenic transcription cofactor YAP having WW1 and WW2 domains. Thus, the ability of verteporfin to bind with the YAP WW domain having modulator activity is implied in this analysis.

Discovery of novel mGluR1 antagonists: a multistep virtual screening approach based on an SVM model and a pharmacophore hypothesis significantly increases the hit rate and enrichment factor.

PubMed

Li, Guo-Bo; Yang, Ling-Ling; Feng, Shan; Zhou, Jian-Ping; Huang, Qi; Xie, Huan-Zhang; Li, Lin-Li; Yang, Sheng-Yong

2011-03-15

Development of glutamate non-competitive antagonists of mGluR1 (Metabotropic glutamate receptor subtype 1) has increasingly attracted much attention in recent years due to their potential therapeutic application for various nervous disorders. Since there is no crystal structure reported for mGluR1, ligand-based virtual screening (VS) methods, typically pharmacophore-based VS (PB-VS), are often used for the discovery of mGluR1 antagonists. Nevertheless, PB-VS usually suffers a lower hit rate and enrichment factor. In this investigation, we established a multistep ligand-based VS approach that is based on a support vector machine (SVM) classification model and a pharmacophore model. Performance evaluation of these methods in virtual screening against a large independent test set, M-MDDR, show that the multistep VS approach significantly increases the hit rate and enrichment factor compared with the individual SB-VS and PB-VS methods. The multistep VS approach was then used to screen several large chemical libraries including PubChem, Specs, and Enamine. Finally a total of 20 compounds were selected from the top ranking compounds, and shifted to the subsequent in vitro and in vivo studies, which results will be reported in the near future. Copyright © 2011 Elsevier Ltd. All rights reserved.

Pharmacophore modeling, molecular docking, and molecular dynamics simulation approaches for identifying new lead compounds for inhibiting aldose reductase 2.

PubMed

Sakkiah, Sugunadevi; Thangapandian, Sundarapandian; Lee, Keun Woo

2012-07-01

Aldose reductase 2 (ALR2), which catalyzes the reduction of glucose to sorbitol using NADP as a cofactor, has been implicated in the etiology of secondary complications of diabetes. A pharmacophore model, Hypo1, was built based on 26 compounds with known ALR2-inhibiting activity values. Hypo1 contains important chemical features required for an ALR2 inhibitor, and demonstrates good predictive ability by having a high correlation coefficient (0.95) as well as the highest cost difference (128.44) and the lowest RMS deviation (1.02) among the ten pharmacophore models examined. Hypo1 was further validated by Fisher's randomization method (95%), test set (r = 0.91), and the decoy set shows the goodness of fit (0.70). Furthermore, during virtual screening, Hypo1 was used as a 3D query to screen the NCI database, and the hit leads were sorted by applying Lipinski's rule of five and ADME properties. The best-fitting leads were subjected to docking to identify a suitable orientation at the ALR2 active site. The molecule that showed the strongest interactions with the critical amino acids was used in molecular dynamics simulations to calculate its binding affinity to the candidate molecules. Thus, Hypo1 describes the key structure-activity relationship along with the estimated activities of ALR2 inhibitors. The hit molecules were searched against PubChem to find similar molecules with new scaffolds. Finally, four molecules were found to satisfy all of the chemical features and the geometric constraints of Hypo1, as well as to show good dock scores, PLPs and PMFs. Thus, we believe that Hypo1 facilitates the selection of novel scaffolds for ALR2, allowing new classes of ALR2 inhibitors to be designed.

Use of in Vitro HTS-Derived Concentration–Response Data as Biological Descriptors Improves the Accuracy of QSAR Models of in Vivo Toxicity

PubMed Central

Sedykh, Alexander; Zhu, Hao; Tang, Hao; Zhang, Liying; Richard, Ann; Rusyn, Ivan; Tropsha, Alexander

2011-01-01

Background Quantitative high-throughput screening (qHTS) assays are increasingly being used to inform chemical hazard identification. Hundreds of chemicals have been tested in dozens of cell lines across extensive concentration ranges by the National Toxicology Program in collaboration with the National Institutes of Health Chemical Genomics Center. Objectives Our goal was to test a hypothesis that dose–response data points of the qHTS assays can serve as biological descriptors of assayed chemicals and, when combined with conventional chemical descriptors, improve the accuracy of quantitative structure–activity relationship (QSAR) models applied to prediction of in vivo toxicity end points. Methods We obtained cell viability qHTS concentration–response data for 1,408 substances assayed in 13 cell lines from PubChem; for a subset of these compounds, rodent acute toxicity half-maximal lethal dose (LD50) data were also available. We used the k nearest neighbor classification and random forest QSAR methods to model LD50 data using chemical descriptors either alone (conventional models) or combined with biological descriptors derived from the concentration–response qHTS data (hybrid models). Critical to our approach was the use of a novel noise-filtering algorithm to treat qHTS data. Results Both the external classification accuracy and coverage (i.e., fraction of compounds in the external set that fall within the applicability domain) of the hybrid QSAR models were superior to conventional models. Conclusions Concentration–response qHTS data may serve as informative biological descriptors of molecules that, when combined with conventional chemical descriptors, may considerably improve the accuracy and utility of computational approaches for predicting in vivo animal toxicity end points. PMID:20980217

A Chemoinformatics Approach to the Discovery of Lead-Like Molecules from Marine and Microbial Sources En Route to Antitumor and Antibiotic Drugs

PubMed Central

Pereira, Florbela; Latino, Diogo A. R. S.; Gaudêncio, Susana P.

2014-01-01

The comprehensive information of small molecules and their biological activities in the PubChem database allows chemoinformatic researchers to access and make use of large-scale biological activity data to improve the precision of drug profiling. A Quantitative Structure–Activity Relationship approach, for classification, was used for the prediction of active/inactive compounds relatively to overall biological activity, antitumor and antibiotic activities using a data set of 1804 compounds from PubChem. Using the best classification models for antibiotic and antitumor activities a data set of marine and microbial natural products from the AntiMarin database were screened—57 and 16 new lead compounds for antibiotic and antitumor drug design were proposed, respectively. All compounds proposed by our approach are classified as non-antibiotic and non-antitumor compounds in the AntiMarin database. Recently several of the lead-like compounds proposed by us were reported as being active in the literature. PMID:24473174

Maximum unbiased validation (MUV) data sets for virtual screening based on PubChem bioactivity data.

PubMed

Rohrer, Sebastian G; Baumann, Knut

2009-02-01

Refined nearest neighbor analysis was recently introduced for the analysis of virtual screening benchmark data sets. It constitutes a technique from the field of spatial statistics and provides a mathematical framework for the nonparametric analysis of mapped point patterns. Here, refined nearest neighbor analysis is used to design benchmark data sets for virtual screening based on PubChem bioactivity data. A workflow is devised that purges data sets of compounds active against pharmaceutically relevant targets from unselective hits. Topological optimization using experimental design strategies monitored by refined nearest neighbor analysis functions is applied to generate corresponding data sets of actives and decoys that are unbiased with regard to analogue bias and artificial enrichment. These data sets provide a tool for Maximum Unbiased Validation (MUV) of virtual screening methods. The data sets and a software package implementing the MUV design workflow are freely available at http://www.pharmchem.tu-bs.de/lehre/baumann/MUV.html.

Docking analysis of verteporfin with YAP WW domain

PubMed Central

Kandoussi, Ilham; Lakhlili, Wiame; Taoufik, Jamal; Ibrahimi, Azeddine

2017-01-01

The YAP oncogene is a known cancer target. Therefore, it is of interest to understand the molecular docking interaction of verteporfin (a derivative of benzo-porphyrin) with the WW domain of YAP (clinically used for photo-dynamic therapy in macular degeneration) as a potential WW domain-ligand modulator by inhibition. A homology protein SWISS MODEL of the human YAP protein was constructed to dock (using AutoDock vina) with the PubChem verteporfin structure for interaction analysis. The docking result shows the possibilities of verteporfin interaction with the oncogenic transcription cofactor YAP having WW1 and WW2 domains. Thus, the ability of verteporfin to bind with the YAP WW domain having modulator activity is implied in this analysis. PMID:28943729

An Informatics Approach to Evaluating Combined Chemical Exposures from Consumer Products: A Case Study of Asthma-Associated Chemicals and Potential Endocrine Disruptors

PubMed Central

Gabb, Henry A.; Blake, Catherine

2016-01-01

Background: Simultaneous or sequential exposure to multiple environmental stressors can affect chemical toxicity. Cumulative risk assessments consider multiple stressors but it is impractical to test every chemical combination to which people are exposed. New methods are needed to prioritize chemical combinations based on their prevalence and possible health impacts. Objectives: We introduce an informatics approach that uses publicly available data to identify chemicals that co-occur in consumer products, which account for a significant proportion of overall chemical load. Methods: Fifty-five asthma-associated and endocrine disrupting chemicals (target chemicals) were selected. A database of 38,975 distinct consumer products and 32,231 distinct ingredient names was created from online sources, and PubChem and the Unified Medical Language System were used to resolve synonymous ingredient names. Synonymous ingredient names are different names for the same chemical (e.g., vitamin E and tocopherol). Results: Nearly one-third of the products (11,688 products, 30%) contained ≥ 1 target chemical and 5,229 products (13%) contained > 1. Of the 55 target chemicals, 31 (56%) appear in ≥ 1 product and 19 (35%) appear under more than one name. The most frequent three-way chemical combination (2-phenoxyethanol, methyl paraben, and ethyl paraben) appears in 1,059 products. Further work is needed to assess combined chemical exposures related to the use of multiple products. Conclusions: The informatics approach increased the number of products considered in a traditional analysis by two orders of magnitude, but missing/incomplete product labels can limit the effectiveness of this approach. Such an approach must resolve synonymy to ensure that chemicals of interest are not missed. Commonly occurring chemical combinations can be used to prioritize cumulative toxicology risk assessments. Citation: Gabb HA, Blake C. 2016. An informatics approach to evaluating combined chemical exposures from consumer products: a case study of asthma-associated chemicals and potential endocrine disruptors. Environ Health Perspect 124:1155–1165; http://dx.doi.org/10.1289/ehp.1510529 PMID:26955064

In silico design and screening of hypothetical MOF-74 analogs and their experimental synthesis

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

Witman, Matthew; Ling, Sanliang; Anderson, Samantha

2016-01-01

We present thein silico designof MOFs exhibiting 1-dimensional rod topologies by enumerating MOF-74-type analogs based on the PubChem Compounds database. We simulate the adsorption behavior of CO 2in the generated analogs and experimentally validate a novel MOF-74 analog, Mg 2(olsalazine).

Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry

PubMed Central

Kind, Tobias; Fiehn, Oliver

2007-01-01

Background Structure elucidation of unknown small molecules by mass spectrometry is a challenge despite advances in instrumentation. The first crucial step is to obtain correct elemental compositions. In order to automatically constrain the thousands of possible candidate structures, rules need to be developed to select the most likely and chemically correct molecular formulas. Results An algorithm for filtering molecular formulas is derived from seven heuristic rules: (1) restrictions for the number of elements, (2) LEWIS and SENIOR chemical rules, (3) isotopic patterns, (4) hydrogen/carbon ratios, (5) element ratio of nitrogen, oxygen, phosphor, and sulphur versus carbon, (6) element ratio probabilities and (7) presence of trimethylsilylated compounds. Formulas are ranked according to their isotopic patterns and subsequently constrained by presence in public chemical databases. The seven rules were developed on 68,237 existing molecular formulas and were validated in four experiments. First, 432,968 formulas covering five million PubChem database entries were checked for consistency. Only 0.6% of these compounds did not pass all rules. Next, the rules were shown to effectively reducing the complement all eight billion theoretically possible C, H, N, S, O, P-formulas up to 2000 Da to only 623 million most probable elemental compositions. Thirdly 6,000 pharmaceutical, toxic and natural compounds were selected from DrugBank, TSCA and DNP databases. The correct formulas were retrieved as top hit at 80–99% probability when assuming data acquisition with complete resolution of unique compounds and 5% absolute isotope ratio deviation and 3 ppm mass accuracy. Last, some exemplary compounds were analyzed by Fourier transform ion cyclotron resonance mass spectrometry and by gas chromatography-time of flight mass spectrometry. In each case, the correct formula was ranked as top hit when combining the seven rules with database queries. Conclusion The seven rules enable an automatic exclusion of molecular formulas which are either wrong or which contain unlikely high or low number of elements. The correct molecular formula is assigned with a probability of 98% if the formula exists in a compound database. For truly novel compounds that are not present in databases, the correct formula is found in the first three hits with a probability of 65–81%. Corresponding software and supplemental data are available for downloads from the authors' website. PMID:17389044

Novel Phenotypic Outcomes Identified for a Public Collection of Approved Drugs from a Publicly Accessible Panel of Assays

PubMed Central

Oliver, Sarah; Willard, Francis S.; Heidler, Steven; Peery, Robert B.; Oler, Jennifer; Chu, Shaoyou; Southall, Noel; Dexheimer, Thomas S.; Smallwood, Jeffrey; Huang, Ruili; Guha, Rajarshi; Jadhav, Ajit; Cox, Karen; Austin, Christopher P.; Simeonov, Anton; Sittampalam, G. Sitta; Husain, Saba; Franklin, Natalie; Wild, David J.; Yang, Jeremy J.; Sutherland, Jeffrey J.; Thomas, Craig J.

2015-01-01

Phenotypic assays have a proven track record for generating leads that become first-in-class therapies. Whole cell assays that inform on a phenotype or mechanism also possess great potential in drug repositioning studies by illuminating new activities for the existing pharmacopeia. The National Center for Advancing Translational Sciences (NCATS) pharmaceutical collection (NPC) is the largest reported collection of approved small molecule therapeutics that is available for screening in a high-throughput setting. Via a wide-ranging collaborative effort, this library was analyzed in the Open Innovation Drug Discovery (OIDD) phenotypic assay modules publicly offered by Lilly. The results of these tests are publically available online at www.ncats.nih.gov/expertise/preclinical/pd2 and via the PubChem Database (https://pubchem.ncbi.nlm.nih.gov/) (AID 1117321). Phenotypic outcomes for numerous drugs were confirmed, including sulfonylureas as insulin secretagogues and the anti-angiogenesis actions of multikinase inhibitors sorafenib, axitinib and pazopanib. Several novel outcomes were also noted including the Wnt potentiating activities of rotenone and the antifolate class of drugs, and the anti-angiogenic activity of cetaben. PMID:26177200

Novel Phenotypic Outcomes Identified for a Public Collection of Approved Drugs from a Publicly Accessible Panel of Assays.

PubMed

Lee, Jonathan A; Shinn, Paul; Jaken, Susan; Oliver, Sarah; Willard, Francis S; Heidler, Steven; Peery, Robert B; Oler, Jennifer; Chu, Shaoyou; Southall, Noel; Dexheimer, Thomas S; Smallwood, Jeffrey; Huang, Ruili; Guha, Rajarshi; Jadhav, Ajit; Cox, Karen; Austin, Christopher P; Simeonov, Anton; Sittampalam, G Sitta; Husain, Saba; Franklin, Natalie; Wild, David J; Yang, Jeremy J; Sutherland, Jeffrey J; Thomas, Craig J

2015-01-01

Phenotypic assays have a proven track record for generating leads that become first-in-class therapies. Whole cell assays that inform on a phenotype or mechanism also possess great potential in drug repositioning studies by illuminating new activities for the existing pharmacopeia. The National Center for Advancing Translational Sciences (NCATS) pharmaceutical collection (NPC) is the largest reported collection of approved small molecule therapeutics that is available for screening in a high-throughput setting. Via a wide-ranging collaborative effort, this library was analyzed in the Open Innovation Drug Discovery (OIDD) phenotypic assay modules publicly offered by Lilly. The results of these tests are publically available online at www.ncats.nih.gov/expertise/preclinical/pd2 and via the PubChem Database (https://pubchem.ncbi.nlm.nih.gov/) (AID 1117321). Phenotypic outcomes for numerous drugs were confirmed, including sulfonylureas as insulin secretagogues and the anti-angiogenesis actions of multikinase inhibitors sorafenib, axitinib and pazopanib. Several novel outcomes were also noted including the Wnt potentiating activities of rotenone and the antifolate class of drugs, and the anti-angiogenic activity of cetaben.

Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure–Activity Relationship Models of Animal Carcinogenicity

PubMed Central

Zhu, Hao; Rusyn, Ivan; Richard, Ann; Tropsha, Alexander

2008-01-01

Background To develop efficient approaches for rapid evaluation of chemical toxicity and human health risk of environmental compounds, the National Toxicology Program (NTP) in collaboration with the National Center for Chemical Genomics has initiated a project on high-throughput screening (HTS) of environmental chemicals. The first HTS results for a set of 1,408 compounds tested for their effects on cell viability in six different cell lines have recently become available via PubChem. Objectives We have explored these data in terms of their utility for predicting adverse health effects of the environmental agents. Methods and results Initially, the classification k nearest neighbor (kNN) quantitative structure–activity relationship (QSAR) modeling method was applied to the HTS data only, for a curated data set of 384 compounds. The resulting models had prediction accuracies for training, test (containing 275 compounds together), and external validation (109 compounds) sets as high as 89%, 71%, and 74%, respectively. We then asked if HTS results could be of value in predicting rodent carcinogenicity. We identified 383 compounds for which data were available from both the Berkeley Carcinogenic Potency Database and NTP–HTS studies. We found that compounds classified by HTS as “actives” in at least one cell line were likely to be rodent carcinogens (sensitivity 77%); however, HTS “inactives” were far less informative (specificity 46%). Using chemical descriptors only, kNN QSAR modeling resulted in 62.3% prediction accuracy for rodent carcinogenicity applied to this data set. Importantly, the prediction accuracy of the model was significantly improved (72.7%) when chemical descriptors were augmented by HTS data, which were regarded as biological descriptors. Conclusions Our studies suggest that combining NTP–HTS profiles with conventional chemical descriptors could considerably improve the predictive power of computational approaches in toxicology. PMID:18414635

Astragaloside IV attenuates inflammatory cytokines by inhibiting TLR4/NF-кB signaling pathway in isoproterenol-induced myocardial hypertrophy.

PubMed

Yang, Juan; Wang, Hong-Xin; Zhang, Ying-Jie; Yang, Yu-Hong; Lu, Mei-Li; Zhang, Jing; Li, Sheng-Tao; Zhang, Su-Ping; Li, Guang

2013-10-25

Astragaloside IV(As IV) is one of the main effective components isolated from the traditional Chinese medical herb Astragalus membranaceus. The protective effect of Astragalus membranaceus on myocardial hypertrophy has been extensively proved. To test the hypothesis that Astragaloside IV can ameliorate the myocardial hypertrophy and inflammatory effect induced by β-adrenergic hyperactivity, we carried out in vivo and in vitro experiments. In in vivo study, the isoproterenol(Iso) (5mg.kg -1 .d -1 ) was used as a model of myocardial hypertrophy by intraperitoneal injection. SD rats were randomly assigned to following six groups: A:the control；B: Iso group；C: Iso plus As IV 20mg.kg -1 .d -1 ；D: Iso plus As IV 40mg.kg -1 .d -1 ；E: Iso plus As IV 80mg.kg -1 .d -1 ；F: Iso plus Propranolol 40mg.kg -1 .d -1 . In in vitro study, cultured neonatal rat cardiomyocytes were pretreated with As IV(3, 10, 30μmol.L -1 ), Propranolol(2μmol.L -1 ) and BAY11-7082(5μmol.L -1 ) for 30minutes, and then incubated with Iso(10μmol.L -1 ) for 48 hours. For the rats in each group, the heart mass index (HMI) and the left ventricular mass index (LVMI) were measured. To measure the transverse diameter of left ventricular myocardial cells (TDM), the hematoxylin-eosin (HE) staining method was applied. In addition, the volume and the total protein content of cardiomyocytes were measured, the mRNA expression of ANP and TLR4 were quantified by RT-PCR, the protein expression of TLR4, IκBα and p65 were quantified by Western blot, and the level of TNF-α and IL-6 were measured by ELISA. In vivo: Comparing the Iso group to the control, the HMI, LVMI, TDM were significantly increased; the protein expression of TLR4 and p65 were increased, while the IκBα were decreased; the expression of ANP, TLR4 mRNA, and TNF-α, IL-6 in serum were significantly increased. These changes could be partly prevented by As IV and Pro. In vitro: the over-expression of the cell size, total protein content could remarkably down-regulated by As IV and Pro, and the results of RT-PCR, Western blot and ELISA were similar to those of in vivo. The results of these studies indicate that Astragaloside IV has good protective effect on myocardial hypertrophy induced by isoproterenol. More specifically, the cardioprotection is related to inhibiting the TLR4/NF-кB signaling pathway and the attenuating inflammatory effect. Astragaloside IV (PubChem CID:122690); BAY 11-7082 (PubChem CID:5353431); Propranolol (PubChem CID:62882); Isoproterenol (PubChem CID: 5806). © 2013 The Authors. Published by Elsevier Ireland Ltd All rights reserved.

GPCR ontology: development and application of a G protein-coupled receptor pharmacology knowledge framework.

PubMed

Przydzial, Magdalena J; Bhhatarai, Barun; Koleti, Amar; Vempati, Uma; Schürer, Stephan C

2013-12-15

Novel tools need to be developed to help scientists analyze large amounts of available screening data with the goal to identify entry points for the development of novel chemical probes and drugs. As the largest class of drug targets, G protein-coupled receptors (GPCRs) remain of particular interest and are pursued by numerous academic and industrial research projects. We report the first GPCR ontology to facilitate integration and aggregation of GPCR-targeting drugs and demonstrate its application to classify and analyze a large subset of the PubChem database. The GPCR ontology, based on previously reported BioAssay Ontology, depicts available pharmacological, biochemical and physiological profiles of GPCRs and their ligands. The novelty of the GPCR ontology lies in the use of diverse experimental datasets linked by a model to formally define these concepts. Using a reasoning system, GPCR ontology offers potential for knowledge-based classification of individuals (such as small molecules) as a function of the data. The GPCR ontology is available at http://www.bioassayontology.org/bao_gpcr and the National Center for Biomedical Ontologies Web site.

Molecular docking studies on tetrahydroimidazo-[4,5,1-jk][1,4]-benzodiazepinone (TIBO) derivatives as HIV-1 NNRT inhibitors

NASA Astrophysics Data System (ADS)

Sapre, Nitin S.; Gupta, Swagata; Pancholi, Nilanjana; Sapre, Neelima

2008-02-01

At present, chemotherapy seems to be the main weapon in the arsenal of remedies for the ongoing crusade against AIDS. The mode of binding of the TIBO family of inhibitors has been of interest because these compounds do not fit the two-hinged-ring model as generally observed in the NNRTIs. Flexible docking simulations were performed with a series of 53 TIBO derivatives as NNRTIs. Binding preferences as well as the structural and energetic factors associated with them were studied. A good correlation ( r 2 = 0.849, q 2 = 0.843) was observed between the biological activity and binding affinity of the compounds which suggest that the identified binding conformations of these inhibitors are reliable. Further screening of PubChem database yielded novel scaffolds. Our studies suggest that modifications to the TIBO group of inhibitors might enhance their binding efficacy and hence, potentially, their therapeutic utility.

Searching for substructures in fragment spaces.

PubMed

Ehrlich, Hans-Christian; Volkamer, Andrea; Rarey, Matthias

2012-12-21

A common task in drug development is the selection of compounds fulfilling specific structural features from a large data pool. While several methods that iteratively search through such data sets exist, their application is limited compared to the infinite character of molecular space. The introduction of the concept of fragment spaces (FSs), which are composed of molecular fragments and their connection rules, made the representation of large combinatorial data sets feasible. At the same time, search algorithms face the problem of structural features spanning over multiple fragments. Due to the combinatorial nature of FSs, an enumeration of all products is impossible. In order to overcome these time and storage issues, we present a method that is able to find substructures in FSs without explicit product enumeration. This is accomplished by splitting substructures into subsubstructures and mapping them onto fragments with respect to fragment connectivity rules. The method has been evaluated on three different drug discovery scenarios considering the exploration of a molecule class, the elaboration of decoration patterns for a molecular core, and the exhaustive query for peptides in FSs. FSs can be searched in seconds, and found products contain novel compounds not present in the PubChem database which may serve as hints for new lead structures.

Signature molecular descriptor : advanced applications.

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

Visco, Donald Patrick, Jr.

In this work we report on the development of the Signature Molecular Descriptor (or Signature) for use in the solution of inverse design problems as well as in highthroughput screening applications. The ultimate goal of using Signature is to identify novel and non-intuitive chemical structures with optimal predicted properties for a given application. We demonstrate this in three studies: green solvent design, glucocorticoid receptor ligand design and the design of inhibitors for Factor XIa. In many areas of engineering, compounds are designed and/or modified in incremental ways which rely upon heuristics or institutional knowledge. Often multiple experiments are performed andmore » the optimal compound is identified in this brute-force fashion. Perhaps a traditional chemical scaffold is identified and movement of a substituent group around a ring constitutes the whole of the design process. Also notably, a chemical being evaluated in one area might demonstrate properties very attractive in another area and serendipity was the mechanism for solution. In contrast to such approaches, computer-aided molecular design (CAMD) looks to encompass both experimental and heuristic-based knowledge into a strategy that will design a molecule on a computer to meet a given target. Depending on the algorithm employed, the molecule which is designed might be quite novel (re: no CAS registration number) and/or non-intuitive relative to what is known about the problem at hand. While CAMD is a fairly recent strategy (dating to the early 1980s), it contains a variety of bottlenecks and limitations which have prevented the technique from garnering more attention in the academic, governmental and industrial institutions. A main reason for this is how the molecules are described in the computer. This step can control how models are developed for the properties of interest on a given problem as well as how to go from an output of the algorithm to an actual chemical structure. This report provides details on a technique to describe molecules on a computer, called Signature, as well as the computer-aided molecule design algorithm built around Signature. Two applications are provided of the CAMD algorithm with Signature. The first describes the design of green solvents based on data in the GlaxoSmithKline (GSK) Solvent Selection Guide. The second provides novel non-steroidal glucocorticoid receptor ligands with some optimally predicted properties. In addition to using the CAMD algorithm with Signature, it is demonstrated how to employ Signature in a high-throughput screening study. Here, after classifying both active and inactive inhibitors for the protein Factor XIa using Signature, the model developed is used to screen a large, publicly-available database called PubChem for the most active compounds.« less

Identification of potential glutaminyl cyclase inhibitors from lead-like libraries by in silico and in vitro fragment-based screening.

PubMed

Szaszkó, Mária; Hajdú, István; Flachner, Beáta; Dobi, Krisztina; Magyar, Csaba; Simon, István; Lőrincz, Zsolt; Kapui, Zoltán; Pázmány, Tamás; Cseh, Sándor; Dormán, György

2017-02-01

A glutaminyl cyclase (QC) fragment library was in silico selected by disconnection of the structure of known QC inhibitors and by lead-like 2D virtual screening of the same set. The resulting fragment library (204 compounds) was acquired from commercial suppliers and pre-screened by differential scanning fluorimetry followed by functional in vitro assays. In this way, 10 fragment hits were identified ([Formula: see text]5 % hit rate, best inhibitory activity: 16 [Formula: see text]). The in vitro hits were then docked to the active site of QC, and the best scoring compounds were analyzed for binding interactions. Two fragments bound to different regions in a complementary manner, and thus, linking those fragments offered a rational strategy to generate novel QC inhibitors. Based on the structure of the virtual linked fragment, a 77-membered QC target focused library was selected from vendor databases and docked to the active site of QC. A PubChem search confirmed that the best scoring analogues are novel, potential QC inhibitors.

Molecular docking studies of banana flower flavonoids as insulin receptor tyrosine kinase activators as a cure for diabetes mellitus.

PubMed

Ganugapati, Jayasree; Baldwa, Aashish; Lalani, Sarfaraz

2012-01-01

Diabetes mellitus is a metabolic disorder caused due to insulin deficiency. Banana flower is a rich source of flavonoids that exhibit anti diabetic activity. Insulin receptor is a tetramer that belongs to a family of receptor tyrosine kinases. It contains two alpha subunits that form the extracellular domain and two beta subunits that constitute the intracellular tyrosine kinase domain. Insulin binds to the extracellular region of the receptor and causes conformational changes that lead to the activation of the tyrosine kinase. This leads to autophosphorylation, a step that is crucial in insulin signaling pathway. Hence, compounds that augment insulin receptor tyrosine kinase activity would be useful in the treatment of diabetes mellitus. The 3D structure of IR tyrosine kinase was obtained from PDB database. The list of flavonoids found in banana flower was obtained from USDA database. The structures of the flavonoids were obtained from NCBI Pubchem. Docking analysis of the flavonoids was performed using Autodock 4.0 and Autodock Vina. The results indicate that few of the flavonoids may be potential activators of IR tyrosine kinase.

Molecular Imaging and Contrast Agent Database (MICAD): evolution and progress.

PubMed

Chopra, Arvind; Shan, Liang; Eckelman, W C; Leung, Kam; Latterner, Martin; Bryant, Stephen H; Menkens, Anne

2012-02-01

The purpose of writing this review is to showcase the Molecular Imaging and Contrast Agent Database (MICAD; www.micad.nlm.nih.gov ) to students, researchers, and clinical investigators interested in the different aspects of molecular imaging. This database provides freely accessible, current, online scientific information regarding molecular imaging (MI) probes and contrast agents (CA) used for positron emission tomography, single-photon emission computed tomography, magnetic resonance imaging, X-ray/computed tomography, optical imaging and ultrasound imaging. Detailed information on >1,000 agents in MICAD is provided in a chapter format and can be accessed through PubMed. Lists containing >4,250 unique MI probes and CAs published in peer-reviewed journals and agents approved by the United States Food and Drug Administration as well as a comma separated values file summarizing all chapters in the database can be downloaded from the MICAD homepage. Users can search for agents in MICAD on the basis of imaging modality, source of signal/contrast, agent or target category, pre-clinical or clinical studies, and text words. Chapters in MICAD describe the chemical characteristics (structures linked to PubChem), the in vitro and in vivo activities, and other relevant information regarding an imaging agent. All references in the chapters have links to PubMed. A Supplemental Information Section in each chapter is available to share unpublished information regarding an agent. A Guest Author Program is available to facilitate rapid expansion of the database. Members of the imaging community registered with MICAD periodically receive an e-mail announcement (eAnnouncement) that lists new chapters uploaded to the database. Users of MICAD are encouraged to provide feedback, comments, or suggestions for further improvement of the database by writing to the editors at micad@nlm.nih.gov.

Molecular Imaging and Contrast Agent Database (MICAD): Evolution and Progress

PubMed Central

Chopra, Arvind; Shan, Liang; Eckelman, W. C.; Leung, Kam; Latterner, Martin; Bryant, Stephen H.; Menkens, Anne

2011-01-01

The purpose of writing this review is to showcase the Molecular Imaging and Contrast Agent Database (MICAD; www.micad.nlm.nih.gov) to students, researchers and clinical investigators interested in the different aspects of molecular imaging. This database provides freely accessible, current, online scientific information regarding molecular imaging (MI) probes and contrast agents (CA) used for positron emission tomography, single-photon emission computed tomography, magnetic resonance imaging, x-ray/computed tomography, optical imaging and ultrasound imaging. Detailed information on >1000 agents in MICAD is provided in a chapter format and can be accessed through PubMed. Lists containing >4250 unique MI probes and CAs published in peer-reviewed journals and agents approved by the United States Food and Drug Administration (FDA) as well as a CSV file summarizing all chapters in the database can be downloaded from the MICAD homepage. Users can search for agents in MICAD on the basis of imaging modality, source of signal/contrast, agent or target category, preclinical or clinical studies, and text words. Chapters in MICAD describe the chemical characteristics (structures linked to PubChem), the in vitro and in vivo activities and other relevant information regarding an imaging agent. All references in the chapters have links to PubMed. A Supplemental Information Section in each chapter is available to share unpublished information regarding an agent. A Guest Author Program is available to facilitate rapid expansion of the database. Members of the imaging community registered with MICAD periodically receive an e-mail announcement (eAnnouncement) that lists new chapters uploaded to the database. Users of MICAD are encouraged to provide feedback, comments or suggestions for further improvement of the database by writing to the editors at: micad@nlm.nih.gov PMID:21989943

Identification of small-molecule inhibitors of the colorectal cancer oncogene Krüppel-like factor 5 expression by ultrahigh-throughput screening.

PubMed

Bialkowska, Agnieszka B; Crisp, Melissa; Bannister, Thomas; He, Yuanjun; Chowdhury, Sarwat; Schürer, Stephan; Chase, Peter; Spicer, Timothy; Madoux, Franck; Tian, Chenlu; Hodder, Peter; Zaharevitz, Daniel; Yang, Vincent W

2011-11-01

The transcription factor Krüppel-like factor 5 (KLF5) is primarily expressed in the proliferative zone of the mammalian intestinal epithelium, where it regulates cell proliferation. Studies showed that inhibition of KLF5 expression reduces proliferation rates in human colorectal cancer cells and intestinal tumor formation in mice. To identify chemical probes that decrease levels of KLF5, we used cell-based ultrahigh-throughput screening (uHTS) to test compounds in the public domain of NIH, the Molecular Libraries Probe Production Centers Network library. The primary screen involved luciferase assays in the DLD-1/pGL4.18hKLF5p cell line, which stably expressed a luciferase reporter driven by the human KLF5 promoter. A cytotoxicity counterscreen was done in the rat intestinal epithelial cell line, IEC-6. We identified 97 KLF5-selective compounds with EC(50) < 10 μmol/L for KLF5 inhibition and EC(50) > 10 μmol/L for IEC-6 cytotoxicity. The two most potent compounds, CIDs (PubChem Compound IDs) 439501 and 5951923, were further characterized on the basis of computational, Western blot, and cell viability analyses. Both of these compounds, and two newly synthesized structural analogs of CID 5951923, significantly reduced endogenous KLF5 protein levels and decreased viability of several colorectal cancer cell lines without any apparent impact on IEC-6 cells. Finally, when tested in the NCI-60 panel of human cancer cell lines, compound CID 5951923 was selectively active against colon cancer cells. Our results show the feasibility of uHTS in identifying novel compounds that inhibit colorectal cancer cell proliferation by targeting KLF5.

Identification of Small-Molecule Inhibitors of the Colorectal Cancer Oncogene Krüppel-Like Factor 5 Expression by Ultrahigh-Throughput Screening

PubMed Central

Bialkowska, Agnieszka B.; Crisp, Melissa; Bannister, Thomas; He, Yuanjun; Chowdhury, Sarwat; Schürer, Stephan; Chase, Peter; Spicer, Timothy; Madoux, Franck; Tian, Chenlu; Hodder, Peter; Zaharevitz, Daniel; Yang, Vincent W.

2011-01-01

The transcription factor Krüppel-like factor 5 (KLF5) is primarily expressed in the proliferative zone of the mammalian intestinal epithelium where it regulates cell proliferation. Studies showed that inhibition of KLF5 expression reduces proliferation rates in human colorectal cancer cells and intestinal tumor formation in mice. To identify chemical probes that decrease levels of KLF5, we used cell-based ultrahigh-throughput screening (uHTS) to test compounds in the NIH’s public domain, the Molecular Libraries Probe Production Centers Network (MLPCN) library. The primary screen involved luciferase assays in the DLD-1/pGL4.18hKLF5p cell line, which stably expressed a luciferase reporter driven by the human KLF5 promoter. A cytotoxicity counterscreen was performed in the rat intestinal epithelial cell line, IEC-6. We identified 97 KLF5-selective compounds with EC50<10 µM for KLF5 inhibition and EC50>10 µM for IEC-6 cytotoxicity. The two most potent compounds, CIDs (PubChem Compound IDs) 439501 and 5951923, were further characterized based on computational, Western blot, and cell viability analyses. Both of these compounds and two newly-synthesized structural analogs of CID 5951923 significantly reduced endogenous KLF5 protein levels and decreased viability of several colorectal cancer cell lines without any apparent impact on IEC-6 cells. Finally, when tested in the NCI-60 panel of human cancer cell lines, compound CID 5951923 was selectively active against colon cancer cells. Our results demonstrate the feasibility of uHTS in identifying novel compounds that inhibit colorectal cancer cell proliferation by targeting KLF5. PMID:21885866

Database resources of the National Center for Biotechnology Information

PubMed Central

2015-01-01

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (Bookshelf, PubMed Central (PMC) and PubReader); medical genetics (ClinVar, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen); genes and genomics (BioProject, BioSample, dbSNP, dbVar, Epigenomics, Gene, Gene Expression Omnibus (GEO), Genome, HomoloGene, the Map Viewer, Nucleotide, PopSet, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser, Trace Archive and UniGene); and proteins and chemicals (Biosystems, COBALT, the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB), Protein Clusters, Protein and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for many of these databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at http://www.ncbi.nlm.nih.gov. PMID:25398906

Database resources of the National Center for Biotechnology Information

PubMed Central

2016-01-01

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (PubMed Central (PMC), Bookshelf and PubReader), health (ClinVar, dbGaP, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen), genomes (BioProject, Assembly, Genome, BioSample, dbSNP, dbVar, Epigenomics, the Map Viewer, Nucleotide, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser and the Trace Archive), genes (Gene, Gene Expression Omnibus (GEO), HomoloGene, PopSet and UniGene), proteins (Protein, the Conserved Domain Database (CDD), COBALT, Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB) and Protein Clusters) and chemicals (Biosystems and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for most of these databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:26615191

QSAR Classification Model for Antibacterial Compounds and Its Use in Virtual Screening

DTIC Science & Technology

2012-09-26

test set molecules that were not used to train the models . This allowed us to more accurately estimate the prediction power of the models . As...pathogens and deposited in PubChem Bioassays. Ultimately, the main purpose of this model is to make predictions , based on known antibacterial and non...the model built form the remaining compounds is used to predict the left out compound. Once all the compounds pass through this cycle of prediction , a

Predicting Mouse Liver Microsomal Stability with “Pruned” Machine Learning Models and Public Data

PubMed Central

Perryman, Alexander L.; Stratton, Thomas P.; Ekins, Sean; Freundlich, Joel S.

2015-01-01

Purpose Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Methods Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). Results “Pruning” out the moderately unstable/moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 hour. Conclusions Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources. PMID:26415647

Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data.

PubMed

Perryman, Alexander L; Stratton, Thomas P; Ekins, Sean; Freundlich, Joel S

2016-02-01

Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). "Pruning" out the moderately unstable / moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 h. Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources.

Computational analysis of EBNA1 ``druggability'' suggests novel insights for Epstein-Barr virus inhibitor design

NASA Astrophysics Data System (ADS)

Gianti, Eleonora; Messick, Troy E.; Lieberman, Paul M.; Zauhar, Randy J.

2016-04-01

The Epstein-Barr Nuclear Antigen 1 (EBNA1) is a critical protein encoded by the Epstein-Barr Virus (EBV). During latent infection, EBNA1 is essential for DNA replication and transcription initiation of viral and cellular genes and is necessary to immortalize primary B-lymphocytes. Nonetheless, the concept of EBNA1 as drug target is novel. Two EBNA1 crystal structures are publicly available and the first small-molecule EBNA1 inhibitors were recently discovered. However, no systematic studies have been reported on the structural details of EBNA1 "druggable" binding sites. We conducted computational identification and structural characterization of EBNA1 binding pockets, likely to accommodate ligand molecules (i.e. "druggable" binding sites). Then, we validated our predictions by docking against a set of compounds previously tested in vitro for EBNA1 inhibition (PubChem AID-2381). Finally, we supported assessments of pocket druggability by performing induced fit docking and molecular dynamics simulations paired with binding affinity predictions by Molecular Mechanics Generalized Born Surface Area calculations for a number of hits belonging to druggable binding sites. Our results establish EBNA1 as a target for drug discovery, and provide the computational evidence that active AID-2381 hits disrupt EBNA1:DNA binding upon interacting at individual sites. Lastly, structural properties of top scoring hits are proposed to support the rational design of the next generation of EBNA1 inhibitors.

Discovery, Synthesis, And Structure-Based Optimization of a Series of N-(tert-Butyl)-2-(N-arylamido)-2-(pyridin-3-yl) Acetamides (ML188) as Potent Noncovalent Small Molecule Inhibitors of the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) 3CL Protease

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

Jacobs, Jon; Grum-Tokars, Valerie; Zhou, Ya

A high-throughput screen of the NIH molecular libraries sample collection and subsequent optimization of a lead dipeptide-like series of severe acute respiratory syndrome (SARS) main protease (3CLpro) inhibitors led to the identification of probe compound ML188 (16-(R), (R)-N-(4-(tert-butyl)phenyl)-N-(2-(tert-butylamino)-2-oxo-1-(pyridin-3-yl)ethyl)furan-2-carboxamide, Pubchem CID: 46897844). But, unlike the majority of reported coronavirus 3CLpro inhibitors that act via covalent modification of the enzyme, 16-(R) is a noncovalent SARS-CoV 3CLpro inhibitor with moderate MW and good enzyme and antiviral inhibitory activity. A multicomponent Ugi reaction was utilized to rapidly explore structure–activity relationships within S1', S1, and S2enzyme binding pockets. Moreover, the X-ray structure of SARS-CoV 3CLpromore » bound with 16-(R) was instrumental in guiding subsequent rounds of chemistry optimization. 16-(R) provides an excellent starting point for the further design and refinement of 3CLpro inhibitors that act by a noncovalent mechanism of action.« less

HIM-herbal ingredients in-vivo metabolism database.

PubMed

Kang, Hong; Tang, Kailin; Liu, Qi; Sun, Yi; Huang, Qi; Zhu, Ruixin; Gao, Jun; Zhang, Duanfeng; Huang, Chenggang; Cao, Zhiwei

2013-05-31

Herbal medicine has long been viewed as a valuable asset for potential new drug discovery and herbal ingredients' metabolites, especially the in vivo metabolites were often found to gain better pharmacological, pharmacokinetic and even better safety profiles compared to their parent compounds. However, these herbal metabolite information is still scattered and waiting to be collected. HIM database manually collected so far the most comprehensive available in-vivo metabolism information for herbal active ingredients, as well as their corresponding bioactivity, organs and/or tissues distribution, toxicity, ADME and the clinical research profile. Currently HIM contains 361 ingredients and 1104 corresponding in-vivo metabolites from 673 reputable herbs. Tools of structural similarity, substructure search and Lipinski's Rule of Five are also provided. Various links were made to PubChem, PubMed, TCM-ID (Traditional Chinese Medicine Information database) and HIT (Herbal ingredients' targets databases). A curated database HIM is set up for the in vivo metabolites information of the active ingredients for Chinese herbs, together with their corresponding bioactivity, toxicity and ADME profile. HIM is freely accessible to academic researchers at http://www.bioinformatics.org.cn/.

MLViS: A Web Tool for Machine Learning-Based Virtual Screening in Early-Phase of Drug Discovery and Development

PubMed Central

Korkmaz, Selcuk; Zararsiz, Gokmen; Goksuluk, Dincer

2015-01-01

Virtual screening is an important step in early-phase of drug discovery process. Since there are thousands of compounds, this step should be both fast and effective in order to distinguish drug-like and nondrug-like molecules. Statistical machine learning methods are widely used in drug discovery studies for classification purpose. Here, we aim to develop a new tool, which can classify molecules as drug-like and nondrug-like based on various machine learning methods, including discriminant, tree-based, kernel-based, ensemble and other algorithms. To construct this tool, first, performances of twenty-three different machine learning algorithms are compared by ten different measures, then, ten best performing algorithms have been selected based on principal component and hierarchical cluster analysis results. Besides classification, this application has also ability to create heat map and dendrogram for visual inspection of the molecules through hierarchical cluster analysis. Moreover, users can connect the PubChem database to download molecular information and to create two-dimensional structures of compounds. This application is freely available through www.biosoft.hacettepe.edu.tr/MLViS/. PMID:25928885

Analysis of Draize Eye Irritation Testing and its Prediction by Mining Publicly Available 2008–2014 REACH Data

PubMed Central

Luechtefeld, Thomas; Maertens, Alexandra; Russo, Daniel P.; Rovida, Costanza; Zhu, Hao; Hartung, Thomas

2017-01-01

Summary Public data from ECHA online dossiers on 9,801 substances encompassing 326,749 experimental key studies and additional information on classification and labeling were made computable. Eye irritation hazard, for which the rabbit Draize eye test still represents the reference method, was analyzed. Dossiers contained 9,782 Draize eye studies on 3,420 unique substances, indicating frequent retesting of substances. This allowed assessment of the test’s reproducibility based on all substances tested more than once. There was a 10% chance of a non-irritant evaluation after a prior severe-irritant result according to UN GHS classification criteria. The most reproducible outcomes were the results negative (94% reproducible) and severe eye irritant (73% reproducible). To evaluate whether other GHS categorizations predict eye irritation, we built a dataset of 5,629 substances (1,931 “irritant” and 3,698 “non-irritant”). The two best decision trees with up to three other GHS classifications resulted in balanced accuracies of 68% and 73%, i.e., in the rank order of the Draize rabbit eye test itself, but both use inhalation toxicity data (“May cause respiratory irritation”), which is not typically available. Next, a dataset of 929 substances with at least one Draize study was mapped to PubChem to compute chemical similarity using 2D conformational fingerprints and Tanimoto similarity. Using a minimum similarity of 0.7 and simple classification by the closest chemical neighbor resulted in balanced accuracy from 73% over 737 substances to 100% at a threshold of 0.975 over 41 substances. This represents a strong support of read-across and (Q)SAR approaches in this area. PMID:26863293

Using information from historical high-throughput screens to predict active compounds.

PubMed

Riniker, Sereina; Wang, Yuan; Jenkins, Jeremy L; Landrum, Gregory A

2014-07-28

Modern high-throughput screening (HTS) is a well-established approach for hit finding in drug discovery that is routinely employed in the pharmaceutical industry to screen more than a million compounds within a few weeks. However, as the industry shifts to more disease-relevant but more complex phenotypic screens, the focus has moved to piloting smaller but smarter chemically/biologically diverse subsets followed by an expansion around hit compounds. One standard method for doing this is to train a machine-learning (ML) model with the chemical fingerprints of the tested subset of molecules and then select the next compounds based on the predictions of this model. An alternative approach would be to take advantage of the wealth of bioactivity information contained in older (full-deck) screens using so-called HTS fingerprints, where each element of the fingerprint corresponds to the outcome of a particular assay, as input to machine-learning algorithms. We constructed HTS fingerprints using two collections of data: 93 in-house assays and 95 publicly available assays from PubChem. For each source, an additional set of 51 and 46 assays, respectively, was collected for testing. Three different ML methods, random forest (RF), logistic regression (LR), and naïve Bayes (NB), were investigated for both the HTS fingerprint and a chemical fingerprint, Morgan2. RF was found to be best suited for learning from HTS fingerprints yielding area under the receiver operating characteristic curve (AUC) values >0.8 for 78% of the internal assays and enrichment factors at 5% (EF(5%)) >10 for 55% of the assays. The RF(HTS-fp) generally outperformed the LR trained with Morgan2, which was the best ML method for the chemical fingerprint, for the majority of assays. In addition, HTS fingerprints were found to retrieve more diverse chemotypes. Combining the two models through heterogeneous classifier fusion led to a similar or better performance than the best individual model for all assays. Further validation using a pair of in-house assays and data from a confirmatory screen--including a prospective set of around 2000 compounds selected based on our approach--confirmed the good performance. Thus, the combination of machine-learning with HTS fingerprints and chemical fingerprints utilizes information from both domains and presents a very promising approach for hit expansion, leading to more hits. The source code used with the public data is provided.

Database resources of the National Center for Biotechnology Information.

PubMed

2016-01-04

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank(®) nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (PubMed Central (PMC), Bookshelf and PubReader), health (ClinVar, dbGaP, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen), genomes (BioProject, Assembly, Genome, BioSample, dbSNP, dbVar, Epigenomics, the Map Viewer, Nucleotide, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser and the Trace Archive), genes (Gene, Gene Expression Omnibus (GEO), HomoloGene, PopSet and UniGene), proteins (Protein, the Conserved Domain Database (CDD), COBALT, Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB) and Protein Clusters) and chemicals (Biosystems and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for most of these databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. Published by Oxford University Press on behalf of Nucleic Acids Research 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Database resources of the National Center for Biotechnology Information.

PubMed

2015-01-01

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank(®) nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (Bookshelf, PubMed Central (PMC) and PubReader); medical genetics (ClinVar, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen); genes and genomics (BioProject, BioSample, dbSNP, dbVar, Epigenomics, Gene, Gene Expression Omnibus (GEO), Genome, HomoloGene, the Map Viewer, Nucleotide, PopSet, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser, Trace Archive and UniGene); and proteins and chemicals (Biosystems, COBALT, the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB), Protein Clusters, Protein and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for many of these databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at http://www.ncbi.nlm.nih.gov. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Plant essential oils and allied volatile fractions as multifunctional additives in meat and fish-based food products: a review.

PubMed

Patel, Seema

2015-01-01

Essential oils are concentrated aromatic volatile compounds derived from botanicals by distillation or mechanical pressing. They play multiple, crucial roles as antioxidants, food pathogen inhibitors, shelf-life enhancers, texture promoters, organoleptic agents and toxicity-reducing agents. For their versatility, they appear promising as food preservatives. Several research findings in recent times have validated their potential as functional ingredients in meat and fish processing. Among the assortment of bioactive compounds in the essential oils, p-cymene, thymol, eugenol, carvacrol, isothiocyanate, cinnamaldehyde, cuminaldehyde, linalool, 1,8-cineol, α-pinene, α-terpineol, γ-terpinene, citral and methyl chavicol are most familiar. These terpenes (monoterpenes and sesquiterpenes) and phenolics (alcohols, esters, aldehydes and ketones) have been extracted from culinary herbs such as oregano, rosemary, basil, coriander, cumin, cinnamon, mint, sage and lavender as well as from trees such as myrtle, fir and eucalyptus. This review presents essential oils as alternatives to conventional chemical additives. Their synergistic actions with modified air packaging, irradiation, edible films, bacteriocins and plant byproducts are discussed. The decisive roles of metabolic engineering, microwave technology and metabolomics in quality and quantity augmentation of essential oil are briefly mooted. The limitations encountered and strategies to overcome them have been illuminated to pave way for their enhanced popularisation. The literature has been mined from scientific databases such as Pubmed, Pubchem, Scopus and SciFinder.

Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

PubMed

Satpathy, Raghunath; Guru, R K; Behera, R; Nayak, B

2015-01-01

Boswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here. To predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches. In this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the study. After energy minimization of the ligands various types of molecular descriptors were computed and corresponding two-dimensional quantitative structure activity relationship (QSAR) models were obtained by taking Andrews coefficient as the dependent variable. Different types of comparative analysis were used for QSAR study are multiple linear regression, partial least squares, support vector machines and artificial neural network. From the study geometrical descriptors shows the highest correlation coefficient, which indicates the binding factor of the compound. To evaluate the anticancer property molecular docking study of six selected ligands based on Andrews affinity were performed with nuclear factor-kappa protein kinase (Protein Data Bank ID 4G3D), which is an established therapeutic target for cancers. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound.

Virtual screening studies of Chinese medicine Coptidis Rhizoma as alpha7 nicotinic acetylcholine receptor agonists for treatment of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Xiang, Li; Xu, Youdong; Zhang, Yan; Meng, Xianli; Wang, Ping

2015-04-01

Alzheimer's disease (AD) is an age-related neurodegenerative disease. Extensive in vitro and in vivo experiments have proved that the decreased activity of the cholinergic neuron is responsible for the memory and cognition deterioration. The alpha7 nicotinic acetylcholine receptor (α7-nAChR) is proposed to a drug target of AD, and compounds which acting as α7-nAChR agonists are considered as candidates in AD treatment. Chinese medicine CoptidisRhizoma and its compounds are reported in various anti-AD effects. In this study, virtual screening, docking approaches and hydrogen bond analyses were applied to screen potential α7-nAChR agonists from CoptidisRhizome. The 3D structure of the protein was obtained from PDB database. 87 reported compounds were included in this research and their structures were accessed by NCBI Pubchem. Docking analysis of the compounds was performed using AutoDock 4.2 and AutoDock Vina. The images of the binding modes hydrogen bonds and the hydrophobic interaction were rendered with PyMOL1.5.0.4. and LigPlot+ respectively. Finally, N-tran-feruloyltyramine, isolariciresinol, flavanone, secoisolariciresinol, (+)-lariciresinol and dihydrochalcone, exhibited the lowest docking energy of protein-ligand complex. The results indicate these 6 compounds are potential α7 nAChR agonists, and expected to be effective in AD treatment.

Estimation of human percutaneous bioavailability for two novel brominated flame retardants, 2-ethylhexyl 2,3,4,5-tetrabromobenzoate (EH-TBB) and bis(2-ethylhexyl) tetrabromophthalate (BEH-TEBP)

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

Knudsen, Gabriel A., E-mail: gabriel.knudsen@nih.g

2-Ethylhexyl-2,3,4,5-tetrabromobenzoate (EH-TBB) and bis(2-ethylhexyl)tetrabromophthalate (BEH-TEBP) are novel brominated flame retardants used in consumer products. A parallelogram approach was used to predict human dermal absorption and flux for EH-TBB and BEH-TEBP. [{sup 14}C]-EH-TBB or [{sup 14}C]-BEH-TEBP was applied to human or rat skin at 100 nmol/cm{sup 2} using a flow-through system. Intact rats received analogous dermal doses. Treated skin was washed and tape-stripped to remove “unabsorbed” [{sup 14}C]-radioactivity after continuous exposure (24 h). “Absorbed” was quantified using dermally retained [{sup 14}C]-radioactivity; “penetrated” was calculated based on [{sup 14}C]-radioactivity in media (in vitro) or excreta + tissues (in vivo). Human skin absorbedmore » EH-TBB (24 ± 1%) while 0.2 ± 0.1% penetrated skin. Rat skin absorbed more (51 ± 10%) and was more permeable (2 ± 0.5%) to EH-TBB in vitro; maximal EH-TBB flux was 11 ± 7 and 102 ± 24 pmol-eq/cm{sup 2}/h for human and rat skin, respectively. In vivo, 27 ± 5% was absorbed and 13% reached systemic circulation after 24 h (maximum flux was 464 ± 65 pmol-eq/cm{sup 2}/h). BEH-TEBP in vitro penetrance was minimal (< 0.01%) for rat or human skin. BEH-TEBP absorption was 12 ± 11% for human skin and 41 ± 3% for rat skin. In vivo, total absorption was 27 ± 9%; 1.2% reached systemic circulation. In vitro maximal BEH-TEBP flux was 0.3 ± 0.2 and 1 ± 0.3 pmol-eq/cm{sup 2}/h for human and rat skin; in vivo maximum flux for rat skin was 16 ± 7 pmol-eq/cm{sup 2}/h. EH-TBB was metabolized in rat and human skin to tetrabromobenzoic acid. BEH-TEBP-derived [{sup 14}C]-radioactivity in the perfusion media could not be characterized. < 1% of the dose of EH-TBB and BEH-TEHP is estimated to reach the systemic circulation following human dermal exposure under the conditions tested. Chemical compounds studied in this article: 2-Ethylhexyl 2,3,4,5-tetrabromobenzoate (PubChem CID: 71316600; CAS No. 183658-27-7 FW: 549.92 g/mol logP{sub est}: 7.73–8.75 (12)) Abdallah et al., 2015a. Other published abbreviations for 2-ethylhexyl-2,3,4,5-tetrabromobenzoate are TBB EHTeBB or EHTBB Abdallah and Harrad, 2011. bis(2-ethylhexyl) tetrabromophthalate (PubChem CID: 117291; CAS No. 26040-51-7 FW: 706.14 g/mol logP{sub est}: 9.48-11.95 (12)). Other published abbreviations for bis(2-ethylhexyl)tetrabromophthalate are TeBrDEPH TBPH or BEHTBP. - Highlights: • Human skin maximal flux was 11 ± 7 (EH-TBB) & 0.3 ± 0.2 (BEH-TEBP) pmol-eq/cm{sup 2}/h. • Predicted systemic bioavailability was < 1% for either chemical after 24 h. • Skin retained EH-TBB & BEH-TEBP after 24 h dermal exposure. • EH-TBB was hydrolyzed to tetrabromobenzoic acid; BEH-TEBP was not metabolized. • Skin contact is an important route of human exposure to EH-TBB & BEH-TEBP.« less

NPACT: Naturally Occurring Plant-based Anti-cancer Compound-Activity-Target database

PubMed Central

Mangal, Manu; Sagar, Parul; Singh, Harinder; Raghava, Gajendra P. S.; Agarwal, Subhash M.

2013-01-01

Plant-derived molecules have been highly valued by biomedical researchers and pharmaceutical companies for developing drugs, as they are thought to be optimized during evolution. Therefore, we have collected and compiled a central resource Naturally Occurring Plant-based Anti-cancer Compound-Activity-Target database (NPACT, http://crdd.osdd.net/raghava/npact/) that gathers the information related to experimentally validated plant-derived natural compounds exhibiting anti-cancerous activity (in vitro and in vivo), to complement the other databases. It currently contains 1574 compound entries, and each record provides information on their structure, manually curated published data on in vitro and in vivo experiments along with reference for users referral, inhibitory values (IC50/ED50/EC50/GI50), properties (physical, elemental and topological), cancer types, cell lines, protein targets, commercial suppliers and drug likeness of compounds. NPACT can easily be browsed or queried using various options, and an online similarity tool has also been made available. Further, to facilitate retrieval of existing data, each record is hyperlinked to similar databases like SuperNatural, Herbal Ingredients’ Targets, Comparative Toxicogenomics Database, PubChem and NCI-60 GI50 data. PMID:23203877

Identifying Novel Type ZBGs and Nonhydroxamate HDAC Inhibitors Through a SVM Based Virtual Screening Approach.

PubMed

Liu, X H; Song, H Y; Zhang, J X; Han, B C; Wei, X N; Ma, X H; Cui, W K; Chen, Y Z

2010-05-17

Histone deacetylase inhibitors (HDACi) have been successfully used for the treatment of cancers and other diseases. Search for novel type ZBGs and development of non-hydroxamate HDACi has become a focus in current research. To complement this, it is desirable to explore a virtual screening (VS) tool capable of identifying different types of potential inhibitors from large compound libraries with high yields and low false-hit rates similar to HTS. This work explored the use of support vector machines (SVM) combined with our newly developed putative non-inhibitor generation method as such a tool. SVM trained by 702 pre-2008 hydroxamate HDACi and 64334 putative non-HDACi showed good yields and low false-hit rates in cross-validation test and independent test using 220 diverse types of HDACi reported since 2008. The SVM hit rates in scanning 13.56 M PubChem and 168K MDDR compounds are comparable to HTS rates. Further structural analysis of SVM virtual hits suggests its potential for identification of non-hydroxamate HDACi. From this analysis, a series of novel ZBG and cap groups were proposed for HDACi design. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

S-adenosyl-L-methionine analogs as enhanced methyl donors: Towards novel epigenetic regulators

NASA Astrophysics Data System (ADS)

Jerbi, Jihène; Springborg, Michael; den-Haan, Helena; Cerón-Carrasco, José P.

2017-12-01

Many efforts have been devoted to discover molecules able to halt methylation processes in DNA. However, less is known about the application of methyl promoters in the framework of hypomethylation diseases. Herein, we used molecular dynamics and ab initio calculations to assess the methylation ability of the parent S-adenosyl-L-methionine cofactor (SAM) and a series of analogues. Two molecules deposited in the PubChem database are shown to be promising candidates for increasing the methyl transfer rate of the original SAM. The reported data might be consequently used to guide further steps into the search of more efficient methyl donor-based drugs.

Designing of Protein Kinase C β-II Inhibitors against Diabetic complications: Structure Based Drug Design, Induced Fit docking and analysis of active site conformational changes

PubMed Central

Vijayakumar, Balakrishnan; Velmurugan, Devadasan

2012-01-01

Protein Kinase C β-II (PKC β-II) is an important enzyme in the development of diabetic complications like cardiomyopathy, retinopathy, neuropathy, nephropathy and angiopathy. PKC β-II is activated in vascular tissues during diabetic vascular abnormalities. Thus, PKC β-II is considered as a potent drug target and the crystal structure of the kinase domain of PKC β-II (PDB id: 2I0E) was used to design inhibitors using Structure-Based Drug Design (SBDD) approach. Sixty inhibitors structurally similar to Staurosporine were retrieved from PubChem Compound database and High Throughput Virtual screening (HTVs) was carried out with PKC β-II. Based on the HTVs results and the nature of active site residues of PKC β-II, Staurosporine inhibitors were designed using SBDD. Induced Fit Docking (IFD) studies were carried out between kinase domain of PKC β-II and the designed inhibitors. These IFD complexes showed favorable docking score, glide energy, glide emodel and hydrogen bond and hydrophobic interactions with the active site of PKC β-II. Binding free energy was calculated for IFD complexes using Prime MM-GBSA method. The conformational changes induced by the inhibitor at the active site of PKC β-II were observed for the back bone Cα atoms and side-chain chi angles. PASS prediction tool was used to analyze the biological activities for the designed inhibitors. The various physicochemical properties were calculated for the compounds. One of the designed inhibitors successively satisfied all the in silico parameters among the others and seems to be a potent inhibitor against PKC β-II. PMID:22829732

Discovery and evaluation of inhibitors to the immunosuppressive enzyme indoleamine 2,3-dioxygenase 1 (IDO1): Probing the active site-inhibitor interactions.

PubMed

Tomek, Petr; Palmer, Brian D; Flanagan, Jack U; Sun, Chuanwen; Raven, Emma L; Ching, Lai-Ming

2017-01-27

High expression of the immunosuppressive enzyme, indoleamine 2,3-dioxygenase 1 (IDO1) for a broad range of malignancies is associated with poor patient prognosis, and the enzyme is a validated target for cancer intervention. To identify novel IDO1 inhibitors suitable for drug development, 1597 compounds in the National Cancer Institute Diversity Set III library were tested for inhibitory activity against recombinant human IDO1. We retrieved 35 hits that inhibited IDO1 activity >50% at 20 μM. Five structural filters and the PubChem Bioassay database were used to guide the selection of five inhibitors with IC 50 between 3 and 12 μM for subsequent experimental evaluation. A pyrimidinone scaffold emerged as being the most promising. It showed excellent cell penetration, negligible cytotoxicity and passed four out of the five structural filters applied. To evaluate the importance of Ser167 and Cys129 residues in the IDO1 active site for inhibitor binding, the entire NCI library was subsequently screened against alanine-replacement mutant enzymes of these two residues. The results established that Ser167 but not Cys129 is important for inhibitory activity of a broad range of IDO1 inhibitors. Structure-activity-relationship studies proposed substituents interacting with Ser167 on four investigated IDO1 inhibitors. Three of these four Ser167 interactions associated with an increased IDO1 inhibition and were correctly predicted by molecular docking supporting Ser167 as an important mediator of potency for IDO1 inhibitors. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Identification of novel tyrosine kinase inhibitors for drug resistant T315I mutant BCR-ABL: a virtual screening and molecular dynamics simulations study

NASA Astrophysics Data System (ADS)

Banavath, Hemanth Naick; Sharma, Om Prakash; Kumar, Muthuvel Suresh; Baskaran, R.

2014-11-01

BCR-ABL tyrosine kinase plays a major role in the pathogenesis of chronic myeloid leukemia (CML) and is a proven target for drug development. Currently available drugs in the market are effective against CML; however, side-effects and drug-resistant mutations in BCR-ABL limit their full potential. Using high throughput virtual screening approach, we have screened several small molecule databases and docked against wild-type and drug resistant T315I mutant BCR-ABL. Drugs that are currently available, such as imatinib and ponatinib, were also docked against BCR-ABL protein to set a cutoff value for our screening. Selected lead compounds were further evaluated for chemical reactivity employing density functional theory approach, all selected ligands shows HLG value > 0.09900 and the binding free energy between protein-ligand complex interactions obtained was rescored using MM-GBSA. The selected compounds showed least ΔG score -71.53 KJ/mol to maximum -126.71 KJ/mol in both wild type and drug resistant T315I mutant BCR-ABL. Following which, the stability of the docking complexes were evaluated by molecular dynamics simulation (MD) using GROMACS4.5.5. Results uncovered seven lead molecules, designated with Drug-Bank and PubChem ids as DB07107, DB06977, ST013616, DB04200, ST007180 ST019342, and DB01172, which shows docking scores higher than imatinib and ponatinib.

In silico prediction of multiple-category classification model for cytochrome P450 inhibitors and non-inhibitors using machine-learning method.

PubMed

Lee, J H; Basith, S; Cui, M; Kim, B; Choi, S

2017-10-01

The cytochrome P450 (CYP) enzyme superfamily is involved in phase I metabolism which chemically modifies a variety of substrates via oxidative reactions to make them more water-soluble and easier to eliminate. Inhibition of these enzymes leads to undesirable effects, including toxic drug accumulations and adverse drug-drug interactions. Hence, it is necessary to develop in silico models that can predict the inhibition potential of compounds for different CYP isoforms. This study focused on five major CYP isoforms, including CYP1A2, 2C9, 2C19, 2D6 and 3A4, that are responsible for more than 90% of the metabolism of clinical drugs. The main aim of this study is to develop a multiple-category classification model (MCM) for the major CYP isoforms using a Laplacian-modified naïve Bayesian method. The dataset composed of more than 4500 compounds was collected from the PubChem Bioassay database. VolSurf+ descriptors and FCFP_8 fingerprint were used as input features to build classification models. The results demonstrated that the developed MCM using Laplacian-modified naïve Bayesian method was successful in classifying inhibitors and non-inhibitors for each CYP isoform. Moreover, the accuracy, sensitivity and specificity values for both training and test sets were above 80% and also yielded satisfactory area under the receiver operating characteristic curve and Matthews correlation coefficient values.

Cdc25B Dual-Specificity Phosphatase Inhibitors Identified in a High-Throughput Screen of the NIH Compound Library

PubMed Central

Foster, Caleb A.; Tierno, Marni Brisson; Shun, Tong Ying; Shinde, Sunita N.; Paquette, William D.; Brummond, Kay M.; Wipf, Peter; Lazo, John S.

2009-01-01

Abstract The University of Pittsburgh Molecular Library Screening Center (Pittsburgh, PA) conducted a screen with the National Institutes of Health compound library for inhibitors of in vitro cell division cycle 25 protein (Cdc25) B activity during the pilot phase of the Molecular Library Screening Center Network. Seventy-nine (0.12%) of the 65,239 compounds screened at 10 μM met the active criterion of ≥50% inhibition of Cdc25B activity, and 25 (31.6%) of these were confirmed as Cdc25B inhibitors with 50% inhibitory concentration (IC50) values <50 μM. Thirteen of the Cdc25B inhibitors were represented by singleton chemical structures, and 12 were divided among four clusters of related structures. Thirteen (52%) of the Cdc25B inhibitor hits were quinone-based structures. The Cdc25B inhibitors were further characterized in a series of in vitro secondary assays to confirm their activity, to determine their phosphatase selectivity against two other dual-specificity phosphatases, mitogen-activated protein kinase phosphatase (MKP)-1 and MKP-3, and to examine if the mechanism of Cdc25B inhibition involved oxidation and inactivation. Nine Cdc25B inhibitors did not appear to affect Cdc25B through a mechanism involving oxidation because they did not generate detectable amounts of H2O2 in the presence of dithiothreitol, and their Cdc25B IC50 values were not significantly affected by exchanging the dithiothreitol for β-mercaptoethanol or reduced glutathione or by adding catalase to the assay. Six of the nonoxidative hits were selective for Cdc25B inhibition versus MKP-1 and MKP-3, but only the two bisfuran-containing hits, PubChem substance identifiers 4258795 and 4260465, significantly inhibited the growth of human MBA-MD-435 breast and PC-3 prostate cancer cell lines. To confirm the structure and biological activity of 4260465, the compound was resynthesized along with two analogs. Neither of the substitutions to the two analogs was tolerated, and only the resynthesized hit 26683752 inhibited Cdc25B activity in vitro (IC50 = 13.83 ± 1.0 μM) and significantly inhibited the growth of the MBA-MD-435 breast and PC-3 prostate cancer cell lines (IC50 = 20.16 ± 2.0 μM and 24.87 ± 2.25 μM, respectively). The two bis-furan-containing hits identified in the screen represent novel nonoxidative Cdc25B inhibitor chemotypes that block tumor cell proliferation. The availability of non-redox active Cdc25B inhibitors should provide valuable tools to explore the inhibition of the Cdc25 phosphatases as potential mono- or combination therapies for cancer. PMID:19530895

Molecular docking performance evaluated on the D3R Grand Challenge 2015 drug-like ligand datasets

NASA Astrophysics Data System (ADS)

Selwa, Edithe; Martiny, Virginie Y.; Iorga, Bogdan I.

2016-09-01

The D3R Grand Challenge 2015 was focused on two protein targets: Heat Shock Protein 90 (HSP90) and Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 (MAP4K4). We used a protocol involving a preliminary analysis of the available data in PDB and PubChem BioAssay, and then a docking/scoring step using more computationally demanding parameters that were required to provide more reliable predictions. We could evidence that different docking software and scoring functions can behave differently on individual ligand datasets, and that the flexibility of specific binding site residues is a crucial element to provide good predictions.

Prediction and mechanism elucidation of analyte retention on phospholipid stationary phases (IAM-HPLC) by in silico calculated physico-chemical descriptors.

PubMed

Russo, Giacomo; Grumetto, Lucia; Barbato, Francesco; Vistoli, Giulio; Pedretti, Alessandro

2017-03-01

The present study proposes a method for an in silico calculation of phospholipophilicity. Phospholipophilicity is intended as the measure of analyte affinity for phospholipids; it is currently assessed by HPLC measures of analyte retention on phosphatidylcholine-like stationary phases (IAM - Immobilized Artificial Membrane) resulting in log k W IAM values. Due to the amphipathic and electrically charged nature of phospholipids, retention on these stationary phases results from complex mechanisms, being affected not only by lipophilicity (as measured by n-octanol/aqueous phase partition coefficients, log P) but also by the occurrence of polar and/or electrostatic intermolecular interaction forces. Differently from log P, to date no method has been proposed for in silico calculation of log k W IAM . The study is aimed both at shedding new light into the retention mechanism on IAM stationary phases and at offering a high-throughput method to achieve such values. A wide set of physico-chemical and topological properties were taken into account, yielding a robust final model including four in silico calculated parameters (lipophilicity, hydrophilic/lipophilic balance, molecular size, and molecule flexibility). The here presented model was based on the analysis of 205 experimentally determined values, taken from the literature and measured by a single research group to minimize the interlaboratory variability; such model is able to predict phospholipophilicity values on both the two IAM stationary phases to date marketed, i.e. IAM.PC.MG and IAM.PC.DD2, with a fairly good degree (r 2 =0.85) of accuracy. The present work allowed the development of a free on-line service aimed at calculating log k W IAM values of any molecule included in the PubChem database, which is freely available at http://nova.disfarm.unimi.it/logkwiam.htm. Copyright © 2016 Elsevier B.V. All rights reserved.

Using PIDs to Support the Full Research Data Publishing Lifecycle

NASA Astrophysics Data System (ADS)

Waard, A. D.

2016-12-01

Persistent identifiers can help support scientific research, track scientific impact and let researchers achieve recognition for their work. We discuss a number of ways in which Elsevier utilizes PIDs to support the scholarly lifecycle: To improve the process of storing and sharing data, Mendeley Data (http://data.mendeley.com) makes use of persistent identifiers to support the dynamic nature of data and software, by tracking and recording the provenance and versioning of datasets. This system now allows the comparison of different versions of a dataset, to see precisely what was changed during a versioning update. To present research data in context for the reader, we include PIDs in research articles as hyperlinks: https://www.elsevier.com/books-and-journals/content-innovation/data-base-linking. In some cases, PIDs fetch data files from the repositories provide that allow the embedding of visualizations, e.g. with PANGAEA and PubChem: https://www.elsevier.com/books-and-journals/content-innovation/protein-viewer; https://www.elsevier.com/books-and-journals/content-innovation/pubchem. To normalize referenced data elements, the Resource Identification Initiative - which we developed together with members of the Force11 RRID group - introduces a unified standard for resource identifiers (RRIDs) that can easily be interpreted by both humans and text mining tools. https://www.force11.org/group/resource-identification-initiative/update-resource-identification-initiative, as can be seen in our Antibody Data app: https://www.elsevier.com/books-and-journals/content-innovation/antibody-data To enable better citation practices and support robust metrics system for sharing research data, we have helped develop, and are early adopters of the Force11 Data Citation Principles and Implementation groups (https://www.force11.org/group/dcip) Lastly, through our work with the Research Data Alliance Publishing Data Services group, we helped create a set of guidelines (http://www.scholix.org/guidelines) and a demonstrator service (http://dliservice.research-infrastructures.eu/#/) for a linked data network connecting datasets, articles, and individuals, which all rely on robust PIDs.

Bayesian models trained with HTS data for predicting β-haematin inhibition and in vitro antimalarial activity.

PubMed

Wicht, Kathryn J; Combrinck, Jill M; Smith, Peter J; Egan, Timothy J

2015-08-15

A large quantity of high throughput screening (HTS) data for antimalarial activity has become available in recent years. This includes both phenotypic and target-based activity. Realising the maximum value of these data remains a challenge. In this respect, methods that allow such data to be used for virtual screening maximise efficiency and reduce costs. In this study both in vitro antimalarial activity and inhibitory data for β-haematin formation, largely obtained from publically available sources, has been used to develop Bayesian models for inhibitors of β-haematin formation and in vitro antimalarial activity. These models were used to screen two in silico compound libraries. In the first, the 1510 U.S. Food and Drug Administration approved drugs available on PubChem were ranked from highest to lowest Bayesian score based on a training set of β-haematin inhibiting compounds active against Plasmodium falciparum that did not include any of the clinical antimalarials or close analogues. The six known clinical antimalarials that inhibit β-haematin formation were ranked in the top 2.1% of compounds. Furthermore, the in vitro antimalarial hit-rate for this prioritised set of compounds was found to be 81% in the case of the subset where activity data are available in PubChem. In the second, a library of about 5000 commercially available compounds (Aldrich(CPR)) was virtually screened for ability to inhibit β-haematin formation and then for in vitro antimalarial activity. A selection of 34 compounds was purchased and tested, of which 24 were predicted to be β-haematin inhibitors. The hit rate for inhibition of β-haematin formation was found to be 25% and a third of these were active against P. falciparum, corresponding to enrichments estimated at about 25- and 140-fold relative to random screening, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

NPCARE: database of natural products and fractional extracts for cancer regulation.

PubMed

Choi, Hwanho; Cho, Sun Young; Pak, Ho Jeong; Kim, Youngsoo; Choi, Jung-Yun; Lee, Yoon Jae; Gong, Byung Hee; Kang, Yeon Seok; Han, Taehoon; Choi, Geunbae; Cho, Yeeun; Lee, Soomin; Ryoo, Dekwoo; Park, Hwangseo

2017-01-01

Natural products have increasingly attracted much attention as a valuable resource for the development of anticancer medicines due to the structural novelty and good bioavailability. This necessitates a comprehensive database for the natural products and the fractional extracts whose anticancer activities have been verified. NPCARE (http://silver.sejong.ac.kr/npcare) is a publicly accessible online database of natural products and fractional extracts for cancer regulation. At NPCARE, one can explore 6578 natural compounds and 2566 fractional extracts isolated from 1952 distinct biological species including plants, marine organisms, fungi, and bacteria whose anticancer activities were validated with 1107 cell lines for 34 cancer types. Each entry in NPCARE is annotated with the cancer type, genus and species names of the biological resource, the cell line used for demonstrating the anticancer activity, PubChem ID, and a wealth of information about the target gene or protein. Besides the augmentation of plant entries up to 743 genus and 197 families, NPCARE is further enriched with the natural products and the fractional extracts of diverse non-traditional biological resources. NPCARE is anticipated to serve as a dominant gateway for the discovery of new anticancer medicines due to the inclusion of a large number of the fractional extracts as well as the natural compounds isolated from a variety of biological resources.

On the Development and Use of Large Chemical Similarity Networks, Informatics Best Practices and Novel Chemical Descriptors Towards Materials Quantitative Structure Property Relationships

NASA Astrophysics Data System (ADS)

Krein, Michael

After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright cheating in the form of explicitly removing data to fit models. These actions do not serve the community well, nor are they beneficial to future predictions based on established models. In practice, in order to select combinations of descriptors and machine learning methods that might work best, one must consider the nature and size of the training and test datasets, be aware of existing hypotheses about the data, and resist the temptation to bias structure representation and modeling to explicitly fit the hypotheses. The definition and application of these best practices is important for obtaining actionable modeling outcomes, and for setting user expectations of modeling accuracy when predicting the endpoint values of unknowns. A wide variety of statistical learning approaches, descriptor types, and model validation strategies are explored herein, with the goals of helping end users understand the factors involved in creating and using QSPR models effectively, and to better understand relationships within the data, especially by looking at the problem space from multiple perspectives. Molecular relationships are commonly envisioned in a continuous high-dimensional space of numerical descriptors, referred to as chemistry space. Descriptor and similarity metric choice influence the partitioning of this space into regions corresponding to local structural similarity. These regions, known as domains of applicability, are most likely to be successfully modeled by a QSPR. In Chapter 2, the network topology and scaling relationships of several chemistry spaces are thoroughly investigated. Chemistry spaces studied include the ZINC data set, a qHTS PubChem bioassay, as well as the protein binding sites from the PDB. The characteristics of these networks are compared and contrasted with those of the bioassay Structure Activity Landscape Index (SALI) subnetwork, which maps discontinuities or cliffs in the structure activity landscape. Mapping this newly generated information over underlying chemistry space networks generated using different descriptors demonstrates local modeling capacity and can guide the choice of better local representations of chemistry space. Chapter 2 introduces and demonstrates this novel concept, which also enables future work in visualization and interpretation of chemical spaces. Initially, it was discovered that there were no community-available tools to leverage best-practice ideas to comprehensively build, compare, and interpret QSPRs. The Yet Another Modeling System (YAMS) tool performs a series of balanced, rational decisions in dataset preprocessing and parameter/feature selection over a choice of modeling methods. To date, YAMS is the only community-available informatics tool that performs such decisions consistently between methods while also providing multiple model performance comparisons and detailed descriptor importance information. The focus of the tool is thus to convey rich information about model quality and predictions that help to "close the loop" between modeling and experimental efforts, for example, in tailoring nanocomposite properties. Polymer nanocomposites (PNC) are complex material systems encompassing many potential structures, chemistries, and self assembled morphologies that could significantly impact commercial and military applications. There is a strong desire to characterize and understand the tradespace of nanocomposites, to identify the important factors relating nanostructure to materials properties and determine an effective way to control materials properties at the manufacturing scale. Due to the complexity of the systems, existing design approaches rely heavily on trial-and-error learning. By leveraging existing experimental data, Materials Quantitative Structure-Property Relationships (MQSPRs) relate molecular structures to the polar and dispersive components of corresponding surface tensions. In turn, existing theories relate polymer and nanofiller polar and dispersive surface tension components to the dispersion state and interfacial polymer relaxation times. These quantities may, in the future, be used as input to continuum mechanics approaches shown able to predict the thermomechanical response of nanocomposites. For a polymer dataset and a particle dataset, multiple structural representations and descriptor sets are benchmarked, including a set of high performance surface-property descriptors developed as part of this work. The systematic variation of structural representations as part of the informatics approach reveals important insight in modeling polymers, and should become common practice when defining new problem spaces.

A non-targeted metabolomic approach to identify food markers to support discrimination between organic and conventional tomato crops.

PubMed

Martínez Bueno, María Jesús; Díaz-Galiano, Francisco José; Rajski, Łukasz; Cutillas, Víctor; Fernández-Alba, Amadeo R

2018-04-20

In the last decade, the consumption trend of organic food has increased dramatically worldwide. However, the lack of reliable chemical markers to discriminate between organic and conventional products makes this market susceptible to food fraud in products labeled as "organic". Metabolomic fingerprinting approach has been demonstrated as the best option for a full characterization of metabolome occurring in plants, since their pattern may reflect the impact of both endogenous and exogenous factors. In the present study, advanced technologies based on high performance liquid chromatography-high-resolution accurate mass spectrometry (HPLC-HRAMS) has been used for marker search in organic and conventional tomatoes grown in greenhouse under controlled agronomic conditions. The screening of unknown compounds comprised the retrospective analysis of all tomato samples throughout the studied period and data processing using databases (mzCloud, ChemSpider and PubChem). In addition, stable nitrogen isotope analysis (δ 15 N) was assessed as a possible indicator to support discrimination between both production systems using crop/fertilizer correlations. Pesticide residue analyses were also applied as a well-established way to evaluate the organic production. Finally, the evaluation by combined chemometric analysis of high-resolution accurate mass spectrometry (HRAMS) and δ 15 N data provided a robust classification model in accordance with the agricultural practices. Principal component analysis (PCA) showed a sample clustering according to farming systems and significant differences in the sample profile was observed for six bioactive components (L-tyrosyl-L-isoleucyl-L-threonyl-L-threonine, trilobatin, phloridzin, tomatine, phloretin and echinenone). Copyright © 2018 Elsevier B.V. All rights reserved.

Experimentally Validated Novel Inhibitors of Helicobacter pylori Phosphopantetheine Adenylyltransferase Discovered by Virtual High-Throughput Screening

PubMed Central

Cheng, Chao-Sheng; Jia, Kai-Fan; Chen, Ting; Chang, Shun-Ya; Lin, Ming-Shen; Yin, Hsien-Sheng

2013-01-01

Helicobacter pylori is a major etiologic agent associated with the development and maintenance of human gastritis. The goal of this study was to develop novel antibiotics against H. pylori, and we thus targeted H. pylori phosphopantetheine adenylyltransferase (HpPPAT). PPAT catalyzes the penultimate step in coenzyme A biosynthesis. Its inactivation effectively prevents bacterial viability, making it an attractive target for antibacterial drug discovery. We employed virtual high-throughput screening and the HpPPAT crystal structure to identify compounds in the PubChem database that might act as inhibitors of HpPPAT. d-amethopterin is a potential inhibitor for blocking HpPPAT activity and suppressing H. pylori viability. Following treatment with d-amethopterin, H. pylori exhibited morphological characteristics associated with cell death. d-amethopterin is a mixed inhibitor of HpPPAT activity; it simultaneously occupies the HpPPAT 4'-phosphopantetheine- and ATP-binding sites. Its binding affinity is in the micromolar range, implying that it is sufficiently potent to serve as a lead compound in subsequent drug development. Characterization of the d-amethopterin and HpPPAT interaction network in a docked model will allow us to initiate rational drug optimization to improve the inhibitory efficacy of d-amethopterin. We anticipate that novel, potent, and selective HpPPAT inhibitors will emerge for the treatment of H. pylori infection. PMID:24040220

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

Molecular docking based screening of compounds against VP40 from Ebola virus.

PubMed

M Alam El-Din, Hanaa; A Loutfy, Samah; Fathy, Nasra; H Elberry, Mostafa; M Mayla, Ahmed; Kassem, Sara; Naqvi, Asif

2016-01-01

Ebola virus causes severe and often fatal hemorrhagic fevers in humans. The 2014 Ebola epidemic affected multiple countries. The virus matrix protein (VP40) plays a central role in virus assembly and budding. Since there is no FDA-approved vaccine or medicine against Ebola viral infection, discovering new compounds with different binding patterns against it is required. Therefore, we aim to identify small molecules that target the Arg 134 RNA binding and active site of VP40 protein. 1800 molecules were retrieved from PubChem compound database based on Structure Similarity and Conformers of pyrimidine-2, 4-dione. Molecular docking approach using Lamarckian Genetic Algorithm was carried out to find the potent inhibitors for VP40 based on calculated ligand-protein pairwise interaction energies. The grid maps representing the protein were calculated using auto grid and grid size was set to 60*60*60 points with grid spacing of 0.375 Ǻ. Ten independent docking runs were carried out for each ligand and results were clustered according to the 1.0 Ǻ RMSD criteria. The post-docking analysis showed that binding energies ranged from -8.87 to 0.6 Kcal/mol. We report 7 molecules, which showed promising ADMET results, LD-50, as well as H-bond interaction in the binding pocket. The small molecules discovered could act as potential inhibitors for VP40 and could interfere with virus assembly and budding process.

Molecular docking based screening of compounds against VP40 from Ebola virus

PubMed Central

M Alam El-Din, Hanaa; A. Loutfy, Samah; Fathy, Nasra; H Elberry, Mostafa; M Mayla, Ahmed; Kassem, Sara; Naqvi, Asif

2016-01-01

Ebola virus causes severe and often fatal hemorrhagic fevers in humans. The 2014 Ebola epidemic affected multiple countries. The virus matrix protein (VP40) plays a central role in virus assembly and budding. Since there is no FDA-approved vaccine or medicine against Ebola viral infection, discovering new compounds with different binding patterns against it is required. Therefore, we aim to identify small molecules that target the Arg 134 RNA binding and active site of VP40 protein. 1800 molecules were retrieved from PubChem compound database based on Structure Similarity and Conformers of pyrimidine-2, 4-dione. Molecular docking approach using Lamarckian Genetic Algorithm was carried out to find the potent inhibitors for VP40 based on calculated ligand-protein pairwise interaction energies. The grid maps representing the protein were calculated using auto grid and grid size was set to 60*60*60 points with grid spacing of 0.375 Ǻ. Ten independent docking runs were carried out for each ligand and results were clustered according to the 1.0 Ǻ RMSD criteria. The post-docking analysis showed that binding energies ranged from -8.87 to 0.6 Kcal/mol. We report 7 molecules, which showed promising ADMET results, LD-50, as well as H-bond interaction in the binding pocket. The small molecules discovered could act as potential inhibitors for VP40 and could interfere with virus assembly and budding process. PMID:28149054

Evaluation and comparison of bioinformatic tools for the enrichment analysis of metabolomics data.

PubMed

Marco-Ramell, Anna; Palau-Rodriguez, Magali; Alay, Ania; Tulipani, Sara; Urpi-Sarda, Mireia; Sanchez-Pla, Alex; Andres-Lacueva, Cristina

2018-01-02

Bioinformatic tools for the enrichment of 'omics' datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined. An exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard's distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites. We have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses. Despite the variability of the tools, they provided consistent results independent of their analytic approach. However, more work on the completeness of metabolite and pathway databases is required, which strongly affects the accuracy of enrichment analyses. Improvements will be translated into more accurate and global insights of the metabolome.

Complete genome-wide screening and subtractive genomic approach revealed new virulence factors, potential drug targets against bio-war pathogen Brucella melitensis 16M

PubMed Central

Pradeepkiran, Jangampalli Adi; Sainath, Sri Bhashyam; Kumar, Konidala Kranthi; Bhaskar, Matcha

2015-01-01

Brucella melitensis 16M is a Gram-negative coccobacillus that infects both animals and humans. It causes a disease known as brucellosis, which is characterized by acute febrile illness in humans and causes abortions in livestock. To prevent and control brucellosis, identification of putative drug targets is crucial. The present study aimed to identify drug targets in B. melitensis 16M by using a subtractive genomic approach. We used available database repositories (Database of Essential Genes, Kyoto Encyclopedia of Genes and Genomes Automatic Annotation Server, and Kyoto Encyclopedia of Genes and Genomes) to identify putative genes that are nonhomologous to humans and essential for pathogen B. melitensis 16M. The results revealed that among 3 Mb genome size of pathogen, 53 putative characterized and 13 uncharacterized hypothetical genes were identified; further, from Basic Local Alignment Search Tool protein analysis, one hypothetical protein showed a close resemblance (50%) to Silicibacter pomeroyi DUF1285 family protein (2RE3). A further homology model of the target was constructed using MODELLER 9.12 and optimized through variable target function method by molecular dynamics optimization with simulating annealing. The stereochemical quality of the restrained model was evaluated by PROCHECK, VERIFY-3D, ERRAT, and WHATIF servers. Furthermore, structure-based virtual screening was carried out against the predicted active site of the respective protein using the glycerol structural analogs from the PubChem database. We identified five best inhibitors with strong affinities, stable interactions, and also with reliable drug-like properties. Hence, these leads might be used as the most effective inhibitors of modeled protein. The outcome of the present work of virtual screening of putative gene targets might facilitate design of potential drugs for better treatment against brucellosis. PMID:25834405

PubMed Central

AMICIZIA, D.; LAI, P.L.; BRAGAZZI, N.L.; PANATTO, D.

2014-01-01

Summary In the first part of this overview, we described the life cycle of the influenza virus and the pharmacological action of the currently available drugs. This second part provides an overview of the molecular mechanisms and targets of still-experimental drugs for the treatment and management of influenza. Briefly, we can distinguish between compounds with anti-influenza activity that target influenza virus proteins or genes, and molecules that target host components that are essential for viral replication and propagation. These latter compounds have been developed quite recently. Among the first group, we will focus especially on hemagglutinin, M2 channel and neuraminidase inhibitors. The second group of compounds may pave the way for personalized treatment and influenza management. Combination therapies are also discussed. In recent decades, few antiviral molecules against influenza virus infections have been available; this has conditioned their use during human and animal outbreaks. Indeed, during seasonal and pandemic outbreaks, antiviral drugs have usually been administered in mono-therapy and, sometimes, in an uncontrolled manner to farm animals. This has led to the emergence of viral strains displaying resistance, especially to compounds of the amantadane family. For this reason, it is particularly important to develop new antiviral drugs against influenza viruses. Indeed, although vaccination is the most powerful means of mitigating the effects of influenza epidemics, antiviral drugs can be very useful, particularly in delaying the spread of new pandemic viruses, thereby enabling manufacturers to prepare large quantities of pandemic vaccine. In addition, antiviral drugs are particularly valuable in complicated cases of influenza, especially in hospitalized patients. To write this overview, we mined various databases, including Embase, PubChem, DrugBank and Chemical Abstracts Service, and patent repositories. PMID:26137785

Development and experimental test of support vector machines virtual screening method for searching Src inhibitors from large compound libraries.

PubMed

Han, Bucong; Ma, Xiaohua; Zhao, Ruiying; Zhang, Jingxian; Wei, Xiaona; Liu, Xianghui; Liu, Xin; Zhang, Cunlong; Tan, Chunyan; Jiang, Yuyang; Chen, Yuzong

2012-11-23

Src plays various roles in tumour progression, invasion, metastasis, angiogenesis and survival. It is one of the multiple targets of multi-target kinase inhibitors in clinical uses and trials for the treatment of leukemia and other cancers. These successes and appearances of drug resistance in some patients have raised significant interest and efforts in discovering new Src inhibitors. Various in-silico methods have been used in some of these efforts. It is desirable to explore additional in-silico methods, particularly those capable of searching large compound libraries at high yields and reduced false-hit rates. We evaluated support vector machines (SVM) as virtual screening tools for searching Src inhibitors from large compound libraries. SVM trained and tested by 1,703 inhibitors and 63,318 putative non-inhibitors correctly identified 93.53%~ 95.01% inhibitors and 99.81%~ 99.90% non-inhibitors in 5-fold cross validation studies. SVM trained by 1,703 inhibitors reported before 2011 and 63,318 putative non-inhibitors correctly identified 70.45% of the 44 inhibitors reported since 2011, and predicted as inhibitors 44,843 (0.33%) of 13.56M PubChem, 1,496 (0.89%) of 168 K MDDR, and 719 (7.73%) of 9,305 MDDR compounds similar to the known inhibitors. SVM showed comparable yield and reduced false hit rates in searching large compound libraries compared to the similarity-based and other machine-learning VS methods developed from the same set of training compounds and molecular descriptors. We tested three virtual hits of the same novel scaffold from in-house chemical libraries not reported as Src inhibitor, one of which showed moderate activity. SVM may be potentially explored for searching Src inhibitors from large compound libraries at low false-hit rates.

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.

Molecular Docking Studies of Flavonoids Derivatives on the Flavonoid 3- O-Glucosyltransferase.

PubMed

Harsa, Alexandra M; Harsa, Teodora E; Diudea, Mircea V; Janezic, Dusanka

2015-01-01

A study of 30 flavonoid derivatives, taken from PubChem database and docked on flavonoid 3-O-glucosyltransferase 3HBF, next submitted to a QSAR study, performed within a hypermolecule frame, to model their LD50 values, is reported. The initial set of molecules was split into a training set and the test set (taken from the best scored molecules in the docking test); the predicted LD50 values, computed on similarity clusters, built up for each of the molecules of the test set, surpassed in accuracy the best model. The binding energies to 3HBF protein, provided by the docking step, are not related to the LD50 of these flavonoids, more protein targets are to be investigated in this respect. However, the docking step was useful in choosing the test set of molecules.

Finding Chemical Structures Corresponding to a Set of Coordinates in Chemical Descriptor Space.

PubMed

Miyao, Tomoyuki; Funatsu, Kimito

2017-08-01

When chemical structures are searched based on descriptor values, or descriptors are interpreted based on values, it is important that corresponding chemical structures actually exist. In order to consider the existence of chemical structures located in a specific region in the chemical space, we propose to search them inside training data domains (TDDs), which are dense areas of a training dataset in the chemical space. We investigated TDDs' features using diverse and local datasets, assuming that GDB11 is the chemical universe. These two analyses showed that considering TDDs gives higher chance of finding chemical structures than a random search-based method, and that novel chemical structures actually exist inside TDDs. In addition to those findings, we tested the hypothesis that chemical structures were distributed on the limited areas of chemical space. This hypothesis was confirmed by the fact that distances among chemical structures in several descriptor spaces were much shorter than those among randomly generated coordinates in the training data range. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of novel inhibitors against UDP-galactopyranose mutase to combat leishmaniasis.

PubMed

Kashif, Mohammad; Tabrez, Shams; Husein, Atahar; Arish, Mohd; Kalaiarasan, Ponnusamy; Manna, Partha P; Subbarao, Naidu; Akhter, Yusuf; Rub, Abdur

2018-03-01

Leishmania, a protozoan parasite that causes leishmaniasis, affects 1-2 million people every year worldwide. Leishmaniasis is a vector born disease and characterized by a diverse group of clinical syndromes. Current treatment is limited because of drug resistance, high cost, poor safety, and low efficacy. The urgent need for potent agents against Leishmania has led to significant advances in the development of novel antileishmanial drugs. β-galactofuranose (β-Galf) is an important component of Leishmanial cell surface matrix and plays a critical role in the pathogenesis of parasite. UDP-galactopyranose mutase (UGM) converts UDP-galactopyranose (UDP-Galp) to UDP-galactofuranose (UDP-Galf) which acts as the precursor for β-Galf synthesis. Due to its absence in human, this enzyme is selected as the potential target in search of new antileishmanial drugs. Three dimensional protein structure model of Leishmania major UGM (LmUGM) has been homology modeled using Trypanosoma cruzi UGM (TcUGM) as a template. The stereochemistry was validated further. We selected already reported active compounds from PubChem database to target the LmUGM. Three compounds (6064500, 44570814, and 6158954) among the top hit occupied the UDP binding site of UGM suggested to work as a possible inhibitor for it. In vitro antileishmanial activity assay was performed with the top ranked inhibitor, 6064500. The 6064500 molecule has inhibited the growth of Leishmania donovani promastigotes significantly. Further, at similar concentrations it has exhibited significantly lesser toxicity than standard drug miltefosine hydrate in mammalian cells. © 2017 Wiley Periodicals, Inc.

KINETIC CHARACTERIZATION AND MOLECULAR DOCKING OF A NOVEL, POTENT, AND SELECTIVE SLOW-BINDING INHIBITOR OF HUMAN CATHEPSIN L

PubMed Central

Shah, Parag P.; Myers, Michael C.; Beavers, Mary Pat; Purvis, Jeremy E.; Jing, Huiyan; Grieser, Heather J.; Sharlow, Elizabeth R.; Napper, Andrew D.; Huryn, Donna M.; Cooperman, Barry S.; Smith, Amos B.; Diamond, Scott L.

2008-01-01

A novel small molecule thiocarbazate (PubChem SID 26681509), a potent inhibitor of human cathepsin L (EC 3.4.22.15) with an IC50 of 56 nM, was developed following a 57,821 compound screen of the NIH Molecular Libraries Small Molecule Repository. After a 4 hr preincubation with cathepsin L, this compound became even more potent, demonstrating an IC50 of 1.0 nM. The thiocarbazate was determined to be a slow-binding and slowly reversible competitive inhibitor. Through a transient kinetic analysis for single-step reversibility, inhibition rate constants were kon = 24,000 M-1s-1 and koff = 2.2 × 10-5 s-1 (Ki = 0.89 nM). Molecular docking studies were undertaken using the experimentally-derived X-ray crystal structure of papain/CLIK-148 (1cvz.pdb). These studies revealed critical hydrogen bonding patterns of the thiocarbazate with key active site residues in papain. The thiocarbazate displayed 7- to 151-fold greater selectivity toward cathepsin L than papain and cathepsins B, K, V, and S with no activity against cathepsin G. The inhibitor demonstrated a lack of toxicity in human aortic endothelial cells and zebrafish. Additionally, the thiocarbazate inhibited in vitro propagation of malaria parasite Plasmodium falciparum with an IC50 of 15.4 μM and inhibited Leishmania major with an IC50 of 12.5 μM. PMID:18403718

Profiling Animal Toxicants by Automatically Mining Public Bioassay Data: A Big Data Approach for Computational Toxicology

PubMed Central

Zhang, Jun; Hsieh, Jui-Hua; Zhu, Hao

2014-01-01

In vitro bioassays have been developed and are currently being evaluated as potential alternatives to traditional animal toxicity models. Already, the progress of high throughput screening techniques has resulted in an enormous amount of publicly available bioassay data having been generated for a large collection of compounds. When a compound is tested using a collection of various bioassays, all the testing results can be considered as providing a unique bio-profile for this compound, which records the responses induced when the compound interacts with different cellular systems or biological targets. Profiling compounds of environmental or pharmaceutical interest using useful toxicity bioassay data is a promising method to study complex animal toxicity. In this study, we developed an automatic virtual profiling tool to evaluate potential animal toxicants. First, we automatically acquired all PubChem bioassay data for a set of 4,841 compounds with publicly available rat acute toxicity results. Next, we developed a scoring system to evaluate the relevance between these extracted bioassays and animal acute toxicity. Finally, the top ranked bioassays were selected to profile the compounds of interest. The resulting response profiles proved to be useful to prioritize untested compounds for their animal toxicity potentials and form a potential in vitro toxicity testing panel. The protocol developed in this study could be combined with structure-activity approaches and used to explore additional publicly available bioassay datasets for modeling a broader range of animal toxicities. PMID:24950175

Profiling animal toxicants by automatically mining public bioassay data: a big data approach for computational toxicology.

PubMed

Zhang, Jun; Hsieh, Jui-Hua; Zhu, Hao

2014-01-01

In vitro bioassays have been developed and are currently being evaluated as potential alternatives to traditional animal toxicity models. Already, the progress of high throughput screening techniques has resulted in an enormous amount of publicly available bioassay data having been generated for a large collection of compounds. When a compound is tested using a collection of various bioassays, all the testing results can be considered as providing a unique bio-profile for this compound, which records the responses induced when the compound interacts with different cellular systems or biological targets. Profiling compounds of environmental or pharmaceutical interest using useful toxicity bioassay data is a promising method to study complex animal toxicity. In this study, we developed an automatic virtual profiling tool to evaluate potential animal toxicants. First, we automatically acquired all PubChem bioassay data for a set of 4,841 compounds with publicly available rat acute toxicity results. Next, we developed a scoring system to evaluate the relevance between these extracted bioassays and animal acute toxicity. Finally, the top ranked bioassays were selected to profile the compounds of interest. The resulting response profiles proved to be useful to prioritize untested compounds for their animal toxicity potentials and form a potential in vitro toxicity testing panel. The protocol developed in this study could be combined with structure-activity approaches and used to explore additional publicly available bioassay datasets for modeling a broader range of animal toxicities.

Protein structure refinement using a quantum mechanics-based chemical shielding predictor.

PubMed

Bratholm, Lars A; Jensen, Jan H

2017-03-01

The accurate prediction of protein chemical shifts using a quantum mechanics (QM)-based method has been the subject of intense research for more than 20 years but so far empirical methods for chemical shift prediction have proven more accurate. In this paper we show that a QM-based predictor of a protein backbone and CB chemical shifts (ProCS15, PeerJ , 2016, 3, e1344) is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors. We present a method by which quantum chemistry based predictions of isotropic chemical shielding values (ProCS15) can be used to refine protein structures using Markov Chain Monte Carlo (MCMC) simulations, relating the chemical shielding values to the experimental chemical shifts probabilistically. Two kinds of MCMC structural refinement simulations were performed using force field geometry optimized X-ray structures as starting points: simulated annealing of the starting structure and constant temperature MCMC simulation followed by simulated annealing of a representative ensemble structure. Annealing of the CHARMM structure changes the CA-RMSD by an average of 0.4 Å but lowers the chemical shift RMSD by 1.0 and 0.7 ppm for CA and N. Conformational averaging has a relatively small effect (0.1-0.2 ppm) on the overall agreement with carbon chemical shifts but lowers the error for nitrogen chemical shifts by 0.4 ppm. If an amino acid specific offset is included the ProCS15 predicted chemical shifts have RMSD values relative to experiments that are comparable to popular empirical chemical shift predictors. The annealed representative ensemble structures differ in CA-RMSD relative to the initial structures by an average of 2.0 Å, with >2.0 Å difference for six proteins. In four of the cases, the largest structural differences arise in structurally flexible regions of the protein as determined by NMR, and in the remaining two cases, the large structural change may be due to force field deficiencies. The overall accuracy of the empirical methods are slightly improved by annealing the CHARMM structure with ProCS15, which may suggest that the minor structural changes introduced by ProCS15-based annealing improves the accuracy of the protein structures. Having established that QM-based chemical shift prediction can deliver the same accuracy as empirical shift predictors we hope this can help increase the accuracy of related approaches such as QM/MM or linear scaling approaches or interpreting protein structural dynamics from QM-derived chemical shift.

Model tool to describe chemical structures in XML format utilizing structural fragments and chemical ontology.

PubMed

Sankar, Punnaivanam; Alain, Krief; Aghila, Gnanasekaran

2010-05-24

We have developed a model structure-editing tool, ChemEd, programmed in JAVA, which allows drawing chemical structures on a graphical user interface (GUI) by selecting appropriate structural fragments defined in a fragment library. The terms representing the structural fragments are organized in fragment ontology to provide a conceptual support. ChemEd describes the chemical structure in an XML document (ChemFul) with rich semantics explicitly encoding the details of the chemical bonding, the hybridization status, and the electron environment around each atom. The document can be further processed through suitable algorithms and with the support of external chemical ontologies to generate understandable reports about the functional groups present in the structure and their specific environment.

THE USE OF STRUCTURE-ACTIVITY RELATIONSHIPS IN INTEGRATING THE CHEMISTRY AND TOXICOLOGY OF ENDOCRINE DISRUPTING CHEMICALS

EPA Science Inventory

Structure activity relationships (SARs) are based on the principle that structurally similar chemicals should have similar biological activity. SARs relate specifically-defined toxicological activity of chemicals to their molecular structure and physico-chemical properties. To de...

Protein structure refinement using a quantum mechanics-based chemical shielding predictor† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6sc04344e Click here for additional data file.

PubMed Central

2017-01-01

The accurate prediction of protein chemical shifts using a quantum mechanics (QM)-based method has been the subject of intense research for more than 20 years but so far empirical methods for chemical shift prediction have proven more accurate. In this paper we show that a QM-based predictor of a protein backbone and CB chemical shifts (ProCS15, PeerJ, 2016, 3, e1344) is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors. We present a method by which quantum chemistry based predictions of isotropic chemical shielding values (ProCS15) can be used to refine protein structures using Markov Chain Monte Carlo (MCMC) simulations, relating the chemical shielding values to the experimental chemical shifts probabilistically. Two kinds of MCMC structural refinement simulations were performed using force field geometry optimized X-ray structures as starting points: simulated annealing of the starting structure and constant temperature MCMC simulation followed by simulated annealing of a representative ensemble structure. Annealing of the CHARMM structure changes the CA-RMSD by an average of 0.4 Å but lowers the chemical shift RMSD by 1.0 and 0.7 ppm for CA and N. Conformational averaging has a relatively small effect (0.1–0.2 ppm) on the overall agreement with carbon chemical shifts but lowers the error for nitrogen chemical shifts by 0.4 ppm. If an amino acid specific offset is included the ProCS15 predicted chemical shifts have RMSD values relative to experiments that are comparable to popular empirical chemical shift predictors. The annealed representative ensemble structures differ in CA-RMSD relative to the initial structures by an average of 2.0 Å, with >2.0 Å difference for six proteins. In four of the cases, the largest structural differences arise in structurally flexible regions of the protein as determined by NMR, and in the remaining two cases, the large structural change may be due to force field deficiencies. The overall accuracy of the empirical methods are slightly improved by annealing the CHARMM structure with ProCS15, which may suggest that the minor structural changes introduced by ProCS15-based annealing improves the accuracy of the protein structures. Having established that QM-based chemical shift prediction can deliver the same accuracy as empirical shift predictors we hope this can help increase the accuracy of related approaches such as QM/MM or linear scaling approaches or interpreting protein structural dynamics from QM-derived chemical shift. PMID:28451325

Identification of potential leads against 4-hydroxytetrahydrodipicolinate synthase from Mycobacterium tuberculosis

PubMed Central

Rehman, Ajijur; Akhtar, Salman; Siddiqui, Mohd Haris; Sayeed, Usman; Ahmad, Syed Sayeed; Arif, Jamal M.; Khan, M. Kalim A.

2016-01-01

4-hydroxy-tetrahydrodipicolinate synthase (DHDPS) is an important enzyme needed for the biosynthesis of lysine and many more key metabolites in Mycobacterium tuberculosis (Mtb). Inhibition of DHDPS is supposed to a promising therapeutic target due to its specific role in sporulation, cross-linking of the peptidiglycan polymers and biosynthesis of amino acids. In this work, a known inhibitor-based similarity search was carried out against a natural products database (Super Natural II) towards identification of more potent phyto-inhibitors. Molecular interaction studies were accomplished using three different tools to understand and establish the participation of active site residues as the key players in stabilizing the binding mode of ligands and target protein. The best phyto-compound deduced on the basis of binding affinity was further used as a template to make similarity scan across the PubChem Compound database (score > = 80 %) to get more divesred leads. In this search 5098 hits were obtained that further reduced to 262 after drug-likeness filtration. These phytochemicallike compounds were docked at the active site of DHDPS.Then, those hits selected from docking analysis that showing stronger binding and forming maximum H-bonds with the active site residues (Thr54, Thr55, Tyr143, Arg148 and Lys171). Finally, we predicted one phytochemical compound (SN00003544), two PubChem-compounds (CID41032023, CID54025334) akin to phytochemical molecule showing better interactions in comaprison of known inhibitors of target protein.These findings might be further useful to gain the structural insight into the designing of novel leads against DapA family. PMID:28293071

Rapid and reliable protein structure determination via chemical shift threading.

PubMed

Hafsa, Noor E; Berjanskii, Mark V; Arndt, David; Wishart, David S

2018-01-01

Protein structure determination using nuclear magnetic resonance (NMR) spectroscopy can be both time-consuming and labor intensive. Here we demonstrate how chemical shift threading can permit rapid, robust, and accurate protein structure determination using only chemical shift data. Threading is a relatively old bioinformatics technique that uses a combination of sequence information and predicted (or experimentally acquired) low-resolution structural data to generate high-resolution 3D protein structures. The key motivations behind using NMR chemical shifts for protein threading lie in the fact that they are easy to measure, they are available prior to 3D structure determination, and they contain vital structural information. The method we have developed uses not only sequence and chemical shift similarity but also chemical shift-derived secondary structure, shift-derived super-secondary structure, and shift-derived accessible surface area to generate a high quality protein structure regardless of the sequence similarity (or lack thereof) to a known structure already in the PDB. The method (called E-Thrifty) was found to be very fast (often < 10 min/structure) and to significantly outperform other shift-based or threading-based structure determination methods (in terms of top template model accuracy)-with an average TM-score performance of 0.68 (vs. 0.50-0.62 for other methods). Coupled with recent developments in chemical shift refinement, these results suggest that protein structure determination, using only NMR chemical shifts, is becoming increasingly practical and reliable. E-Thrifty is available as a web server at http://ethrifty.ca .

Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry.

PubMed

Rappoport, Dmitrij; Galvin, Cooper J; Zubarev, Dmitry Yu; Aspuru-Guzik, Alán

2014-03-11

While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reactive potential energy surfaces and are combined here with quantum chemical structure optimizations, which yield the structures and energies of the reaction intermediates and products. Application of heuristics-aided quantum chemical methodology to the formose reaction reproduces the experimentally observed reaction products, major reaction pathways, and autocatalytic cycles.

Predicting Odor Pleasantness from Odorant Structure: Pleasantness as a Reflection of the Physical World

DTIC Science & Technology

2009-11-01

34 ( Engen , 1982). We next reduced the dimensionality of physico- chemical properties, and identified a primary axis of physico- chemical space. This axis...words, there is no scientist or perfumer who can predict the smell of a novel molecule by its physico- chemical structure, or the physico- chemical ...structure of a novel smell. Understanding this link between physico- chemical structure and percept has been elusive because the percept is in large

A novel approach: chemical relational databases, and the role of the ISSCAN database on assessing chemical carcinogenicity.

PubMed

Benigni, Romualdo; Bossa, Cecilia; Richard, Ann M; Yang, Chihae

2008-01-01

Mutagenicity and carcinogenicity databases are crucial resources for toxicologists and regulators involved in chemicals risk assessment. Until recently, existing public toxicity databases have been constructed primarily as "look-up-tables" of existing data, and most often did not contain chemical structures. Concepts and technologies originated from the structure-activity relationships science have provided powerful tools to create new types of databases, where the effective linkage of chemical toxicity with chemical structure can facilitate and greatly enhance data gathering and hypothesis generation, by permitting: a) exploration across both chemical and biological domains; and b) structure-searchability through the data. This paper reviews the main public databases, together with the progress in the field of chemical relational databases, and presents the ISSCAN database on experimental chemical carcinogens.

Automated extraction of chemical structure information from digital raster images

PubMed Central

Park, Jungkap; Rosania, Gus R; Shedden, Kerby A; Nguyen, Mandee; Lyu, Naesung; Saitou, Kazuhiro

2009-01-01

Background To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader – a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links to scientific research articles. PMID:19196483

Teaching Structural Formulas in Chemistry: How Students Relate Structural Formulas to the Solubility of Substances.

ERIC Educational Resources Information Center

Goedhart, Martin; van Duin, Yvonne

Structural formulas give professional chemists information about physical and chemical properties of corresponding compounds. In chemistry education at secondary schools, structural formulas are introduced in the context of chemical bonding. Structural formulas are not introduced as representations of the properties of chemical compounds. This…

Development and experimental test of support vector machines virtual screening method for searching Src inhibitors from large compound libraries

PubMed Central

2012-01-01

Background Src plays various roles in tumour progression, invasion, metastasis, angiogenesis and survival. It is one of the multiple targets of multi-target kinase inhibitors in clinical uses and trials for the treatment of leukemia and other cancers. These successes and appearances of drug resistance in some patients have raised significant interest and efforts in discovering new Src inhibitors. Various in-silico methods have been used in some of these efforts. It is desirable to explore additional in-silico methods, particularly those capable of searching large compound libraries at high yields and reduced false-hit rates. Results We evaluated support vector machines (SVM) as virtual screening tools for searching Src inhibitors from large compound libraries. SVM trained and tested by 1,703 inhibitors and 63,318 putative non-inhibitors correctly identified 93.53%~ 95.01% inhibitors and 99.81%~ 99.90% non-inhibitors in 5-fold cross validation studies. SVM trained by 1,703 inhibitors reported before 2011 and 63,318 putative non-inhibitors correctly identified 70.45% of the 44 inhibitors reported since 2011, and predicted as inhibitors 44,843 (0.33%) of 13.56M PubChem, 1,496 (0.89%) of 168 K MDDR, and 719 (7.73%) of 9,305 MDDR compounds similar to the known inhibitors. Conclusions SVM showed comparable yield and reduced false hit rates in searching large compound libraries compared to the similarity-based and other machine-learning VS methods developed from the same set of training compounds and molecular descriptors. We tested three virtual hits of the same novel scaffold from in-house chemical libraries not reported as Src inhibitor, one of which showed moderate activity. SVM may be potentially explored for searching Src inhibitors from large compound libraries at low false-hit rates. PMID:23173901

Effect of training data size and noise level on support vector machines virtual screening of genotoxic compounds from large compound libraries.

PubMed

Kumar, Pankaj; Ma, Xiaohua; Liu, Xianghui; Jia, Jia; Bucong, Han; Xue, Ying; Li, Ze Rong; Yang, Sheng Yong; Wei, Yu Quan; Chen, Yu Zong

2011-05-01

Various in vitro and in-silico methods have been used for drug genotoxicity tests, which show limited genotoxicity (GT+) and non-genotoxicity (GT-) identification rates. New methods and combinatorial approaches have been explored for enhanced collective identification capability. The rates of in-silco methods may be further improved by significantly diversified training data enriched by the large number of recently reported GT+ and GT- compounds, but a major concern is the increased noise levels arising from high false-positive rates of in vitro data. In this work, we evaluated the effect of training data size and noise level on the performance of support vector machines (SVM) method known to tolerate high noise levels in training data. Two SVMs of different diversity/noise levels were developed and tested. H-SVM trained by higher diversity higher noise data (GT+ in any in vivo or in vitro test) outperforms L-SVM trained by lower noise lower diversity data (GT+ in in vivo or Ames test only). H-SVM trained by 4,763 GT+ compounds reported before 2008 and 8,232 GT- compounds excluding clinical trial drugs correctly identified 81.6% of the 38 GT+ compounds reported since 2008, predicted 83.1% of the 2,008 clinical trial drugs as GT-, and 23.96% of 168 K MDDR and 27.23% of 17.86M PubChem compounds as GT+. These are comparable to the 43.1-51.9% GT+ and 75-93% GT- rates of existing in-silico methods, 58.8% GT+ and 79% GT- rates of Ames method, and the estimated percentages of 23% in vivo and 31-33% in vitro GT+ compounds in the "universe of chemicals". There is a substantial level of agreement between H-SVM and L-SVM predicted GT+ and GT- MDDR compounds and the prediction from TOPKAT. SVM showed good potential in identifying GT+ compounds from large compound libraries based on higher diversity and higher noise training data.

Wikipedia Chemical Structure Explorer: substructure and similarity searching of molecules from Wikipedia.

PubMed

Ertl, Peter; Patiny, Luc; Sander, Thomas; Rufener, Christian; Zasso, Michaël

2015-01-01

Wikipedia, the world's largest and most popular encyclopedia is an indispensable source of chemistry information. It contains among others also entries for over 15,000 chemicals including metabolites, drugs, agrochemicals and industrial chemicals. To provide an easy access to this wealth of information we decided to develop a substructure and similarity search tool for chemical structures referenced in Wikipedia. We extracted chemical structures from entries in Wikipedia and implemented a web system allowing structure and similarity searching on these data. The whole search as well as visualization system is written in JavaScript and therefore can run locally within a web page and does not require a central server. The Wikipedia Chemical Structure Explorer is accessible on-line at www.cheminfo.org/wikipedia and is available also as an open source project from GitHub for local installation. The web-based Wikipedia Chemical Structure Explorer provides a useful resource for research as well as for chemical education enabling both researchers and students easy and user friendly chemistry searching and identification of relevant information in Wikipedia. The tool can also help to improve quality of chemical entries in Wikipedia by providing potential contributors regularly updated list of entries with problematic structures. And last but not least this search system is a nice example of how the modern web technology can be applied in the field of cheminformatics. Graphical abstractWikipedia Chemical Structure Explorer allows substructure and similarity searches on molecules referenced in Wikipedia.

Distributed Structure Searchable Toxicity

EPA Pesticide Factsheets

The Distributed Structure Searchable Toxicity (DSSTox) online resource provides high quality chemical structures and annotations in association with toxicity data. It helps to build a data foundation for improved structure-activity relationships and predictive toxicology. DSSTox publishes summarized chemical activity representations for structure-activity modeling and provides a structure browser. This tool also houses the chemical inventories for the ToxCast and Tox21 projects.

Sensitivity of ab Initio vs Empirical Methods in Computing Structural Effects on NMR Chemical Shifts for the Example of Peptides.

PubMed

Sumowski, Chris Vanessa; Hanni, Matti; Schweizer, Sabine; Ochsenfeld, Christian

2014-01-14

The structural sensitivity of NMR chemical shifts as computed by quantum chemical methods is compared to a variety of empirical approaches for the example of a prototypical peptide, the 38-residue kaliotoxin KTX comprising 573 atoms. Despite the simplicity of empirical chemical shift prediction programs, the agreement with experimental results is rather good, underlining their usefulness. However, we show in our present work that they are highly insensitive to structural changes, which renders their use for validating predicted structures questionable. In contrast, quantum chemical methods show the expected high sensitivity to structural and electronic changes. This appears to be independent of the quantum chemical approach or the inclusion of solvent effects. For the latter, explicit solvent simulations with increasing number of snapshots were performed for two conformers of an eight amino acid sequence. In conclusion, the empirical approaches neither provide the expected magnitude nor the patterns of NMR chemical shifts determined by the clearly more costly ab initio methods upon structural changes. This restricts the use of empirical prediction programs in studies where peptide and protein structures are utilized for the NMR chemical shift evaluation such as in NMR refinement processes, structural model verifications, or calculations of NMR nuclear spin relaxation rates.

Automated compound classification using a chemical ontology.

PubMed

Bobach, Claudia; Böhme, Timo; Laube, Ulf; Püschel, Anett; Weber, Lutz

2012-12-29

Classification of chemical compounds into compound classes by using structure derived descriptors is a well-established method to aid the evaluation and abstraction of compound properties in chemical compound databases. MeSH and recently ChEBI are examples of chemical ontologies that provide a hierarchical classification of compounds into general compound classes of biological interest based on their structural as well as property or use features. In these ontologies, compounds have been assigned manually to their respective classes. However, with the ever increasing possibilities to extract new compounds from text documents using name-to-structure tools and considering the large number of compounds deposited in databases, automated and comprehensive chemical classification methods are needed to avoid the error prone and time consuming manual classification of compounds. In the present work we implement principles and methods to construct a chemical ontology of classes that shall support the automated, high-quality compound classification in chemical databases or text documents. While SMARTS expressions have already been used to define chemical structure class concepts, in the present work we have extended the expressive power of such class definitions by expanding their structure-based reasoning logic. Thus, to achieve the required precision and granularity of chemical class definitions, sets of SMARTS class definitions are connected by OR and NOT logical operators. In addition, AND logic has been implemented to allow the concomitant use of flexible atom lists and stereochemistry definitions. The resulting chemical ontology is a multi-hierarchical taxonomy of concept nodes connected by directed, transitive relationships. A proposal for a rule based definition of chemical classes has been made that allows to define chemical compound classes more precisely than before. The proposed structure-based reasoning logic allows to translate chemistry expert knowledge into a computer interpretable form, preventing erroneous compound assignments and allowing automatic compound classification. The automated assignment of compounds in databases, compound structure files or text documents to their related ontology classes is possible through the integration with a chemical structure search engine. As an application example, the annotation of chemical structure files with a prototypic ontology is demonstrated.

Automated compound classification using a chemical ontology

PubMed Central

2012-01-01

Background Classification of chemical compounds into compound classes by using structure derived descriptors is a well-established method to aid the evaluation and abstraction of compound properties in chemical compound databases. MeSH and recently ChEBI are examples of chemical ontologies that provide a hierarchical classification of compounds into general compound classes of biological interest based on their structural as well as property or use features. In these ontologies, compounds have been assigned manually to their respective classes. However, with the ever increasing possibilities to extract new compounds from text documents using name-to-structure tools and considering the large number of compounds deposited in databases, automated and comprehensive chemical classification methods are needed to avoid the error prone and time consuming manual classification of compounds. Results In the present work we implement principles and methods to construct a chemical ontology of classes that shall support the automated, high-quality compound classification in chemical databases or text documents. While SMARTS expressions have already been used to define chemical structure class concepts, in the present work we have extended the expressive power of such class definitions by expanding their structure-based reasoning logic. Thus, to achieve the required precision and granularity of chemical class definitions, sets of SMARTS class definitions are connected by OR and NOT logical operators. In addition, AND logic has been implemented to allow the concomitant use of flexible atom lists and stereochemistry definitions. The resulting chemical ontology is a multi-hierarchical taxonomy of concept nodes connected by directed, transitive relationships. Conclusions A proposal for a rule based definition of chemical classes has been made that allows to define chemical compound classes more precisely than before. The proposed structure-based reasoning logic allows to translate chemistry expert knowledge into a computer interpretable form, preventing erroneous compound assignments and allowing automatic compound classification. The automated assignment of compounds in databases, compound structure files or text documents to their related ontology classes is possible through the integration with a chemical structure search engine. As an application example, the annotation of chemical structure files with a prototypic ontology is demonstrated. PMID:23273256

Shining light on the differences in molecular structural chemical makeup and the cause of distinct degradation behavior between malting- and feed-type barley using synchrotron FTIR microspectroscopy: a novel approach.

PubMed

Yu, Peiqiang; Doiron, Kevin; Liu, Dasen

2008-05-14

The objective of this study was to use advanced synchrotron-sourced FTIR microspectroscopy (SFTIRM) as a novel approach to identify the differences in protein and carbohydrate molecular structure (chemical makeup) between these two varieties of barley and illustrate the exact causes for their significantly different degradation kinetics. Items assessed included (1) molecular structural differences in protein amide I to amide II intensities and their ratio within cellular dimensions, (2) molecular structural differences in protein secondary structure profile and their ratios, and (3) molecular structural differences in carbohydrate component peak profile. Our hypothesis was that molecular structure (chemical makeup) affects barley quality, fermentation, and degradation behavior in both humans and animals. Using SFTIRM, the protein and carbohydrate molecular structural chemical makeup of barley was revealed and identified. The protein molecular structural chemical makeup differed significantly between the two varieties of barleys. No difference in carbohydrate molecular structural chemical makeup was detected. Harrington was lower than Valier in protein amide I, amide II, and protein amide I to amide II ratio, while Harrington was relatively higher in model-fitted protein alpha-helix and beta-sheet, but lower in the others (beta-turn and random coil). These results indicated that it is the molecular structure of protein (chemical makeup) that may play a major role in the different degradation kinetics between the two varieties of barleys (not the molecular structure of carbohydrate). It is believed that use of the advanced synchrotron technology will make a significant step and an important contribution to research in examining the molecular structure (chemical makeup) of plant, feed, and seeds.

Tautomerism in chemical information management systems

NASA Astrophysics Data System (ADS)

Warr, Wendy A.

2010-06-01

Tautomerism has an impact on many of the processes in chemical information management systems including novelty checking during registration into chemical structure databases; storage of structures; exact and substructure searching in chemical structure databases; and depiction of structures retrieved by a search. The approaches taken by 27 different software vendors and database producers are compared. It is hoped that this comparison will act as a discussion document that could ultimately improve databases and software for researchers in the future.

PREDICTING TOXICOLOGICAL ENDPOINTS OF CHEMICALS USING QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS (QSARS)

EPA Science Inventory

Quantitative structure-activity relationships (QSARs) are being developed to predict the toxicological endpoints for untested chemicals similar in structure to chemicals that have known experimental toxicological data. Based on a very large number of predetermined descriptors, a...

STRUCTURE-ACTIVITY RELATIONSHIP STUIDES AND THEIR ROLE IN PREDICTING AND INVESTIGATING CHEMICAL TOXICITY

EPA Science Inventory

Structure-Activity Relationship Studies and their Role in Predicting and Investigating Chemical Toxicity

Structure-activity relationships (SAR) represent attempts to generalize chemical information relative to biological activity for the twin purposes of generating insigh...

Correction of erroneously packed protein's side chains in the NMR structure based on ab initio chemical shift calculations.

PubMed

Zhu, Tong; Zhang, John Z H; He, Xiao

2014-09-14

In this work, protein side chain (1)H chemical shifts are used as probes to detect and correct side-chain packing errors in protein's NMR structures through structural refinement. By applying the automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) method for ab initio calculation of chemical shifts, incorrect side chain packing was detected in the NMR structures of the Pin1 WW domain. The NMR structure is then refined by using molecular dynamics simulation and the polarized protein-specific charge (PPC) model. The computationally refined structure of the Pin1 WW domain is in excellent agreement with the corresponding X-ray structure. In particular, the use of the PPC model yields a more accurate structure than that using the standard (nonpolarizable) force field. For comparison, some of the widely used empirical models for chemical shift calculations are unable to correctly describe the relationship between the particular proton chemical shift and protein structures. The AF-QM/MM method can be used as a powerful tool for protein NMR structure validation and structural flaw detection.

Application of Functional Use Predictions to Aid in Structure ...

EPA Pesticide Factsheets

Humans are potentially exposed to thousands of anthropogenic chemicals in commerce. Recent work has shown that the bulk of this exposure may occur in near-field indoor environments (e.g., home, school, work, etc.). Advances in suspect screening analyses (SSA) now allow an improved understanding of the chemicals present in these environments. However, due to the nature of suspect screening techniques, investigators are often left with chemical formula predictions, with the possibility of many chemical structures matching to each formula. Here, newly developed quantitative structure-use relationship (QSUR) models are used to identify potential exposure sources for candidate structures. Previously, a suspect screening workflow was introduced and applied to house dust samples collected from the U.S. Department of Housing and Urban Development’s American Healthy Homes Survey (AHHS) [Rager, et al., Env. Int. 88 (2016)]. This workflow utilized the US EPA’s Distributed Structure-Searchable Toxicity (DSSTox) Database to link identified molecular features to molecular formulas, and ultimately chemical structures. Multiple QSUR models were applied to support the evaluation of candidate structures. These QSURs predict the likelihood of a chemical having a functional use commonly associated with consumer products having near-field use. For 3,228 structures identified as possible chemicals in AHHS house dust samples, we were able to obtain the required descriptors to appl

Why relevant chemical information cannot be exchanged without disclosing structures

NASA Astrophysics Data System (ADS)

Filimonov, Dmitry; Poroikov, Vladimir

2005-09-01

Both society and industry are interested in increasing the safety of pharmaceuticals. Potentially dangerous compounds could be filtered out at early stages of R&D by computer prediction of biological activity and ADMET characteristics. Accuracy of such predictions strongly depends on the quality & quantity of information contained in a training set. Suggestion that some relevant chemical information can be added to such training sets without disclosing chemical structures was generated at the recent ACS Symposium. We presented arguments that such safety exchange of relevant chemical information is impossible. Any relevant information about chemical structures can be used for search of either a particular compound itself or its close analogues. Risk of identifying such structures is enough to prevent pharma industry from relevant chemical information exchange.

Millimeter-Wave Chemical Sensor Using Substrate-Integrated-Waveguide Cavity

PubMed Central

Memon, Muhammad Usman; Lim, Sungjoon

2016-01-01

This research proposes a substrate-integrated waveguide (SIW) cavity sensor to detect several chemicals using the millimeter-wave frequency range. The frequency response of the presented SIW sensor is switched by filling a very small quantity of chemical inside of the fluidic channel, which also causes a difference in the effective permittivity. The fluidic channel on this structure is either empty or filled with a chemical; when it is empty the structure resonates at 17.08 GHz. There is always a different resonant frequency when any chemical is injected into the fluidic channel. The maximum amount of chemical after injection is held in the center of the SIW structure, which has the maximum magnitude of the electric field distribution. Thus, the objective of sensing chemicals in this research is achieved by perturbing the electric fields of the SIW structure. PMID:27809240

Modular Chemical Descriptor Language (MCDL): Stereochemical modules

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

Gakh, Andrei A; Burnett, Michael N; Trepalin, Sergei V.

2011-01-01

In our previous papers we introduced the Modular Chemical Descriptor Language (MCDL) for providing a linear representation of chemical information. A subsequent development was the MCDL Java Chemical Structure Editor which is capable of drawing chemical structures from linear representations and generating MCDL descriptors from structures. In this paper we present MCDL modules and accompanying software that incorporate unique representation of molecular stereochemistry based on Cahn-Ingold-Prelog and Fischer ideas in constructing stereoisomer descriptors. The paper also contains additional discussions regarding canonical representation of stereochemical isomers, and brief algorithm descriptions of the open source LINDES, Java applet, and Open Babel MCDLmore » processing module software packages. Testing of the upgraded MCDL Java Chemical Structure Editor on compounds taken from several large and diverse chemical databases demonstrated satisfactory performance for storage and processing of stereochemical information in MCDL format.« less

Method of photocatalytic nanotagging

DOEpatents

Shelnutt, John A [Tijeras, NM; Medforth, Craig J [Winters, CA; Song, Yujiang [Albuquerque, NM

2010-04-27

A nanotagged chemical structure comprising a chemical structure with an associated photocatalyst and a tagging nanoparticle (a nanotag) grown in proximity to the photocatalyst, and a method for making the nanotagged chemical structure. The nanoparticle is grown in proximity to the photocatalyst by using a photocatalytic reduction reaction.

SCRIPDB: a portal for easy access to syntheses, chemicals and reactions in patents

PubMed Central

Heifets, Abraham; Jurisica, Igor

2012-01-01

The patent literature is a rich catalog of biologically relevant chemicals; many public and commercial molecular databases contain the structures disclosed in patent claims. However, patents are an equally rich source of metadata about bioactive molecules, including mechanism of action, disease class, homologous experimental series, structural alternatives, or the synthetic pathways used to produce molecules of interest. Unfortunately, this metadata is discarded when chemical structures are deposited separately in databases. SCRIPDB is a chemical structure database designed to make this metadata accessible. SCRIPDB provides the full original patent text, reactions and relationships described within any individual patent, in addition to the molecular files common to structural databases. We discuss how such information is valuable in medical text mining, chemical image analysis, reaction extraction and in silico pharmaceutical lead optimization. SCRIPDB may be searched by exact chemical structure, substructure or molecular similarity and the results may be restricted to patents describing synthetic routes. SCRIPDB is available at http://dcv.uhnres.utoronto.ca/SCRIPDB. PMID:22067445

Computing the Ediz eccentric connectivity index of discrete dynamic structures

NASA Astrophysics Data System (ADS)

Wu, Hualong; Kamran Siddiqui, Muhammad; Zhao, Bo; Gan, Jianhou; Gao, Wei

2017-06-01

From the earlier studies in physical and chemical sciences, it is found that the physico-chemical characteristics of chemical compounds are internally connected with their molecular structures. As a theoretical basis, it provides a new way of thinking by analyzing the molecular structure of the compounds to understand their physical and chemical properties. In our article, we study the physico-chemical properties of certain molecular structures via computing the Ediz eccentric connectivity index from mathematical standpoint. The results we yielded mainly apply to the techniques of distance and degree computation of mathematical derivation, and the conclusions have guiding significance in physical engineering.

Prediction of Human Cytochrome P450 Inhibition Using a Multitask Deep Autoencoder Neural Network.

PubMed

Li, Xiang; Xu, Youjun; Lai, Luhua; Pei, Jianfeng

2018-05-30

Adverse side effects of drug-drug interactions induced by human cytochrome P450 (CYP450) inhibition is an important consideration in drug discovery. It is highly desirable to develop computational models that can predict the inhibitive effect of a compound against a specific CYP450 isoform. In this study, we developed a multitask model for concurrent inhibition prediction of five major CYP450 isoforms, namely, 1A2, 2C9, 2C19, 2D6, and 3A4. The model was built by training a multitask autoencoder deep neural network (DNN) on a large dataset containing more than 13 000 compounds, extracted from the PubChem BioAssay Database. We demonstrate that the multitask model gave better prediction results than that of single-task models, previous reported classifiers, and traditional machine learning methods on an average of five prediction tasks. Our multitask DNN model gave average prediction accuracies of 86.4% for the 10-fold cross-validation and 88.7% for the external test datasets. In addition, we built linear regression models to quantify how the other tasks contributed to the prediction difference of a given task between single-task and multitask models, and we explained under what conditions the multitask model will outperform the single-task model, which suggested how to use multitask DNN models more effectively. We applied sensitivity analysis to extract useful knowledge about CYP450 inhibition, which may shed light on the structural features of these isoforms and give hints about how to avoid side effects during drug development. Our models are freely available at http://repharma.pku.edu.cn/deepcyp/home.php or http://www.pkumdl.cn/deepcyp/home.php .

Reporter enzyme inhibitor study to aid assembly of orthogonal reporter gene assays.

PubMed

Ho, Pei-i; Yue, Kimberley; Pandey, Pramod; Breault, Lyne; Harbinski, Fred; McBride, Aaron J; Webb, Brian; Narahari, Janaki; Karassina, Natasha; Wood, Keith V; Hill, Adam; Auld, Douglas S

2013-05-17

Reporter gene assays (RGAs) are commonly used to measure biological pathway modulation by small molecules. Understanding how such compounds interact with the reporter enzyme is critical to accurately interpret RGA results. To improve our understanding of reporter enzymes and to develop optimal RGA systems, we investigated eight reporter enzymes differing in brightness, emission spectrum, stability, and substrate requirements. These included common reporter enzymes such as firefly luciferase (Photinus pyralis), Renilla reniformis luciferase, and β-lactamase, as well as mutated forms of R. reniformis luciferase emitting either blue- or green-shifted luminescence, a red-light emitting form of Luciola cruciata firefly luciferase, a mutated form of Gaussia princeps luciferase, and a proprietary luciferase termed "NanoLuc" derived from the luminescent sea shrimp Oplophorus gracilirostris. To determine hit rates and structure-activity relationships, we screened a collection of 42,460 PubChem compounds at 10 μM using purified enzyme preparations. We then compared hit rates and chemotypes of actives for each enzyme. The hit rates ranged from <0.1% for β-lactamase to as high as 10% for mutated forms of Renilla luciferase. Related luciferases such as Renilla luciferase mutants showed high degrees of inhibitor overlap (40-70%), while unrelated luciferases such as firefly luciferases, Gaussia luciferase, and NanoLuc showed <10% overlap. Examination of representative inhibitors in cell-based assays revealed that inhibitor-based enzyme stabilization can lead to increases in bioluminescent signal for firefly luciferase, Renilla luciferase, and NanoLuc, with shorter half-life reporters showing increased activation responses. From this study we suggest strategies to improve the construction and interpretation of assays employing these reporter enzymes.

Chemical-Space-Based de Novo Design Method To Generate Drug-Like Molecules.

PubMed

Takeda, Shunichi; Kaneko, Hiromasa; Funatsu, Kimito

2016-10-24

To discover drug compounds in chemical space containing an enormous number of compounds, a structure generator is required to produce virtual drug-like chemical structures. The de novo design algorithm for exploring chemical space (DAECS) visualizes the activity distribution on a two-dimensional plane corresponding to chemical space and generates structures in a target area on a plane selected by the user. In this study, we modify the DAECS to enable the user to select a target area to consider properties other than activity and improve the diversity of the generated structures by visualizing the drug-likeness distribution and the activity distribution, generating structures by substructure-based structural changes, including addition, deletion, and substitution of substructures, as well as the slight structural changes used in the DAECS. Through case studies using ligand data for the human adrenergic alpha2A receptor and the human histamine H1 receptor, the modified DAECS can generate high diversity drug-like structures, and the usefulness of the modification of the DAECS is verified.

Distributed Structure-Searchable Toxicity (DSSTox) Database

EPA Pesticide Factsheets

The Distributed Structure-Searchable Toxicity network provides a public forum for publishing downloadable, structure-searchable, standardized chemical structure files associated with chemical inventories or toxicity data sets of environmental relevance.

Automated workflows for data curation and standardization of chemical structures for QSAR modeling

EPA Science Inventory

Large collections of chemical structures and associated experimental data are publicly available, and can be used to build robust QSAR models for applications in different fields. One common concern is the quality of both the chemical structure information and associated experime...

Enumeration method for tree-like chemical compounds with benzene rings and naphthalene rings by breadth-first search order.

PubMed

Jindalertudomdee, Jira; Hayashida, Morihiro; Zhao, Yang; Akutsu, Tatsuya

2016-03-01

Drug discovery and design are important research fields in bioinformatics. Enumeration of chemical compounds is essential not only for the purpose, but also for analysis of chemical space and structure elucidation. In our previous study, we developed enumeration methods BfsSimEnum and BfsMulEnum for tree-like chemical compounds using a tree-structure to represent a chemical compound, which is limited to acyclic chemical compounds only. In this paper, we extend the methods, and develop BfsBenNaphEnum that can enumerate tree-like chemical compounds containing benzene rings and naphthalene rings, which include benzene isomers and naphthalene isomers such as ortho, meta, and para, by treating a benzene ring as an atom with valence six, instead of a ring of six carbon atoms, and treating a naphthalene ring as two benzene rings having a special bond. We compare our method with MOLGEN 5.0, which is a well-known general purpose structure generator, to enumerate chemical structures from a set of chemical formulas in terms of the number of enumerated structures and the computational time. The result suggests that our proposed method can reduce the computational time efficiently. We propose the enumeration method BfsBenNaphEnum for tree-like chemical compounds containing benzene rings and naphthalene rings as cyclic structures. BfsBenNaphEnum was from 50 times to 5,000,000 times faster than MOLGEN 5.0 for instances with 8 to 14 carbon atoms in our experiments.

Chemical structure of the Chromophoric Dissolved Organic Matter (CDOM) fluorescent matter.

NASA Astrophysics Data System (ADS)

Blough, N. V.; Del Vecchio, R.; Cartisano, C. M.; Bianca, M.

2017-12-01

The structure(s), distribution and dynamics of CDOM have been investigated over the last several decades largely through optical spectroscopy (including both absorption and fluorescence) due to the fairly inexpensive instrumentation and the easy-to-gather data (over thousands published papers from 1990-2016). Yet, the chemical structure(s) of the light absorbing and emitting species or constituents within CDOM has only recently being proposed and tested through chemical manipulation of selected functional groups (such as carbonyl and carboxylic/phenolic containing molecules) naturally occurring within the organic matter pool. Similarly, fitting models (among which the PArallel FACtor analysis, PARAFAC) have been developed to better understand the nature of a subset of DOM, the CDOM fluorescent matter (FDOM). Fluorescence spectroscopy coupled with chemical tests and PARAFAC analyses could potentially provide valuable insights on CDOM sources and chemical nature of the FDOM pool. However, despite that applications (and publications) of PARAFAC model to FDOM have grown exponentially since its first application/publication (2003), a large fraction of such publications has misinterpreted the chemical meaning of the delivered PARAFAC `components' leading to more confusion than clarification on the nature, distribution and dynamics of the FDOM pool. In this context, we employed chemical manipulation of selected functional groups to gain further insights on the chemical structure of the FDOM and we tested to what extent the PARAFAC `components' represent true fluorophores through a controlled chemical approach with the ultimate goal to provide insights on the chemical nature of such `components' (as well as on the chemical nature of the FDOM) along with the advantages and limitations of the PARAFAC application.

Recent advances in the in silico modelling of UDP glucuronosyltransferase substrates.

PubMed

Sorich, Michael J; Smith, Paul A; Miners, John O; Mackenzie, Peter I; McKinnon, Ross A

2008-01-01

UDP glucurononosyltransferases (UGT) are a superfamily of enzymes that catalyse the conjugation of a range of structurally diverse drugs, environmental and endogenous chemicals with glucuronic acid. This process plays a significant role in the clearance and detoxification of many chemicals. Over the last decade the regulation and substrate profiles of UGT isoforms have been increasingly characterised. The resulting data has facilitated the prototyping of ligand based in silico models capable of predicting, and gaining insights into, binding affinity and the substrate- and regio- selectivity of glucuronidation by UGT isoforms. Pharmacophore modelling has produced particularly insightful models and quantitative structure-activity relationships based on machine learning algorithms result in accurate predictions. Simple structural chemical descriptors were found to capture much of the chemical information relevant to UGT metabolism. However, quantum chemical properties of molecules and the nucleophilic atoms in the molecule can enhance both the predictivity and chemical intuitiveness of structure-activity models. Chemical diversity analysis of known substrates has shown some bias towards chemicals with aromatic and aliphatic hydroxyl groups. Future progress in in silico development will depend on larger and more diverse high quality metabolic datasets. Furthermore, improved protein structure data on UGTs will enable the application of structural modelling techniques likely leading to greater insight into the binding and reactive processes of UGT catalysed glucuronidation.

20180318 - Automated workflows for data curation and standardization of chemical structures for QSAR modeling (ACS Spring)

EPA Science Inventory

Large collections of chemical structures and associated experimental data are publicly available, and can be used to build robust QSAR models for applications in different fields. One common concern is the quality of both the chemical structure information and associated experime...

Predicting hepatotoxicity using ToxCast in vitro bioactivity and chemical structure

EPA Science Inventory

Background: The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. We represented chemicals based on bioactivity and chemical structure descriptors ...

40 CFR 159.179 - Metabolites, degradates, contaminants, and impurities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... chemical properties of the metabolite or degradate. (B) Data regarding structurally analogous chemicals. (C) Data regarding chemical reactivity of the metabolite or degradate and structurally analogous substances... any person described in § 159.158(a) that the metabolite or degradate, or analogous chemicals, may...

40 CFR 159.179 - Metabolites, degradates, contaminants, and impurities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... chemical properties of the metabolite or degradate. (B) Data regarding structurally analogous chemicals. (C) Data regarding chemical reactivity of the metabolite or degradate and structurally analogous substances... any person described in § 159.158(a) that the metabolite or degradate, or analogous chemicals, may...

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

PubMed

Tamiola, Kamil; Mulder, Frans A A

2012-10-01

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

An automated curation procedure for addressing chemical errors and inconsistencies in public datasets used in QSAR modelling.

PubMed

Mansouri, K; Grulke, C M; Richard, A M; Judson, R S; Williams, A J

2016-11-01

The increasing availability of large collections of chemical structures and associated experimental data provides an opportunity to build robust QSAR models for applications in different fields. One common concern is the quality of both the chemical structure information and associated experimental data. Here we describe the development of an automated KNIME workflow to curate and correct errors in the structure and identity of chemicals using the publicly available PHYSPROP physicochemical properties and environmental fate datasets. The workflow first assembles structure-identity pairs using up to four provided chemical identifiers, including chemical name, CASRNs, SMILES, and MolBlock. Problems detected included errors and mismatches in chemical structure formats, identifiers and various structure validation issues, including hypervalency and stereochemistry descriptions. Subsequently, a machine learning procedure was applied to evaluate the impact of this curation process. The performance of QSAR models built on only the highest-quality subset of the original dataset was compared with the larger curated and corrected dataset. The latter showed statistically improved predictive performance. The final workflow was used to curate the full list of PHYSPROP datasets, and is being made publicly available for further usage and integration by the scientific community.

Medicinal plants of the genus Anthocleista--A review of their ethnobotany, phytochemistry and pharmacology.

PubMed

Anyanwu, Gabriel O; Nisar-ur-Rehman; Onyeneke, Chukwu E; Rauf, Khalid

2015-12-04

The genus Anthocleista of the Gentianaceae family contains 14 species of trees and shrub-like plants distributed in tropical Africa, in Madagascar and on the Comoros. Traditionally, they are commonly used in the treatment of diabetes, hypertension, malaria, typhoid fever, obesity, diarrhea, dysentery, hyperprolactinemia, abdominal pain, ulcer, jaundice, asthma, hemorrhoids, hernia, cancer, wounds, chest pains, inflammations, rheumatism, STDs, infertility and skin diseases. They serve as an anthelmintic, laxative, diuretic and contraceptive. This review aims to provide for the first time a repository of ethnopharmacological information while critically evaluating the relation between the traditional medicinal uses, chemical constituents and pharmacological activities of the Anthocleista species so as to unveil opportunities for future research. A search for relevant information on Anthocleista species was performed on scientific databases (Pubmed, Google Scholar, SciFinder, Web of Science, Scopus, PubChem and other web sources such as The Plant List, Kew Botanical Garden and PROTA) and books, PhD and MSc dissertations for un-published resources. Out of the 14 species of Anthocleista, 6 have been reported in literature to be widely used in traditional medicine for the treatment of various ailments. The six species include: A. djalonensis, A. vogelii, A. nobilis, A. grandiflora, A. schweinfurthii, and A. liebrechtsiana. The chemical compounds isolated from Anthocleista species fall into the class of phytochemicals such as secoiridoids, nor-secoiridoids, xanthones, phytosterols, triterpenes, alkaloids, and others of which majority of the compounds were isolated from A. djalonensis and A. vogelii. The in vitro and in vivo pharmacological studies on the crude extracts, fractions and few isolated compounds of Anthocleista species showed antidiabetic, antiplasmodial, antimicrobial, hypotensive, spasmogenic, anti-obesity, antiulcerogenic, analgesic, anti-inflammatory, antioxidant, antitrypanosomal, anthelmintic, fertility, diuretic and laxative activities which supports most of their uses in traditional medicine. However, the bulk of the studies where centered on the antidiabetic, antiplasmodial and antimicrobial activities of Anthocleista species, although the evidence of its antiplasmodial effect was not convincing enough due to the discrepancies between the in vitro and in vivo results. A. djalonensis and A. vogelii are potential antidiabetic and antibacterial agents. The antibacterial potency relates to infections or diseases caused by E. coli, S. typhi and S. aureus such as urinary tract infections, typhoid, diarrhea, skin diseases, and food poisoning. Pharmacological research on this genus is quite elementary and limited, thus, more advanced research is necessary to isolate and determine the activities of bioactive compounds in vitro and in vivo, establish their mechanisms of action and commence the process of clinical research. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Chemical and biological sensing using tuning forks

DOEpatents

Tao, Nongjian; Boussaad, Salah

2012-07-10

A device for sensing a chemical analyte is disclosed. The device is comprised of a vibrating structure having first and second surfaces and having an associated resonant frequency and a wire coupled between the first and second surfaces of the vibrating structure, wherein the analyte interacts with the wire and causes a change in the resonant frequency of the vibrating structure. The vibrating structure can include a tuning fork. The vibrating structure can be comprised of quartz. The wire can be comprised of polymer. A plurality of vibrating structures are arranged in an array to increase confidence by promoting a redundancy of measurement or to detect a plurality of chemical analytes. A method of making a device for sensing a chemical analyte is also disclosed.

Computational Study on Atomic Structures, Electronic Properties, and Chemical Reactions at Surfaces and Interfaces and in Biomaterials

NASA Astrophysics Data System (ADS)

Takano, Yu; Kobayashi, Nobuhiko; Morikawa, Yoshitada

2018-06-01

Through computer simulations using atomistic models, it is becoming possible to calculate the atomic structures of localized defects or dopants in semiconductors, chemically active sites in heterogeneous catalysts, nanoscale structures, and active sites in biological systems precisely. Furthermore, it is also possible to clarify physical and chemical properties possessed by these nanoscale structures such as electronic states, electronic and atomic transport properties, optical properties, and chemical reactivity. It is sometimes quite difficult to clarify these nanoscale structure-function relations experimentally and, therefore, accurate computational studies are indispensable in materials science. In this paper, we review recent studies on the relation between local structures and functions for inorganic, organic, and biological systems by using atomistic computer simulations.

An Event-Related Potentials Study of Mental Rotation in Identifying Chemical Structural Formulas

ERIC Educational Resources Information Center

Huang, Chin-Fei; Liu, Chia-Ju

2012-01-01

The purpose of this study was to investigate how mental rotation strategies affect the identification of chemical structural formulas. This study conducted event-related potentials (ERPs) experiments. In addition to the data collected in the ERPs, a Chemical Structure Conceptual Questionnaire and interviews were also admin-istered for data…

Chemical compositions, methods of making the chemical compositions, and structures made from the chemical compositions

DOEpatents

Yang, Lei; Cheng, Zhe; Liu, Ze; Liu, Meilin

2015-01-13

Embodiments of the present disclosure include chemical compositions, structures, anodes, cathodes, electrolytes for solid oxide fuel cells, solid oxide fuel cells, fuel cells, fuel cell membranes, separation membranes, catalytic membranes, sensors, coatings for electrolytes, electrodes, membranes, and catalysts, and the like, are disclosed.

20180311 - Use of ToxPrint chemotypes for exploring chemical feature enrichments across the ToxCast chemical-assay landscape (SOT)

EPA Science Inventory

EPA’s ToxCast chemical library spans diverse chemical use-types, functionalities, structures and features potentially relevant to toxicity and environmental exposure. However, this structural diversity, along with assay noise and low average hit rates across the varied Tox...

Use of ToxPrint chemotypes for exploring chemical feature enrichments across the ToxCast chemical-assay landscape

EPA Science Inventory

EPA’s ToxCast chemical library spans diverse chemical use-types, functionalities, structures and features potentially relevant to toxicity and environmental exposure. However, this structural diversity, along with assay noise and low average hit rates across the varied ToxCast h...

Systematic chemical-genetic and chemical-chemical interaction datasets for prediction of compound synergism

PubMed Central

Wildenhain, Jan; Spitzer, Michaela; Dolma, Sonam; Jarvik, Nick; White, Rachel; Roy, Marcia; Griffiths, Emma; Bellows, David S.; Wright, Gerard D.; Tyers, Mike

2016-01-01

The network structure of biological systems suggests that effective therapeutic intervention may require combinations of agents that act synergistically. However, a dearth of systematic chemical combination datasets have limited the development of predictive algorithms for chemical synergism. Here, we report two large datasets of linked chemical-genetic and chemical-chemical interactions in the budding yeast Saccharomyces cerevisiae. We screened 5,518 unique compounds against 242 diverse yeast gene deletion strains to generate an extended chemical-genetic matrix (CGM) of 492,126 chemical-gene interaction measurements. This CGM dataset contained 1,434 genotype-specific inhibitors, termed cryptagens. We selected 128 structurally diverse cryptagens and tested all pairwise combinations to generate a benchmark dataset of 8,128 pairwise chemical-chemical interaction tests for synergy prediction, termed the cryptagen matrix (CM). An accompanying database resource called ChemGRID was developed to enable analysis, visualisation and downloads of all data. The CGM and CM datasets will facilitate the benchmarking of computational approaches for synergy prediction, as well as chemical structure-activity relationship models for anti-fungal drug discovery. PMID:27874849

Study of the structure and chemical composition of the protective coating of a fist stage gas turbine blade after regenerative heat treatment

NASA Astrophysics Data System (ADS)

Davidov, D. I.; Kazantseva, N. V.; Vinogradova, N. I.; Ezhov, I. V.

2017-12-01

Investigation of the structure and chemical composition of the protective coating of the first stage IN738 gas turbine blade after standard regenerative heat treatment was done. It was found the degradation of microstructure and chemical composition of both the blade feather and its protective coating. Redistribution of the chemical elements decreasing the corrosion resistance was observed inside the protective coating. Cracks on the boundary between the blade feather and the protective coating were found by scanning electron microscopy. The carbide transformation and sigma phase were found in the structure of the blade feather. Based upon the structural and chemical composition studies, it is concluded that the standard regenerative heat treatment of the IN738 operative gas turbine blade does not provide full structure regeneration.

One Hundred False-Positive Amphetamine Specimens Characterized by Liquid Chromatography Time-of-Flight Mass Spectrometry.

PubMed

Marin, Stephanie J; Doyle, Kelly; Chang, Annie; Concheiro-Guisan, Marta; Huestis, Marilyn A; Johnson-Davis, Kamisha L

2016-01-01

Some amphetamine (AMP) and ecstacy (MDMA) urine immunoassay (IA) kits are prone to false-positive results due to poor specificity of the antibody. We employed two techniques, high-resolution mass spectrometry (HRMS) and an in silico structure search, to identify compounds likely to cause false-positive results. Hundred false-positive IA specimens for AMP and/or MDMA were analyzed by an Agilent 6230 time-of-flight (TOF) mass spectrometer. Separately, SciFinder (Chemical Abstracts) was used as an in silico structure search to generate a library of compounds that are known to cross-react with AMP/MDMA IAs. Chemical formulas and exact masses of 145 structures were then compared against masses identified by TOF. Compounds known to have cross-reactivity with the IAs were identified in the structure-based search. The chemical formulas and exact masses of 145 structures (of 20 chemical formulas) were compared against masses identified by TOF. Urine analysis by HRMS correlates accurate mass with chemical formulae, but provides little information regarding compound structure. Structural data of targeted antigens can be utilized to correlate HRMS-derived chemical formulas with structural analogs. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Unraveling the meaning of chemical shifts in protein NMR.

PubMed

Berjanskii, Mark V; Wishart, David S

2017-11-01

Chemical shifts are among the most informative parameters in protein NMR. They provide wealth of information about protein secondary and tertiary structure, protein flexibility, and protein-ligand binding. In this report, we review the progress in interpreting and utilizing protein chemical shifts that has occurred over the past 25years, with a particular focus on the large body of work arising from our group and other Canadian NMR laboratories. More specifically, this review focuses on describing, assessing, and providing some historical context for various chemical shift-based methods to: (1) determine protein secondary and super-secondary structure; (2) derive protein torsion angles; (3) assess protein flexibility; (4) predict residue accessible surface area; (5) refine 3D protein structures; (6) determine 3D protein structures and (7) characterize intrinsically disordered proteins. This review also briefly covers some of the methods that we previously developed to predict chemical shifts from 3D protein structures and/or protein sequence data. It is hoped that this review will help to increase awareness of the considerable utility of NMR chemical shifts in structural biology and facilitate more widespread adoption of chemical-shift based methods by the NMR spectroscopists, structural biologists, protein biophysicists, and biochemists worldwide. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.

Clathrate Structure Determination by Combining Crystal Structure Prediction with Computational and Experimental 129Xe NMR Spectroscopy

PubMed Central

Selent, Marcin; Nyman, Jonas; Roukala, Juho; Ilczyszyn, Marek; Oilunkaniemi, Raija; Bygrave, Peter J.; Laitinen, Risto; Jokisaari, Jukka

2017-01-01

Abstract An approach is presented for the structure determination of clathrates using NMR spectroscopy of enclathrated xenon to select from a set of predicted crystal structures. Crystal structure prediction methods have been used to generate an ensemble of putative structures of o‐ and m‐fluorophenol, whose previously unknown clathrate structures have been studied by 129Xe NMR spectroscopy. The high sensitivity of the 129Xe chemical shift tensor to the chemical environment and shape of the crystalline cavity makes it ideal as a probe for porous materials. The experimental powder NMR spectra can be used to directly confirm or reject hypothetical crystal structures generated by computational prediction, whose chemical shift tensors have been simulated using density functional theory. For each fluorophenol isomer one predicted crystal structure was found, whose measured and computed chemical shift tensors agree within experimental and computational error margins and these are thus proposed as the true fluorophenol xenon clathrate structures. PMID:28111848

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.

A SEM Model in Assessing the Effect of Convergent, Divergent and Logical Thinking on Students' Understanding of Chemical Phenomena

ERIC Educational Resources Information Center

Stamovlasis, D.; Kypraios, N.; Papageorgiou, G.

2015-01-01

In this study, structural equation modeling (SEM) is applied to an instrument assessing students' understanding of chemical change. The instrument comprised items on understanding the structure of substances, chemical changes and their interpretation. The structural relationships among particular groups of items are investigated and analyzed using…

Chemical Information Literacy at a Liberal Arts College

ERIC Educational Resources Information Center

Greco, George E.

2016-01-01

Chemistry majors at Goucher College are now required to take a 1-credit course in their sophomore year entitled Chemical Information Literacy. Students in the course learn the structure and organization of the chemical literature, and how to carry out searches of various databases for topic, author, chemical compound, or structure. They learn…

Atomic Scale Structure-Chemistry Relationships at Oxide Catalyst Surfaces and Interfaces

NASA Astrophysics Data System (ADS)

McBriarty, Martin E.

Oxide catalysts are integral to chemical production, fuel refining, and the removal of environmental pollutants. However, the atomic-scale phenomena which lead to the useful reactive properties of catalyst materials are not sufficiently understood. In this work, the tools of surface and interface science and electronic structure theory are applied to investigate the structure and chemical properties of catalytically active particles and ultrathin films supported on oxide single crystals. These studies focus on structure-property relationships in vanadium oxide, tungsten oxide, and mixed V-W oxides on the surfaces of alpha-Al2O3 and alpha-Fe2O 3 (0001)-oriented single crystal substrates, two materials with nearly identical crystal structures but drastically different chemical properties. In situ synchrotron X-ray standing wave (XSW) measurements are sensitive to changes in the atomic-scale geometry of single crystal model catalyst surfaces through chemical reaction cycles, while X-ray photoelectron spectroscopy (XPS) reveals corresponding chemical changes. Experimental results agree with theoretical calculations of surface structures, allowing for detailed electronic structure investigations and predictions of surface chemical phenomena. The surface configurations and oxidation states of V and W are found to depend on the coverage of each, and reversible structural shifts accompany chemical state changes through reduction-oxidation cycles. Substrate-dependent effects suggest how the choice of oxide support material may affect catalytic behavior. Additionally, the structure and chemistry of W deposited on alpha-Fe 2O3 nanopowders is studied using X-ray absorption fine structure (XAFS) measurements in an attempt to bridge single crystal surface studies with real catalysts. These investigations of catalytically active material surfaces can inform the rational design of new catalysts for more efficient and sustainable chemistry.

Database resources of the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Barrett, Tanya; Benson, Dennis A.; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Kenton, David L.; Khovayko, Oleg; Lipman, David J.; Madden, Thomas L.; Maglott, Donna R.; Ostell, James; Pruitt, Kim D.; Schuler, Gregory D.; Schriml, Lynn M.; Sequeira, Edwin; Sherry, Stephen T.; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Suzek, Tugba O.; Tatusov, Roman; Tatusova, Tatiana A.; Wagner, Lukas; Yaschenko, Eugene

2006-01-01

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups, Retroviral Genotyping Tools, HIV-1, Human Protein Interaction Database, SAGEmap, Gene Expression Omnibus, Entrez Probe, GENSAT, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of the resources can be accessed through the NCBI home page at: . PMID:16381840

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bolton, Evan; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; Dicuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Krasnov, Sergey; Landsman, David; Lipman, David J; Lu, Zhiyong; Madden, Thomas L; Madej, Tom; Maglott, Donna R; Marchler-Bauer, Aron; Miller, Vadim; Karsch-Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Wang, Yanli; Wilbur, W John; Yaschenko, Eugene; Ye, Jian

2012-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Website. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Probe, Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique.

PubMed

Hao, Ming; Wang, Yanli; Bryant, Stephen H

2016-02-25

Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision-recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. Published by Elsevier B.V.

Database resources of the National Center for Biotechnology Information

PubMed Central

Acland, Abigail; Agarwala, Richa; Barrett, Tanya; Beck, Jeff; Benson, Dennis A.; Bollin, Colleen; Bolton, Evan; Bryant, Stephen H.; Canese, Kathi; Church, Deanna M.; Clark, Karen; DiCuccio, Michael; Dondoshansky, Ilya; Federhen, Scott; Feolo, Michael; Geer, Lewis Y.; Gorelenkov, Viatcheslav; Hoeppner, Marilu; Johnson, Mark; Kelly, Christopher; Khotomlianski, Viatcheslav; Kimchi, Avi; Kimelman, Michael; Kitts, Paul; Krasnov, Sergey; Kuznetsov, Anatoliy; Landsman, David; Lipman, David J.; Lu, Zhiyong; Madden, Thomas L.; Madej, Tom; Maglott, Donna R.; Marchler-Bauer, Aron; Karsch-Mizrachi, Ilene; Murphy, Terence; Ostell, James; O'Sullivan, Christopher; Panchenko, Anna; Phan, Lon; Pruitt, Don Preussm Kim D.; Rubinstein, Wendy; Sayers, Eric W.; Schneider, Valerie; Schuler, Gregory D.; Sequeira, Edwin; Sherry, Stephen T.; Shumway, Martin; Sirotkin, Karl; Siyan, Karanjit; Slotta, Douglas; Soboleva, Alexandra; Soussov, Vladimir; Starchenko, Grigory; Tatusova, Tatiana A.; Trawick, Bart W.; Vakatov, Denis; Wang, Yanli; Ward, Minghong; John Wilbur, W.; Yaschenko, Eugene; Zbicz, Kerry

2014-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, PubReader, Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link, Primer-BLAST, COBALT, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, the Genetic Testing Registry, Genome and related tools, the Map Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, ClinVar, MedGen, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Probe, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All these resources can be accessed through the NCBI home page. PMID:24259429

Metabolic Fingerprints from the Human Oral Microbiome Reveal a Vast Knowledge Gap of Secreted Small Peptidic Molecules.

PubMed

Edlund, Anna; Garg, Neha; Mohimani, Hosein; Gurevich, Alexey; He, Xuesong; Shi, Wenyuan; Dorrestein, Pieter C; McLean, Jeffrey S

2017-01-01

Recent research indicates that the human microbiota play key roles in maintaining health by providing essential nutrients, providing immune education, and preventing pathogen expansion. Processes underlying the transition from a healthy human microbiome to a disease-associated microbiome are poorly understood, partially because of the potential influences from a wide diversity of bacterium-derived compounds that are illy defined. Here, we present the analysis of peptidic small molecules (SMs) secreted from bacteria and viewed from a temporal perspective. Through comparative analysis of mass spectral profiles from a collection of cultured oral isolates and an established in vitro multispecies oral community, we found that the production of SMs both delineates a temporal expression pattern and allows discrimination between bacterial isolates at the species level. Importantly, the majority of the identified molecules were of unknown identity, and only ~2.2% could be annotated and classified. The catalogue of bacterially produced SMs we obtained in this study reveals an undiscovered molecular world for which compound isolation and ecosystem testing will facilitate a better understanding of their roles in human health and disease. IMPORTANCE Metabolomics is the ultimate tool for studies of microbial functions under any specific set of environmental conditions (D. S. Wishart, Nat Rev Drug Discov 45:473-484, 2016, https://doi.org/10.1038/nrd.2016.32). This is a great advance over studying genes alone, which only inform about metabolic potential. Approximately 25,000 compounds have been chemically characterized thus far; however, the richness of metabolites such as SMs has been estimated to be as high as 1 × 10 30 in the biosphere (K. Garber, Nat Biotechnol 33:228-231, 2015, https://doi.org/10.1038/nbt.3161). Our classical, one-at-a-time activity-guided approach to compound identification continues to find the same known compounds and is also incredibly tedious, which represents a major bottleneck for global SM identification. These challenges have prompted new developments of databases and analysis tools that provide putative classifications of SMs by mass spectral alignments to already characterized tandem mass spectrometry spectra and databases containing structural information (e.g., PubChem and AntiMarin). In this study, we assessed secreted peptidic SMs (PSMs) from 27 oral bacterial isolates and a complex oral in vitro biofilm community of >100 species by using the Global Natural Products Social molecular Networking and the DEREPLICATOR infrastructures, which are methodologies that allow automated and putative annotation of PSMs. These approaches enabled the identification of an untapped resource of PSMs from oral bacteria showing species-unique patterns of secretion with putative matches to known bioactive compounds.

Topological Characterization of Carbon Graphite and Crystal Cubic Carbon Structures.

PubMed

Siddiqui, Wei Gao Muhammad Kamran; Naeem, Muhammad; Rehman, Najma Abdul

2017-09-07

Graph theory is used for modeling, designing, analysis and understanding chemical structures or chemical networks and their properties. The molecular graph is a graph consisting of atoms called vertices and the chemical bond between atoms called edges. In this article, we study the chemical graphs of carbon graphite and crystal structure of cubic carbon. Moreover, we compute and give closed formulas of degree based additive topological indices, namely hyper-Zagreb index, first multiple and second multiple Zagreb indices, and first and second Zagreb polynomials.

Chem I Supplement: The Chemical Composition of the Cell.

ERIC Educational Resources Information Center

Holum, John R.

1984-01-01

Describes the principal chemical substances which occur in most cells. These chemicals are the lipids, carbohydrates, proteins, and nucleic acids. Suggests that the structures of these substances be taught first since structure determines function. (JN)

Thin-film chemical sensors based on electron tunneling

NASA Technical Reports Server (NTRS)

Khanna, S. K.; Lambe, J.; Leduc, H. G.; Thakoor, A. P.

1985-01-01

The physical mechanisms underlying a novel chemical sensor based on electron tunneling in metal-insulator-metal (MIM) tunnel junctions were studied. Chemical sensors based on electron tunneling were shown to be sensitive to a variety of substances that include iodine, mercury, bismuth, ethylenedibromide, and ethylenedichloride. A sensitivity of 13 parts per billion of iodine dissolved in hexane was demonstrated. The physical mechanisms involved in the chemical sensitivity of these devices were determined to be the chemical alteration of the surface electronic structure of the top metal electrode in the MIM structure. In addition, electroreflectance spectroscopy (ERS) was studied as a complementary surface-sensitive technique. ERS was shown to be sensitive to both iodine and mercury. Electrolyte electroreflectance and solid-state MIM electroreflectance revealed qualitatively the same chemical response. A modified thin-film structure was also studied in which a chemically active layer was introduced at the top Metal-Insulator interface of the MIM devices. Cobalt phthalocyanine was used for the chemically active layer in this study. Devices modified in this way were shown to be sensitive to iodine and nitrogen dioxide. The chemical sensitivity of the modified structure was due to conductance changes in the active layer.

ACToR – Aggregated Computational Toxicology Resource ...

EPA Pesticide Factsheets

ACToR (Aggregated Computational Toxicology Resource) is a collection of databases collated or developed by the US EPA National Center for Computational Toxicology (NCCT). More than 200 sources of publicly available data on environmental chemicals have been brought together and made searchable by chemical name and other identifiers, and by chemical structure. Data includes chemical structure, physico-chemical values, in vitro assay data and in vivo toxicology data. Chemicals include, but are not limited to, high and medium production volume industrial chemicals, pesticides (active and inert ingredients), and potential ground and drinking water contaminants.

Marine Chemical Ecology: Chemical Signals and Cues Structure Marine Populations, Communities, and Ecosystems

PubMed Central

Hay, Mark E.

2012-01-01

Chemical cues constitute much of the language of life in the sea. Our understanding of biotic interactions and their effects on marine ecosystems will advance more rapidly if this language is studied and understood. Here, I review how chemical cues regulate critical aspects of the behavior of marine organisms from bacteria to phytoplankton to benthic invertebrates and water column fishes. These chemically mediated interactions strongly affect population structure, community organization, and ecosystem function. Chemical cues determine foraging strategies, feeding choices, commensal associations, selection of mates and habitats, competitive interactions, and transfer of energy and nutrients within and among ecosystems. In numerous cases, the indirect effects of chemical signals on behavior have as much or more effect on community structure and function as the direct effects of consumers and pathogens. Chemical cues are critical for understanding marine systems, but their omnipresence and impact are inadequately recognized. PMID:21141035

Ring system-based chemical graph generation for de novo molecular design

NASA Astrophysics Data System (ADS)

Miyao, Tomoyuki; Kaneko, Hiromasa; Funatsu, Kimito

2016-05-01

Generating chemical graphs in silico by combining building blocks is important and fundamental in virtual combinatorial chemistry. A premise in this area is that generated structures should be irredundant as well as exhaustive. In this study, we develop structure generation algorithms regarding combining ring systems as well as atom fragments. The proposed algorithms consist of three parts. First, chemical structures are generated through a canonical construction path. During structure generation, ring systems can be treated as reduced graphs having fewer vertices than those in the original ones. Second, diversified structures are generated by a simple rule-based generation algorithm. Third, the number of structures to be generated can be estimated with adequate accuracy without actual exhaustive generation. The proposed algorithms were implemented in structure generator Molgilla. As a practical application, Molgilla generated chemical structures mimicking rosiglitazone in terms of a two dimensional pharmacophore pattern. The strength of the algorithms lies in simplicity and flexibility. Therefore, they may be applied to various computer programs regarding structure generation by combining building blocks.

The Use of Chemical-Chemical Interaction and Chemical Structure to Identify New Candidate Chemicals Related to Lung Cancer

PubMed Central

Zheng, Mingyue; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong

2015-01-01

Lung cancer causes over one million deaths every year worldwide. However, prevention and treatment methods for this serious disease are limited. The identification of new chemicals related to lung cancer may aid in disease prevention and the design of more effective treatments. This study employed a weighted network, constructed using chemical-chemical interaction information, to identify new chemicals related to two types of lung cancer: non-small lung cancer and small-cell lung cancer. Then, a randomization test as well as chemical-chemical interaction and chemical structure information were utilized to make further selections. A final analysis of these new chemicals in the context of the current literature indicates that several chemicals are strongly linked to lung cancer. PMID:26047514

NC-AFM observation of atomic scale structure of rutile-type TiO2(110) surface prepared by wet chemical process.

PubMed

Namai, Yoshimichi; Matsuoka, Osamu

2006-04-06

We succeeded in observing the atomic scale structure of a rutile-type TiO2(110) single-crystal surface prepared by the wet chemical method of chemical etching in an acid solution and surface annealing in air. Ultrahigh vacuum noncontact atomic force microscopy (UHV-NC-AFM) was used for observing the atomic scale structures of the surface. The UHV-NC-AFM measurements at 450 K, which is above a desorption temperature of molecularly adsorbed water on the TiO2(110) surface, enabled us to observe the atomic scale structure of the TiO2(110) surface prepared by the wet chemical method. In the UHV-NC-AFM measurements at room temperature (RT), however, the atomic scale structure of the TiO2(110) surface was not observed. The TiO2(110) surface may be covered with molecularly adsorbed water after the surface was prepared by the wet chemical method. The structure of the TiO2(110) surface that was prepared by the wet chemical method was consistent with the (1 x 1) bulk-terminated model of the TiO2(110) surface.

Protein Structure Validation and Refinement Using Amide Proton Chemical Shifts Derived from Quantum Mechanics

PubMed Central

Christensen, Anders S.; Linnet, Troels E.; Borg, Mikael; Boomsma, Wouter; Lindorff-Larsen, Kresten; Hamelryck, Thomas; Jensen, Jan H.

2013-01-01

We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts - sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level QM results obtained for a small protein with an RMSD of 0.25 ppm (r = 0.94). ProCS is interfaced with the PHAISTOS protein simulation program and is used to infer statistical protein ensembles that reflect experimentally measured amide proton chemical shift values. Such chemical shift-based structural refinements, starting from high-resolution X-ray structures of Protein G, ubiquitin, and SMN Tudor Domain, result in average chemical shifts, hydrogen bond geometries, and trans-hydrogen bond (h3 JNC') spin-spin coupling constants that are in excellent agreement with experiment. We show that the structural sensitivity of the QM-based amide proton chemical shift predictions is needed to obtain this agreement. The ProCS method thus offers a powerful new tool for refining the structures of hydrogen bonding networks to high accuracy with many potential applications such as protein flexibility in ligand binding. PMID:24391900

The Role of Hypothalamic Insulin and Dopamine in the Anorectic Effect of Cocaine and d-amphetamine

DTIC Science & Technology

1992-08-21

15: Figure 16: Figure 17: Figure 18: LIST OF FIGURES Chemical structure of cocaine Chemical structure of amphetamine Cocaine groups! Average...prevent hypotension (Hoffman, 1987). The chemical structure of amphetamine is shown in figure 2. General Aspects: The term amphetamine applies to a group...cormnunication, 1991). 26 Germany in the 1930’s, with c hemical structures resembling those of epinephrine and NE. Their effects are similar to those of

NMRDSP: an accurate prediction of protein shape strings from NMR chemical shifts and sequence data.

PubMed

Mao, Wusong; Cong, Peisheng; Wang, Zhiheng; Lu, Longjian; Zhu, Zhongliang; Li, Tonghua

2013-01-01

Shape string is structural sequence and is an extremely important structure representation of protein backbone conformations. Nuclear magnetic resonance chemical shifts give a strong correlation with the local protein structure, and are exploited to predict protein structures in conjunction with computational approaches. Here we demonstrate a novel approach, NMRDSP, which can accurately predict the protein shape string based on nuclear magnetic resonance chemical shifts and structural profiles obtained from sequence data. The NMRDSP uses six chemical shifts (HA, H, N, CA, CB and C) and eight elements of structure profiles as features, a non-redundant set (1,003 entries) as the training set, and a conditional random field as a classification algorithm. For an independent testing set (203 entries), we achieved an accuracy of 75.8% for S8 (the eight states accuracy) and 87.8% for S3 (the three states accuracy). This is higher than only using chemical shifts or sequence data, and confirms that the chemical shift and the structure profile are significant features for shape string prediction and their combination prominently improves the accuracy of the predictor. We have constructed the NMRDSP web server and believe it could be employed to provide a solid platform to predict other protein structures and functions. The NMRDSP web server is freely available at http://cal.tongji.edu.cn/NMRDSP/index.jsp.

Miraxanthin-V, Liriodenin and Chitranone are Hepcidin Antagonist In silico for Iron Deficiency Anemia

NASA Astrophysics Data System (ADS)

Yotriana, S.; Suselo, YH; Muthmainah; Indarto, D.

2018-03-01

Anemia is one of the greatest nutrition problem in the world that is commonly found in children, pregnant women and reproductive women. This disorder is predominantly caused by iron deficiency. Hepcidin, a hepatic hormone, regulates iron metabolism and high serum levels of this hormone are detected in patients with iron deficiency anemia (IDA). Anticalin is a sintetic compound which is able to interacts with hepcidin leading to inhibition of ferroportin-hepcidin binding complexes but its therapeutic effects are still under investigation. Indonesia has various herbal plants which are potentially developed to treat some human diseases. Therefore, the purpose of this study was to identify phytochemicals derived from Indonesian plants that is able to inhibit hepcidin-ferroportin interaction. A bioinformatics study with molecular docking method was used in this study. Three-dimensional structures of human hepcidin and anticalin were obtained from the Protein Data Bank (ID: 1M4F and 4QAE respectively). Because their molecular size was big, each molecule was cut into 2 parts of its binding sites. All phytochemicals structures were obtained from HerbalDB and PubChem NCBI database. Truncated anticalin/phytochemicals were molecularly docked with truncated hepcidin by using AutoDock Vina 1.1.2. and their interactions were visualized using PyMol 1.3. Truncated Anticalin had -4.6 and -4.2 kcal/mol binding affinity to truncated human hepcidin. Truncated anticalin 1 was bound to Cys13, Cys14, Arg16 and Ser17 residues in truncated hepcidin 1 while truncated anticalin 2 was at Cy23 and Lys24 residues in truncated hepcidin 2. Miraxanthine-V, Liriodenin and Chitranone had lower binding affinity (-4.8±0.77, -4.7±0.33 and -5.01±0.30 kcal/mol respectively) than that of anticalin and occupied binding sites as same as anticalin did. There are three phytochemicals that potentially become hepcidin antagonists in silico. In vitro assays are required for verification of the antagonist effect of these phytochemicals on iron metabolism.

Inhibition of VEGF: a novel mechanism to control angiogenesis by Withania somnifera's key metabolite Withaferin A.

PubMed

Saha, Sanjib; Islam, Md Khirul; Shilpi, Jamil A; Hasan, Shihab

2013-01-01

Angiogenesis, or new blood vessel formation from existing one, plays both beneficial and detrimental roles in living organisms in different aspects. Vascular endothelial growth factor (VEGF), a signal protein, well established as key regulator of vasculogenesis and angiogenesis. VEGF ensures oxygen supply to the tissues when blood supply is not adequate, or tissue environment is in hypoxic condition. Limited expression of VEGF is necessary, but if it is over expressed, then it can lead to serious disease like cancer. Cancers that have ability to express VEGF are more efficient to grow and metastasize because solid cancers cannot grow larger than a limited size without adequate blood and oxygen supply. Anti-VEGF drugs are already available in the market to control angiogenesis, but they are often associated with severe side-effects like fetal bleeding and proteinuria in the large number of patients. To avoid such side-effects, new insight is required to find potential compounds as anti-VEGF from natural sources. In the present investigation, molecular docking studies were carried out to find the potentiality of Withaferin A, a key metabolite of Withania somnifera, as an inhibitor of VEGF. Molecular Docking studies were performed in DockingServer and SwissDock. Bevacizumab, a commercial anti-VEGF drug, was used as reference to compare the activity of Withaferin A. X-ray crystallographic structure of VEGF, was retrieved from Protein Data Bank (PDB), and used as drug target protein. Structure of Withaferin A and Bevacizumab was obtained from PubChem and ZINC databases. Molecular visualization was performed using UCSF Chimera. Withaferin A showed favorable binding with VEGF with low binding energy in comparison to Bevacizumab. Molecular Docking studies also revealed potential protein-ligand interactions for both Withaferin A and Bevacizumab. Conclusively our results strongly suggest that Withaferin A is a potent anti-VEGF agent as ascertained by its potential interaction with VEGF. This scientific hypothesis might provide a better insight to control angiogenesis as well as to control solid cancer growth and metastasis.

Chemical graphs, molecular matrices and topological indices in chemoinformatics and quantitative structure-activity relationships.

PubMed

Ivanciuc, Ovidiu

2013-06-01

Chemical and molecular graphs have fundamental applications in chemoinformatics, quantitative structureproperty relationships (QSPR), quantitative structure-activity relationships (QSAR), virtual screening of chemical libraries, and computational drug design. Chemoinformatics applications of graphs include chemical structure representation and coding, database search and retrieval, and physicochemical property prediction. QSPR, QSAR and virtual screening are based on the structure-property principle, which states that the physicochemical and biological properties of chemical compounds can be predicted from their chemical structure. Such structure-property correlations are usually developed from topological indices and fingerprints computed from the molecular graph and from molecular descriptors computed from the three-dimensional chemical structure. We present here a selection of the most important graph descriptors and topological indices, including molecular matrices, graph spectra, spectral moments, graph polynomials, and vertex topological indices. These graph descriptors are used to define several topological indices based on molecular connectivity, graph distance, reciprocal distance, distance-degree, distance-valency, spectra, polynomials, and information theory concepts. The molecular descriptors and topological indices can be developed with a more general approach, based on molecular graph operators, which define a family of graph indices related by a common formula. Graph descriptors and topological indices for molecules containing heteroatoms and multiple bonds are computed with weighting schemes based on atomic properties, such as the atomic number, covalent radius, or electronegativity. The correlation in QSPR and QSAR models can be improved by optimizing some parameters in the formula of topological indices, as demonstrated for structural descriptors based on atomic connectivity and graph distance.

ESTIMATION OF CHEMICAL SPECIFIC PARAMETERS WITHIN PHYSIOLOGICALLY BASED PHARMACOKINETIC/PHARMACODYNAMIC MODELS

EPA Science Inventory

While relationships between chemical structure and observed properties or activities (QSAR - quantitative structure activity relationship) can be used to predict the behavior of unknown chemicals, this method is semiempirical in nature relying on high quality experimental data to...

THYROID HORMONE DISRUPTION: FROM KINETICS TO DYNAMICS.

EPA Science Inventory

A wide range of chemicals with diverse structures act as thyroid disrupting chemicals (TDCs). Broadly defined, TDCs are chemicals that alter the structure or function of the thyroid gland, alter regulatory enzymes associated with thyroid hormones (THs), or change circulating or t...

A SURVEY OF CHEMICAL AND BIOLOGICAL STRUCTURE IN THREE FLORIDA BAYOU-ESTUARIES

EPA Science Inventory

Structural and functional characteristics of the benthic biota were determined and compared for three urbanized bayous, in conjuction with sediment chemical quality and acute toxicity. Sediment chemical contamination in the bayous was common. Numerical sediment quality assessmen...

[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.

Estimation of human percutaneous bioavailability for two novel brominated flame retardants, 2-ethylhexyl 2,3,4,5-tetrabromobenzoate (EH-TBB) and bis(2-ethylhexyl) tetrabromophthalate (BEH-TEBP).

PubMed

Knudsen, Gabriel A; Hughes, Michael F; Sanders, J Michael; Hall, Samantha M; Birnbaum, Linda S

2016-11-15

2-Ethylhexyl-2,3,4,5-tetrabromobenzoate (EH-TBB) and bis(2-ethylhexyl)tetrabromophthalate (BEH-TEBP) are novel brominated flame retardants used in consumer products. A parallelogram approach was used to predict human dermal absorption and flux for EH-TBB and BEH-TEBP. [ 14 C]-EH-TBB or [ 14 C]-BEH-TEBP was applied to human or rat skin at 100nmol/cm 2 using a flow-through system. Intact rats received analogous dermal doses. Treated skin was washed and tape-stripped to remove "unabsorbed" [ 14 C]-radioactivity after continuous exposure (24h). "Absorbed" was quantified using dermally retained [ 14 C]-radioactivity; "penetrated" was calculated based on [ 14 C]-radioactivity in media (in vitro) or excreta+tissues (in vivo). Human skin absorbed EH-TBB (24±1%) while 0.2±0.1% penetrated skin. Rat skin absorbed more (51±10%) and was more permeable (2±0.5%) to EH-TBB in vitro; maximal EH-TBB flux was 11±7 and 102±24pmol-eq/cm 2 /h for human and rat skin, respectively. In vivo, 27±5% was absorbed and 13% reached systemic circulation after 24h (maximum flux was 464±65pmol-eq/cm 2 /h). BEH-TEBP in vitro penetrance was minimal (<0.01%) for rat or human skin. BEH-TEBP absorption was 12±11% for human skin and 41±3% for rat skin. In vivo, total absorption was 27±9%; 1.2% reached systemic circulation. In vitro maximal BEH-TEBP flux was 0.3±0.2 and 1±0.3pmol-eq/cm 2 /h for human and rat skin; in vivo maximum flux for rat skin was 16±7pmol-eq/cm 2 /h. EH-TBB was metabolized in rat and human skin to tetrabromobenzoic acid. BEH-TEBP-derived [ 14 C]-radioactivity in the perfusion media could not be characterized. <1% of the dose of EH-TBB and BEH-TEHP is estimated to reach the systemic circulation following human dermal exposure under the conditions tested. 2-Ethylhexyl 2,3,4,5-tetrabromobenzoate (PubChem CID: 71316600; CAS No. 183658-27-7 FW: 549.92g/mol logP est : 7.73-8.75 (12)) Abdallah et al., 2015a. Other published abbreviations for 2-ethylhexyl-2,3,4,5-tetrabromobenzoate are TBB EHTeBB or EHTBB Abdallah and Harrad, 2011. bis(2-ethylhexyl) tetrabromophthalate (PubChem CID: 117291; CAS No. 26040-51-7 FW: 706.14g/mol logP est : 9.48-11.95 (12)). Other published abbreviations for bis(2-ethylhexyl)tetrabromophthalate are TeBrDEPH TBPH or BEHTBP. Published by Elsevier Inc.

Deducing chemical structure from crystallographically determined atomic coordinates

PubMed Central

Bruno, Ian J.; Shields, Gregory P.; Taylor, Robin

2011-01-01

An improved algorithm has been developed for assigning chemical structures to incoming entries to the Cambridge Structural Database, using only the information available in the deposited CIF. Steps in the algorithm include detection of bonds, selection of polymer unit, resolution of disorder, and assignment of bond types and formal charges. The chief difficulty is posed by the large number of metallo-organic crystal structures that must be processed, given our aspiration that assigned chemical structures should accurately reflect properties such as the oxidation states of metals and redox-active ligands, metal coordination numbers and hapticities, and the aromaticity or otherwise of metal ligands. Other complications arise from disorder, especially when it is symmetry imposed or modelled with the SQUEEZE algorithm. Each assigned structure is accompanied by an estimate of reliability and, where necessary, diagnostic information indicating probable points of error. Although the algorithm was written to aid building of the Cambridge Structural Database, it has the potential to develop into a general-purpose tool for adding chemical information to newly determined crystal structures. PMID:21775812

"Just as the Structural Formula Does": Names, Diagrams, and the Structure of Organic Chemistry at the 1892 Geneva Nomenclature Congress.

PubMed

Hepler-Smith, Evan

2015-02-01

At the Geneva Nomenclature Congress of 1892, some of the foremost organic chemists of the late nineteenth century crafted a novel relationship between chemical substances, chemical diagrams, and chemical names that has shaped practices of chemical representation ever since. During the 1880s, the French chemist Charles Friedel organised the nomenclature reform effort that culminated in the Geneva Congress; in the disorderly nomenclature of German synthetic chemistry, Friedel saw an opportunity to advance French national interests and his own pedagogical goals. Friedel and a group of close colleagues reconceived nomenclature as a unified field, in which all chemical names ought to relate clearly to one another and to the structure of the compounds they represented. The German chemist Adolf von Baeyer went a step farther, arguing for names that precisely and uniquely corresponded to the structural formula of each compound, tailored for use in chemical dictionaries and handbooks. Baeyer's vision prevailed at the Geneva Congress, which consequently codified rules for rigorously mapping structural formulas into names, resulting in names that faithfully represented the features of these diagrams but not always the chemical behaviour of the compounds themselves. This approach ultimately limited both the number of chemical compounds that the Geneva rules were able to encompass and the breadth of their application. However, the relationship between diagram and name established at the Geneva Congress became the foundation not only of subsequent systems of chemical nomenclature but of methods of organising information that have supported the modern chemical sciences.

MICROBIAL TRANSFORMATION RATE CONSTANTS OF STRUCTURALLY DIVERSE MAN-MADE CHEMICALS

EPA Science Inventory

To assist in estimating microbially mediated transformation rates of man-made chemicals from their chemical structures, all second order rate constants that have been measured under conditions that make the values comparable have been extracted from the literature and combined wi...

AI AND SAR APPROACHES FOR PREDICTING CHEMICAL CARCINOGENICITY: SURVEY AND STATUS REPORT

EPA Science Inventory

A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoin...

Forecasting the Environmental Impacts of New Energetic Materials

DTIC Science & Technology

2010-11-30

Quantitative structure- activity relationships for chemical reductions of organic contaminants. Environmental Toxicology and Chemistry 22(8): 1733-1742. QSARs ...activity relationships [ QSARs ]) and the use of these properties to predict the chemical?s fate with multimedia assessment models. SERDP has recently...has several parts, including the prediction of chemical properties (e.g., with quantitative structure-activity relationships [ QSARs ]) and the use of

Identification of Lilial as a fragrance sensitizer in a perfume by bioassay-guided chemical fractionation and structure-activity relationships.

PubMed

Arnau, E G; Andersen, K E; Bruze, M; Frosch, P J; Johansen, J D; Menné, T; Rastogi, S C; White, I R; Lepoittevin, J P

2000-12-01

Fragrance materials are among the most common causes of allergic contact dermatitis. The aim of this study was to identify in a perfume fragrance allergens not included in the fragrance mix, by use of bioassay-guided chemical fractionation and chemical analysis/structure-activity relationships (SARs). The basis for the investigation was a 45-year-old woman allergic to her own perfume. She had a negative patch test to the fragrance mix and agreed to participate in the study. Chemical fractionation of the perfume concentrate was used for repeated patch testing and/or repeated open application test on the pre-sensitized patient. The chemical composition of the fractions giving a positive patch-test response and repeated open application test reactions was obtained by gas chromatography-mass spectrometry. From the compounds identified, those that contained a "structural alert" in their chemical structure, indicating an ability to modify skin proteins and thus behave as a skin sensitizer, were tested on the patient. The patient reacted positively to the synthetic fragrance p-t-butyl-alpha-methylhydrocinnamic aldehyde (Lilial), a widely used fragrance compound not present in the fragrance mix. The combination of bioassay-guided chemical fractionation and chemical analysis/structure-activity relationships seems to be a valuable tool for the investigation of contact allergy to fragrance materials.

LigandBox: A database for 3D structures of chemical compounds

PubMed Central

Kawabata, Takeshi; Sugihara, Yusuke; Fukunishi, Yoshifumi; Nakamura, Haruki

2013-01-01

A database for the 3D structures of available compounds is essential for the virtual screening by molecular docking. We have developed the LigandBox database (http://ligandbox.protein.osaka-u.ac.jp/ligandbox/) containing four million available compounds, collected from the catalogues of 37 commercial suppliers, and approved drugs and biochemical compounds taken from KEGG_DRUG, KEGG_COMPOUND and PDB databases. Each chemical compound in the database has several 3D conformers with hydrogen atoms and atomic charges, which are ready to be docked into receptors using docking programs. The 3D conformations were generated using our molecular simulation program package, myPresto. Various physical properties, such as aqueous solubility (LogS) and carcinogenicity have also been calculated to characterize the ADME-Tox properties of the compounds. The Web database provides two services for compound searches: a property/chemical ID search and a chemical structure search. The chemical structure search is performed by a descriptor search and a maximum common substructure (MCS) search combination, using our program kcombu. By specifying a query chemical structure, users can find similar compounds among the millions of compounds in the database within a few minutes. Our database is expected to assist a wide range of researchers, in the fields of medical science, chemical biology, and biochemistry, who are seeking to discover active chemical compounds by the virtual screening. PMID:27493549

LigandBox: A database for 3D structures of chemical compounds.

PubMed

Kawabata, Takeshi; Sugihara, Yusuke; Fukunishi, Yoshifumi; Nakamura, Haruki

2013-01-01

A database for the 3D structures of available compounds is essential for the virtual screening by molecular docking. We have developed the LigandBox database (http://ligandbox.protein.osaka-u.ac.jp/ligandbox/) containing four million available compounds, collected from the catalogues of 37 commercial suppliers, and approved drugs and biochemical compounds taken from KEGG_DRUG, KEGG_COMPOUND and PDB databases. Each chemical compound in the database has several 3D conformers with hydrogen atoms and atomic charges, which are ready to be docked into receptors using docking programs. The 3D conformations were generated using our molecular simulation program package, myPresto. Various physical properties, such as aqueous solubility (LogS) and carcinogenicity have also been calculated to characterize the ADME-Tox properties of the compounds. The Web database provides two services for compound searches: a property/chemical ID search and a chemical structure search. The chemical structure search is performed by a descriptor search and a maximum common substructure (MCS) search combination, using our program kcombu. By specifying a query chemical structure, users can find similar compounds among the millions of compounds in the database within a few minutes. Our database is expected to assist a wide range of researchers, in the fields of medical science, chemical biology, and biochemistry, who are seeking to discover active chemical compounds by the virtual screening.

Alarms about structural alerts.

PubMed

Alves, Vinicius; Muratov, Eugene; Capuzzi, Stephen; Politi, Regina; Low, Yen; Braga, Rodolpho; Zakharov, Alexey V; Sedykh, Alexander; Mokshyna, Elena; Farag, Sherif; Andrade, Carolina; Kuz'min, Victor; Fourches, Denis; Tropsha, Alexander

2016-08-21

Structural alerts are widely accepted in chemical toxicology and regulatory decision support as a simple and transparent means to flag potential chemical hazards or group compounds into categories for read-across. However, there has been a growing concern that alerts disproportionally flag too many chemicals as toxic, which questions their reliability as toxicity markers. Conversely, the rigorously developed and properly validated statistical QSAR models can accurately and reliably predict the toxicity of a chemical; however, their use in regulatory toxicology has been hampered by the lack of transparency and interpretability. We demonstrate that contrary to the common perception of QSAR models as "black boxes" they can be used to identify statistically significant chemical substructures (QSAR-based alerts) that influence toxicity. We show through several case studies, however, that the mere presence of structural alerts in a chemical, irrespective of the derivation method (expert-based or QSAR-based), should be perceived only as hypotheses of possible toxicological effect. We propose a new approach that synergistically integrates structural alerts and rigorously validated QSAR models for a more transparent and accurate safety assessment of new chemicals.

Efficient enumeration of monocyclic chemical graphs with given path frequencies

PubMed Central

2014-01-01

Background The enumeration of chemical graphs (molecular graphs) satisfying given constraints is one of the fundamental problems in chemoinformatics and bioinformatics because it leads to a variety of useful applications including structure determination and development of novel chemical compounds. Results We consider the problem of enumerating chemical graphs with monocyclic structure (a graph structure that contains exactly one cycle) from a given set of feature vectors, where a feature vector represents the frequency of the prescribed paths in a chemical compound to be constructed and the set is specified by a pair of upper and lower feature vectors. To enumerate all tree-like (acyclic) chemical graphs from a given set of feature vectors, Shimizu et al. and Suzuki et al. proposed efficient branch-and-bound algorithms based on a fast tree enumeration algorithm. In this study, we devise a novel method for extending these algorithms to enumeration of chemical graphs with monocyclic structure by designing a fast algorithm for testing uniqueness. The results of computational experiments reveal that the computational efficiency of the new algorithm is as good as those for enumeration of tree-like chemical compounds. Conclusions We succeed in expanding the class of chemical graphs that are able to be enumerated efficiently. PMID:24955135

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.

THE PRACTICE OF STRUCTURE ACTIVITY RELATIONSHIPS (SAR) IN TOXICOLOGY

EPA Science Inventory

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

Chemically Patterned Inverse Opal Created by a Selective Photolysis Modification Process.

PubMed

Tian, Tian; Gao, Ning; Gu, Chen; Li, Jian; Wang, Hui; Lan, Yue; Yin, Xianpeng; Li, Guangtao

2015-09-02

Anisotropic photonic crystal materials have long been pursued for their broad applications. A novel method for creating chemically patterned inverse opals is proposed here. The patterning technique is based on selective photolysis of a photolabile polymer together with postmodification on released amine groups. The patterning method allows regioselective modification within an inverse opal structure, taking advantage of selective chemical reaction. Moreover, combined with the unique signal self-reporting feature of the photonic crystal, the fabricated structure is capable of various applications, including gradient photonic bandgap and dynamic chemical patterns. The proposed method provides the ability to extend the structural and chemical complexity of the photonic crystal, as well as its potential applications.

The past and future of chemical information - A report of the Chemical Information Division Session of the 200th Meeting of the American Chemical Society

NASA Astrophysics Data System (ADS)

Tokizane, Soichi

At the historical meeting of the ACS CINF Division, the 1990 Herman Skolnik Award was presented to Dr. Ernst Meyer, who at BASF in Germany had developed a computer storage and retrieval system of chemical structures in 1960s. His and his colleagues' speeches in the award symposium were about the history of the development of chemical structure information in Germany. In the symposium of the Markush structure system, a hottest topic in this field, CAS's MARPAT and Markush-DARC co-developed by Questel, INPI, and Derwent were discussed by many papers. Other topics of this meeting were discussed, too.

Toxmatch-a new software tool to aid in the development and evaluation of chemically similar groups.

PubMed

Patlewicz, G; Jeliazkova, N; Gallegos Saliner, A; Worth, A P

2008-01-01

Chemical similarity is a widely used concept in toxicology, and is based on the hypothesis that similar compounds should have similar biological activities. This forms the underlying basis for performing read-across, forming chemical groups and developing (Quantitative) Structure-Activity Relationships ((Q)SARs). Chemical similarity is often perceived as structural similarity but in fact there are a number of other approaches that can be used to assess similarity. A systematic similarity analysis usually comprises two main steps. Firstly the chemical structures to be compared need to be characterised in terms of relevant descriptors which encode their physicochemical, topological, geometrical and/or surface properties. A second step involves a quantitative comparison of those descriptors using similarity (or dissimilarity) indices. This work outlines the use of chemical similarity principles in the formation of endpoint specific chemical groupings. Examples are provided to illustrate the development and evaluation of chemical groupings using a new software application called Toxmatch that was recently commissioned by the European Chemicals Bureau (ECB), of the European Commission's Joint Research Centre. Insights from using this software are highlighted with specific focus on the prospective application of chemical groupings under the new chemicals legislation, REACH.

Atoms versus Bonds: How Students Look at Spectra

ERIC Educational Resources Information Center

Cullipher, Steven; Sevian, Hannah

2015-01-01

Students often face difficulties when presented with chemical structures and asked to relate them to properties of those substances. Learning to relate structures to properties, both in predicting properties based on chemical structures and interpreting properties to infer structure, is pivotal in students' education in chemistry. This troublesome…

Wu-Tou Decoction in Rheumatoid Arthritis: Integrating Network Pharmacology and In Vivo Pharmacological Evaluation

PubMed Central

Guo, Qingqing; Zheng, Kang; Fan, Danping; Zhao, Yukun; Li, Li; Bian, Yanqin; Qiu, Xuemei; Liu, Xue; Zhang, Ge; Ma, Chaoying; He, Xiaojuan; Lu, Aiping

2017-01-01

Purpose: This study aimed to explore underlying action mechanism of Wu-Tou decoction (WTD) in rheumatoid arthritis (RA) through network pharmacology prediction and experimental verification. Methods: Chemical compounds and human target proteins of WTD as well as RA-related human genes were obtained from TCM Database @ Taiwan, PubChem and GenBank, respectively. Subsequently, molecular networks and canonical pathways presumably involved in the treatment of WTD on RA were generated by ingenuity pathway analysis (IPA) software. Furthermore, experimental validation was carried out with MIP-1β-induced U937 cell model and collagen induced arthritis (CIA) rat model. Results: CCR5 signaling pathway in macrophages was shown to be the top one shared signaling pathway associated with both cell immune response and cytokine signaling. In addition, protein kinase C (PKC) δ and p38 in this pathway were treated as target proteins of WTD in RA. In vitro experiments indicated that WTD inhibited MIP-1β-induced production of TNF-α, MIP-1α, and RANTES as well as phosphorylation of CCR5, PKC δ, and p38 in U937 cells. WTD treatment maintained the inhibitory effects on production of TNF-α and RANTES in MIP-1β-induced U937 cells after CCR5 knockdown. In vivo experiments demonstrated that WTD ameliorated symptoms in CIA rats, decreased the levels of IL-1β, IL-2, IL-6, TNF-α, MIP-1α, MIP-2, RANTES, and IP-10 in serum of CIA rats, as well as mRNA levels of MIP-1α, MIP-2, RANTES, and IP-10 in ankle joints of CIA rats. Furthermore, WTD also lowered the phosphorylation levels of CCR5, PKC δ and p38 in both ankle joints and macrophages in ankle joints from CIA rats. Conclusion: It was demonstrated in this research that WTD played a role in inhibiting inflammatory response in RA which was closely connected with the modulation effect of WTD on CCR5 signaling pathway in macrophages. PMID:28515692

Kigelia africana (Lam.) Benth. (Sausage tree): Phytochemistry and pharmacological review of a quintessential African traditional medicinal plant.

PubMed

Bello, Idris; Shehu, Mustapha W; Musa, Mustapha; Zaini Asmawi, Mohd; Mahmud, Roziahanim

2016-08-02

Kigelia africana is a quintessential African herbal medicinal plant with a pan-African distribution and immense indigenous medicinal and non-medicinal applications. The plant is use traditionally as a remedy for numerous disease such as use wounds healing, rheumatism, psoriasis, diarrhea and stomach ailments. It is also use as an aphrodisiac and for skin care. The present review aims to compile an up-to-date review of the progress made in the continuous pharmacological and phytochemistry investigation of K. africana and the corresponding commercial and pharmaceutical application of these findings with the ultimate objective of providing a guide for future research on this plant. The scholarly information needed for this paper were predominantly sourced from the electronic search engines such as Google, Google scholar; publishing sites such as Elsevier, scienceDirect, BMC, PubMed; other scientific database sites for chemicals such as ChemSpider, PubChem, and also from online books. Pharmacological investigations conducted confirm the anti-inflammatory, analgesic, antioxidant and anticancer activity of the extract of different parts of the plant. Bioactive constituents are found to be present in all parts of the plant. So far, approximately 150 compounds have been characterized from different part of the plant. Iridoids, naphthoquinones, flavonoids, terpenes and phenylethanoglycosides are the major class of compounds isolated. Novel compounds with potent antioxidant, antimicrobial and anticancer effect such as verbascoside, verminoside and pinnatal among others, have been identified. Commercial trade of K. africana has boosted in the las few decades. Its effect in the maintenance of skin has been recognized resulting in a handful of skin formulations in the market. The pharmaceutical potentials of K. africana has been recognized and have witness a surge in research interest. However, till date, many of its traditional medicinal uses has not been investigated scientifically. Further probing of the existential researches on its pharmacological activity is recommended with the end-goal of unravelling the pharmacodynamics, pharmacokinetics, clinical relevance and possible toxicity and side effects of both the extract and the active ingredients isolated. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The Nature of the Chemical Bond--1990.

ERIC Educational Resources Information Center

Ogilvie, J. F.

1990-01-01

Three aspects of quantum mechanics in modern chemistry are stressed: the fundamental structure of quantum mechanics as a basis of chemical applications, the relationship of quantum mechanics to atomic and molecular structure, and the consequent implications for chemical education. A list of 64 references is included. (CW)

Sharing chemical structures with peer-reviewed publications. Are we there yet?

EPA Science Inventory

In the domain of chemistry one of the greatest benefits to publishing research is that data are shared. Unfortunately, the vast majority of chemical structure data remain locked up in document form, primarily as PDF files. Despite the explosive growth of online chemical databases...

DSSTox and Chemical Information Technologies in Support of PredictiveToxicology

EPA Science Inventory

The EPA NCCT Distributed Structure-Searchable Toxicity (DSSTox) Database project initially focused on the curation and publication of high-quality, standardized, chemical structure-annotated toxicity databases for use in structure-activity relationship (SAR) modeling. In recent y...

Distributed structure-searchable toxicity (DSSTox) public database network: a proposal.

PubMed

Richard, Ann M; Williams, ClarLynda R

2002-01-29

The ability to assess the potential genotoxicity, carcinogenicity, or other toxicity of pharmaceutical or industrial chemicals based on chemical structure information is a highly coveted and shared goal of varied academic, commercial, and government regulatory groups. These diverse interests often employ different approaches and have different criteria and use for toxicity assessments, but they share a need for unrestricted access to existing public toxicity data linked with chemical structure information. Currently, there exists no central repository of toxicity information, commercial or public, that adequately meets the data requirements for flexible analogue searching, Structure-Activity Relationship (SAR) model development, or building of chemical relational databases (CRD). The distributed structure-searchable toxicity (DSSTox) public database network is being proposed as a community-supported, web-based effort to address these shared needs of the SAR and toxicology communities. The DSSTox project has the following major elements: (1) to adopt and encourage the use of a common standard file format (structure data file (SDF)) for public toxicity databases that includes chemical structure, text and property information, and that can easily be imported into available CRD applications; (2) to implement a distributed source approach, managed by a DSSTox Central Website, that will enable decentralized, free public access to structure-toxicity data files, and that will effectively link knowledgeable toxicity data sources with potential users of these data from other disciplines (such as chemistry, modeling, and computer science); and (3) to engage public/commercial/academic/industry groups in contributing to and expanding this community-wide, public data sharing and distribution effort. The DSSTox project's overall aims are to effect the closer association of chemical structure information with existing toxicity data, and to promote and facilitate structure-based exploration of these data within a common chemistry-based framework that spans toxicological disciplines.

Fragment-Based Electronic Structure Approach for Computing Nuclear Magnetic Resonance Chemical Shifts in Molecular Crystals.

PubMed

Hartman, Joshua D; Beran, Gregory J O

2014-11-11

First-principles chemical shielding tensor predictions play a critical role in studying molecular crystal structures using nuclear magnetic resonance. Fragment-based electronic structure methods have dramatically improved the ability to model molecular crystal structures and energetics using high-level electronic structure methods. Here, a many-body expansion fragment approach is applied to the calculation of chemical shielding tensors in molecular crystals. First, the impact of truncating the many-body expansion at different orders and the role of electrostatic embedding are examined on a series of molecular clusters extracted from molecular crystals. Second, the ability of these techniques to assign three polymorphic forms of the drug sulfanilamide to the corresponding experimental (13)C spectra is assessed. This challenging example requires discriminating among spectra whose (13)C chemical shifts differ by only a few parts per million (ppm) across the different polymorphs. Fragment-based PBE0/6-311+G(2d,p) level chemical shielding predictions correctly assign these three polymorphs and reproduce the sulfanilamide experimental (13)C chemical shifts with 1 ppm accuracy. The results demonstrate that fragment approaches are competitive with the widely used gauge-invariant projector augmented wave (GIPAW) periodic density functional theory calculations.

Determination of conformation and orientation of immobilized peptides and proteins at buried interfaces

NASA Astrophysics Data System (ADS)

Shen, Lei; Ulrich, Nathan W.; Mello, Charlene M.; Chen, Zhan

2015-01-01

Surface immobilized peptides/proteins have important applications such as antimicrobial coating and biosensing. We report a study of such peptides/proteins using sum frequency generation vibrational spectroscopy and ATR-FTIR. Immobilization on surfaces via physical adsorption and chemical coupling revealed that structures of chemically immobilized peptides are determined by immobilization sites, chemical environments, and substrate surfaces. In addition, controlling enzyme orientation by engineering the surface immobilization site demonstrated that structures can be well-correlated to measured chemical activity. This research facilitates the development of immobilized peptides/proteins with improved activities by optimizing their surface orientation and structure.

Neural network based chemical structure indexing.

PubMed

Rughooputh, S D; Rughooputh, H C

2001-01-01

Searches on chemical databases are presently dominated by the text-based content of a paper which can be indexed into a keyword searchable form. Such traditional searches can prove to be very time-consuming and discouraging to the less frequent scientist. We report a simple chemical indexing based on the molecular structure alone. The method used is based on a one-to-one correspondence between the chemical structure presented as an image to a neural network and the corresponding binary output. The method is direct and less cumbersome (compared with traditional methods) and proves to be robust, elegant, and very versatile.

Low-thrust chemical orbit transfer propulsion

NASA Technical Reports Server (NTRS)

Pelouch, J. J., Jr.

1979-01-01

The need for large structures in high orbit is reported in terms of the many mission opportunities which require such structures. Mission and transportation options for large structures are presented, and it is shown that low-thrust propulsion is an enabling requirement for some missions and greatly enhancing to many others. Electric and low-thrust chemical propulsion are compared, and the need for an requirements of low-thrust chemical propulsion are discussed in terms of the interactions that are perceived to exist between the propulsion system and the large structure.

Combustion flame-plasma hybrid reactor systems, and chemical reactant sources

DOEpatents

Kong, Peter C

2013-11-26

Combustion flame-plasma hybrid reactor systems, chemical reactant sources, and related methods are disclosed. In one embodiment, a combustion flame-plasma hybrid reactor system comprising a reaction chamber, a combustion torch positioned to direct a flame into the reaction chamber, and one or more reactant feed assemblies configured to electrically energize at least one electrically conductive solid reactant structure to form a plasma and feed each electrically conductive solid reactant structure into the plasma to form at least one product is disclosed. In an additional embodiment, a chemical reactant source for a combustion flame-plasma hybrid reactor comprising an elongated electrically conductive reactant structure consisting essentially of at least one chemical reactant is disclosed. In further embodiments, methods of forming a chemical reactant source and methods of chemically converting at least one reactant into at least one product are disclosed.

20180318 - Sharing chemical structures with peer-reviewed publications. Are we there yet? (ACS Spring)

EPA Science Inventory

In the domain of chemistry one of the greatest benefits to publishing research is that data are shared. Unfortunately, the vast majority of chemical structure data remain locked up in document form, primarily as PDF files. Despite the explosive growth of online chemical databases...

Discovering More Chemical Concepts from 3D Chemical Information Searches of Crystal Structure Databases

ERIC Educational Resources Information Center

Rzepa, Henry S.

2016-01-01

Three new examples are presented illustrating three-dimensional chemical information searches of the Cambridge structure database (CSD) from which basic core concepts in organic and inorganic chemistry emerge. These include connecting the regiochemistry of aromatic electrophilic substitution with the geometrical properties of hydrogen bonding…

40 CFR 355.61 - How are key words in this part defined?

Code of Federal Regulations, 2011 CFR

2011-07-01

... includes manmade structures, as well as all natural structures in which chemicals are purposefully placed... agricultural products during a year. Hazardous chemical means any hazardous chemical as defined under 29 CFR... of a technically qualified individual; or (iii) In routine agricultural operations or is a fertilizer...

40 CFR 355.61 - How are key words in this part defined?

Code of Federal Regulations, 2014 CFR

2014-07-01

... includes manmade structures, as well as all natural structures in which chemicals are purposefully placed... agricultural products during a year. Hazardous chemical means any hazardous chemical as defined under 29 CFR... of a technically qualified individual; or (iii) In routine agricultural operations or is a fertilizer...

Chemical modification of nanocellulose with canola oil fatty acid methyl ester

Treesearch

Liqing Wei; Umesh P. Agarwal; Kolby C. Hirth; Laurent M. Matuana; Ronald C. Sabo; Nicole M. Stark

2017-01-01

Cellulose nanocrystals (CNCs), produced from dissolving wood pulp, were chemically functionalized by transesterification with canola oil fatty acid methyl ester (CME). CME performs as both the reaction reagent and solvent. Transesterified CNC (CNCFE) was characterized for their chemical structure, morphology, crystalline structure, thermal stability, and hydrophobicity...

DSSTox chemical-index files for exposure-related experiments in ArrayExpress and Gene Expression Omnibus: enabling toxico-chemogenomics data linkages

EPA Science Inventory

The Distributed Structure-Searchable Toxicity (DSSTox) ARYEXP and GEOGSE files are newly published, structure-annotated files of the chemical-associated and chemical exposure-related summary experimental content contained in the ArrayExpress Repository and Gene Expression Omnibus...

An automated curation procedure for addressing chemical errors and inconsistencies in public datasets used in QSAR modeling

EPA Science Inventory

Increasing availability of large collections of chemical structures and associated experimental data provides an opportunity to build robust QSAR models for applications in different fields. One common concern is the quality of both the chemical structure information and associat...

Kekule.js: An Open Source JavaScript Chemoinformatics Toolkit.

PubMed

Jiang, Chen; Jin, Xi; Dong, Ying; Chen, Ming

2016-06-27

Kekule.js is an open-source, object-oriented JavaScript toolkit for chemoinformatics. It provides methods for many common tasks in molecular informatics, including chemical data input/output (I/O), two- and three-dimensional (2D/3D) rendering of chemical structure, stereo identification, ring perception, structure comparison, and substructure search. Encapsulated widgets to display and edit chemical structures directly in web context are also supplied. Developed with web standards, the toolkit is ideal for building chemoinformatics applications over the Internet. Moreover, it is highly platform-independent and can also be used in desktop or mobile environments. Some initial applications, such as plugins for inputting chemical structures on the web and uses in chemistry education, have been developed based on the toolkit.

Fabrication, characterization and applications of iron selenide

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

Hussain, Raja Azadar, E-mail: hussainazadar@yahoo.com; Badshah, Amin; Lal, Bhajan

This review article presents fabrication of FeSe by solid state reactions, solution chemistry routes, chemical vapor deposition, spray pyrolysis and chemical vapor transport. Different properties and applications such as crystal structure and phase transition, band structure, spectroscopy, superconductivity, photocatalytic activity, electrochemical sensing, and fuel cell activity of FeSe have been discussed. - Graphical abstract: Iron selenide can be synthesized by solid state reactions, chemical vapor deposition, solution chemistry routes, chemical vapor transport and spray pyrolysis. - Highlights: • Different fabrication methods of iron selenide (FeSe) have been reviewed. • Crystal structure, band structure and spectroscopy of FeSe have been discussed.more » • Superconducting, catalytic and fuel cell application of FeSe have been presented.« less

A computational method for the identification of new candidate carcinogenic and non-carcinogenic chemicals.

PubMed

Chen, Lei; Chu, Chen; Lu, Jing; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong

2015-09-01

Cancer is one of the leading causes of human death. Based on current knowledge, one of the causes of cancer is exposure to toxic chemical compounds, including radioactive compounds, dioxin, and arsenic. The identification of new carcinogenic chemicals may warn us of potential danger and help to identify new ways to prevent cancer. In this study, a computational method was proposed to identify potential carcinogenic chemicals, as well as non-carcinogenic chemicals. According to the current validated carcinogenic and non-carcinogenic chemicals from the CPDB (Carcinogenic Potency Database), the candidate chemicals were searched in a weighted chemical network constructed according to chemical-chemical interactions. Then, the obtained candidate chemicals were further selected by a randomization test and information on chemical interactions and structures. The analyses identified several candidate carcinogenic chemicals, while those candidates identified as non-carcinogenic were supported by a literature search. In addition, several candidate carcinogenic/non-carcinogenic chemicals exhibit structural dissimilarity with validated carcinogenic/non-carcinogenic chemicals.

Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria

PubMed Central

Hong, Mei

2016-01-01

We have determined refined multidimensional chemical shift ranges for intra-residue correlations (13C–13C, 15N–13C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 13C chemical shifts and >3 million chemical shifts in total); these data were originally derived from the Biological Magnetic Resonance Data Bank. Using relatively simple non-parametric statistics to find peak maxima in the distributions of helix, sheet, coil and turn chemical shifts, and without the use of limited “hand-picked” data sets, we show that ~94 % of the 13C NMR data and almost all 15N data are quite accurately referenced and assigned, with smaller standard deviations (0.2 and 0.8 ppm, respectively) than recognized previously. On the other hand, approximately 6 % of the 13C chemical shift data in the PACSY database are shown to be clearly misreferenced, mostly by ca. −2.4 ppm. The removal of the misreferenced data and other outliers by this purging by intrinsic quality criteria (PIQC) allows for reliable identification of secondary maxima in the two-dimensional chemical-shift distributions already pre-separated by secondary structure. We demonstrate that some of these correspond to specific regions in the Ramachandran plot, including left-handed helix dihedral angles, reflect unusual hydrogen bonding, or are due to the influence of a following proline residue. With appropriate smoothing, significantly more tightly defined chemical shift ranges are obtained for each amino acid type in the different secondary structures. These chemical shift ranges, which may be defined at any statistical threshold, can be used for amino-acid type assignment and secondary-structure analysis of chemical shifts from intra-residue cross peaks by inspection or by using a provided command-line Python script (PLUQin), which should be useful in protein structure determination. The refined chemical shift distributions are utilized in a simple quality test (SQAT) that should be applied to new protein NMR data before deposition in a databank, and they could benefit many other chemical-shift based tools. PMID:26787537

On a Molecular Basis, Investigate Association of Molecular Structure with Bioactive Compounds, Anti-Nutritional Factors and Chemical and Nutrient Profiles of Canola Seeds and Co-Products from Canola Processing: Comparison Crusher Plants within Canada and within China as well as between Canada and China.

PubMed

Gomaa, Walaa M S; Mosaad, Gamal M; Yu, Peiqiang

2018-04-21

The objectives of this study were to: (1) Use molecular spectroscopy as a novel technique to quantify protein molecular structures in relation to its chemical profiles and bioenergy values in oil-seeds and co-products from bio-oil processing. (2) Determine and compare: (a) protein molecular structure using Fourier transform infrared (FT/IR-ATR) molecular spectroscopy technique; (b) bioactive compounds, anti-nutritional factors, and chemical composition; and (c) bioenergy values in oil seeds (canola seeds), co-products (meal or pellets) from bio-oil processing plants in Canada in comparison with China. (3) Determine the relationship between protein molecular structural features and nutrient profiles in oil-seeds and co-products from bio-oil processing. Our results showed the possibility to characterize protein molecular structure using FT/IR molecular spectroscopy. Processing induced changes between oil seeds and co-products were found in the chemical, bioenergy profiles and protein molecular structure. However, no strong correlation was found between the chemical and nutrient profiles of oil seeds (canola seeds) and their protein molecular structure. On the other hand, co-products were strongly correlated with protein molecular structure in the chemical profile and bioenergy values. Generally, comparisons of oil seeds (canola seeds) and co-products (meal or pellets) in Canada, in China, and between Canada and China indicated the presence of variations among different crusher plants and bio-oil processing products.

Redox-dependent structure change and hyperfine nuclear magnetic resonance shifts in cytochrome c

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

Feng, Yiquing; Roder, H.; Englander, S.W.

1990-04-10

Proton nuclear magnetic resonance assignments for reduced and oxidized equine cytochrome c show that many individual protons exhibit different chemical shifts in the two protein forms, reflecting diamagnetic shift effects due to structure change, and in addition contact and pseudocontact shifts that occur only in the paramagnetic oxidized form. To evaluate the chemical shift differences for structure change, the authors removed the pseudocontact shift contribution by a calculation based on knowledge of the electron spin g tensor. The g-tensor calculation, when repeated using only 12 available C{sub {alpha}}H proton resonances for cytochrom c from tuna, proved to be remarkably stable.more » The derived g tensor was then used together with spatial coordinates for the oxidized form to calculate the pseudocontact shift contribution to proton resonances at 400 identifiable sites throughout the protein, so that the redox-dependent chemical shift discrepancy, could be evaluated. Large residual changes in chemical shift define the Fermi contact shifts, where are found as expected to be limited to the immediate covalent structure of the heme and its ligands and to be asymmetrically distributed over the heme. The chemical shift discrepancies observed appear in the main to reflect structure-dependent diamagnetic shifts rather than hyperfine effects due to displacements in the pseudocontact shift field. Although 51 protons in 29 different residues exhibit significant chemical shift changes, the general impressions one of small structural adjustments to redox-dependent strain rather than sizeable structural displacements or rearrangements.« less

DISTRIBUTED STRUCTURE-SEARCHABLE TOXICITY ...

EPA Pesticide Factsheets

The ability to assess the potential genotoxicity, carcinogenicity, or other toxicity of pharmaceutical or industrial chemicals based on chemical structure information is a highly coveted and shared goal of varied academic, commercial, and government regulatory groups. These diverse interests often employ different approaches and have different criteria and use for toxicity assessments, but they share a need for unrestricted access to existing public toxicity data linked with chemical structure information. Currently, there exists no central repository of toxicity information, commercial or public, that adequately meets the data requirements for flexible analogue searching, SAR model development, or building of chemical relational databases (CRD). The Distributed Structure-Searchable Toxicity (DSSTox) Public Database Network is being proposed as a community-supported, web-based effort to address these shared needs of the SAR and toxicology communities. The DSSTox project has the following major elements: 1) to adopt and encourage the use of a common standard file format (SDF) for public toxicity databases that includes chemical structure, text and property information, and that can easily be imported into available CRD applications; 2) to implement a distributed source approach, managed by a DSSTox Central Website, that will enable decentralized, free public access to structure-toxicity data files, and that will effectively link knowledgeable toxicity data s

Atomic scale chemical tomography of human bone

NASA Astrophysics Data System (ADS)

Langelier, Brian; Wang, Xiaoyue; Grandfield, Kathryn

2017-01-01

Human bone is a complex hierarchical material. Understanding bone structure and its corresponding composition at the nanometer scale is critical for elucidating mechanisms of biomineralization under healthy and pathological states. However, the three-dimensional structure and chemical nature of bone remains largely unexplored at the nanometer scale due to the challenges associated with characterizing both the structural and chemical integrity of bone simultaneously. Here, we use correlative transmission electron microscopy and atom probe tomography for the first time, to our knowledge, to reveal structures in human bone at the atomic level. This approach provides an overlaying chemical map of the organic and inorganic constituents of bone on its structure. This first use of atom probe tomography on human bone reveals local gradients, trace element detection of Mg, and the co-localization of Na with the inorganic-organic interface of bone mineral and collagen fibrils, suggesting the important role of Na-rich organics in the structural connection between mineral and collagen. Our findings provide the first insights into the hierarchical organization and chemical heterogeneity in human bone in three-dimensions at its smallest length scale - the atomic level. We demonstrate that atom probe tomography shows potential for new insights in biomineralization research on bone.

Reducing Electroosmotic Flow Enables DNA Separations in Ultrathin Channels.

DTIC Science & Technology

1998-08-01

Chemical structure of DNA bases 2 Figure 1-2: Schematic diagram of DNA base pairing 5 Figure 1-3: Schematic diagram of the capillary and the...hydrogen atoms near one of the Figure 1-1: A. Chemical structure of the DNA backbone. B. Chemical structure of DNA bases . The DNA backbone consists...of pentose sugar (deoxyribose) held together by phosphodiester bonds. The DNA bases that are derivatives of purine are adenine (A) and guanine (G

An open workflow to generate “MS Ready” structures and improve non-targeted mass spectrometry (ACS Fall 1 of 3)

EPA Science Inventory

High-throughput non-targeted analyses (NTA) rely on chemical reference databases for tentative identification of observed chemical features. Many of these databases and online resources incorporate chemical structure data not in a form that is readily observed by mass spectromet...

Chemical structure of wood charcoal by infrared spectroscopy and multivariate analysis

Treesearch

Nicole Labbe; David Harper; Timothy Rials; Thomas Elder

2006-01-01

In this work, the effect of temperature on charcoal structure and chemical composition is investigated for four tree species. Wood charcoal carbonized at various temperatures is analyzed by mid infrared spectroscopy coupled with multivariate analysis and by thermogravimetric analysis to characterize the chemical composition during the carbonization process. The...

An in silico algal toxicity model with a wide applicability potential for industrial chemicals and pharmaceuticals.

PubMed

Önlü, Serli; Saçan, Melek Türker

2017-04-01

The authors modeled the 72-h algal toxicity data of hundreds of chemicals with different modes of action as a function of chemical structures. They developed mode of action-based local quantitative structure-toxicity relationship (QSTR) models for nonpolar and polar narcotics as well as a global QSTR model with a wide applicability potential for industrial chemicals and pharmaceuticals. The present study rigorously evaluated the generated models, meeting the Organisation for Economic Co-operation and Development principles of robustness, validity, and transparency. The proposed global model had a broad structural coverage for the toxicity prediction of diverse chemicals (some of which are high-production volume chemicals) with no experimental toxicity data. The global model is potentially useful for endpoint predictions, the evaluation of algal toxicity screening, and the prioritization of chemicals, as well as for the decision of further testing and the development of risk-management measures in a scientific and regulatory frame. Environ Toxicol Chem 2017;36:1012-1019. © 2016 SETAC. © 2016 SETAC.

Chemical grafting of the superhydrophobic surface on copper with hierarchical microstructure and its formation mechanism

NASA Astrophysics Data System (ADS)

Cai, Junyan; Wang, Shuhui; Zhang, Junhong; Liu, Yang; Hang, Tao; Ling, Huiqin; Li, Ming

2018-04-01

In this paper, a superhydrophobic surface with hierarchical structure was fabricated by chemical deposition of Cu micro-cones array, followed by chemical grafting of poly(methyl methacrylate) (PMMA). Water contact measurements give contact angle of 131.0° on these surfaces after PMMA grafting of 2 min and 165.2° after 6 min. The superhydrophobicity results from two factors: (1) the hierarchical structure due to Cu micro-cones array and the second level structure caused by intergranular corrosion during grafting of PMMA (confirmed by the scanning electron microscopy) and (2) the chemical modification of a low surface energy PMMA layer (confirmed by Fourier transform infrared spectrometer and X-ray photoelectron spectroscopy). In the chemical grafting process, the spontaneous reduction of nitrobenzene diazonium (NBD) tetrafluoroborate not only causes the corrosion of the Cu surface that leads to a hierarchical structure, but also initiates the polymerization of methyl methacrylate (MMA) monomers and thus the low free energy surface. Such a robust approach to fabricate the hierarchical structured surface with superhydrophobicity is expected to have practical application in anti-corrosion industry.

Chemicals used in the rubber industry. An overview.

PubMed

Fishbein, L

1983-01-01

Hundreds of chemicals illustrative of many structural and use categories are employed in the rubber industry. The present overview has centered on the structural features of a number of compounds representative of several select use categories, eg, vulcanizing agents, accelerators, antioxidants, antiozonants, and blowing agents, with focus on the nature of their impurities, their chemical degradation, and by-products, as well as on those chemicals that can be converted to N-nitrosamines.

Protein Structural Information Derived from NMR Chemical Shift with the Neural Network Program TALOS-N

PubMed Central

Shen, Yang; Bax, Ad

2015-01-01

Summary Chemical shifts are obtained at the first stage of any protein structural study by NMR spectroscopy. Chemical shifts are known to be impacted by a wide range of structural factors and the artificial neural network based TALOS-N program has been trained to extract backbone and sidechain torsion angles from 1H, 15N and 13C shifts. The program is quite robust, and typically yields backbone torsion angles for more than 90% of the residues, and sidechain χ1 rotamer information for about half of these, in addition to reliably predicting secondary structure. The use of TALOS-N is illustrated for the protein DinI, and torsion angles obtained by TALOS-N analysis from the measured chemical shifts of its backbone and 13Cβ nuclei are compared to those seen in a prior, experimentally determined structure. The program is also particularly useful for generating torsion angle restraints, which then can be used during standard NMR protein structure calculations. PMID:25502373

High-Yield Synthesis of Stoichiometric Boron Nitride Nanostructures

DOE PAGES

Nocua, José E.; Piazza, Fabrice; Weiner, Brad R.; ...

2009-01-01

Boron nimore » tride (BN) nanostructures are structural analogues of carbon nanostructures but have completely different bonding character and structural defects. They are chemically inert, electrically insulating, and potentially important in mechanical applications that include the strengthening of light structural materials. These applications require the reliable production of bulk amounts of pure BN nanostructures in order to be able to reinforce large quantities of structural materials, hence the need for the development of high-yield synthesis methods of pure BN nanostructures. Using borazine ( B 3 N 3 H 6 ) as chemical precursor and the hot-filament chemical vapor deposition (HFCVD) technique, pure BN nanostructures with cross-sectional sizes ranging between 20 and 50 nm were obtained, including nanoparticles and nanofibers. Their crystalline structure was characterized by (XRD), their morphology and nanostructure was examined by (SEM) and (TEM), while their chemical composition was studied by (EDS), (FTIR), (EELS), and (XPS). Taken altogether, the results indicate that all the material obtained is stoichiometric nanostructured BN with hexagonal and rhombohedral crystalline structure.« less

Electronic, structural and chemical properties of GaAs/ZnSe heterovalent interfaces as dependent on MBE growth conditions and ex situ annealing

NASA Astrophysics Data System (ADS)

Komissarova, T. A.; Lebedev, M. V.; Sorokin, S. V.; Klimko, G. V.; Sedova, I. V.; Gronin, S. V.; Komissarov, K. A.; Calvet, W.; Drozdov, M. N.; Ivanov, S. V.

2017-04-01

A study of electronic, structural and chemical properties of GaAs/ZnSe heterovalent interfaces (HI) in dependence on molecular beam epitaxy (MBE) growth conditions and post-growth annealing was performed. Initial GaAs surface reconstructions ((2 × 4)As or c(4 × 4)As) and ZnSe growth mode (MBE or migration-enhanced epitaxy (MEE)) were varied for different undoped and n-doped heterovalent structures. Although all the structures have low extended defect density (less than 106 cm-2) and rather small (less than 5 nm) atomic interdiffusion at the HI, the structural, chemical and electronic properties of the near-interface area (short-distance interdiffusion effects, dominant chemical bonds, and valence band offset values) as well as electrical properties of the n-GaAs/n-ZnSe heterovalent structures were found to be influenced strongly by the MBE growth conditions and post-growth annealing.

Aziridinyl-substituted benzo-1,4-quinones: A preliminary investigation on the theoretical and experimental studies of their structure and spectroscopic properties

NASA Astrophysics Data System (ADS)

Šarlauskas, Jonas; Tamulienė, Jelena; Čėnas, Narimantas

2017-05-01

The detailed structure, chemical and spectroscopic properties of the derivatives of the selected 2,5-bis(1-aziridinyl)-benzo-1,4-quinone conformers were studied by applying quantum chemical and experimental methods. The relationship between the structure and chemical activity of the selected 3 bifunctional bioreductive quinonic anticancer agents - aziridinyl benzoquinones (AzBQ compounds) was obtained. The results obtained showed that the position of aziridine rings influenced by the chemical activity of the investigated compound were more significant than the substitutions of the benzene ring of the AzBQ compounds. The solvents influencing this activity were obtained, too.

Local atomic and electronic structure of oxide/GaAs and SiO2/Si interfaces using high-resolution XPS

NASA Technical Reports Server (NTRS)

Grunthaner, F. J.; Grunthaner, P. J.; Vasquez, R. P.; Lewis, B. F.; Maserjian, J.; Madhukar, A.

1979-01-01

The chemical structures of thin SiO2 films, thin native oxides of GaAs (20-30 A), and the respective oxide-semiconductor interfaces, have been investigated using high-resolution X-ray photoelectron spectroscopy. Depth profiles of these structures have been obtained using argon ion bombardment and wet chemical etching techniques. The chemical destruction induced by the ion profiling method is shown by direct comparison of these methods for identical samples. Fourier transform data-reduction methods based on linear prediction with maximum entropy constraints are used to analyze the discrete structure in oxides and substrates. This discrete structure is interpreted by means of a structure-induced charge-transfer model.

Proposal of an in silico profiler for categorisation of repeat dose toxicity data of hair dyes.

PubMed

Nelms, M D; Ates, G; Madden, J C; Vinken, M; Cronin, M T D; Rogiers, V; Enoch, S J

2015-05-01

This study outlines the analysis of 94 chemicals with repeat dose toxicity data taken from Scientific Committee on Consumer Safety opinions for commonly used hair dyes in the European Union. Structural similarity was applied to group these chemicals into categories. Subsequent mechanistic analysis suggested that toxicity to mitochondria is potentially a key driver of repeat dose toxicity for chemicals within each of the categories. The mechanistic hypothesis allowed for an in silico profiler consisting of four mechanism-based structural alerts to be proposed. These structural alerts related to a number of important chemical classes such as quinones, anthraquinones, substituted nitrobenzenes and aromatic azos. This in silico profiler is intended for grouping chemicals into mechanism-based categories within the adverse outcome pathway paradigm.

Reassigning the Structures of Natural Products Using NMR Chemical Shifts Computed with Quantum Mechanics: A Laboratory Exercise

ERIC Educational Resources Information Center

Palazzo, Teresa A.; Truong, Tiana T.; Wong, Shirley M. T.; Mack, Emma T.; Lodewyk, Michael W.; Harrison, Jason G.; Gamage, R. Alan; Siegel, Justin B.; Kurth, Mark J.; Tantillo, Dean J.

2015-01-01

An applied computational chemistry laboratory exercise is described in which students use modern quantum chemical calculations of chemical shifts to assign the structure of a recently isolated natural product. A pre/post assessment was used to measure student learning gains and verify that students demonstrated proficiency of key learning…

Quinones from plants of northeastern Brazil: structural diversity, chemical transformations, NMR data and biological activities.

PubMed

Lemos, Telma L G; Monte, Francisco J Q; Santos, Allana Kellen L; Fonseca, Aluisio M; Santos, Hélcio S; Oliveira, Mailcar F; Costa, Sonia M O; Pessoa, Otilia D L; Braz-Filho, Raimundo

2007-05-20

The present review focus in quinones found in species of Brazilian northeastern Capraria biflora, Lippia sidoides, Lippia microphylla and Tabebuia serratifolia. The review cover ethnopharmacological aspects including photography of species, chemical structure feature, NMR datea and biological properties. Chemical transformations of lapachol to form enamine derivatives and biological activities are discussed.

Importance of Kier-Hall topological indices in the QSAR of anticancer drug design.

PubMed

Nandi, Sisir; Bagchi, Manish C

2012-06-01

An important area of theoretical drug design research is quantitative structure activity relationship (QSAR) using structural invariants. The impetus for this research trend comes from various directions. Researchers in chemical documentation have searched for a set of invariants which will be more convenient than the adjacency matrix (or connection table) for the storage and comparison of chemical structures. Molecular structure can be looked upon as the representation of the relationship among its various constituents. The term molecular structure represents a set of nonequivalent and probably disjoint concepts. There is no reason to believe that when we discuss diverse topics (e.g. chemical synthesis, reaction rates, spectroscopic transitions, reaction mechanisms, and ab initio calculations) using the notion of molecular structure, the different meanings we attach to the single term molecular structure originate from the same fundamental concept. On the contrary, there is a theoretical and philosophical basis for the non-homogeneity of concepts covered by the term molecular structure. In the context of molecular science, the various concepts of molecular structure (e.g. classical valence bond representations, various chemical graph-theoretic representations, ball and spoke model of a molecule, representation of a molecule by minimum energy conformation, semi symbolic contour map of a molecule, or symbolic representation of chemical species by Hamiltonian operators) are model objects derived through different abstractions of the same chemical reality. In each instance, the equivalence class (concept or model of molecular structure) is generated by selecting certain aspects while ignoring some unique properties of those actual events. This explains the plurality of the concept of molecular structure and their autonomous nature, the word autonomous being used in the same sense that one concept is not logically derived from the other. At the most fundamental level, the structural model of an assembled entity (e.g. a molecule consisting of atoms) may be defined as the pattern of relationship among its parts as distinct from the values associated with them. Constitutional formulae of molecules are graphs where vertices represent the set of atoms and edges represent chemical bonds. The pattern of connectedness of atoms in a molecule is preserved by constitutional graphs. A graph (more correctly a non-directed graph) G = [V, E] consists of a finite non-empty set V of points together with a prescribed set E of unordered pairs of distinct points of V. Thus the mathematical characterization of structures represents structural invariants having successful applications in chemical documentation, characterization of molecular branching, enumeration of molecular constitutional associated with a particular empirical formula, calculation of quantum chemical parameters for the generation of quantitative structure-property-activity correlations. Kier developed a number of structural invariants which are now-a-days called as topological indices with wide range of practical applications for QSAR and drug design. The present paper is restricted to the review of Kier-Hall topological indices for QSAR and anticancer drug design for 2,5-bis(1-aziridinyl) 1,4-benzoquinone (BABQ), pyridopyrimidine, 4-anilinoquinazoline and 2-Phenylindoles compounds utilizing various statistical multivariate regression analyses.

Aggregating Data for Computational Toxicology Applications ...

EPA Pesticide Factsheets

Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built usi

Use of chemical-mechanical polishing for fabricating photonic bandgap structures

DOEpatents

Fleming, James G.; Lin, Shawn-Yu; Hetherington, Dale L.; Smith, Bradley K.

1999-01-01

A method is disclosed for fabricating a two- or three-dimensional photonic bandgap structure (also termed a photonic crystal, photonic lattice, or photonic dielectric structure). The method uses microelectronic integrated circuit (IC) processes to fabricate the photonic bandgap structure directly upon a silicon substrate. One or more layers of arrayed elements used to form the structure are deposited and patterned, with chemical-mechanical polishing being used to planarize each layer for uniformity and a precise vertical tolerancing of the layer. The use of chemical-mechanical planarization allows the photonic bandgap structure to be formed over a large area with a layer uniformity of about two-percent. Air-gap photonic bandgap structures can also be formed by removing a spacer material separating the arrayed elements by selective etching. The method is useful for fabricating photonic bandgap structures including Fabry-Perot resonators and optical filters for use at wavelengths in the range of about 0.2-20 .mu.m.

Influence of heating procedures on the surface structure of stabilized polyacrylonitrile fibers

NASA Astrophysics Data System (ADS)

Zhao, Rui-Xue; Sun, Peng-fei; Liu, Rui-jian; Ding, Zhan-hui; Li, Xiang-shan; Liu, Xiao-yang; Zhao, Xu-dong; Gao, Zhong-min

2018-03-01

The stabilized polyacrylonitrile (PAN) fibers were obtained after heating the precursor PAN fibers under air atmosphere by different procedures. The surface structures and compositions of as-prepared stabilized PAN fibers have been investigated by SEM, SSNMR, XPS and Raman spectroscopy. The results show that 200 °C, 220 °C, 250 °C, and 280 °C are key temperatures for the preparation of stabilized PAN fibers. The effect of heating gradient on the structure of stabilized PAN fibers has been studied. The possible chemical structural formulas for the PAN fibers is provided, which include the stable and unstable structure. The stable structure (α-type) could endure the strong chemical reactions and the unstable structure (β- or γ-type) could mitigate the drastic oxidation reactions. The inferences of chemical formula of stabilized PAN fibers are benefit to the design of appropriate surface structure for the production for high quality carbon fibers.

Ambiguity of non-systematic chemical identifiers within and between small-molecule databases.

PubMed

Akhondi, Saber A; Muresan, Sorel; Williams, Antony J; Kors, Jan A

2015-01-01

A wide range of chemical compound databases are currently available for pharmaceutical research. To retrieve compound information, including structures, researchers can query these chemical databases using non-systematic identifiers. These are source-dependent identifiers (e.g., brand names, generic names), which are usually assigned to the compound at the point of registration. The correctness of non-systematic identifiers (i.e., whether an identifier matches the associated structure) can only be assessed manually, which is cumbersome, but it is possible to automatically check their ambiguity (i.e., whether an identifier matches more than one structure). In this study we have quantified the ambiguity of non-systematic identifiers within and between eight widely used chemical databases. We also studied the effect of chemical structure standardization on reducing the ambiguity of non-systematic identifiers. The ambiguity of non-systematic identifiers within databases varied from 0.1 to 15.2 % (median 2.5 %). Standardization reduced the ambiguity only to a small extent for most databases. A wide range of ambiguity existed for non-systematic identifiers that are shared between databases (17.7-60.2 %, median of 40.3 %). Removing stereochemistry information provided the largest reduction in ambiguity across databases (median reduction 13.7 percentage points). Ambiguity of non-systematic identifiers within chemical databases is generally low, but ambiguity of non-systematic identifiers that are shared between databases, is high. Chemical structure standardization reduces the ambiguity to a limited extent. Our findings can help to improve database integration, curation, and maintenance.

Database resources of the National Center for Biotechnology Information

PubMed Central

Sayers, Eric W.; Barrett, Tanya; Benson, Dennis A.; Bolton, Evan; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M.; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Krasnov, Sergey; Landsman, David; Lipman, David J.; Lu, Zhiyong; Madden, Thomas L.; Madej, Tom; Maglott, Donna R.; Marchler-Bauer, Aron; Miller, Vadim; Karsch-Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D.; Schuler, Gregory D.; Sequeira, Edwin; Sherry, Stephen T.; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A.; Wagner, Lukas; Wang, Yanli; Wilbur, W. John; Yaschenko, Eugene; Ye, Jian

2012-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Website. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Probe, Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:22140104

In silico search of energy metabolism inhibitors for alternative leishmaniasis treatments.

PubMed

Silva, Lourival A; Vinaud, Marina C; Castro, Ana Maria; Cravo, Pedro Vítor L; Bezerra, José Clecildo B

2015-01-01

Leishmaniasis is a complex disease that affects mammals and is caused by approximately 20 distinct protozoa from the genus Leishmania. Leishmaniasis is an endemic disease that exerts a large socioeconomic impact on poor and developing countries. The current treatment for leishmaniasis is complex, expensive, and poorly efficacious. Thus, there is an urgent need to develop more selective, less expensive new drugs. The energy metabolism pathways of Leishmania include several interesting targets for specific inhibitors. In the present study, we sought to establish which energy metabolism enzymes in Leishmania could be targets for inhibitors that have already been approved for the treatment of other diseases. We were able to identify 94 genes and 93 Leishmania energy metabolism targets. Using each gene's designation as a search criterion in the TriTrypDB database, we located the predicted peptide sequences, which in turn were used to interrogate the DrugBank, Therapeutic Target Database (TTD), and PubChem databases. We identified 44 putative targets of which 11 are predicted to be amenable to inhibition by drugs which have already been approved for use in humans for 11 of these targets. We propose that these drugs should be experimentally tested and potentially used in the treatment of leishmaniasis.

Discovery of DNA dyes Hoechst 34580 and 33342 as good candidates for inhibiting amyloid beta formation: in silico and in vitro study

NASA Astrophysics Data System (ADS)

Thai, Nguyen Quoc; Tseng, Ning-Hsuan; Vu, Mui Thi; Nguyen, Tin Trung; Linh, Huynh Quang; Hu, Chin-Kun; Chen, Yun-Ru; Li, Mai Suan

2016-08-01

Combining Lipinski's rule with the docking and steered molecular dynamics simulations and using the PubChem data base of about 1.4 million compounds, we have obtained DNA dyes Hoechst 34580 and Hoechst 33342 as top-leads for the Alzheimer's disease. The binding properties of these ligands to amyloid beta (Aβ) fibril were thoroughly studied by in silico and in vitro experiments. Hoechst 34580 and Hoechst 33342 prefer to locate near hydrophobic regions with binding affinity mainly governed by the van der Waals interaction. By the Thioflavin T assay, it was found that the inhibition constant IC50 ≈ 0.86 and 0.68 μM for Hoechst 34580 and Hoechst 33342, respectively. This result qualitatively agrees with the binding free energy estimated using the molecular mechanic-Poisson Boltzmann surface area method and all-atom simulations with the AMBER-f99SB-ILDN force field and water model TIP3P. In addition, DNA dyes have the high capability to cross the blood brain barrier. Thus, both in silico and in vitro experiments have shown that Hoechst 34580 and 33342 are good candidates for treating the Alzheimer's disease by inhibiting Aβ formation.

Database resources of the National Center for Biotechnology Information

PubMed Central

2013-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, the Genetic Testing Registry, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Probe, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page. PMID:23193264

Database resources of the National Center for Biotechnology Information.

PubMed

Wheeler, David L; Barrett, Tanya; Benson, Dennis A; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Geer, Lewis Y; Kapustin, Yuri; Khovayko, Oleg; Landsman, David; Lipman, David J; Madden, Thomas L; Maglott, Donna R; Ostell, James; Miller, Vadim; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Steven T; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusov, Roman L; Tatusova, Tatiana A; Wagner, Lukas; Yaschenko, Eugene

2007-01-01

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, the Entrez Programming Utilities, My NCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link(BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genome, Genome Project and related tools, the Trace and Assembly Archives, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Viral Genotyping Tools, Influenza Viral Resources, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. These resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Feolo, Michael; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Landsman, David; Lipman, David J; Madden, Thomas L; Maglott, Donna R; Miller, Vadim; Mizrachi, Ilene; Ostell, James; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Yaschenko, Eugene; Ye, Jian

2009-01-01

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the web applications is custom implementation of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Database resources of the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Barrett, Tanya; Benson, Dennis A.; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Feolo, Michael; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Khovayko, Oleg; Landsman, David; Lipman, David J.; Madden, Thomas L.; Maglott, Donna R.; Miller, Vadim; Ostell, James; Pruitt, Kim D.; Schuler, Gregory D.; Shumway, Martin; Sequeira, Edwin; Sherry, Steven T.; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusov, Roman L.; Tatusova, Tatiana A.; Wagner, Lukas; Yaschenko, Eugene

2008-01-01

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data available through NCBI's web site. NCBI resources include Entrez, the Entrez Programming Utilities, My NCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link, Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genome, Genome Project and related tools, the Trace, Assembly, and Short Read Archives, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups, Influenza Viral Resources, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Entrez Probe, GENSAT, Database of Genotype and Phenotype, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool and the PubChem suite of small molecule databases. Augmenting the web applications are custom implementations of the BLAST program optimized to search specialized data sets. These resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:18045790

Hit Dexter: A Machine-Learning Model for the Prediction of Frequent Hitters.

PubMed

Stork, Conrad; Wagner, Johannes; Friedrich, Nils-Ole; de Bruyn Kops, Christina; Šícho, Martin; Kirchmair, Johannes

2018-03-20

False-positive assay readouts caused by badly behaving compounds-frequent hitters, pan-assay interference compounds (PAINS), aggregators, and others-continue to pose a major challenge to experimental screening. There are only a few in silico methods that allow the prediction of such problematic compounds. We report the development of Hit Dexter, two extremely randomized trees classifiers for the prediction of compounds likely to trigger positive assay readouts either by true promiscuity or by assay interference. The models were trained on a well-prepared dataset extracted from the PubChem Bioassay database, consisting of approximately 311 000 compounds tested for activity on at least 50 proteins. Hit Dexter reached MCC and AUC values of up to 0.67 and 0.96 on an independent test set, respectively. The models are expected to be of high value, in particular to medicinal chemists and biochemists who can use Hit Dexter to identify compounds for which extra caution should be exercised with positive assay readouts. Hit Dexter is available as a free web service at http://hitdexter.zbh. uni-hamburg.de. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quercetin derivatives as non-nucleoside inhibitors for dengue polymerase: molecular docking, molecular dynamics simulation, and binding free energy calculation.

PubMed

Anusuya, Shanmugam; Gromiha, M Michael

2017-10-01

Dengue is an important public health problem in tropical and subtropical regions of the world. Neither vaccine nor an antiviral medication is available to treat dengue. This insists the need of drug discovery for dengue. In order to find a potent lead molecule, RNA-dependent RNA polymerase which is essential for dengue viral replication is chosen as a drug target. As Quercetin showed antiviral activity against several viruses, quercetin derivatives developed by combinatorial library synthesis and mined from PubChem databases were screened for a potent anti-dengue viral agent. Our study predicted Quercetin 3-(6″-(E)-p-coumaroylsophoroside)-7-rhamnoside as a dengue polymerase inhibitor. The results were validated by molecular dynamics simulation studies which reveal water bridges and hydrogen bonds as major contributors for the stability of the polymerase-lead complex. Interactions formed by this compound with residues Trp795, Arg792 and Glu351 are found to be essential for the stability of the polymerase-lead complex. Our study demonstrates Quercetin 3-(6″-(E)-p-coumaroylsophoroside)-7-rhamnoside as a potent non-nucleoside inhibitor for dengue polymerase.

The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology

PubMed Central

Kadurin, Artur; Aliper, Alexander; Kazennov, Andrey; Mamoshina, Polina; Vanhaelen, Quentin; Khrabrov, Kuzma; Zhavoronkov, Alex

2017-01-01

Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and videos upon request even using natural language as input. In this paper we present the first application of generative adversarial autoencoders (AAE) for generating novel molecular fingerprints with a defined set of parameters. We developed a 7-layer AAE architecture with the latent middle layer serving as a discriminator. As an input and output the AAE uses a vector of binary fingerprints and concentration of the molecule. In the latent layer we also introduced a neuron responsible for growth inhibition percentage, which when negative indicates the reduction in the number of tumor cells after the treatment. To train the AAE we used the NCI-60 cell line assay data for 6252 compounds profiled on MCF-7 cell line. The output of the AAE was used to screen 72 million compounds in PubChem and select candidate molecules with potential anti-cancer properties. This approach is a proof of concept of an artificially-intelligent drug discovery engine, where AAEs are used to generate new molecular fingerprints with the desired molecular properties. PMID:28029644

QSAR modeling of cumulative environmental end-points for the prioritization of hazardous chemicals.

PubMed

Gramatica, Paola; Papa, Ester; Sangion, Alessandro

2018-01-24

The hazard of chemicals in the environment is inherently related to the molecular structure and derives simultaneously from various chemical properties/activities/reactivities. Models based on Quantitative Structure Activity Relationships (QSARs) are useful to screen, rank and prioritize chemicals that may have an adverse impact on humans and the environment. This paper reviews a selection of QSAR models (based on theoretical molecular descriptors) developed for cumulative multivariate endpoints, which were derived by mathematical combination of multiple effects and properties. The cumulative end-points provide an integrated holistic point of view to address environmentally relevant properties of chemicals.

Confluence of structural and chemical biology: plant polyketide synthases as biocatalysts for a bio-based future.

PubMed

Stewart, Charles; Vickery, Christopher R; Burkart, Michael D; Noel, Joseph P

2013-06-01

Type III plant polyketide synthases (PKSs) biosynthesize a dazzling array of polyphenolic products that serve important roles in both plant and human health. Recent advances in structural characterization of these enzymes and new tools from the field of chemical biology have facilitated exquisite probing of plant PKS iterative catalysis. These tools have also been used to exploit type III PKSs as biocatalysts to generate new chemicals. Going forward, chemical, structural and biochemical analyses will provide an atomic resolution understanding of plant PKSs and will serve as a springboard for bioengineering and scalable production of valuable molecules in vitro, by fermentation and in planta. Copyright © 2013 Elsevier Ltd. All rights reserved.

Structure elucidation of organic compounds aided by the computer program system SCANNET

NASA Astrophysics Data System (ADS)

Guzowska-Swider, B.; Hippe, Z. S.

1992-12-01

Recognition of chemical structure is a very important problem currently solved by molecular spectroscopy, particularly IR, UV, NMR and Raman spectroscopy, and mass spectrometry. Nowadays, solution of the problem is frequently aided by the computer. SCANNET is a computer program system for structure elucidation of organic compounds, developed by our group. The structure recognition of an unknown substance is made by comparing its spectrum with successive reference spectra of standard compounds, i.e. chemical compounds of known chemical structure, stored in a spectral database. The computer program system SCANNET consists of six different spectral databases for following the analytical methods: IR, UV, 13C-NMR, 1H-NMR and Raman spectroscopy, and mass spectrometry. A chemist, to elucidate a structure, can use one of these spectral methods or a combination of them and search the appropriate databases. As the result of searching each spectral database, the user obtains a list of chemical substances whose spectra are identical and/or similar to the spectrum input into the computer. The final information obtained from searching the spectral databases is in the form of a list of chemical substances having all the examined spectra, for each type of spectroscopy, identical or simlar to those of the unknown compound.

ClassyFire: automated chemical classification with a comprehensive, computable taxonomy.

PubMed

Djoumbou Feunang, Yannick; Eisner, Roman; Knox, Craig; Chepelev, Leonid; Hastings, Janna; Owen, Gareth; Fahy, Eoin; Steinbeck, Christoph; Subramanian, Shankar; Bolton, Evan; Greiner, Russell; Wishart, David S

2016-01-01

Scientists have long been driven by the desire to describe, organize, classify, and compare objects using taxonomies and/or ontologies. In contrast to biology, geology, and many other scientific disciplines, the world of chemistry still lacks a standardized chemical ontology or taxonomy. Several attempts at chemical classification have been made; but they have mostly been limited to either manual, or semi-automated proof-of-principle applications. This is regrettable as comprehensive chemical classification and description tools could not only improve our understanding of chemistry but also improve the linkage between chemistry and many other fields. For instance, the chemical classification of a compound could help predict its metabolic fate in humans, its druggability or potential hazards associated with it, among others. However, the sheer number (tens of millions of compounds) and complexity of chemical structures is such that any manual classification effort would prove to be near impossible. We have developed a comprehensive, flexible, and computable, purely structure-based chemical taxonomy (ChemOnt), along with a computer program (ClassyFire) that uses only chemical structures and structural features to automatically assign all known chemical compounds to a taxonomy consisting of >4800 different categories. This new chemical taxonomy consists of up to 11 different levels (Kingdom, SuperClass, Class, SubClass, etc.) with each of the categories defined by unambiguous, computable structural rules. Furthermore each category is named using a consensus-based nomenclature and described (in English) based on the characteristic common structural properties of the compounds it contains. The ClassyFire webserver is freely accessible at http://classyfire.wishartlab.com/. Moreover, a Ruby API version is available at https://bitbucket.org/wishartlab/classyfire_api, which provides programmatic access to the ClassyFire server and database. ClassyFire has been used to annotate over 77 million compounds and has already been integrated into other software packages to automatically generate textual descriptions for, and/or infer biological properties of over 100,000 compounds. Additional examples and applications are provided in this paper. ClassyFire, in combination with ChemOnt (ClassyFire's comprehensive chemical taxonomy), now allows chemists and cheminformaticians to perform large-scale, rapid and automated chemical classification. Moreover, a freely accessible API allows easy access to more than 77 million "ClassyFire" classified compounds. The results can be used to help annotate well studied, as well as lesser-known compounds. In addition, these chemical classifications can be used as input for data integration, and many other cheminformatics-related tasks.

Selectivity on-target of bromodomain chemical probes by structure-guided medicinal chemistry and chemical biology

PubMed Central

Galdeano, Carles; Ciulli, Alessio

2017-01-01

Targeting epigenetic proteins is a rapidly growing area for medicinal chemistry and drug discovery. Recent years have seen an explosion of interest in developing small molecules binding to bromodomains, the readers of acetyl-lysine modifications. A plethora of co-crystal structures has motivated focused fragment-based design and optimization programs within both industry and academia. These efforts have yielded several compounds entering the clinic, and many more are increasingly being used as chemical probes to interrogate bromodomain biology. High selectivity of chemical probes is necessary to ensure biological activity is due to an on-target effect. Here, we review the state-of-the-art of bromodomain-targeting compounds, focusing on the structural basis for their on-target selectivity or lack thereof. We also highlight chemical biology approaches to enhance on-target selectivity. PMID:27193077

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

Beauchamp, R.O. Jr.

A preliminary examination of chemical-substructure analysis (CSA) demonstrates the effective use of the Chemical Abstracts compound connectivity file in conjunction with the bibliographic file for relating chemical structures to biological activity. The importance of considering the role of metabolic intermediates under a variety of conditions is illustrated, suggesting structures that should be examined that may exhibit potential activity. This CSA technique, which utilizes existing large files accessible with online personal computers, is recommended for use as another tool in examining chemicals in drugs. 2 refs., 4 figs.

Materials ``alchemy'': Shape-preserving chemical transformation of micro-to-macroscopic 3-D structures

NASA Astrophysics Data System (ADS)

Sandhage, Kenneth H.

2010-06-01

The scalable fabrication of nano-structured materials with complex morphologies and tailorable chemistries remains a significant challenge. One strategy for such synthesis consists of the generation of a solid structure with a desired morphology (a “preform”), followed by reactive conversion of the preform into a new chemistry. Several gas/solid and liquid/solid reaction processes that are capable of such chemical conversion into new micro-to-nano-structured materials, while preserving the macroscopic-to-microscopic preform morphologies, are described in this overview. Such shape-preserving chemical transformation of one material into another could be considered a modern type of materials “alchemy.”

STATISTICAL DATA ON CHEMICAL COMPOUNDS.

DTIC Science & Technology

DATA STORAGE SYSTEMS, FEASIBILITY STUDIES, COMPUTERS, STATISTICAL DATA , DOCUMENTS, ARMY...CHEMICAL COMPOUNDS, INFORMATION RETRIEVAL), (*INFORMATION RETRIEVAL, CHEMICAL COMPOUNDS), MOLECULAR STRUCTURE, BIBLIOGRAPHIES, DATA PROCESSING

Occupational and Qualification Structures in the Field of Environmental Protection in the Metal and Chemical Industries in the United Kingdom.

ERIC Educational Resources Information Center

European Centre for the Development of Vocational Training, Berlin (Germany).

A study analyzed the occupational structure and qualifications associated with the field of environmental protection in the metal and chemical industries in the United Kingdom. The analysis included nine case studies based on interviews with firms in the chemicals and metals sectors. Information was gathered within an analytical framework that…

Chemical Shifts of the Carbohydrate Binding Domain of Galectin-3 from Magic Angle Spinning NMR and Hybrid Quantum Mechanics/Molecular Mechanics Calculations.

PubMed

Kraus, Jodi; Gupta, Rupal; Yehl, Jenna; Lu, Manman; Case, David A; Gronenborn, Angela M; Akke, Mikael; Polenova, Tatyana

2018-03-22

Magic angle spinning NMR spectroscopy is uniquely suited to probe the structure and dynamics of insoluble proteins and protein assemblies at atomic resolution, with NMR chemical shifts containing rich information about biomolecular structure. Access to this information, however, is problematic, since accurate quantum mechanical calculation of chemical shifts in proteins remains challenging, particularly for 15 N H . Here we report on isotropic chemical shift predictions for the carbohydrate recognition domain of microcrystalline galectin-3, obtained from using hybrid quantum mechanics/molecular mechanics (QM/MM) calculations, implemented using an automated fragmentation approach, and using very high resolution (0.86 Å lactose-bound and 1.25 Å apo form) X-ray crystal structures. The resolution of the X-ray crystal structure used as an input into the AF-NMR program did not affect the accuracy of the chemical shift calculations to any significant extent. Excellent agreement between experimental and computed shifts is obtained for 13 C α , while larger scatter is observed for 15 N H chemical shifts, which are influenced to a greater extent by electrostatic interactions, hydrogen bonding, and solvation.

Interspecies quantitative structure-activity relationships (QSARs) for eco-toxicity screening of chemicals: the role of physicochemical properties.

PubMed

Furuhama, A; Hasunuma, K; Aoki, Y

2015-01-01

In addition to molecular structure profiles, descriptors based on physicochemical properties are useful for explaining the eco-toxicities of chemicals. In a previous study we reported that a criterion based on the difference between the partition coefficient (log POW) and distribution coefficient (log D) values of chemicals enabled us to identify aromatic amines and phenols for which interspecies relationships with strong correlations could be developed for fish-daphnid and algal-daphnid toxicities. The chemicals that met the log D-based criterion were expected to have similar toxicity mechanisms (related to membrane penetration). Here, we investigated the applicability of log D-based criteria to the eco-toxicity of other kinds of chemicals, including aliphatic compounds. At pH 10, use of a log POW - log D > 0 criterion and omission of outliers resulted in the selection of more than 100 chemicals whose acute fish toxicities or algal growth inhibition toxicities were almost equal to their acute daphnid toxicities. The advantage of log D-based criteria is that they allow for simple, rapid screening and prioritizing of chemicals. However, inorganic molecules and chemicals containing certain structural elements cannot be evaluated, because calculated log D values are unavailable.

PROPOSED STANDARD TO GREATLY EXPAND PUBLIC ACCESS AND EXPLORATION OF TOXICITY DATA: EVALUATION OF STRUCTURE DATA FILE FORMAT

EPA Science Inventory

PROPOSED ST ANDARD TO GREA TL Y EXP AND PUBLIC ACCESS AND EXPLORATION OF TOXICITY DATA: EVALUATION OF STRUCTURE DATA FILE FORMAT

The ability to assess the potential toxicity of environmental, pharmaceutical, or industrial chemicals based on chemical structure in...

Identifying Chemical Groups for Biomonitoring

PubMed Central

Krowech, Gail; Hoover, Sara; Plummer, Laurel; Sandy, Martha; Zeise, Lauren; Solomon, Gina

2016-01-01

Summary: Regulatory agencies face daunting challenges identifying emerging chemical hazards because of the large number of chemicals in commerce and limited data on exposure and toxicology. Evaluating one chemical at a time is inefficient and can lead to replacement with uncharacterized chemicals or chemicals with structural features already linked to toxicity. The Office of Environmental Health Hazard Assessment (OEHHA) has developed a process for constructing and assessing chemical groups for potential biomonitoring in California. We screen for chemicals with significant exposure potential and propose possible chemical groups, based on structure and function. To support formal consideration of these groups by Biomonitoring California’s Scientific Guidance Panel, we conduct a detailed review of exposure and toxicity data and examine the likelihood of detection in biological samples. To date, 12 chemical groups have been constructed and added to the pool of chemicals that can be selected for Biomonitoring California studies, including p,p´-bisphenols, brominated and chlorinated organic compounds used as flame retardants, non-halogenated aromatic phosphates, and synthetic polycyclic musks. Evaluating chemical groups, rather than individual chemicals, is an efficient way to respond to shifts in chemical use and the emergence of new chemicals. This strategy can enable earlier identification of important chemicals for monitoring and intervention. PMID:27905275

Chemical structures and characteristics of animal manures and composts during composting and assessment of maturity indices

PubMed Central

Huang, Jieying; Yu, Zixuan; Gao, Hongjian; Yan, Xiaoming; Chang, Jiang; Wang, Chengming; Hu, Jingwei

2017-01-01

Changes in physicochemical characteristics, chemical structures and maturity of swine, cattle and chicken manures and composts during 70-day composting without addition of bulking agents were investigated. Physicochemical characteristics were measured by routine analyses and chemical structures by solid-state 13C NMR and FT-IR. Three manures were of distinct properties. Their changes in physicochemical characteristics, chemical structures, and maturity were different not only from each other but also from those with addition of bulking agents during composting. Aromaticity in chicken manure composts decreased at first, and then increased whereas that in cattle and swine manure composts increased. Enhanced ammonia volatilization occurred without addition of bulking agents. NMR structural information indicated that cattle and chicken composts were relatively stable at day 36 and 56, respectively, but swine manure composts were not mature up to day 70. Finally, the days required for three manures to reach the threshold values of different maturity indices were different. PMID:28604783

Applications of the Cambridge Structural Database in chemical education1

PubMed Central

Battle, Gary M.; Ferrence, Gregory M.; Allen, Frank H.

2010-01-01

The Cambridge Structural Database (CSD) is a vast and ever growing compendium of accurate three-dimensional structures that has massive chemical diversity across organic and metal–organic compounds. For these reasons, the CSD is finding significant uses in chemical education, and these applications are reviewed. As part of the teaching initiative of the Cambridge Crystallographic Data Centre (CCDC), a teaching subset of more than 500 CSD structures has been created that illustrate key chemical concepts, and a number of teaching modules have been devised that make use of this subset in a teaching environment. All of this material is freely available from the CCDC website, and the subset can be freely viewed and interrogated using WebCSD, an internet application for searching and displaying CSD information content. In some cases, however, the complete CSD System is required for specific educational applications, and some examples of these more extensive teaching modules are also discussed. The educational value of visualizing real three-dimensional structures, and of handling real experimental results, is stressed throughout. PMID:20877495

Effect of mechanical activation on structure changes and reactivity in further chemical modification of lignin.

PubMed

Zhao, Xiaohong; Zhang, Yanjuan; Hu, Huayu; Huang, Zuqiang; Yang, Mei; Chen, Dong; Huang, Kai; Huang, Aimin; Qin, Xingzhen; Feng, Zhenfei

2016-10-01

Lignin was treated by mechanical activation (MA) in a customized stirring ball mill, and the structure and reactivity in further esterification were studied. The chemical structure and morphology of MA-treated lignin and the esterified products were analyzed by chemical analysis combined with UV/vis spectrometer, FTIR,NMR, SEM and particle size analyzer. The results showed that MA contributed to the increase of aliphatic hydroxyl, phenolic hydroxyl, carbonyl and carboxyl groups but the decrease of methoxyl groups. Moreover, MA led to the decrease of particle size and the increase of specific surface area and roughness of surface in lignin. The reactivity of lignin was enhanced significantly for the increase of hydroxyl content and the improvement of mass transfer in chemical reaction caused by the changes of molecular structure and morphological structure. The process of MA is green and simple, and is an effective method for enhancing the reactivity of lignin. Copyright © 2016 Elsevier B.V. All rights reserved.

Applications of the Cambridge Structural Database in chemical education.

PubMed

Battle, Gary M; Ferrence, Gregory M; Allen, Frank H

2010-10-01

The Cambridge Structural Database (CSD) is a vast and ever growing compendium of accurate three-dimensional structures that has massive chemical diversity across organic and metal-organic compounds. For these reasons, the CSD is finding significant uses in chemical education, and these applications are reviewed. As part of the teaching initiative of the Cambridge Crystallographic Data Centre (CCDC), a teaching subset of more than 500 CSD structures has been created that illustrate key chemical concepts, and a number of teaching modules have been devised that make use of this subset in a teaching environment. All of this material is freely available from the CCDC website, and the subset can be freely viewed and interrogated using WebCSD, an internet application for searching and displaying CSD information content. In some cases, however, the complete CSD System is required for specific educational applications, and some examples of these more extensive teaching modules are also discussed. The educational value of visualizing real three-dimensional structures, and of handling real experimental results, is stressed throughout.

Non a Priori Automatic Discovery of 3D Chemical Patterns: Application to Mutagenicity.

PubMed

Rabatel, Julien; Fannes, Thomas; Lepailleur, Alban; Le Goff, Jérémie; Crémilleux, Bruno; Ramon, Jan; Bureau, Ronan; Cuissart, Bertrand

2017-10-01

This article introduces a new type of structural fragment called a geometrical pattern. Such geometrical patterns are defined as molecular graphs that include a labelling of atoms together with constraints on interatomic distances. The discovery of geometrical patterns in a chemical dataset relies on the induction of multiple decision trees combined in random forests. Each computational step corresponds to a refinement of a preceding set of constraints, extending a previous geometrical pattern. This paper focuses on the mutagenicity of chemicals via the definition of structural alerts in relation with these geometrical patterns. It follows an experimental assessment of the main geometrical patterns to show how they can efficiently originate the definition of a chemical feature related to a chemical function or a chemical property. Geometrical patterns have provided a valuable and innovative approach to bring new pieces of information for discovering and assessing structural characteristics in relation to a particular biological phenotype. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

REPDOSE: A database on repeated dose toxicity studies of commercial chemicals--A multifunctional tool.

PubMed

Bitsch, A; Jacobi, S; Melber, C; Wahnschaffe, U; Simetska, N; Mangelsdorf, I

2006-12-01

A database for repeated dose toxicity data has been developed. Studies were selected by data quality. Review documents or risk assessments were used to get a pre-screened selection of available valid data. The structure of the chemicals should be rather simple for well defined chemical categories. The database consists of three core data sets for each chemical: (1) structural features and physico-chemical data, (2) data on study design, (3) study results. To allow consistent queries, a high degree of standardization categories and glossaries were developed for relevant parameters. At present, the database consists of 364 chemicals investigated in 1018 studies which resulted in a total of 6002 specific effects. Standard queries have been developed, which allow analyzing the influence of structural features or PC data on LOELs, target organs and effects. Furthermore, it can be used as an expert system. First queries have shown that the database is a very valuable tool.

Importance of asparagine on the conformational stability and chemical reactivity of selected anti-inflammatory peptides

NASA Astrophysics Data System (ADS)

Soriano-Correa, Catalina; Barrientos-Salcedo, Carolina; Campos-Fernández, Linda; Alvarado-Salazar, Andres; Esquivel, Rodolfo O.

2015-08-01

Inflammatory response events are initiated by a complex series of molecular reactions that generate chemical intermediaries. The structure and properties of peptides and proteins are determined by the charge distribution of their side chains, which play an essential role in its electronic structure and physicochemical properties, hence on its biological functionality. The aim of this study was to analyze the effect of changing one central amino acid, such as substituting asparagine for aspartic acid, from Cys-Asn-Ser in aqueous solution, by assessing the conformational stability, physicochemical properties, chemical reactivity and their relationship with anti-inflammatory activity; employing quantum-chemical descriptors at the M06-2X/6-311+G(d,p) level. Our results suggest that asparagine plays a more critical role than aspartic acid in the structural stability, physicochemical features, and chemical reactivity of these tripeptides. Substituent groups in the side chain cause significant changes on the conformational stability and chemical reactivity, and consequently on their anti-inflammatory activity.

Density Functionals of Chemical Bonding

PubMed Central

Putz, Mihai V.

2008-01-01

The behavior of electrons in general many-electronic systems throughout the density functionals of energy is reviewed. The basic physico-chemical concepts of density functional theory are employed to highlight the energy role in chemical structure while its extended influence in electronic localization function helps in chemical bonding understanding. In this context the energy functionals accompanied by electronic localization functions may provide a comprehensive description of the global-local levels electronic structures in general and of chemical bonds in special. Becke-Edgecombe and author’s Markovian electronic localization functions are discussed at atomic, molecular and solid state levels. Then, the analytical survey of the main workable kinetic, exchange, and correlation density functionals within local and gradient density approximations is undertaken. The hierarchy of various energy functionals is formulated by employing both the parabolic and statistical correlation degree of them with the electronegativity and chemical hardness indices by means of quantitative structure-property relationship (QSPR) analysis for basic atomic and molecular systems. PMID:19325846

Chemical shift-based identification of monosaccharide spin-systems with NMR spectroscopy to complement untargeted glycomics.

PubMed

Klukowski, Piotr; Schubert, Mario

2018-06-15

A better understanding of oligosaccharides and their wide-ranging functions in almost every aspect of biology and medicine promises to uncover hidden layers of biology and will support the development of better therapies. Elucidating the chemical structure of an unknown oligosaccharide is still a challenge. Efficient tools are required for non-targeted glycomics. Chemical shifts are a rich source of information about the topology and configuration of biomolecules, whose potential is however not fully explored for oligosaccharides. We hypothesize that the chemical shifts of each monosaccharide are unique for each saccharide type with a certain linkage pattern, so that correlated data measured by NMR spectroscopy can be used to identify the chemical nature of a carbohydrate. We present here an efficient search algorithm, GlycoNMRSearch, that matches either a subset or the entire set of chemical shifts of an unidentified monosaccharide spin system to all spin systems in an NMR database. The search output is much more precise than earlier search functions and highly similar matches suggest the chemical structure of the spin system within the oligosaccharide. Thus searching for connected chemical shift correlations within all electronically available NMR data of oligosaccharides is a very efficient way of identifying the chemical structure of unknown oligosaccharides. With an improved database in the future, GlycoNMRSearch will be even more efficient deducing chemical structures of oligosaccharides and there is a high chance that it becomes an indispensable technique for glycomics. The search algorithm presented here, together with a graphical user interface, is available at http://glyconmrsearch.santos.pwr.edu.pl. Supplementary data are available at Bioinformatics online.

The Influence of Chemical Structure on the Strength of Rubber.

DTIC Science & Technology

1986-04-01

sticky, as if covered with an oily or tarry film. The debris from carbon-black-filled natural rubber vulcanizates is even more highly degraded , so...RD-RI66 355 THE INFLUENCE OF CHEMICAL STRUCTURE ON THE STRENGTH OF 1 1) RS 5355 RUBBER (U) KRON UNJY OH INST OF POLYMER SCIENCE UNCLSSIFEIDA N GENT...85-K-0222 .- Project NR 092-555 UTechnical Report No. 4 THE INFLUENCE OF CHEMICAL STRUCTURE ON THE * 4: STRENGTH OF RUBBER by S 2LECTE by A P R 0 9 I

Profiling the NIH Small Molecule Repository for Compounds That Generate H2O2 by Redox Cycling in Reducing Environments

PubMed Central

2010-01-01

We have screened the Library of Pharmacologically Active Compounds (LOPAC) and the National Institutes of Health (NIH) Small Molecule Repository (SMR) libraries in a horseradish peroxidase–phenol red (HRP-PR) H2O2 detection assay to identify redox cycling compounds (RCCs) capable of generating H2O2 in buffers containing dithiothreitol (DTT). Two RCCs were identified in the LOPAC set, the ortho-naphthoquinone β-lapachone and the para-naphthoquinone NSC 95397. Thirty-seven (0.02%) concentration-dependent RCCs were identified from 195,826 compounds in the NIH SMR library; 3 singleton structures, 9 ortho-quinones, 2 para-quinones, 4 pyrimidotriazinediones, 15 arylsulfonamides, 2 nitrothiophene-2-carboxylates, and 2 tolyl hydrazides. Sixty percent of the ortho-quinones and 80% of the pyrimidotriazinediones in the library were confirmed as RCCs. In contrast, only 3.9% of the para-quinones were confirmed as RCCs. Fifteen of the 251 arylsulfonamides in the library were confirmed as RCCs, and since we screened 17,868 compounds with a sulfonamide functional group we conclude that the redox cycling activity of the arylsulfonamide RCCs is due to peripheral reactive enone, aromatic, or heterocyclic functions. Cross-target queries of the University of Pittsburgh Drug Discovery Institute (UPDDI) and PubChem databases revealed that the RCCs exhibited promiscuous bioactivity profiles and have populated both screening databases with significantly higher numbers of active flags than non-RCCs. RCCs were promiscuously active against protein targets known to be susceptible to oxidation, but were also active in cell growth inhibition assays, and against other targets thought to be insensitive to oxidation. Profiling compound libraries or the hits from screening campaigns in the HRP-PR H2O2 detection assay significantly reduce the timelines and resources required to identify and eliminate promiscuous nuisance RCCs from the candidates for lead optimization. PMID:20070233

Overview of data and conceptual approaches for derivation of quantitative structure-activity relationships for ecotoxicological effects of organic chemicals.

PubMed

Bradbury, Steven P; Russom, Christine L; Ankley, Gerald T; Schultz, T Wayne; Walker, John D

2003-08-01

The use of quantitative structure-activity relationships (QSARs) in assessing potential toxic effects of organic chemicals on aquatic organisms continues to evolve as computational efficiency and toxicological understanding advance. With the ever-increasing production of new chemicals, and the need to optimize resources to assess thousands of existing chemicals in commerce, regulatory agencies have turned to QSARs as essential tools to help prioritize tiered risk assessments when empirical data are not available to evaluate toxicological effects. Progress in designing scientifically credible QSARs is intimately associated with the development of empirically derived databases of well-defined and quantified toxicity endpoints, which are based on a strategic evaluation of diverse sets of chemical structures, modes of toxic action, and species. This review provides a brief overview of four databases created for the purpose of developing QSARs for estimating toxicity of chemicals to aquatic organisms. The evolution of QSARs based initially on general chemical classification schemes, to models founded on modes of toxic action that range from nonspecific partitioning into hydrophobic cellular membranes to receptor-mediated mechanisms is summarized. Finally, an overview of expert systems that integrate chemical-specific mode of action classification and associated QSAR selection for estimating potential toxicological effects of organic chemicals is presented.

Building Scientific Confidence in the Development and ...

EPA Pesticide Factsheets

Read-across remains a popular data gap filling technique within category and analogue approaches for regulatory purposes. Acceptance of read-across is an ongoing challenge with several efforts underway for identifying and addressing uncertainties. Here we demonstrate an algorithmic approach to facilitate read-across using ToxCast in vitro bioactivity data in conjunction with chemical descriptor information to predict in vivo outcomes in guideline testing studies from ToxRefDB. Over 3400 different chemical structure descriptors were generated for a set of 976 chemicals and supplemented with the outcomes from 821 in vitro assays. The read-across prediction for a given chemical was based on the similarity weighted endpoint outcomes of its nearest neighbors calculated using in vitro bioactivity and chemical structure descriptors, called GenRA. GenRA is based on a computational approach for: (i) defining local validity domains using chemical and bioactivity descriptors, (ii) systematically deriving endpoint read-across predictions within these domains using similarity weighted activity of nearest neighbours, (iii) objectively evaluating predicted performance using tested chemicals, and (iv) assigning read-across predictions to untested chemicals along with estimates of uncertainty. We found in vitro bioactivity descriptors were often found to be more predictive of in vivo toxicity outcomes than chemical structure descriptors. We believe GenRA is an important first st

Structural and Chemical Biology of Terpenoid Cyclases

PubMed Central

2017-01-01

The year 2017 marks the twentieth anniversary of terpenoid cyclase structural biology: a trio of terpenoid cyclase structures reported together in 1997 were the first to set the foundation for understanding the enzymes largely responsible for the exquisite chemodiversity of more than 80000 terpenoid natural products. Terpenoid cyclases catalyze the most complex chemical reactions in biology, in that more than half of the substrate carbon atoms undergo changes in bonding and hybridization during a single enzyme-catalyzed cyclization reaction. The past two decades have witnessed structural, functional, and computational studies illuminating the modes of substrate activation that initiate the cyclization cascade, the management and manipulation of high-energy carbocation intermediates that propagate the cyclization cascade, and the chemical strategies that terminate the cyclization cascade. The role of the terpenoid cyclase as a template for catalysis is paramount to its function, and protein engineering can be used to reprogram the cyclization cascade to generate alternative and commercially important products. Here, I review key advances in terpenoid cyclase structural and chemical biology, focusing mainly on terpenoid cyclases and related prenyltransferases for which X-ray crystal structures have informed and advanced our understanding of enzyme structure and function. PMID:28841019

Characterization of the chemical structure and innate immune-stimulating activity of an extracellular polysaccharide from Rhizobium sp. strain M2 screened using a silkworm muscle contraction assay.

PubMed

Urai, Makoto; Aizawa, Tomoko; Imamura, Katsutoshi; Hamamoto, Hiroshi; Sekimizu, Kazuhisa

2017-11-22

We screened innate immunostimulant-producing bacteria using a silkworm muscle contraction assay, and isolated Rhizobium sp. strain M2 from soil. We purified the innate immunostimulant from strain M2, and characterized the chemical structure by nuclear magnetic resonance spectroscopy and chemical analyses. The innate immunostimulant (M2 EPS) comprised glucose, galactose, pyruvic acid, and succinic acid with a molar ratio of 6.8:1.0:0.9:0.4, and had a succinoglycan-like high molecular-weight heteropolysaccharide structure. To determine the structural motif involved in the innate immunostimulating activity, we modified the M2 EPS structure chemically, and found that the activity was increased by removal of the succinic and pyruvic acid substitutions. Strong acid hydrolysis completely inactivated the M2 EPS. Unmasking of the β-1,3/6-glucan structure of the side-chain by deacylation and depyruvylation may enhance the innate immune-stimulating activity of M2 EPS. These findings suggest that the succinoglycan-like polysaccharide purified from strain M2 has innate immune-stimulating activity, and its glycan structure is necessary for the activity.

DSSTOX MASTER STRUCTURE-INDEX FILE: SDF FILE AND ...

EPA Pesticide Factsheets

The DSSTox Master Structure-Index File serves to consolidate, manage, and ensure quality and uniformity of the chemical and substance information spanning all DSSTox Structure Data Files, including those in development but not yet published separately on this website. The DSSTox Master Structure-Index File serves to consolidate, manage, and ensure quality and uniformity of the chemical and substance information spanning all DSSTox Structure Data Files, including those in development but not yet published separately on this website.

Computational neural networks in chemistry: Model free mapping devices for predicting chemical reactivity from molecular structure

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

Elrod, D.W.

1992-01-01

Computational neural networks (CNNs) are a computational paradigm inspired by the brain's massively parallel network of highly interconnected neurons. The power of computational neural networks derives not so much from their ability to model the brain as from their ability to learn by example and to map highly complex, nonlinear functions, without the need to explicitly specify the functional relationship. Two central questions about CNNs were investigated in the context of predicting chemical reactions: (1) the mapping properties of neural networks and (2) the representation of chemical information for use in CNNs. Chemical reactivity is here considered an example ofmore » a complex, nonlinear function of molecular structure. CNN's were trained using modifications of the back propagation learning rule to map a three dimensional response surface similar to those typically observed in quantitative structure-activity and structure-property relationships. The computational neural network's mapping of the response surface was found to be robust to the effects of training sample size, noisy data and intercorrelated input variables. The investigation of chemical structure representation led to the development of a molecular structure-based connection-table representation suitable for neural network training. An extension of this work led to a BE-matrix structure representation that was found to be general for several classes of reactions. The CNN prediction of chemical reactivity and regiochemistry was investigated for electrophilic aromatic substitution reactions, Markovnikov addition to alkenes, Saytzeff elimination from haloalkanes, Diels-Alder cycloaddition, and retro Diels-Alder ring opening reactions using these connectivity-matrix derived representations. The reaction predictions made by the CNNs were more accurate than those of an expert system and were comparable to predictions made by chemists.« less

DSSTOX (DISTRIBUTED STRUCTURE-SEARCHABLE ...

EPA Pesticide Factsheets

Distributed Structure-Searchable Toxicity Database Network Major trends affecting public toxicity information resources have the potential to significantly alter the future of predictive toxicology. Chemical toxicity screening is undergoing shifts towards greater use of more fundamental information on gene/protein expression patterns and bioactivity and bioassay profiles, the latter generated with highthroughput screening technologies. Curated, systematically organized, and webaccessible toxicity and biological activity data in association with chemical structures, enabling the integration of diverse data information domains, will fuel the next frontier of advancement for QSAR (quantitative structure-activity relationship) and data mining technologies. The DSSTox project is supporting progress towards these goals on many fronts, promoting the use of formalized and structure-annotated toxicity data models, helping to interface these efforts with QSAR modelers, linking data from diverse sources, and creating a large, quality reviewed, central chemical structure information resource linked to various toxicity data sources

Classification of Chemicals Based On Structured Toxicity ...

EPA Pesticide Factsheets

Thirty years and millions of dollars worth of pesticide registration toxicity studies, historically stored as hardcopy and scanned documents, have been digitized into highly standardized and structured toxicity data within the Toxicity Reference Database (ToxRefDB). Toxicity-based classifications of chemicals were performed as a model application of ToxRefDB. These endpoints will ultimately provide the anchoring toxicity information for the development of predictive models and biological signatures utilizing in vitro assay data. Utilizing query and structured data mining approaches, toxicity profiles were uniformly generated for greater than 300 chemicals. Based on observation rate, species concordance and regulatory relevance, individual and aggregated effects have been selected to classify the chemicals providing a set of predictable endpoints. ToxRefDB exhibits the utility of transforming unstructured toxicity data into structured data and, furthermore, into computable outputs, and serves as a model for applying such data to address modern toxicological problems.

Porous silicon structures with high surface area/specific pore size

DOEpatents

Northrup, M.A.; Yu, C.M.; Raley, N.F.

1999-03-16

Fabrication and use of porous silicon structures to increase surface area of heated reaction chambers, electrophoresis devices, and thermopneumatic sensor-actuators, chemical preconcentrates, and filtering or control flow devices. In particular, such high surface area or specific pore size porous silicon structures will be useful in significantly augmenting the adsorption, vaporization, desorption, condensation and flow of liquids and gases in applications that use such processes on a miniature scale. Examples that will benefit from a high surface area, porous silicon structure include sample preconcentrators that are designed to adsorb and subsequently desorb specific chemical species from a sample background; chemical reaction chambers with enhanced surface reaction rates; and sensor-actuator chamber devices with increased pressure for thermopneumatic actuation of integrated membranes. Examples that benefit from specific pore sized porous silicon are chemical/biological filters and thermally-activated flow devices with active or adjacent surfaces such as electrodes or heaters. 9 figs.

Porous silicon structures with high surface area/specific pore size

DOEpatents

Northrup, M. Allen; Yu, Conrad M.; Raley, Norman F.

1999-01-01

Fabrication and use of porous silicon structures to increase surface area of heated reaction chambers, electrophoresis devices, and thermopneumatic sensor-actuators, chemical preconcentrates, and filtering or control flow devices. In particular, such high surface area or specific pore size porous silicon structures will be useful in significantly augmenting the adsorption, vaporization, desorption, condensation and flow of liquids and gasses in applications that use such processes on a miniature scale. Examples that will benefit from a high surface area, porous silicon structure include sample preconcentrators that are designed to adsorb and subsequently desorb specific chemical species from a sample background; chemical reaction chambers with enhanced surface reaction rates; and sensor-actuator chamber devices with increased pressure for thermopneumatic actuation of integrated membranes. Examples that benefit from specific pore sized porous silicon are chemical/biological filters and thermally-activated flow devices with active or adjacent surfaces such as electrodes or heaters.

Recent developments in broadly applicable structure-biodegradability relationships.

PubMed

Jaworska, Joanna S; Boethling, Robert S; Howard, Philip H

2003-08-01

Biodegradation is one of the most important processes influencing concentration of a chemical substance after its release to the environment. It is the main process for removal of many chemicals from the environment and therefore is an important factor in risk assessments. This article reviews available methods and models for predicting biodegradability of organic chemicals from structure. The first section of the article briefly discusses current needs for biodegradability estimation methods related to new and existing chemicals and in the context of multimedia exposure models. Following sections include biodegradation test methods and endpoints used in modeling, with special attention given to the Japanese Ministry of International Trade and Industry test; a primer on modeling, describing the various approaches that have been used in the structure/biodegradability relationship work, and contrasting statistical and mechanistic approaches; and recent developments in structure/biodegradability relationships, divided into group contribution, chemometric, and artificial intelligence approaches.

Use of Chemotypes for Profiling and Exploring the ToxCast Chemical-Assay Landscape (ACS Spring meeting)

EPA Science Inventory

EPA's ToxCast chemical library, currently exceeding 4000 unique chemicals, has successfully captured a broad diversity of chemical use-types, functionality, and structures and features potentially relevant to toxicity and environmental exposure landscapes. Chemical diversity in ...

The Chemical Validation and Standardization Platform (CVSP): large-scale automated validation of chemical structure datasets.

PubMed

Karapetyan, Karen; Batchelor, Colin; Sharpe, David; Tkachenko, Valery; Williams, Antony J

2015-01-01

There are presently hundreds of online databases hosting millions of chemical compounds and associated data. As a result of the number of cheminformatics software tools that can be used to produce the data, subtle differences between the various cheminformatics platforms, as well as the naivety of the software users, there are a myriad of issues that can exist with chemical structure representations online. In order to help facilitate validation and standardization of chemical structure datasets from various sources we have delivered a freely available internet-based platform to the community for the processing of chemical compound datasets. The chemical validation and standardization platform (CVSP) both validates and standardizes chemical structure representations according to sets of systematic rules. The chemical validation algorithms detect issues with submitted molecular representations using pre-defined or user-defined dictionary-based molecular patterns that are chemically suspicious or potentially requiring manual review. Each identified issue is assigned one of three levels of severity - Information, Warning, and Error - in order to conveniently inform the user of the need to browse and review subsets of their data. The validation process includes validation of atoms and bonds (e.g., making aware of query atoms and bonds), valences, and stereo. The standard form of submission of collections of data, the SDF file, allows the user to map the data fields to predefined CVSP fields for the purpose of cross-validating associated SMILES and InChIs with the connection tables contained within the SDF file. This platform has been applied to the analysis of a large number of data sets prepared for deposition to our ChemSpider database and in preparation of data for the Open PHACTS project. In this work we review the results of the automated validation of the DrugBank dataset, a popular drug and drug target database utilized by the community, and ChEMBL 17 data set. CVSP web site is located at http://cvsp.chemspider.com/. A platform for the validation and standardization of chemical structure representations of various formats has been developed and made available to the community to assist and encourage the processing of chemical structure files to produce more homogeneous compound representations for exchange and interchange between online databases. While the CVSP platform is designed with flexibility inherent to the rules that can be used for processing the data we have produced a recommended rule set based on our own experiences with the large data sets such as DrugBank, ChEMBL, and data sets from ChemSpider.

Coulombic Interaction in Finnish Middle School Chemistry: A Systemic Perspective on Students' Conceptual Structure of Chemical Bonding

ERIC Educational Resources Information Center

Joki, Jarkko; Lavonen, Jari; Juuti, Kalle; Aksela, Maija

2015-01-01

The aim of this study was to design a novel and holistic way to teach chemical bonding at the middle school level according to research on the teaching and learning of bonding. A further aim was to investigate high achieving middle school students' conceptual structures concerning chemical bonding by using a systemic perspective. Students in one…

Structure-mechanism-based engineering of chemical regulators targeting distinct pathological factors in Alzheimer's disease

NASA Astrophysics Data System (ADS)

Beck, Michael W.; Derrick, Jeffrey S.; Kerr, Richard A.; Oh, Shin Bi; Cho, Woo Jong; Lee, Shin Jung C.; Ji, Yonghwan; Han, Jiyeon; Tehrani, Zahra Aliakbar; Suh, Nayoung; Kim, Sujeong; Larsen, Scott D.; Kim, Kwang S.; Lee, Joo-Yong; Ruotolo, Brandon T.; Lim, Mi Hee

2016-10-01

The absence of effective therapeutics against Alzheimer's disease (AD) is a result of the limited understanding of its multifaceted aetiology. Because of the lack of chemical tools to identify pathological factors, investigations into AD pathogenesis have also been insubstantial. Here we report chemical regulators that demonstrate distinct specificity towards targets linked to AD pathology, including metals, amyloid-β (Aβ), metal-Aβ, reactive oxygen species, and free organic radicals. We obtained these chemical regulators through a rational structure-mechanism-based design strategy. We performed structural variations of small molecules for fine-tuning their electronic properties, such as ionization potentials and mechanistic pathways for reactivity towards different targets. We established in vitro and/or in vivo efficacies of the regulators for modulating their targets' reactivities, ameliorating toxicity, reducing amyloid pathology, and improving cognitive deficits. Our chemical tools show promise for deciphering AD pathogenesis and discovering effective drugs.

Structure-mechanism-based engineering of chemical regulators targeting distinct pathological factors in Alzheimer's disease.

PubMed

Beck, Michael W; Derrick, Jeffrey S; Kerr, Richard A; Oh, Shin Bi; Cho, Woo Jong; Lee, Shin Jung C; Ji, Yonghwan; Han, Jiyeon; Tehrani, Zahra Aliakbar; Suh, Nayoung; Kim, Sujeong; Larsen, Scott D; Kim, Kwang S; Lee, Joo-Yong; Ruotolo, Brandon T; Lim, Mi Hee

2016-10-13

The absence of effective therapeutics against Alzheimer's disease (AD) is a result of the limited understanding of its multifaceted aetiology. Because of the lack of chemical tools to identify pathological factors, investigations into AD pathogenesis have also been insubstantial. Here we report chemical regulators that demonstrate distinct specificity towards targets linked to AD pathology, including metals, amyloid-β (Aβ), metal-Aβ, reactive oxygen species, and free organic radicals. We obtained these chemical regulators through a rational structure-mechanism-based design strategy. We performed structural variations of small molecules for fine-tuning their electronic properties, such as ionization potentials and mechanistic pathways for reactivity towards different targets. We established in vitro and/or in vivo efficacies of the regulators for modulating their targets' reactivities, ameliorating toxicity, reducing amyloid pathology, and improving cognitive deficits. Our chemical tools show promise for deciphering AD pathogenesis and discovering effective drugs.

Chemical structure and dynamics: Annual report 1996

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

Colson, S.D.; McDowell, R.S.

1997-03-01

The Chemical Structure and Dynamics (CS&D) program is a major component of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) developed by Pacific Northwest National Laboratory (PNNL) to provide a state-of-the-art collaborative facility for studies of chemical structure and dynamics. We respond to the need for a fundamental, molecular-level understanding of chemistry at a wide variety of environmentally important interfaces by (1) extending the experimental characterization and theoretical description of chemical reactions to encompass the effects of condensed media and interfaces; (2) developing a multidisciplinary capability for describing interfacial chemical processes within which the new knowledge generated can bemore » brought to bear on complex phenomena in environmental chemistry and in nuclear waste processing and storage; and (3) developing state-of-the-art analytical methods for characterizing waste tanks and pollutant distributions, and for detecting and monitoring trace atmospheric species.« less

Information Theory and Voting Based Consensus Clustering for Combining Multiple Clusterings of Chemical Structures.

PubMed

Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2013-07-01

Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Determination of equilibrium structures of bromothymol blue revealed by using quantum chemistry with an aid of multivariate analysis of electronic absorption spectra

NASA Astrophysics Data System (ADS)

Shimada, Toru; Hasegawa, Takeshi

2017-10-01

The pH dependent chemical structures of bromothymol blue (BTB), which have long been under controversy, are determined by employing a combined technique of multivariate analysis of electronic absorption spectra and quantum chemistry. Principle component analysis (PCA) of the pH dependent spectra apparently reveals that only two chemical species are adequate to fully account for the color changes, with which the spectral decomposition is readily performed by using augmented alternative least-squares (ALS) regression analysis. The quantity variation by the ALS analysis also reveals the practical acid dissociation constant, pKa‧. The determination of pKa‧ is performed for various ionic strengths, which reveals the thermodynamic acid constant (pKa = 7.5) and the number of charge on each chemical species; the yellow form is negatively charged species of - 1 and the blue form that of - 2. On this chemical information, the quantum chemical calculation is carried out to find that BTB molecules take the pure quinoid form in an acid solution and the quinoid-phenolate form in an alkaline solution. The time-dependent density functional theory (TD-DFT) calculations for the theoretically determined chemical structures account for the peak shift of the electronic spectra. In this manner, the structures of all the chemical species appeared in equilibrium have finally been confirmed.

Determination of equilibrium structures of bromothymol blue revealed by using quantum chemistry with an aid of multivariate analysis of electronic absorption spectra.

PubMed

Shimada, Toru; Hasegawa, Takeshi

2017-10-05

The pH dependent chemical structures of bromothymol blue (BTB), which have long been under controversy, are determined by employing a combined technique of multivariate analysis of electronic absorption spectra and quantum chemistry. Principle component analysis (PCA) of the pH dependent spectra apparently reveals that only two chemical species are adequate to fully account for the color changes, with which the spectral decomposition is readily performed by using augmented alternative least-squares (ALS) regression analysis. The quantity variation by the ALS analysis also reveals the practical acid dissociation constant, pK a '. The determination of pK a ' is performed for various ionic strengths, which reveals the thermodynamic acid constant (pK a =7.5) and the number of charge on each chemical species; the yellow form is negatively charged species of -1 and the blue form that of -2. On this chemical information, the quantum chemical calculation is carried out to find that BTB molecules take the pure quinoid form in an acid solution and the quinoid-phenolate form in an alkaline solution. The time-dependent density functional theory (TD-DFT) calculations for the theoretically determined chemical structures account for the peak shift of the electronic spectra. In this manner, the structures of all the chemical species appeared in equilibrium have finally been confirmed. Copyright © 2017 Elsevier B.V. All rights reserved.

Chemically derived graphene oxide: towards large-area thin-film electronics and optoelectronics.

PubMed

Eda, Goki; Chhowalla, Manish

2010-06-11

Chemically derived graphene oxide (GO) possesses a unique set of properties arising from oxygen functional groups that are introduced during chemical exfoliation of graphite. Large-area thin-film deposition of GO, enabled by its solubility in a variety of solvents, offers a route towards GO-based thin-film electronics and optoelectronics. The electrical and optical properties of GO are strongly dependent on its chemical and atomic structure and are tunable over a wide range via chemical engineering. In this Review, the fundamental structure and properties of GO-based thin films are discussed in relation to their potential applications in electronics and optoelectronics.

Chemical warfare agents.

PubMed

Kuca, Kamil; Pohanka, Miroslav

2010-01-01

Chemical warfare agents are compounds of different chemical structures. Simple molecules such as chlorine as well as complex structures such as ricin belong to this group. Nerve agents, vesicants, incapacitating agents, blood agents, lung-damaging agents, riot-control agents and several toxins are among chemical warfare agents. Although the use of these compounds is strictly prohibited, the possible misuse by terrorist groups is a reality nowadays. Owing to this fact, knowledge of the basic properties of these substances is of a high importance. This chapter briefly introduces the separate groups of chemical warfare agents together with their members and the potential therapy that should be applied in case someone is intoxicated by these agents.

TRAX-CHEM: A pre-chemical and chemical stage extension of the particle track structure code TRAX in water targets

NASA Astrophysics Data System (ADS)

Boscolo, D.; Krämer, M.; Durante, M.; Fuss, M. C.; Scifoni, E.

2018-04-01

The production, diffusion, and interaction of particle beam induced water-derived radicals is studied with the a pre-chemical and chemical module of the Monte Carlo particle track structure code TRAX, based on a step by step approach. After a description of the model implemented, the chemical evolution of the most important products of water radiolysis is studied for electron, proton, helium, and carbon ion radiation at different energies. The validity of the model is verified by comparing the calculated time and LET dependent yield with experimental data from literature and other simulation approaches.

Epitaxial BiFeO3 thin films fabricated by chemical solution deposition

NASA Astrophysics Data System (ADS)

Singh, S. K.; Kim, Y. K.; Funakubo, H.; Ishiwara, H.

2006-04-01

Epitaxial BiFeO3 (BFO) thin films were fabricated on (001)-, (110)-, and (111)-oriented single-crystal SrRuO3(SRO )/SrTiO3(STO) structures by chemical solution deposition. X-ray diffraction indicates the formation of an epitaxial single-phase perovskite structure and pole figure measurement confirms the cube-on-cube epitaxial relationship of BFO ‖SRO‖STO. Chemical-solution-deposited BFO films have a rhombohedral structure with lattice parameter of 0.395nm, which is the same structure as that of a bulk single crystal. The remanent polarization of approximately 50μC/cm2 was observed in BFO (001) thin films at 80K.

Essential Set of Molecular Descriptors for ADME Prediction in Drug and Environmental Chemical Space

EPA Science Inventory

Historically, the disciplines of pharmacology and toxicology have embraced quantitative structure-activity relationships (QSAR) and quantitative structure-property relationships (QSPR) to predict ADME properties or biological activities of untested chemicals. The question arises ...

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

PubMed

Papamokos, George; Silins, Ilona

2016-01-01

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

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

PubMed Central

Papamokos, George; Silins, Ilona

2016-01-01

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

The Intersection of Structural and Chemical Biology - An Essential Synergy.

PubMed

Zuercher, William J; Elkins, Jonathan M; Knapp, Stefan

2016-01-21

The continual improvement in our ability to generate high resolution structural models of biological molecules has stimulated and supported innovative chemical biology projects that target increasingly challenging ligand interaction sites. In this review we outline some of the recent developments in chemical biology and rational ligand design and show selected examples that illustrate the synergy between these research areas. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relationship between chemical structure and the occupational asthma hazard of low molecular weight organic compounds

PubMed Central

Jarvis, J; Seed, M; Elton, R; Sawyer, L; Agius, R

2005-01-01

Aims: To investigate quantitatively, relationships between chemical structure and reported occupational asthma hazard for low molecular weight (LMW) organic compounds; to develop and validate a model linking asthma hazard with chemical substructure; and to generate mechanistic hypotheses that might explain the relationships. Methods: A learning dataset used 78 LMW chemical asthmagens reported in the literature before 1995, and 301 control compounds with recognised occupational exposures and hazards other than respiratory sensitisation. The chemical structures of the asthmagens and control compounds were characterised by the presence of chemical substructure fragments. Odds ratios were calculated for these fragments to determine which were associated with a likelihood of being reported as an occupational asthmagen. Logistic regression modelling was used to identify the independent contribution of these substructures. A post-1995 set of 21 asthmagens and 77 controls were selected to externally validate the model. Results: Nitrogen or oxygen containing functional groups such as isocyanate, amine, acid anhydride, and carbonyl were associated with an occupational asthma hazard, particularly when the functional group was present twice or more in the same molecule. A logistic regression model using only statistically significant independent variables for occupational asthma hazard correctly assigned 90% of the model development set. The external validation showed a sensitivity of 86% and specificity of 99%. Conclusions: Although a wide variety of chemical structures are associated with occupational asthma, bifunctional reactivity is strongly associated with occupational asthma hazard across a range of chemical substructures. This suggests that chemical cross-linking is an important molecular mechanism leading to the development of occupational asthma. The logistic regression model is freely available on the internet and may offer a useful but inexpensive adjunct to the prediction of occupational asthma hazard. PMID:15778257

DISTRIBUTED STRUCTURE-SEARCHABLE TOXICITY (DSSTOX) PUBLIC DATABASE NETWORK: A PROPOSAL

EPA Science Inventory

The ability to assess the potential genotoxicity, carcinogenicity, or other toxicity of pharmaceutical or industrial chemicals based on chemical structure information is a highly coveted and shared goal of varied academic, commercial, and government regulatory groups. These dive...

Self-assembled lipid bilayer materials

DOEpatents

Sasaki, Darryl Y.; Waggoner, Tina A.; Last, Julie A.

2005-11-08

The present invention is a self-assembling material comprised of stacks of lipid bilayers formed in a columnar structure, where the assembly process is mediated and regulated by chemical recognition events. The material, through the chemical recognition interactions, has a self-regulating system that corrects the radial size of the assembly creating a uniform diameter throughout most of the structure. The materials form and are stable in aqueous solution. These materials are useful as structural elements for the architecture of materials and components in nanotechnology, efficient light harvesting systems for optical sensing, chemical processing centers, and drug delivery vehicles.

Denaturation of collagen structures and their transformation under the physical and chemical effects

NASA Astrophysics Data System (ADS)

Ivankin, A.; Boldirev, V.; Fadeev, G.; Baburina, M.; Kulikovskii, A.; Vostrikova, N.

2017-11-01

The process of denaturation of collagen structures under the influence of physical and chemical factors play an important role in the manufacture of food technology and the production of drugs for medicine and cosmetology. The paper discussed the problem of the combined effects of heat treatment, mechanical dispersion and ultrasonic action on the structural changes of the animal collagen in the presence of weak protonated organic acids. Algorithm combined effects of physical and chemical factors as a result of the formation of the technological properties of products containing collagen has been shown.

Identification of helix capping and β-turn motifs from NMR chemical shifts

PubMed Central

Shen, Yang; Bax, Ad

2012-01-01

We present an empirical method for identification of distinct structural motifs in proteins on the basis of experimentally determined backbone and 13Cβ chemical shifts. Elements identified include the N-terminal and C-terminal helix capping motifs and five types of β-turns: I, II, I′, II′ and VIII. Using a database of proteins of known structure, the NMR chemical shifts, together with the PDB-extracted amino acid preference of the helix capping and β-turn motifs are used as input data for training an artificial neural network algorithm, which outputs the statistical probability of finding each motif at any given position in the protein. The trained neural networks, contained in the MICS (motif identification from chemical shifts) program, also provide a confidence level for each of their predictions, and values ranging from ca 0.7–0.9 for the Matthews correlation coefficient of its predictions far exceed that attainable by sequence analysis. MICS is anticipated to be useful both in the conventional NMR structure determination process and for enhancing on-going efforts to determine protein structures solely on the basis of chemical shift information, where it can aid in identifying protein database fragments suitable for use in building such structures. PMID:22314702

Structural analysis of an innate immunostimulant from broccoli, Brassica oleracea var. italica.

PubMed

Urai, Makoto; Kataoka, Keiko; Nishida, Satoshi; Sekimizu, Kazuhisa

2017-11-22

Vegetables are eaten as part of a healthy diet throughout the world, and some are also applied topically as a traditional medicine. We evaluated the innate immunostimulating activities of hot water extracts of various vegetables using the silkworm muscle contraction assay system, and found that broccoli, Brassica oleracea var. italica, contains a strong innate immunostimulant. We purified the innate immunostimulant from broccoli, and characterized the chemical structure by chemical analyses and NMR spectroscopy. The innate immunostimulant comprised galacturonic acid, galactose, glucose, arabinose, and rhamnose, and had a pectic-like polysaccharide structure. To determine the structural motif involved in the innate immunostimulating activity, we modified the structure by chemical and enzymatic treatment, and found that the activity was attenuated by pectinase digestion. These findings suggest that a pectic-like polysaccharide purified from broccoli has innate immune-stimulating activity, for which the polygalacturonic acid structure is necessary.

Corn stalks char from fast pyrolysis as precursor material for preparation of activated carbon in fluidized bed reactor.

PubMed

Wang, Zhiqi; Wu, Jingli; He, Tao; Wu, Jinhu

2014-09-01

Corn stalks char from fast pyrolysis was activated by physical and chemical activation process in a fluidized bed reactor. The structure and morphology of the carbons were characterized by N2 adsorption and SEM. Effects of activation time and activation agents on the structure of activation carbon were investigated. The physically activated carbons with CO2 have BET specific surface area up to 880 m(2)/g, and exhibit microporous structure. The chemically activated carbons with H3PO4 have BET specific surface area up to 600 m(2)/g, and exhibit mesoporous structure. The surface morphology shows that physically activated carbons exhibit fibrous like structure in nature with long ridges, resembling parallel lines. Whereas chemically activated carbons have cross-interconnected smooth open pores without the fibrous like structure. Copyright © 2014 Elsevier Ltd. All rights reserved.

Structure-based classification and ontology in chemistry

PubMed Central

2012-01-01

Background Recent years have seen an explosion in the availability of data in the chemistry domain. With this information explosion, however, retrieving relevant results from the available information, and organising those results, become even harder problems. Computational processing is essential to filter and organise the available resources so as to better facilitate the work of scientists. Ontologies encode expert domain knowledge in a hierarchically organised machine-processable format. One such ontology for the chemical domain is ChEBI. ChEBI provides a classification of chemicals based on their structural features and a role or activity-based classification. An example of a structure-based class is 'pentacyclic compound' (compounds containing five-ring structures), while an example of a role-based class is 'analgesic', since many different chemicals can act as analgesics without sharing structural features. Structure-based classification in chemistry exploits elegant regularities and symmetries in the underlying chemical domain. As yet, there has been neither a systematic analysis of the types of structural classification in use in chemistry nor a comparison to the capabilities of available technologies. Results We analyze the different categories of structural classes in chemistry, presenting a list of patterns for features found in class definitions. We compare these patterns of class definition to tools which allow for automation of hierarchy construction within cheminformatics and within logic-based ontology technology, going into detail in the latter case with respect to the expressive capabilities of the Web Ontology Language and recent extensions for modelling structured objects. Finally we discuss the relationships and interactions between cheminformatics approaches and logic-based approaches. Conclusion Systems that perform intelligent reasoning tasks on chemistry data require a diverse set of underlying computational utilities including algorithmic, statistical and logic-based tools. For the task of automatic structure-based classification of chemical entities, essential to managing the vast swathes of chemical data being brought online, systems which are capable of hybrid reasoning combining several different approaches are crucial. We provide a thorough review of the available tools and methodologies, and identify areas of open research. PMID:22480202

Equilibrium simulations of proteins using molecular fragment replacement and NMR chemical shifts.

PubMed

Boomsma, Wouter; Tian, Pengfei; Frellsen, Jes; Ferkinghoff-Borg, Jesper; Hamelryck, Thomas; Lindorff-Larsen, Kresten; Vendruscolo, Michele

2014-09-23

Methods of protein structure determination based on NMR chemical shifts are becoming increasingly common. The most widely used approaches adopt the molecular fragment replacement strategy, in which structural fragments are repeatedly reassembled into different complete conformations in molecular simulations. Although these approaches are effective in generating individual structures consistent with the chemical shift data, they do not enable the sampling of the conformational space of proteins with correct statistical weights. Here, we present a method of molecular fragment replacement that makes it possible to perform equilibrium simulations of proteins, and hence to determine their free energy landscapes. This strategy is based on the encoding of the chemical shift information in a probabilistic model in Markov chain Monte Carlo simulations. First, we demonstrate that with this approach it is possible to fold proteins to their native states starting from extended structures. Second, we show that the method satisfies the detailed balance condition and hence it can be used to carry out an equilibrium sampling from the Boltzmann distribution corresponding to the force field used in the simulations. Third, by comparing the results of simulations carried out with and without chemical shift restraints we describe quantitatively the effects that these restraints have on the free energy landscapes of proteins. Taken together, these results demonstrate that the molecular fragment replacement strategy can be used in combination with chemical shift information to characterize not only the native structures of proteins but also their conformational fluctuations.

Investigation of the impedance modulation of thin films with a chemically-sensitive field-effect transistor

NASA Astrophysics Data System (ADS)

Wiseman, John M.

1988-12-01

This study resulted in the design and fabrication of a Chemically-Sensitive Field-Effect Transistor (CHEMFET) with an interdigitated gate electrode structure. The electrical performance of the CHEMFET, both in the time-domain and frequency domain, was evaluated for detecting changes in the molecular structure and chemical composition in three thin films: an epoxy, copper phthalocyanine (CuPc), and acetylcholinesterase (ACHE). The change in the chemical state of a film was manifested as a change in the electrical impedance of the interdigitated gate electrode structure. For the epoxy, its molecular structure changed as a result of the curing reaction. To induce a change in the chemical state of the CuPc and ACHE films they were exposed to part-per billion concentrations of a challenge gas, either nitrogen dioxide (NO2) or the the organophosphorus compound, diisopropyl methylphosphonate (DIMP). The results clearly show that the CHEMFET can detect chemical and structural changes in an epoxy and CuPc film. The sensitivity of the ACHE film was not unequivocally determined due to long term drift in the ACHE film's electrical properties. The most remarkable result of this effort was the demonstration of a unique selectivity feature in the CHEMFET's frequency dependent response to a challenge gas. The examination of the relative changes in the electrical properties of the CHEMFET at different frequencies showed that the CHEMFET can be used to distinguish between NO2 and Dimp EXPOSURE.

Temporal Control over Transient Chemical Systems using Structurally Diverse Chemical Fuels.

PubMed

Chen, Jack L-Y; Maiti, Subhabrata; Fortunati, Ilaria; Ferrante, Camilla; Prins, Leonard J

2017-08-25

The next generation of adaptive, intelligent chemical systems will rely on a continuous supply of energy to maintain the functional state. Such systems will require chemical methodology that provides precise control over the energy dissipation process, and thus, the lifetime of the transiently activated function. This manuscript reports on the use of structurally diverse chemical fuels to control the lifetime of two different systems under dissipative conditions: transient signal generation and the transient formation of self-assembled aggregates. The energy stored in the fuels is dissipated at different rates by an enzyme, which installs a dependence of the lifetime of the active system on the chemical structure of the fuel. In the case of transient signal generation, it is shown that different chemical fuels can be used to generate a vast range of signal profiles, allowing temporal control over two orders of magnitude. Regarding self-assembly under dissipative conditions, the ability to control the lifetime using different fuels turns out to be particularly important as stable aggregates are formed only at well-defined surfactant/fuel ratios, meaning that temporal control cannot be achieved by simply changing the fuel concentration. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Native chemical ligation at Asx-Cys, Glx-Cys: chemical synthesis and high-resolution X-ray structure of ShK toxin by racemic protein crystallography.

PubMed

Dang, Bobo; Kubota, Tomoya; Mandal, Kalyaneswar; Bezanilla, Francisco; Kent, Stephen B H

2013-08-14

We have re-examined the utility of native chemical ligation at -Gln/Glu-Cys- [Glx-Cys] and -Asn/Asp-Cys- [Asx-Cys] sites. Using the improved thioaryl catalyst 4-mercaptophenylacetic acid (MPAA), native chemical ligation could be performed at -Gln-Cys- and Asn-Cys- sites without side reactions. After optimization, ligation at a -Glu-Cys- site could also be used as a ligation site, with minimal levels of byproduct formation. However, -Asp-Cys- is not appropriate for use as a site for native chemical ligation because of formation of significant amounts of β-linked byproduct. The feasibility of native chemical ligation at -Gln-Cys- enabled a convergent total chemical synthesis of the enantiomeric forms of the ShK toxin protein molecule. The D-ShK protein molecule was ~50,000-fold less active in blocking the Kv1.3 channel than the L-ShK protein molecule. Racemic protein crystallography was used to obtain high-resolution X-ray diffraction data for ShK toxin. The structure was solved by direct methods and showed significant differences from the previously reported NMR structures in some regions of the ShK protein molecule.

The Need for, and the Role of the Toxicological Chemist in the Design of Safer Chemicals.

PubMed

DeVito, Stephen C

2018-02-01

During the past several decades, there has been an ever increasing emphasis for designers of new commercial (nonpharmaceutical) chemicals to include considerations of the potential impacts a planned chemical may have on human health and the environment as part of the design of the chemical, and to design chemicals such that they possess the desired use efficacy while minimizing threats to human health and the environment. Achievement of this goal would be facilitated by the availability of individuals specifically and formally trained to design such chemicals. Medicinal chemists are specifically trained to design and develop safe and clinically efficacious pharmaceutical substances. No such formally trained science hybrid exists for the design of safer commercial (nonpharmaceutical) chemicals. This article describes the need for and role of the "toxicological chemist," an individual who is formally trained in synthetic organic chemistry, biochemistry, physiology, toxicology, environmental science, and in the relationships between structure and commercial use efficacy, structure and toxicity, structure and environmental fate and effects, and global hazard, and trained to integrate this knowledge to design safer commercially efficacious chemicals. Using examples, this article illustrates the role of the toxicological chemist in designing commercially efficacious, safer chemical candidates. Published by Oxford University Press on behalf of the Society of Toxicology 2017. This work is written by a US Government employee and is in the public domain in the US.

Bioalerts: a python library for the derivation of structural alerts from bioactivity and toxicity data sets.

PubMed

Cortes-Ciriano, Isidro

2016-01-01

Assessing compound toxicity at early stages of the drug discovery process is a crucial task to dismiss drug candidates likely to fail in clinical trials. Screening drug candidates against structural alerts, i.e. chemical fragments associated to a toxicological response prior or after being metabolized (bioactivation), has proved a valuable approach for this task. During the last decades, diverse algorithms have been proposed for the automatic derivation of structural alerts from categorical toxicity data sets. Here, the python library bioalerts is presented, which comprises functionalities for the automatic derivation of structural alerts from categorical (dichotomous), e.g. toxic/non-toxic, and continuous bioactivity data sets, e.g. [Formula: see text] or [Formula: see text] values. The library bioalerts relies on the RDKit implementation of the circular Morgan fingerprint algorithm to compute chemical substructures, which are derived by considering radial atom neighbourhoods of increasing bond radius. In addition to the derivation of structural alerts, bioalerts provides functionalities for the calculation of unhashed (keyed) Morgan fingerprints, which can be used in predictive bioactivity modelling with the advantage of allowing for a chemically meaningful deconvolution of the chemical space. Finally, bioalerts provides functionalities for the easy visualization of the derived structural alerts.

Intermolecular shielding contributions studied by modeling the 13C chemical-shift tensors of organic single crystals with plane waves

PubMed Central

Johnston, Jessica C.; Iuliucci, Robbie J.; Facelli, Julio C.; Fitzgerald, George; Mueller, Karl T.

2009-01-01

In order to predict accurately the chemical shift of NMR-active nuclei in solid phase systems, magnetic shielding calculations must be capable of considering the complete lattice structure. Here we assess the accuracy of the density functional theory gauge-including projector augmented wave method, which uses pseudopotentials to approximate the nodal structure of the core electrons, to determine the magnetic properties of crystals by predicting the full chemical-shift tensors of all 13C nuclides in 14 organic single crystals from which experimental tensors have previously been reported. Plane-wave methods use periodic boundary conditions to incorporate the lattice structure, providing a substantial improvement for modeling the chemical shifts in hydrogen-bonded systems. Principal tensor components can now be predicted to an accuracy that approaches the typical experimental uncertainty. Moreover, methods that include the full solid-phase structure enable geometry optimizations to be performed on the input structures prior to calculation of the shielding. Improvement after optimization is noted here even when neutron diffraction data are used for determining the initial structures. After geometry optimization, the isotropic shift can be predicted to within 1 ppm. PMID:19831448

A new candidate of calcium channel blocker in silico from Tectona grandis for treatment of gestational hypertension

NASA Astrophysics Data System (ADS)

Azizah, A.; Suselo, Y. H.; Muthmainah, M.; Indarto, D.

2018-05-01

Gestational Hypertension is one of the three main causes of maternal mortality in Indonesia. Nifedipine which blockes the Cav1.2 calcium channel has frequently been used to treat gestational hypertension. However the efficacy of nifedipine has not been established yet and the prevalence of gestational hypertension is still high (27.1 %). Indonesian herbal plants have potential to be developed as natural drugs. Molecular docking, a computational method, is very often used to depict interaction between molecules and target receptor This study was therefore to identify Indonesian herbal plants that could inhibit the calcium channel in silico. This was a bioinformatics study with molecular docking approach. Three-dimensional structure of human calcium channel Cav1.2 was determined by modelling with rabbit calcium channel (ID:5GJW) as template and using the SWISS MODEL software. Nifedipine was used as a standard ligand and obtained from ZINC database with the access code ZINC19594578. Active compounds of Indonesian herbal plants were registered in HerbalDB database and their molecular structure was obtained from PubChem. Binding affinity of human Cav1.2 model-ligand complexes were assesed using AutoDock Vina 1.1.2 software and visualization of molecular conformation used Chimera 1.10 and PyMol 1.3 softwares. The Lipinsky’s rules of five were used to determine active compounds which fullfilled drug criteria. The human Cav1-2 model had 72.35% sequence identity with rabbit Cav1.1. Nifedipine bound to the human Cav1.2 model with -2.1 kcal/mol binding affinity and had binding sites at Gln1060, Phe1129, Ser1132, and Ile1173 residues. A lower binding affinity was observed in 8 phytochemicals but only obtusifolin 2-glucoside (-2.2 kcal/mol) had similar binding sites as nifedipin did. In addition, obtusifolin 2-glucoside met the Lipinsky criteria and the molecule conformation was similar with nifedipine. From the HerbalDB database, obtusifolin 2-glucoside is found in Tectona grandis. Obtusifolin 2-glucoside computationally becomes a potensial candidate of calcium channel blocker. In vitro assays should be performed to evaluate the antagonist effect of obtusifolin 2-glucoside on calcium channel Cav1.2.

Characterizing TPS Microstructure: A Review of Some techniques

NASA Technical Reports Server (NTRS)

Gasch, Matthew; Stackpole, Mairead; Agrawal, Parul; Chavez-Garcie, Jose

2011-01-01

I. When seeking to understand ablator microstructure and morphology there are several useful techniques A. SEM 1) Visual characteriza3on at various length scales. 2) Chemical mapping by backscatter or x-ray highlights areas of interest. 3) Combined with other techniques (density, weight change, chemical analysis) SEM is a powerful tool to aid in explaining thermo/structural data. B. ASAP. 1) Chemical characteriza3on at various length scales. 2) Chemical mapping of pore structure by gas adsorption. 3) Provides a map of pore size vs. pore volume. 4) Provided surface area of exposed TPS. II. Both methods help characterize and understand how ablators react with other chemical species and provides insight into how they oxidize.

SPECTRa-T: machine-based data extraction and semantic searching of chemistry e-theses.

PubMed

Downing, Jim; Harvey, Matt J; Morgan, Peter B; Murray-Rust, Peter; Rzepa, Henry S; Stewart, Diana C; Tonge, Alan P; Townsend, Joe A

2010-02-22

The SPECTRa-T project has developed text-mining tools to extract named chemical entities (NCEs), such as chemical names and terms, and chemical objects (COs), e.g., experimental spectral assignments and physical chemistry properties, from electronic theses (e-theses). Although NCEs were readily identified within the two major document formats studied, only the use of structured documents enabled identification of chemical objects and their association with the relevant chemical entity (e.g., systematic chemical name). A corpus of theses was analyzed and it is shown that a high degree of semantic information can be extracted from structured documents. This integrated information has been deposited in a persistent Resource Description Framework (RDF) triple-store that allows users to conduct semantic searches. The strength and weaknesses of several document formats are reviewed.

Effects of chemical and mineral admixtures on performance of Florida structural concrete.

DOT National Transportation Integrated Search

2016-06-21

Several mineral and chemical admixtures, commonly used in Florida structural concrete, were studied here to assess their effect on the fresh and hardened properties of cementitious systems. Pozzolans examined here were Class F fly ash, silica fume, b...

Accessibility of selenomethionine proteins by total chemical synthesis: structural studies of human herpesvirus-8 MIP-II.

PubMed

Shao, W; Fernandez, E; Wilken, J; Thompson, D A; Siani, M A; West, J; Lolis, E; Schweitzer, B I

1998-12-11

The determination of high resolution three-dimensional structures by X-ray crystallography or nuclear magnetic resonance (NMR) is a time-consuming process. Here we describe an approach to circumvent the cloning and expression of a recombinant protein as well as screening for heavy atom derivatives. The selenomethionine-modified chemokine macrophage inflammatory protein-II (MIP-II) from human herpesvirus-8 has been produced by total chemical synthesis, crystallized, and characterized by NMR. The protein has a secondary structure typical of other chemokines and forms a monomer in solution. These results indicate that total chemical synthesis can be used to accelerate the determination of three-dimensional structures of new proteins identified in genome programs.

Structural and vibrational spectral investigations of melaminium maleate monohydrate by FTIR, FT-Raman and quantum chemical calculations

NASA Astrophysics Data System (ADS)

Arjunan, V.; Kalaivani, M.; Marchewka, M. K.; Mohan, S.

2013-04-01

The structural investigations of the molecular complex of melamine with maleic acid, namely melaminium maleate monohydrate have been carried out by quantum chemical methods in addition to FTIR, FT-Raman and far-infrared spectral studies. The quantum chemical studies were performed with DFT (B3LYP) method using 6-31G**, cc-pVDZ and 6-311++G** basis sets to determine the energy, structural and thermodynamic parameters of melaminium maleate monohydrate. The hydrogen atom from maleic acid was transferred to the melamine molecule giving the singly protonated melaminium cation. The ability of ions to form spontaneous three-dimensional structure through weak Osbnd H⋯O and Nsbnd H⋯O hydrogen bonds shows notable vibrational effects.

Chemical Routes to Ceramics with Tunable Properties and Structures: Chemical Routes to Nano and Micro-Structured Ceramics

DTIC Science & Technology

2009-12-20

condensations, ordered macroporous arrays of titania , zirconia, and alumina . Other work employing the silica templates has yielded macroporous carbons...Final 3. DATES COVERED (From - To) 05/01/05-09/30/09 4. TITLE AND SUBTITLE Chemical Routes to Ceramics with Tunable Properties and...ORGANIZATION REPORT NUMBER 9-2009 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) Air Force Office of Scientific Research Ceramic and

Exploring Conceptual Frameworks of Models of Atomic Structures and Periodic Variations, Chemical Bonding, and Molecular Shape and Polarity: A Comparison of Undergraduate General Chemistry Students with High and Low Levels of Content Knowledge

ERIC Educational Resources Information Center

Wang, Chia-Yu; Barrow, Lloyd H.

2013-01-01

The purpose of the study was to explore students' conceptual frameworks of models of atomic structure and periodic variations, chemical bonding, and molecular shape and polarity, and how these conceptual frameworks influence their quality of explanations and ability to shift among chemical representations. This study employed a purposeful sampling…

Aggregating Data for Computational Toxicology Applications: The U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System

PubMed Central

Judson, Richard S.; Martin, Matthew T.; Egeghy, Peter; Gangwal, Sumit; Reif, David M.; Kothiya, Parth; Wolf, Maritja; Cathey, Tommy; Transue, Thomas; Smith, Doris; Vail, James; Frame, Alicia; Mosher, Shad; Cohen Hubal, Elaine A.; Richard, Ann M.

2012-01-01

Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built using open source tools and is freely available to download. This review describes the organization of the data repository and provides selected examples of use cases. PMID:22408426

Aggregating data for computational toxicology applications: The U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System.

PubMed

Judson, Richard S; Martin, Matthew T; Egeghy, Peter; Gangwal, Sumit; Reif, David M; Kothiya, Parth; Wolf, Maritja; Cathey, Tommy; Transue, Thomas; Smith, Doris; Vail, James; Frame, Alicia; Mosher, Shad; Cohen Hubal, Elaine A; Richard, Ann M

2012-01-01

Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built using open source tools and is freely available to download. This review describes the organization of the data repository and provides selected examples of use cases.

A Computer Oriented Scheme for Coding Chemicals in the Field of Biomedicine.

ERIC Educational Resources Information Center

Bobka, Marilyn E.; Subramaniam, J.B.

The chemical coding scheme of the Medical Coding Scheme (MCS), developed for use in the Comparative Systems Laboratory (CSL), is outlined and evaluated in this report. The chemical coding scheme provides a classification scheme and encoding method for drugs and chemical terms. Using the scheme complicated chemical structures may be expressed…

2D-3D MIGRATION AND CONFORMATIONAL MULTIPLICATION OF CHEMICALS IN LARGE CHEMICAL INVENTORIES

EPA Science Inventory

Chemical interactions are three-dimensional (3D) in nature and require modeling chemicals as 3D entities. In turn, using 3D models of chemicals leads to the realization that a single 2D structure can have hundreds of different conformations, and the electronic properties of these...

Contamination and restoration of groundwater aquifers.

PubMed Central

Piver, W T

1993-01-01

Humans are exposed to chemicals in contaminated groundwaters that are used as sources of drinking water. Chemicals contaminate groundwater resources as a result of waste disposal methods for toxic chemicals, overuse of agricultural chemicals, and leakage of chemicals into the subsurface from buried tanks used to hold fluid chemicals and fuels. In the process, both the solid portions of the subsurface and the groundwaters that flow through these porous structures have become contaminated. Restoring these aquifers and minimizing human exposure to the parent chemicals and their degradation products will require the identification of suitable biomarkers of human exposure; better understandings of how exposure can be related to disease outcome; better understandings of mechanisms of transport of pollutants in the heterogeneous structures of the subsurface; and field testing and evaluation of methods proposed to restore and cleanup contaminated aquifers. In this review, progress in these many different but related activities is presented. PMID:8354172

[Studies on chemical constituents from leaves and stems of Aconitum coreanum].

PubMed

Li, Yan; Liang, Shuai

2009-05-01

To study the chemical constituents in the leaves and stems of Aconitum coreanum. The isolation and purification of chemical constituents were carried out on silica gel and polyamide column chromatographic. Their structures were identified by physico-chemical properties and spectral analysis. Five compounds were obtained and their structures were identified as guan-fu base I (1), guan-fu base R (2), beta-sitosterol (3), D-mannitol (4), daucosterol (5). Compound 2 is a new compound. Compounds 1 and 3, 4 are isolated from the leaves and stems of A. coreanum for the first time.

Application of kernel functions for accurate similarity search in large chemical databases.

PubMed

Wang, Xiaohong; Huan, Jun; Smalter, Aaron; Lushington, Gerald H

2010-04-29

Similarity search in chemical structure databases is an important problem with many applications in chemical genomics, drug design, and efficient chemical probe screening among others. It is widely believed that structure based methods provide an efficient way to do the query. Recently various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models, graph kernel functions can not be applied to large chemical compound database due to the high computational complexity and the difficulties in indexing similarity search for large databases. To bridge graph kernel function and similarity search in chemical databases, we applied a novel kernel-based similarity measurement, developed in our team, to measure similarity of graph represented chemicals. In our method, we utilize a hash table to support new graph kernel function definition, efficient storage and fast search. We have applied our method, named G-hash, to large chemical databases. Our results show that the G-hash method achieves state-of-the-art performance for k-nearest neighbor (k-NN) classification. Moreover, the similarity measurement and the index structure is scalable to large chemical databases with smaller indexing size, and faster query processing time as compared to state-of-the-art indexing methods such as Daylight fingerprints, C-tree and GraphGrep. Efficient similarity query processing method for large chemical databases is challenging since we need to balance running time efficiency and similarity search accuracy. Our previous similarity search method, G-hash, provides a new way to perform similarity search in chemical databases. Experimental study validates the utility of G-hash in chemical databases.

CHEMICAL STRUCTURE INDEXING OF TOXICITY DATA ON THE INTERNET: MOVING TOWARDS A FLAT WORLD

EPA Science Inventory

Standardized chemical structure annotation of public toxicity databases and information resources is playing an increasingly important role in the 'flattening' and integration of diverse sets of biological activity data on the Internet. This review discusses public initiatives th...

PREDICTION OF CHEMICAL REACTIVITY PARAMETERS AND PHYSICAL PROPERTIES OF ORGANIC COMPOUNDS FROM MOLECULAR STRUCTURE USING SPARC

EPA Science Inventory

The computer program SPARC (SPARC Performs Automated Reasoning in Chemistry) has been under development for several years to estimate physical properties and chemical reactivity parameters of organic compounds strictly from molecular structure. SPARC uses computational algorithms...

20180312 - Structure-based QSAR Models to Predict Systemic Toxicity Points of Departure (SOT)

EPA Science Inventory

Human health risk assessment associated with environmental chemical exposure is limited by the tens of thousands of chemicals with little or no experimental in vivo toxicity data. Data gap filling techniques, such as quantitative structure activity relationship (QSAR) models base...

Chemical Structure and Surface Modification of Dendritic Nanomaterials Tailored for Therapeutic and Diagnostic Applications.

PubMed

Myung, Ja Hye; Hsu, Hao-Jui; Bugno, Jason; Tam, Kevin A; Hong, Seungpyo

2017-01-01

Dendritic nanomaterials have attracted a great deal of scientific interest due to their high capacity for multifunctionalization and potential in various biomedical applications, such as drug/gene delivery and diagnostic systems. Depending on the molecular structure and starting monomers, several different types of dendrimers have been developed, including poly(amidoamine) (PAMAM), poly(propylenimine) (PPI), and poly(L-lysine) (PLL) dendrimers, in addition to modified dendritic nanomaterials, such as Janus dendrimers and dendritic block copolymers. The chemical structure and surface modification of dendritic nanomaterials have been found to play a critical role in governing their biological behaviors. In this review, we present a comprehensive overview focusing on the synthesis and chemical structures of dendrimers and modified dendritic nanomaterials that are currently being investigated for drug delivery, gene delivery, and diagnostic applications. In addition, the impact of chemical surface modification and functionalization to the dendritic nanomaterials on their therapeutic and diagnostic applications are highlighted. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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.

Structure alerts for carcinogenicity, and the Salmonella assay system: a novel insight through the chemical relational databases technology.

PubMed

Benigni, Romualdo; Bossa, Cecilia

2008-01-01

In the past decades, chemical carcinogenicity has been the object of mechanistic studies that have been translated into valuable experimental (e.g., the Salmonella assays system) and theoretical (e.g., compilations of structure alerts for chemical carcinogenicity) models. These findings remain the basis of the science and regulation of mutagens and carcinogens. Recent advances in the organization and treatment of large databases consisting of both biological and chemical information nowadays allows for a much easier and more refined view of data. This paper reviews recent analyses on the predictive performance of various lists of structure alerts, including a new compilation of alerts that combines previous work in an optimized form for computer implementation. The revised compilation is part of the Toxtree 1.50 software (freely available from the European Chemicals Bureau website). The use of structural alerts for the chemical biological profiling of a large database of Salmonella mutagenicity results is also reported. Together with being a repository of the science on the chemical biological interactions at the basis of chemical carcinogenicity, the SAs have a crucial role in practical applications for risk assessment, for: (a) description of sets of chemicals; (b) preliminary hazard characterization; (c) formation of categories for e.g., regulatory purposes; (d) generation of subsets of congeneric chemicals to be analyzed subsequently with QSAR methods; (e) priority setting. An important aspect of SAs as predictive toxicity tools is that they derive directly from mechanistic knowledge. The crucial role of mechanistic knowledge in the process of applying (Q)SAR considerations to risk assessment should be strongly emphasized. Mechanistic knowledge provides a ground for interaction and dialogue between model developers, toxicologists and regulators, and permits the integration of the (Q)SAR results into a wider regulatory framework, where different types of evidence and data concur or complement each other as a basis for making decisions and taking actions.

The Molecular Structure of Penicillin

NASA Astrophysics Data System (ADS)

Bentley, Ronald

2004-10-01

The chemical structure of penicillin was determined between 1942 and 1945 under conditions of secrecy established by the U.S. and U.K. governments. The evidence was not published in the open literature but as a monograph. This complex volume does not present a structure proof that can be readily comprehended by a student. In this article, a basic structural proof for the penicillin molecule is provided, emphasizing the chemical work. The stereochemistry of penicillin is also described, and various rearrangements are considered on the basis of the accepted β-lactam structure.

Effects of SPORL and dilute acid pretreatment on substrate morphology, cell physical and chemical wall structures, and subsequent enzymatic hydrolysis of lodgepole pine

Treesearch

Xinping Li; Xiaolin Luo; Kecheng Li; J.Y. Zhu; J. Dennis Fougere; Kimberley Clarke

2012-01-01

The effects of pretreatment by dilute acid and sulfite pretreatment to overcome recalcitrance of lignocellulose (SPORL) on substrate morphology, cell wall physical and chemical structures, along with the subsequent enzymatic hydrolysis of lodgepole pine substrate were investigated. FE-SEM and TEM images of substrate structural morphological changes showed that SPORL...

Sampling the structure and chemical order in assemblies of ferromagnetic nanoparticles by nuclear magnetic resonance

PubMed Central

Liu, Yuefeng; Luo, Jingjie; Shin, Yooleemi; Moldovan, Simona; Ersen, Ovidiu; Hébraud, Anne; Schlatter, Guy; Pham-Huu, Cuong; Meny, Christian

2016-01-01

Assemblies of nanoparticles are studied in many research fields from physics to medicine. However, as it is often difficult to produce mono-dispersed particles, investigating the key parameters enhancing their efficiency is blurred by wide size distributions. Indeed, near-field methods analyse a part of the sample that might not be representative of the full size distribution and macroscopic methods give average information including all particle sizes. Here, we introduce temperature differential ferromagnetic nuclear resonance spectra that allow sampling the crystallographic structure, the chemical composition and the chemical order of non-interacting ferromagnetic nanoparticles for specific size ranges within their size distribution. The method is applied to cobalt nanoparticles for catalysis and allows extracting the size effect from the crystallographic structure effect on their catalytic activity. It also allows sampling of the chemical composition and chemical order within the size distribution of alloyed nanoparticles and can thus be useful in many research fields. PMID:27156575

Chemical Speciation and Bond Lengths of Organic Solutes by Core-Level Spectroscopy: pH and Solvent Influence on p-Aminobenzoic Acid.

PubMed

Stevens, Joanna S; Gainar, Adrian; Suljoti, Edlira; Xiao, Jie; Golnak, Ronny; Aziz, Emad F; Schroeder, Sven L M

2015-05-04

Through X-ray absorption and emission spectroscopies, the chemical, electronic and structural properties of organic species in solution can be observed. Near-edge X-ray absorption fine structure (NEXAFS) and resonant inelastic X-ray scattering (RIXS) measurements at the nitrogen K-edge of para-aminobenzoic acid reveal both pH- and solvent-dependent variations in the ionisation potential (IP), 1s→π* resonances and HOMO-LUMO gap. These changes unequivocally identify the chemical species (neutral, cationic or anionic) present in solution. It is shown how this incisive chemical state sensitivity is further enhanced by the possibility of quantitative bond length determination, based on the analysis of chemical shifts in IPs and σ* shape resonances in the NEXAFS spectra. This provides experimental access to detecting even minor variations in the molecular structure of solutes in solution, thereby providing an avenue to examining computational predictions of solute properties and solute-solvent interactions. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Role of the nanocrystallinity on the chemical ordering of Co(x)Pt(100-x) nanocrystals synthesized by wet chemistry.

PubMed

Kameche, Farid; Ngo, Anh-Tu; Salzemann, Caroline; Cordeiro, Marco; Sutter, Eli; Petit, Christophe

2015-11-14

Co(x)Pt(100-x) nanoalloys have been synthesized by two different chemical processes either at high or at low temperature. Their physical properties and the order/disorder phase transition induced by annealing have been investigated depending on the route of synthesis. It is demonstrated that the chemical synthesis at high temperature allows stabilization of the fcc structure of the native nanoalloys while the soft chemical approach yields mainly poly or non crystalline structure. As a result the approach of the order/disorder phase transition is strongly modified as observed by high-resolution transmission electron microscopy (HR-TEM) studies performed during in situ annealing of the different nanoalloys. The control of the nanocrystallinity leads to significant decrease in the chemical ordering temperature as the ordered structure is observed at temperatures as low as 420 °C. This in turn preserves the individual nanocrystals and prevents their coalescence usually observed during the annealing necessary for the transition to an ordered phase.

Chemical Speciation and Bond Lengths of Organic Solutes by Core-Level Spectroscopy: pH and Solvent Influence on p -Aminobenzoic Acid

DOE PAGES

Stevens, Joanna S.; Gainar, Adrian; Suljoti, Edlira; ...

2015-03-18

Through X-ray absorption and emission spectroscopies, the chemical, electronic and structural properties of organic species in solution can be observed. Near-edge X-ray absorption fine structure (NEXAFS) and resonant inelastic X-ray scattering (RIXS) measurements at the nitrogen K-edge of para-aminobenzoic acid reveal both pH- and solvent-dependent variations in the ionisation potential (IP), 1s→π* resonances and HOMO–LUMO gap. These changes unequivocally identify the chemical species (neutral, cationic or anionic) present in solution. It is shown how this incisive chemical state sensitivity is further enhanced by the possibility of quantitative bond length determination, based on the analysis of chemical shifts in IPs andmore » σ* shape resonances in the NEXAFS spectra. Finally, this provides experimental access to detecting even minor variations in the molecular structure of solutes in solution, thereby providing an avenue to examining computational predictions of solute properties and solute–solvent interactions.« less

Study of Structural Morphology of Hemp Fiber from the Micro to the Nanoscale

NASA Astrophysics Data System (ADS)

Wang, Bei; Sain, Mohini; Oksman, Kristiina

2007-03-01

The focus of this work has been to study how high pressure defibrillation and chemical purification affect the hemp fiber morphology from micro to nanoscale. Microscopy techniques, chemical analysis and X-ray diffraction were used to study the structure and properties of the prepared micro and nanofibers. Microscopy studies showed that the used individualization processes lead to a unique morphology of interconnected web-like structure of hemp fibers. The nanofibers are bundles of cellulose fibers of widths ranging between 30 and 100 nm and estimated lengths of several micrometers. The chemical analysis showed that selective chemical treatments increased the α-cellulose content of hemp nanofibers from 75 to 94%. Fourier transform infrared spectroscopy (FTIR) study showed that the pectins were partially removed during the individualization treatments. X-ray analysis showed that the relative crystallinity of the studied fibers increased after each stage of chemical and mechanical treatments. It was also observed that the hemp nanofibers had an increased crystallinity of 71 from 57% of untreated hemp fibers.

CSI 3.0: a web server for identifying secondary and super-secondary structure in proteins using NMR chemical shifts

PubMed Central

Hafsa, Noor E.; Arndt, David; Wishart, David S.

2015-01-01

The Chemical Shift Index or CSI 3.0 (http://csi3.wishartlab.com) is a web server designed to accurately identify the location of secondary and super-secondary structures in protein chains using only nuclear magnetic resonance (NMR) backbone chemical shifts and their corresponding protein sequence data. Unlike earlier versions of CSI, which only identified three types of secondary structure (helix, β-strand and coil), CSI 3.0 now identifies total of 11 types of secondary and super-secondary structures, including helices, β-strands, coil regions, five common β-turns (type I, II, I′, II′ and VIII), β hairpins as well as interior and edge β-strands. CSI 3.0 accepts experimental NMR chemical shift data in multiple formats (NMR Star 2.1, NMR Star 3.1 and SHIFTY) and generates colorful CSI plots (bar graphs) and secondary/super-secondary structure assignments. The output can be readily used as constraints for structure determination and refinement or the images may be used for presentations and publications. CSI 3.0 uses a pipeline of several well-tested, previously published programs to identify the secondary and super-secondary structures in protein chains. Comparisons with secondary and super-secondary structure assignments made via standard coordinate analysis programs such as DSSP, STRIDE and VADAR on high-resolution protein structures solved by X-ray and NMR show >90% agreement between those made with CSI 3.0. PMID:25979265

Correlation of chemical shifts predicted by molecular dynamics simulations for partially disordered proteins.

PubMed

Karp, Jerome M; Eryilmaz, Ertan; Erylimaz, Ertan; Cowburn, David

2015-01-01

There has been a longstanding interest in being able to accurately predict NMR chemical shifts from structural data. Recent studies have focused on using molecular dynamics (MD) simulation data as input for improved prediction. Here we examine the accuracy of chemical shift prediction for intein systems, which have regions of intrinsic disorder. We find that using MD simulation data as input for chemical shift prediction does not consistently improve prediction accuracy over use of a static X-ray crystal structure. This appears to result from the complex conformational ensemble of the disordered protein segments. We show that using accelerated molecular dynamics (aMD) simulations improves chemical shift prediction, suggesting that methods which better sample the conformational ensemble like aMD are more appropriate tools for use in chemical shift prediction for proteins with disordered regions. Moreover, our study suggests that data accurately reflecting protein dynamics must be used as input for chemical shift prediction in order to correctly predict chemical shifts in systems with disorder.

Polymeric binder for explosives

NASA Technical Reports Server (NTRS)

Bissell, E. R.

1972-01-01

Chemical reaction for producing a polymer which can be mixed with explosives to produce a rigid material is discussed. Physical and chemical properties of polymers are described and chemical structure of the polymer is illustrated.

Lessons from an evolving rRNA: 16S and 23S rRNA structures from a comparative perspective

NASA Technical Reports Server (NTRS)

Gutell, R. R.; Larsen, N.; Woese, C. R.

1994-01-01

The 16S and 23S rRNA higher-order structures inferred from comparative analysis are now quite refined. The models presented here differ from their immediate predecessors only in minor detail. Thus, it is safe to assert that all of the standard secondary-structure elements in (prokaryotic) rRNAs have been identified, with approximately 90% of the individual base pairs in each molecule having independent comparative support, and that at least some of the tertiary interactions have been revealed. It is interesting to compare the rRNAs in this respect with tRNA, whose higher-order structure is known in detail from its crystal structure (36) (Table 2). It can be seen that rRNAs have as great a fraction of their sequence in established secondary-structure elements as does tRNA. However, the fact that the former show a much lower fraction of identified tertiary interactions and a greater fraction of unpaired nucleotides than the latter implies that many of the rRNA tertiary interactions remain to be located. (Alternatively, the ribosome might involve protein-rRNA rather than intramolecular rRNA interactions to stabilize three-dimensional structure.) Experimental studies on rRNA are consistent to a first approximation with the structures proposed here, confirming the basic assumption of comparative analysis, i.e., that bases whose compositions strictly covary are physically interacting. In the exhaustive study of Moazed et al. (45) on protection of the bases in the small-subunit rRNA against chemical modification, the vast majority of bases inferred to pair by covariation are found to be protected from chemical modification, both in isolated small-subunit rRNA and in the 30S subunit. The majority of the tertiary interactions are reflected in the chemical protection data as well (45). On the other hand, many of the bases not shown as paired in Fig. 1 are accessible to chemical attack (45). However, in this case a sizeable fraction of them are also protected against chemical modification (in the isolated rRNA), which suggests that considerable higher-order structure remains to be found (although all of it may not involve base-base interactions and so may not be detectable by comparative analysis). The agreement between the higher-order structure of the small-subunit rRNA and protection against chemical modification is not perfect, however; some bases shown to covary canonically are accessible to chemical modification (45).(ABSTRACT TRUNCATED AT 400 WORDS).

76 FR 56156 - Application(s) for Duty-Free Entry of Scientific Instruments

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-12

... materials for energy production. The experiments will involve structural and chemical analyses of materials... experiments will involve structural and chemical analyses of materials on the electron based nanometer scale... tissues, viruses, and bacteria, to determine the morphology of multiphase materials, determine the...

RULES FOR DISTINGUISHING TOXICANTS THAT CAUSE TYPE (I) AND TYPE (II) NARCOSIS SYNDROMES

EPA Science Inventory

Narcosis is a non-specific reversible state of arrested activity of protoplasmic structures caused by a wide variety of organic chemicals. he vast majority of industrial organic chemicals can be characterized by a baseline structure-toxicity relationship as developed for diverse ...

Using Concept Mapping to Uncover Students' Knowledge Structures of Chemical Bonding Concepts

ERIC Educational Resources Information Center

Burrows, Nikita L.; Mooring, Suazette Reid

2015-01-01

General chemistry is the first undergraduate course in which students further develop their understanding of fundamental chemical concepts. Many of these fundamental topics highlight the numerous conceptual interconnections present in chemistry. However, many students possess incoherent knowledge structures regarding these topics. Therefore,…

Effect of chemical structure on film-forming properties of seed oils

USDA-ARS?s Scientific Manuscript database

The film thickness of seven seed oils and two petroleum-based oils of varying chemical structures, was investigated by the method of optical interferometry under pure rolling conditions, and various combinations of entrainment speed (u), load, and temperature. The measured film thickness (h measured...

Development of a category approach to predict the testicular toxicity of chemical substances structurally related to ethylene glycol methyl ether.

PubMed

Yamada, Takashi; Tanaka, Yushiro; Hasegawa, Ryuichi; Sakuratani, Yuki; Yamazoe, Yasushi; Ono, Atsushi; Hirose, Akihiko; Hayashi, Makoto

2014-12-01

We propose a category approach to assessing the testicular toxicity of chemicals with a similar structure to ethylene glycol methyl ether (EGME). Based on toxicity information for EGME and related chemicals and accompanied by adverse outcome pathway information on the testicular toxicity of EGME, this category was defined as chemicals that are metabolized to methoxy- or ethoxyacetic acid, a substance responsible for testicular toxicity. A Japanese chemical inventory was screened using the Hazard Evaluation Support System, which we have developed to support a category approach for predicting the repeated-dose toxicity of chemical substances. Quantitative metabolic information on the related chemicals was then considered, and seventeen chemicals were finally obtained from the inventory as a shortlist for the category. Available data in the literature shows that chemicals for which information is available on the metabolic formation of EGME, ethylene glycol ethyl ether, methoxy- or ethoxyacetic acid do in fact possess testicular toxicity, suggesting that testicular toxicity is a concern, due to metabolic activation, for the remaining chemicals. Our results clearly demonstrate practical utility of AOP-based category approach for predicting repeated-dose toxicity of chemicals. Copyright © 2014 Elsevier Inc. All rights reserved.

Conformational analysis of α-helical polypeptide included L-proline residue by high-resolution solid-state NMR measurement and quantum chemical calculation

NASA Astrophysics Data System (ADS)

Souma, Hiroyuki; Shoji, Akira; Kurosu, Hiromichi

2008-10-01

We challenged the problem about the stabilization mechanism of an α-helix formation for polypeptides containing L-proline (Pro) residue. We computed the optimized structure of α-helical poly( L-alanine) molecules including a Pro residue, H-(Ala) 8-Pro-(Ala) 9-OH, based on the molecular orbital calculation with density functional theory, B3LYP/6-31G(d) and the 13C and 15N chemical shift values based on the GIAO-CHF method with B3LYP/6-311G(d,p), respectively. It was found that two kinds of optimized structures, 'Bent structure' and 'Included α-helix structure', were preferred structures in H-(Ala) 8-Pro-(Ala) 9-OH. In addition, based on the precise 13C and 15N chemical shift data of the simple model, we successfully analyzed the secondary structure of well-defined synthetic polypeptide H-(Phe-Leu-Ala) 3-Phe C-Pro-Ala N-(Phe-Leu-Ala) 2-OH (FLA-11P), the secondary structure of which was proven to the 'Included α-helix structure'.

Multimetallic nanoparticle catalysts with enhanced electrooxidation

DOEpatents

Sun, Shouheng; Zhang, Sen; Zhu, Huiyuan; Guo, Shaojun

2015-07-28

A new structure-control strategy to optimize nanoparticle catalysis is provided. The presence of Au in FePtAu facilitates FePt structure transformation from chemically disordered face centered cubic (fcc) structure to chemically ordered face centered tetragonal (fct) structure, and further promotes formic acid oxidation reaction (FAOR). The fct-FePtAu nanoparticles show high CO poisoning resistance, achieve mass activity as high as about 2810 mA/mg Pt, and retain greater than 90% activity after a 13 hour stability test.

Quantum-mechanics-derived 13Cα chemical shift server (CheShift) for protein structure validation

PubMed Central

Vila, Jorge A.; Arnautova, Yelena A.; Martin, Osvaldo A.; Scheraga, Harold A.

2009-01-01

A server (CheShift) has been developed to predict 13Cα chemical shifts of protein structures. It is based on the generation of 696,916 conformations as a function of the φ, ψ, ω, χ1 and χ2 torsional angles for all 20 naturally occurring amino acids. Their 13Cα chemical shifts were computed at the DFT level of theory with a small basis set and extrapolated, with an empirically-determined linear regression formula, to reproduce the values obtained with a larger basis set. Analysis of the accuracy and sensitivity of the CheShift predictions, in terms of both the correlation coefficient R and the conformational-averaged rmsd between the observed and predicted 13Cα chemical shifts, was carried out for 3 sets of conformations: (i) 36 x-ray-derived protein structures solved at 2.3 Å or better resolution, for which sets of 13Cα chemical shifts were available; (ii) 15 pairs of x-ray and NMR-derived sets of protein conformations; and (iii) a set of decoys for 3 proteins showing an rmsd with respect to the x-ray structure from which they were derived of up to 3 Å. Comparative analysis carried out with 4 popular servers, namely SHIFTS, SHIFTX, SPARTA, and PROSHIFT, for these 3 sets of conformations demonstrated that CheShift is the most sensitive server with which to detect subtle differences between protein models and, hence, to validate protein structures determined by either x-ray or NMR methods, if the observed 13Cα chemical shifts are available. CheShift is available as a web server. PMID:19805131

Ab initio/GIAO-CCSD(T) study of structures, energies, and 13C NMR chemical shifts of C4H7(+) and C5H9(+) ions: relative stability and dynamic aspects of the cyclopropylcarbinyl vs bicyclobutonium ions.

PubMed

Olah, George A; Surya Prakash, G K; Rasul, Golam

2008-07-16

The structures and energies of the carbocations C 4H 7 (+) and C 5H 9 (+) were calculated using the ab initio method. The (13)C NMR chemical shifts of the carbocations were calculated using the GIAO-CCSD(T) method. The pisigma-delocalized bisected cyclopropylcarbinyl cation, 1 and nonclassical bicyclobutonium ion, 2 were found to be the minima for C 4H 7 (+) at the MP2/cc-pVTZ level. At the MP4(SDTQ)/cc-pVTZ//MP2/cc-pVTZ + ZPE level the structure 2 is 0.4 kcal/mol more stable than the structure 1. The (13)C NMR chemical shifts of 1 and 2 were calculated by the GIAO-CCSD(T) method. Based on relative energies and (13)C NMR chemical shift calculations, an equilibrium involving the 1 and 2 in superacid solutions is most likely responsible for the experimentally observed (13)C NMR chemical shifts, with the latter as the predominant equilibrating species. The alpha-methylcyclopropylcarbinyl cation, 4, and nonclassical bicyclobutonium ion, 5, were found to be the minima for C 5H 9 (+) at the MP2/cc-pVTZ level. At the MP4(SDTQ)/cc-pVTZ//MP2/cc-pVTZ + ZPE level ion 5 is 5.9 kcal/mol more stable than the structure 4. The calculated (13)C NMR chemical shifts of 5 agree rather well with the experimental values of C 5H 9 (+).

Counteracting chemical chaperone effects on the single-molecule α-synuclein structural landscape.

PubMed

Ferreon, Allan Chris M; Moosa, Mahdi Muhammad; Gambin, Yann; Deniz, Ashok A

2012-10-30

Protein structure and function depend on a close interplay between intrinsic folding energy landscapes and the chemistry of the protein environment. Osmolytes are small-molecule compounds that can act as chemical chaperones by altering the environment in a cellular context. Despite their importance, detailed studies on the role of these chemical chaperones in modulating structure and dimensions of intrinsically disordered proteins have been limited. Here, we used single-molecule Förster resonance energy transfer to test the counteraction hypothesis of counterbalancing effects between the protecting osmolyte trimethylamine-N-oxide (TMAO) and denaturing osmolyte urea for the case of α-synuclein, a Parkinson's disease-linked protein whose monomer exhibits significant disorder. The single-molecule experiments, which avoid complications from protein aggregation, do not exhibit clear solvent-induced cooperative protein transitions for these osmolytes, unlike results from previous studies on globular proteins. Our data demonstrate the ability of TMAO and urea to shift α-synuclein structures towards either more compact or expanded average dimensions. Strikingly, the experiments directly reveal that a 21 [urea][TMAO] ratio has a net neutral effect on the protein's dimensions, a result that holds regardless of the absolute osmolyte concentrations. Our findings shed light on a surprisingly simple aspect of the interplay between urea and TMAO on α-synuclein in the context of intrinsically disordered proteins, with potential implications for the biological roles of such chemical chaperones. The results also highlight the strengths of single-molecule experiments in directly probing the chemical physics of protein structure and disorder in more chemically complex environments.

Counteracting chemical chaperone effects on the single-molecule α-synuclein structural landscape

PubMed Central

Ferreon, Allan Chris M.; Moosa, Mahdi Muhammad; Deniz, Ashok A.

2012-01-01

Protein structure and function depend on a close interplay between intrinsic folding energy landscapes and the chemistry of the protein environment. Osmolytes are small-molecule compounds that can act as chemical chaperones by altering the environment in a cellular context. Despite their importance, detailed studies on the role of these chemical chaperones in modulating structure and dimensions of intrinsically disordered proteins have been limited. Here, we used single-molecule Förster resonance energy transfer to test the counteraction hypothesis of counterbalancing effects between the protecting osmolyte trimethylamine-N-oxide (TMAO) and denaturing osmolyte urea for the case of α-synuclein, a Parkinson’s disease-linked protein whose monomer exhibits significant disorder. The single-molecule experiments, which avoid complications from protein aggregation, do not exhibit clear solvent-induced cooperative protein transitions for these osmolytes, unlike results from previous studies on globular proteins. Our data demonstrate the ability of TMAO and urea to shift α-synuclein structures towards either more compact or expanded average dimensions. Strikingly, the experiments directly reveal that a 2∶1 [urea]∶[TMAO] ratio has a net neutral effect on the protein’s dimensions, a result that holds regardless of the absolute osmolyte concentrations. Our findings shed light on a surprisingly simple aspect of the interplay between urea and TMAO on α-synuclein in the context of intrinsically disordered proteins, with potential implications for the biological roles of such chemical chaperones. The results also highlight the strengths of single-molecule experiments in directly probing the chemical physics of protein structure and disorder in more chemically complex environments. PMID:22826265

Chemical depth profiles of the GaAs/native oxide interface

NASA Technical Reports Server (NTRS)

Grunthaner, P. J.; Vasquez, R. P.; Grunthaner, F. J.

1980-01-01

The final-state oxidation products and their distribution in thin native oxides (30-40 A) on GaAs have been studied using X-ray photoelectron spectroscopy in conjunction with chemical depth profiling. Extended room-temperature-oxidation conditions have been chosen to allow the native oxide to attain its equilibrium composition and structure. The work emphasizes the use of chemical depth-profiling methods which make it possible to examine the variation in chemical reactivity of the oxide structure. A minimum of two distinct regions of Ga2O3 with differing chemical reactivity is observed. Chemical shift data indicate the presence of As2O3 in the oxide together with an elemental As overlayer at the interface. A change in relative charge transfer between oxygen and both arsenic and gallium-oxide species is observed in the region of the interface.

A mechanism-mediated model for carcinogenicity: Model content and prediction of the outcome of rodent carcinogenicity bioassays currently being conducted on 25 organic chemicals

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

Purdy, R.

A hierarchical model consisting of quantitative structure-activity relationships based mainly on chemical reactivity was developed to predict the carcinogenicity of organic chemicals to rodents. The model is comprised of quantitative structure-activity relationships, QSARs based on hypothesized mechanisms of action, metabolism, and partitioning. Predictors included octanol/water partition coefficient, molecular size, atomic partial charge, bond angle strain, atomic acceptor delocalizibility, atomic radical superdelocalizibility, the lowest unoccupied molecular orbital (LUMO) energy of hypothesized intermediate nitrenium ion of primary aromatic amines, difference in charge of ionized and unionized carbon-chlorine bonds, substituent size and pattern on polynuclear aromatic hydrocarbons, the distance between lone electron pairsmore » over a rigid structure, and the presence of functionalities such as nitroso and hydrazine. The model correctly classified 96% of the carcinogens in the training set of 306 chemicals, and 90% of the carcinogens in the test set of 301 chemicals. The test set by chance contained 84% of the positive thiocontaining chemicals. A QSAR for these chemicals was developed. This posttest set modified model correctly predicted 94% of the carcinogens in the test set. This model was used to predict the carcinogenicity of the 25 organic chemicals the U.S. National Toxicology Program was testing at the writing of this article. 12 refs., 3 tabs.« less

Feasibility Analysis of Incorporating In-Vitro Toxicokinetic Data ...

EPA Pesticide Factsheets

The underlying principle of read-across is that biological activity is a function of physical and structural properties of chemicals. Analogs are typically identified on the basis of structural similarity and subsequently evaluated for their use in read-across on the basis of their bioavailability, reactivity and metabolic similarity. While the concept of similarity is the major tenet in grouping chemicals for read-across, a critical consideration is to evaluate if structural differences significantly impact toxicological activity. This is a key source of uncertainty in read-across predictions. We hypothesize that inclusion of toxicokinetic (TK) information will reduce the uncertainty in read-across predictions. TK information can help substantiate whether chemicals within a category have similar ADME properties and, hence, increase the likelihood of exhibiting similar toxicological properties. This current case study is part of a larger study aimed at performing a systematic assessment of the extent to which in-vitro TK data can obviate in-vivo TK data, while maintaining or increasing scientific confidence in read-across predictions. The analysis relied on a dataset of ~7k chemicals with predicted exposure data (chemical inventory), of which 819 chemicals had rat and/or human in-vitro TK data (analog inventory), and 33 chemicals had rat in-vivo TK data (target inventory). The set of chemicals with human in vitro TK data was investigated to determine whether str

Use of 13Cα Chemical-Shifts in Protein Structure Determination

PubMed Central

Vila, Jorge A.; Ripoll, Daniel R.; Scheraga, Harold A.

2008-01-01

A physics-based method, aimed at determining protein structures by using NOE-derived distances together with observed and computed 13C chemical shifts, is proposed. The approach makes use of 13Cα chemical shifts, computed at the density functional level of theory, to obtain torsional constraints for all backbone and side-chain torsional angles without making a priori use of the occupancy of any region of the Ramachandran map by the amino acid residues. The torsional constraints are not fixed but are changed dynamically in each step of the procedure, following an iterative self-consistent approach intended to identify a set of conformations for which the computed 13Cα chemical shifts match the experimental ones. A test is carried out on a 76-amino acid all-α-helical protein, namely the B. Subtilis acyl carrier protein. It is shown that, starting from randomly generated conformations, the final protein models are more accurate than an existing NMR-derived structure model of this protein, in terms of both the agreement between predicted and observed 13Cα chemical shifts and some stereochemical quality indicators, and of similar accuracy as one of the protein models solved at a high level of resolution. The results provide evidence that this methodology can be used not only for structure determination but also for additional protein structure refinement of NMR-derived models deposited in the Protein Data Bank. PMID:17516673

Predictive Modeling of Chemical Hazard by Integrating Numerical Descriptors of Chemical Structures and Short-term Toxicity Assay Data

PubMed Central

Rusyn, Ivan; Sedykh, Alexander; Guyton, Kathryn Z.; Tropsha, Alexander

2012-01-01

Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR–like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage. PMID:22387746

Biochemical Activities of 320 ToxCast Chemicals Evaluated Across 239 Functional Targets

EPA Science Inventory

EPA’s ToxCast research program is profiling chemical bioactivity in order to generate predictive signatures of toxicity. The present study evaluated 320 chemicals across 239 biochemical assays. ToxCast phase I chemicals include 309 unique structures, most of which are pesticide ...

Nature of the binding interaction for 50 structurally diverse chemicals with rat estrogen receptors

EPA Science Inventory

This study was conducted to characterize the estrogen receptor (ER)-binding affinities of 50 chemicals selected from among the high production volume chemicals under the U.S. EPA's (U.S. Environmental Protection Agency's) Toxic Substances Control Act inventory. The chemicals were...

Synergistic influence of Al, Ni, Bi and Sn addition to a zinc bath upon growth kinetics and the structure of coatings

NASA Astrophysics Data System (ADS)

Kania, H.; Liberski, P.

2012-05-01

In this article the authors have analysed the current knowledge about the influence of alloy additions used in galvanizing baths. The optimum concentration of Al, Ni, Bi and Sn addition has been established. Some tests have been conducted to determine the synergistic effect of the addition of AlNiBiSn to a zinc bath upon the structure and growth kinetics of coatings. The structure of the coatings obtained on steel with low silicon contents and on Sandelin steel as well as their chemical composition have been revealed. It has been established that the addition of AlNiBiSn helps to reduce excessive growth of coating on Sandelin steel. The chemical composition and the structure of the coating on Sandelin steel are similar to the chemical composition and structure obtained on steel with regular silicon contents.

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

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

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

2013-09-01

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

Anticorrelation between polar lattice instability and superconductivity in the Weyl semimetal candidate MoTe2

NASA Astrophysics Data System (ADS)

Takahashi, H.; Akiba, T.; Imura, K.; Shiino, T.; Deguchi, K.; Sato, N. K.; Sakai, H.; Bahramy, M. S.; Ishiwata, S.

2017-03-01

The relation between the polar structural instability and superconductivity in a Weyl semimetal candidate MoTe2 has been clarified by finely controlled physical and chemical pressure. The physical pressure as well as the chemical pressure, i.e., the Se substitution for Te, enhances the superconducting transition temperature Tc at around the critical pressure where the polar structure transition disappears. From the heat capacity and thermopower measurements, we ascribe the significant enhancement of Tc at the critical pressure to a subtle modification of the phonon dispersion or the semimetallic band structure upon the polar-to-nonpolar transition. On the other hand, the physical pressure, which strongly reduces the interlayer distance, is more effective on the suppression of the polar structural transition and the enhancement of Tc as compared with the chemical pressure, which emphasizes the importance of the interlayer coupling on the structural and superconducting instability in MoTe2.

Mechanical-chemical analyses and sub-chronic systemic toxicity of chemical treated organic bovine bone.

PubMed

Lee, Kwang-il; Lee, Jung-soo; Lee, Keun-soo; Jung, Hong-hee; Ahn, Chan-min; Kim, Young-sik; Shim, Young-bock; Jang, Ju-woong

2015-12-01

Sequentially chemical-treated bovine bone was not only evaluated by mechanical and chemical analyses but also implanted into the gluteal muscles of rats for 12 weeks to investigate potential local pathological effects and systemic toxicities. The test (chemical treated bone) and control (heat treated bone) materials were compared using scanning electron microscope (SEM), x-ray diffraction pattern, inductively coupled plasma analysis, and bending strength test. In the SEM images, the micro-porous structure of heat-treated bone was changed to sintered ceramic-like structure. The structure of bone mineral from test and control materials was analyzed as100% hydroxyapatite. The ratio of calcium (Ca) to potassium (P), the main inorganic elements, was same even though the Ca and P percentages of the control material was relatively higher than the test material. No death or critical symptoms arose from implantation of the test (chemical treated bone) and control (physiological saline) materials during 12 weeks. The implanted sites were macroscopically examined, with all the groups showing non-irritant results. Our results indicate that chemical processed bovine bone has a better mechanical property than the heat treated bone and the implantation of this material does not produce systemic or pathological toxicity. Copyright © 2015 Elsevier Inc. All rights reserved.

Self-regulating chemo-mechano-chemical systems

DOEpatents

Aizenberg, Joanna; He, Ximin; Aizenberg, Michael

2017-05-16

A chemo-mechano-chemical (C.sub.1-M-C.sub.2) system includes a base supporting an actuatable structure, said structure comprising a functionalized portion and being embedded in an environmentally responsive gel capable of volume change in response to an environmental stimulus; a first fluid layer disposed over the base and in contact with the actuatable structure, said first fluid layer comprising the environmentally responsive gel; and a second fluid layer in contact with the actuatable structure, wherein the layers are positioned such that the functionalized portion is in contact with the second layer in a first relaxed state and in contact with the first layer in a second actuated state and wherein the functionalized portion interacts with at least one of the layers to provide a chemical or physical response.

Structural and vibrational spectral investigations of melaminium maleate monohydrate by FTIR, FT-Raman and quantum chemical calculations.

PubMed

Arjunan, V; Kalaivani, M; Marchewka, M K; Mohan, S

2013-04-15

The structural investigations of the molecular complex of melamine with maleic acid, namely melaminium maleate monohydrate have been carried out by quantum chemical methods in addition to FTIR, FT-Raman and far-infrared spectral studies. The quantum chemical studies were performed with DFT (B3LYP) method using 6-31G(**), cc-pVDZ and 6-311++G(**) basis sets to determine the energy, structural and thermodynamic parameters of melaminium maleate monohydrate. The hydrogen atom from maleic acid was transferred to the melamine molecule giving the singly protonated melaminium cation. The ability of ions to form spontaneous three-dimensional structure through weak OH···O and NH···O hydrogen bonds shows notable vibrational effects. Copyright © 2013 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2017-01-01

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

Human sex hormone-binding globulin binding affinities of 125 structurally diverse chemicals and comparison with their binding to androgen receptor, estrogen receptor, and α-fetoprotein.

PubMed

Hong, Huixiao; Branham, William S; Ng, Hui Wen; Moland, Carrie L; Dial, Stacey L; Fang, Hong; Perkins, Roger; Sheehan, Daniel; Tong, Weida

2015-02-01

One endocrine disruption mechanism is through binding to nuclear receptors such as the androgen receptor (AR) and estrogen receptor (ER) in target cells. The concentration of a chemical in serum is important for its entry into the target cells to bind the receptors, which is regulated by the serum proteins. Human sex hormone-binding globulin (SHBG) is the major transport protein in serum that can bind androgens and estrogens and thus change a chemical's availability to enter the target cells. Sequestration of an androgen or estrogen in the serum can alter the chemical elicited AR- and ER-mediated responses. To better understand the chemical-induced endocrine activity, we developed a competitive binding assay using human pregnancy plasma and measured the binding to the human SHBG for 125 structurally diverse chemicals, most of which were known to bind AR and ER. Eighty seven chemicals were able to bind the human SHBG in the assay, whereas 38 chemicals were nonbinders. Binding data for human SHBG are compared with that for rat α-fetoprotein, ER and AR. Knowing the binding profiles between serum and nuclear receptors will improve assessment of a chemical's potential for endocrine disruption. The SHBG binding data reported here represent the largest data set of structurally diverse chemicals tested for human SHBG binding. Utilization of the SHBG binding data with AR and ER binding data could enable better evaluation of endocrine disrupting potential of chemicals through AR- and ER-mediated responses since sequestration in serum could be considered. Published by Oxford University Press on behalf of the Society of Toxicology 2014. This work is written by US Government employees and is in the public domain in the US.

Advances in QSPR/QSTR models of ionic liquids for the design of greener solvents of the future.

PubMed

Das, Rudra Narayan; Roy, Kunal

2013-02-01

In order to protect the life of all creatures living in the environment, the toxicity arising from various hazardous chemicals must be controlled. This imposes a serious responsibility on different chemical, pharmaceutical, and other biological industries to produce less harmful chemicals. Among various international initiatives on harmful aspects of chemicals, the 'Green Chemistry' ideology appears to be one of the most highlighted concepts that focus on the use of eco-friendly chemicals. Ionic liquids are a comparatively new addition to the huge garrison of chemical compounds released from the industry. Extensive research on ionic liquids in the past decade has shown them to be highly useful chemicals with a good degree of thermal and chemical stability, appreciable task specificity and minimal environmental release resulting in a notion of 'green chemical'. However, studies have also shown that ionic liquids are not intrinsically non-toxic agents and can pose severe degree of toxicity as well as the risk of bioaccumulation depending upon their structural components. Moreover, ionic liquids possess issues of waste generation during synthesis as well as separation problems. Predictive quantitative structure-activity relationship (QSAR) models constitute a rational opportunity to explore the structural attributes of ionic liquids towards various physicochemical and toxicological endpoints and thereby leading to the design of environmentally more benevolent analogues with higher process selectivity. Such studies on ionic liquids have been less extensive compared to other industrial chemicals. The present review attempts to summarize different QSAR studies performed on these chemicals and also highlights the safety, health and environmental issues along with the application specificity on the dogma of 'green chemistry'.

Phyto-fungicides: Structure activity relationships of the thymol derivatives against Rhizoctonia solani

USDA-ARS?s Scientific Manuscript database

Thymol, the key component of thyme oil and its derivatives were evaluated for their structure activity relationship as fungicide against Rhizoctonia solani. Since plant based chemicals are considered as “Generally Recognized as Safe” (GRAS) chemicals, there is a great potential to use phytochemicals...

The Chemical Structure and Acid Deterioration of Paper.

ERIC Educational Resources Information Center

Hollinger, William K., Jr.

1984-01-01

Describes the chemical structure of paper, including subatomic particles, atoms and molecules, and the forces that bond atoms into molecules, molecules into chains, chains into sheets, and sheets into layers. Acid is defined, and the deleterious role of acid in breaking the forces that bond atoms into molecules is detailed. (EJS)

Recent investigations of ergot alkaloids incorporated into plant and/or animal systems

USDA-ARS?s Scientific Manuscript database

Ergot alkaloids produced by fungi have a basic chemical structure but different chemical moieties at substituent sites resulting in various forms of alkaloids that are distinguishable from one another. Since the ergoline ring structure found in ergot alkaloids is similar to that of biogenic amines (...

Emerging Issues in Genotoxicity and Carcinogenicity with Implications for Structure Activity Analyses

EPA Science Inventory

In silico systems for the prediction of the ability of chemicals to induce carcinogenicity in rodents have generally relied on knowledge of the structure and physical-chemical features of the compound, as well as the mutagenic and genotoxic features of the compound in various bio...

Toxicity challenges in environmental chemicals: Prediction of human plasma protein binding through quantitative structure-activity relationship (QSAR) models

EPA Science Inventory

The present study explores the merit of utilizing available pharmaceutical data to construct a quantitative structure-activity relationship (QSAR) for prediction of the fraction of a chemical unbound to plasma protein (Fub) in environmentally relevant compounds. Independent model...

Protein Structure Determination from Pseudocontact Shifts Using ROSETTA

PubMed Central

Schmitz, Christophe; Vernon, Robert; Otting, Gottfried; Baker, David; Huber, Thomas

2013-01-01

Paramagnetic metal ions generate pseudocontact shifts (PCSs) in nuclear magnetic resonance spectra that are manifested as easily measurable changes in chemical shifts. Metals can be incorporated into proteins through metal binding tags, and PCS data constitute powerful long-range restraints on the positions of nuclear spins relative to the coordinate system of the magnetic susceptibility anisotropy tensor (Δχ-tensor) of the metal ion. We show that three-dimensional structures of proteins can reliably be determined using PCS data from a single metal binding site combined with backbone chemical shifts. The program PCS-ROSETTA automatically determines the Δχ-tensor and metal position from the PCS data during the structure calculations, without any prior knowledge of the protein structure. The program can determine structures accurately for proteins of up to 150 residues, offering a powerful new approach to protein structure determination that relies exclusively on readily measurable backbone chemical shifts and easily discriminates between correctly and incorrectly folded conformations. PMID:22285518

Frontiers in Chemistry.

ERIC Educational Resources Information Center

Joyce, Robert M., Ed.

1980-01-01

This article describes recent progress in chemical synthesis which depends on comparable advances in other areas of chemistry. Analysis and theories of chemical structure and reactions are determinants in progress in chemical synthesis and are described also. (Author/SA)

In Silico Studies of the Toxcast Chemicals Interacting with Biomolecular targets

EPA Science Inventory

Molecular docking, a structure-based in silico tool for chemical library pre-screening in drug discovery, can be used to explore the potential toxicity of environmental chemicals acting at specific biomelcular targets.

Alternative Life Styles for Extraterrestrial Chemists

NASA Astrophysics Data System (ADS)

Benner, S.

2002-12-01

Life is no more (and no less) than a special type of organic chemistry, one that combines a frequently encountered property of organic molecules (the ability to undergo spontaneous chemical transformation) with an uncommon property (the ability to direct the synthesis of self-copies) in a way that allows new molecular features arising through spontaneous transformation to themselves be copied. Any chemical system having this combination will undergo natural selection, evolving in structure to replicate faster through more efficient use of molecular resources and energy. Axiomatically, life cannot exist in an environment at thermodynamic equilibrium. If it were, by the second law of thermodynamics, no net chemical transformation would be possible. Beyond this constraint, it is difficult to define environmental conditions or chemical structures necessary for life. Water is certainly not required for a chemical system to copy itself; in the laboratory, non-aqueous environments appear to support this behavior better. Chemical transformations that might support energy and chemical metabolisms are known in environments as acidic as the aerosols in the atmosphere of Venus, or as basic as the atmosphere of Jupiter. Laboratory experiments with analogs of the nucleic acids, proteins, sugars, and lipids show that the particular molecular structures found in terrean life need not be universal, even those life in water near neutral pH. Indeed, while both water and biological macromolecules are commonly regarded as essential for terrean-like life, water destroys terrean biological macromolecules. These chemical realities create a complex decision environment as NASA attempts to design instrumentation carried by missions, select places in the solar system to send them, and chose laboratory studies on Earth to provide their scientific support. This talk will review a hierarchy of chemical possibilities and constraints that start with the chemistry of terrean life, and takes steps towards weird life. We shall consider alternative amino acid building blocks for proteins, alternative building blocks for nucleic acids, alternative structural features of genetic and catalytic molecules, alternative nucleophile-electrophile pairs to support metabolism, non-polar reaction modes that might support metabolism, non-terrean pH (< 0, > 14) and solvent environments for life, extreme temperature ranges (especially sub zero Celsius) low temperature ranges, alternative thermodynamic design for metabolic pathways, alternative dimensionalities of genetic and catalytic molecules, and approaches for isolating life other than conventional cell structures. Each of these discussions will combine experimental and theoretical information. The first involves organic chemical synthesis that creates new forms of chemical matter to ask "What if?" and "Why not?" questions. The second draws on a century of literature in physical organic chemistry to formulate general constraints on the structure and transformation of organic matter to provide constraints on possible Darwinian chemistries in the galaxy.

Student Teachers' Knowledge about Chemical Representations

ERIC Educational Resources Information Center

Taskin, Vahide; Bernholt, Sascha; Parchmann, Ilka

2017-01-01

Chemical representations serve as a communication tool not only in exchanges between scientists but also in chemistry lessons. The goals of the present study were to measure the extent of student teachers' knowledge about chemical representations, focusing on chemical formulae and structures in particular, and to explore which factors related to…

Development of a Consumer Product Ingredient Database for Chemical ExposureScreening and Prioritization

EPA Science Inventory

Consumer products are a primary source of chemical exposures, yet little structured information is available on the chemical ingredients of these products and the concentrations at which ingredients are present. To address this data gap, we created a database of chemicals in cons...

Chemical Literature Exercises and Resources (CLEAR).

ERIC Educational Resources Information Center

Hostettler, John D.; And Others

These materials were developed to make the structure and use of the chemical literature clear to chemistry students and to help them become independent and intelligent users of the library. The design of Chemical Literature Exercises and Resources (CLEAR) includes a users' note and five main parts: introduction to chemical literature, chemical…

Calculating the dermal flux of chemicals with OELs based on their molecular structure: An attempt to assign the skin notation.

PubMed

Kupczewska-Dobecka, Małgorzata; Jakubowski, Marek; Czerczak, Sławomir

2010-09-01

Our objectives included calculating the permeability coefficient and dermal penetration rates (flux value) for 112 chemicals with occupational exposure limits (OELs) according to the LFER (linear free-energy relationship) model developed using published methods. We also attempted to assign skin notations based on each chemical's molecular structure. There are many studies available where formulae for coefficients of permeability from saturated aqueous solutions (K(p)) have been related to physicochemical characteristics of chemicals. The LFER model is based on the solvation equation, which contains five main descriptors predicted from chemical structure: solute excess molar refractivity, dipolarity/polarisability, summation hydrogen bond acidity and basicity, and the McGowan characteristic volume. Descriptor values, available for about 5000 compounds in the Pharma Algorithms Database were used to calculate permeability coefficients. Dermal penetration rate was estimated as a ratio of permeability coefficient and concentration of chemical in saturated aqueous solution. Finally, estimated dermal penetration rates were used to assign the skin notation to chemicals. Defined critical fluxes defined from the literature were recommended as reference values for skin notation. The application of Abraham descriptors predicted from chemical structure and LFER analysis in calculation of permeability coefficients and flux values for chemicals with OELs was successful. Comparison of calculated K(p) values with data obtained earlier from other models showed that LFER predictions were comparable to those obtained by some previously published models, but the differences were much more significant for others. It seems reasonable to conclude that skin should not be characterised as a simple lipophilic barrier alone. Both lipophilic and polar pathways of permeation exist across the stratum corneum. It is feasible to predict skin notation on the basis of the LFER and other published models; from among 112 chemicals 94 (84%) should have the skin notation in the OEL list based on the LFER calculations. The skin notation had been estimated by other published models for almost 94% of the chemicals. Twenty-nine (25.8%) chemicals were identified to have significant absorption and 65 (58%) the potential for dermal toxicity. We found major differences between alternative published analytical models and their ability to determine whether particular chemicals were potentially dermotoxic. Copyright © 2010 Elsevier B.V. All rights reserved.

Relationships between chemical structure, mechanical properties and materials processing in nanopatterned organosilicate fins.

PubMed

Stan, Gheorghe; Gates, Richard S; Hu, Qichi; Kjoller, Kevin; Prater, Craig; Jit Singh, Kanwal; Mays, Ebony; King, Sean W

2017-01-01

The exploitation of nanoscale size effects to create new nanostructured materials necessitates the development of an understanding of relationships between molecular structure, physical properties and material processing at the nanoscale. Numerous metrologies capable of thermal, mechanical, and electrical characterization at the nanoscale have been demonstrated over the past two decades. However, the ability to perform nanoscale molecular/chemical structure characterization has only been recently demonstrated with the advent of atomic-force-microscopy-based infrared spectroscopy (AFM-IR) and related techniques. Therefore, we have combined measurements of chemical structures with AFM-IR and of mechanical properties with contact resonance AFM (CR-AFM) to investigate the fabrication of 20-500 nm wide fin structures in a nanoporous organosilicate material. We show that by combining these two techniques, one can clearly observe variations of chemical structure and mechanical properties that correlate with the fabrication process and the feature size of the organosilicate fins. Specifically, we have observed an inverse correlation between the concentration of terminal organic groups and the stiffness of nanopatterned organosilicate fins. The selective removal of the organic component during etching results in a stiffness increase and reinsertion via chemical silylation results in a stiffness decrease. Examination of this effect as a function of fin width indicates that the loss of terminal organic groups and stiffness increase occur primarily at the exposed surfaces of the fins over a length scale of 10-20 nm. While the observed structure-property relationships are specific to organosilicates, we believe the combined demonstration of AFM-IR with CR-AFM should pave the way for a similar nanoscale characterization of other materials where the understanding of such relationships is essential.

Complex, Dynamic Combination of Physical, Chemical and Nutritional Variables Controls Spatio-Temporal Variation of Sandy Beach Community Structure

PubMed Central

Ortega Cisneros, Kelly; Smit, Albertus J.; Laudien, Jürgen; Schoeman, David S.

2011-01-01

Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right. PMID:21858213

Complex, dynamic combination of physical, chemical and nutritional variables controls spatio-temporal variation of sandy beach community structure.

PubMed

Ortega Cisneros, Kelly; Smit, Albertus J; Laudien, Jürgen; Schoeman, David S

2011-01-01

Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right.

DSSTOX WEBSITE LAUNCH: IMPROVING PUBLIC ACCESS ...

EPA Pesticide Factsheets

DSSTox Website Launch: Improving Public Access to Databases for Building Structure-Toxicity Prediction ModelsAnn M. RichardUS Environmental Protection Agency, Research Triangle Park, NC, USADistributed: Decentralized set of standardized, field-delimited databases, each separatelyauthored and maintained, that are able to accommodate diverse toxicity data content;Structure-Searchable: Standard format (SDF) structure-data files that can be readily imported into available chemical relational databases and structure-searched;Tox: Toxicity data as it exists in widely disparate forms in current public databases, spanning diverse toxicity endpoints, test systems, levels of biological content, degrees of summarization, and information content.INTRODUCTIONThe economic and social pressures to reduce the need for animal testing and to better anticipate the potential for human and eco-toxicity of environmental, industrial, or pharmaceutical chemicals are as pressing today as at any time prior. However, the goal of predicting chemical toxicity in its many manifestations, the `T' in 'ADMET' (adsorption, distribution, metabolism, elimination, toxicity), remains one of the most difficult and largely unmet challenges in a chemical screening paradigm [1]. It is widely acknowledged that the single greatest hurdle to improving structure-activity relationship (SAR) toxicity prediction capabilities, in both the pharmaceutical and environmental regulation arenas, is the lack of suffici

Simultaneous Speciation, Structure, and Equilibrium Constant Determination in the Ni2+-EDTA-CN- Ternary System via High-Resolution Laboratory X-ray Absorption Fine Structure Spectroscopy and Theoretical Calculations.

PubMed

Bajnóczi, Éva G; Németh, Zoltán; Vankó, György

2017-11-20

Even quite simple chemical systems can involve many components and chemical states, and sometimes it can be very difficult to differentiate them by their hardly separable physical-chemical properties. The Ni II -EDTA-CN - (EDTA = ethylenediaminetetraacetic acid) ternary system is a good example for this problem where, in spite of its fairly simple components and numerous investigations, several molecular combinations can exist, all of them not having been identified unambiguously yet. In order to achieve a detailed understanding of the reaction steps and chemical equilibria, methods are required in which the structural transitions in the different reaction steps can be followed via element-selective complex spectral feature sets. With the help of our recently developed von Hámos type high-resolution laboratory X-ray absorption spectrometer, both the structural variations and stability constants of the forming complexes were determined from the same measurement series, proving that X-ray absorption spectroscopy can be considered as a multifaced, table-top tool in coordination chemistry. Furthermore, with the help of theoretical calculations, independent structural evidence was also given for the formation of the [NiEDTA(CN)] 3- mixed complex.

Double-Layer Structured CO2 Adsorbent Functionalized with Modified Polyethyleneimine for High Physical and Chemical Stability.

PubMed

Jeon, Sunbin; Jung, Hyunchul; Kim, Sung Hyun; Lee, Ki Bong

2018-06-18

CO 2 capture using polyethyleneimine (PEI)-impregnated silica adsorbents has been receiving a lot of attention. However, the absence of physical stability (evaporation and leaching of amine) and chemical stability (urea formation) of the PEI-impregnated silica adsorbent has been generally established. Therefore, in this study, a double-layer impregnated structure, developed using modified PEI, is newly proposed to enhance the physical and chemical stabilities of the adsorbent. Epoxy-modified PEI and diepoxide-cross-linked PEI were impregnated via a dry impregnation method in the first and second layers, respectively. The physical stability of the double-layer structured adsorbent was noticeably enhanced when compared to the conventional adsorbents with a single layer. In addition to the enhanced physical stability, the result of simulated temperature swing adsorption cycles revealed that the double-layer structured adsorbent presented a high potential working capacity (3.5 mmol/g) and less urea formation under CO 2 -rich regeneration conditions. The enhanced physical and chemical stabilities as well as the high CO 2 working capacity of the double-layer structured adsorbent were mainly attributed to the second layer consisting of diepoxide-cross-linked PEI.

Chemical and Conformational Diversity of Modified Nucleosides Affects tRNA Structure and Function.

PubMed

Väre, Ville Y P; Eruysal, Emily R; Narendran, Amithi; Sarachan, Kathryn L; Agris, Paul F

2017-03-16

RNAs are central to all gene expression through the control of protein synthesis. Four major nucleosides, adenosine, guanosine, cytidine and uridine, compose RNAs and provide sequence variation, but are limited in contributions to structural variation as well as distinct chemical properties. The ability of RNAs to play multiple roles in cellular metabolism is made possible by extensive variation in length, conformational dynamics, and the over 100 post-transcriptional modifications. There are several reviews of the biochemical pathways leading to RNA modification, but the physicochemical nature of modified nucleosides and how they facilitate RNA function is of keen interest, particularly with regard to the contributions of modified nucleosides. Transfer RNAs (tRNAs) are the most extensively modified RNAs. The diversity of modifications provide versatility to the chemical and structural environments. The added chemistry, conformation and dynamics of modified nucleosides occurring at the termini of stems in tRNA's cloverleaf secondary structure affect the global three-dimensional conformation, produce unique recognition determinants for macromolecules to recognize tRNAs, and affect the accurate and efficient decoding ability of tRNAs. This review will discuss the impact of specific chemical moieties on the structure, stability, electrochemical properties, and function of tRNAs.

Lifetime of a Chemically Bound Helium Compound

NASA Technical Reports Server (NTRS)

Chaban, Galina M.; Lundell, Jan; Gerber, R. Benny; Kwak, Dochan (Technical Monitor)

2001-01-01

The rare-gas atoms are chemically inert, to an extent unique among all elements. This is due to the stable electronic structure of the atoms. Stable molecules with chemically bound rare-gas atoms are, however, known. A first such compound, XePtF6, W2S prepared in 1962 and since then a range of molecules containing radon, xenon and krypton have been obtained. Most recently, a first stable chemically bound compound of argon was prepared, leaving neon and helium as the only elements for which stable chemically bound molecules are not yet known. Electronic structure calculations predict that a metastable species HHeF exists, but significance of the result depends on the unknown lifetime. Here we report quantum dynamics calculations of the lifetime of HHeF, using accurate interactions computed from electronic structure theory. HHeF is shown to disintegrate by tunneling through energy barriers into He + HF and H + He + F the first channel greatly dominating. The lifetime of HHeF is more than 120 picoseconds, that of DHeF is 14 nanoseconds. The relatively long lifetimes are encouraging for the preparation prospects of this first chemically bound helium compound.

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

PubMed

Rabal, Obdulia; Oyarzabal, Julen

2012-05-25

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

Biogeographical Analysis of Chemical Co-Occurrence Data to ...

EPA Pesticide Factsheets

A challenge with multiple chemical risk assessment is the need to consider the joint behavior of chemicals in mixtures. To address this need, pharmacologists and toxicologists have developed methods over the years to evaluate and test chemical interaction. In practice, however, testing of chemical interaction more often comprises ad hoc binary combinations and rarely examines higher order combinations. One explanation for this practice is the belief that there are simply too many possible combinations of chemicals to consider. Indeed, under stochastic conditions the possible number of chemical combinations scales geometrically as the pool of chemicals increases. However, the occurrence of chemicals in the environment is determined by factors, economic in part, which favor some chemicals over others. We investigate methods from the field of biogeography, originally developed to study avian species co-occurrence patterns, and adapt these approaches to examine chemical co-occurrence. These methods were applied to a national survey of pesticide residues in 168 child care centers from across the country. Our findings show that pesticide co-occurrence in the child care center was not random but highly structured, leading to the co-occurrence of specific pesticide combinations. Thus, ecological studies of species co-occurrence parallel the issue of chemical co-occurrence at specific locations. Both are driven by processes that introduce structure in the pattern of co-o

Peristalticity-driven banded chemical garden

NASA Astrophysics Data System (ADS)

Pópity-Tóth, É.; Schuszter, G.; Horváth, D.; Tóth, Á.

2018-05-01

Complex structures in nature are often formed by self-assembly. In order to mimic the formation, to enhance the production, or to modify the structures, easy-to-use methods are sought to couple engineering and self-assembly. Chemical-garden-like precipitation reactions are frequently used to study such couplings because of the intrinsic chemical and hydrodynamic interplays. In this work, we present a simple method of applying periodic pressure fluctuations given by a peristaltic pump which can be used to achieve regularly banded precipitate membranes in the copper-phosphate system.

Core-shell SrTiO3/graphene structure by chemical vapor deposition for enhanced photocatalytic performance

NASA Astrophysics Data System (ADS)

He, Chenye; Bu, Xiuming; Yang, Siwei; He, Peng; Ding, Guqiao; Xie, Xiaoming

2018-04-01

Direct growth of high quality graphene on the surface of SrTiO3 (STO) was realized through chemical vapor deposition (CVD), to construct few-layer 'graphene shell' on every STO nanoparticle. The STO/graphene composite shows significantly enhanced UV light photocatalytic activity compared with the STO/rGO reference. Mechanism analysis confirms the role of special core-shell structure and chemical bond (Tisbnd C) for rapid interfacial electron transfer and effective electron-hole separation.

Design and analysis of a silicon-based antiresonant reflecting optical waveguide chemical sensor

NASA Astrophysics Data System (ADS)

Remley, Kate A.; Weisshaar, Andreas

1996-08-01

The design of a silicon-based antiresonant reflecting optical waveguide (ARROW) chemical sensor is presented, and its theoretical performance is compared with that of a conventional structure. The use of an ARROW structure permits incorporation of a thick guiding region for efficient coupling to a single-mode fiber. A high-index overlay is added to fine tune the sensitivity of the ARROW chemical sensor. The sensitivity of the sensor is presented, and design trade-offs are discussed.

Xuefu zhuyu decoction improves cognitive impairment in experimental traumatic brain injury via synaptic regulation

PubMed Central

Zhou, Jing; Liu, Tao; Cui, Hanjin; Fan, Rong; Zhang, Chunhu; Peng, Weijun; Yang, Ali; Zhu, Lin; Wang, Yang; Tang, Tao

2017-01-01

An overarching consequence of traumatic brain injury (TBI) is the cognitive impairment. It may hinder individual performance of daily tasks and determine people's subjective well-being. The damage to synaptic plasticity, one of the key mechanisms of cognitive dysfunction, becomes the potential therapeutic strategy of TBI. In this study, we aimed to investigate whether Xuefu Zhuyu Decoction (XFZYD), a traditional Chinese medicine, provided a synaptic regulation to improve cognitive disorder following TBI. Morris water maze and modified neurological severity scores were performed to assess the neurological and cognitive abilities. The PubChem Compound IDs of the major compounds of XFZYD were submitted into BATMAN-TCM, an online bioinformatics analysis tool, to predict the druggable targets related to synaptic function. Furthermore, we validated the prediction through immunohistochemical, RT-PCR and western blot analyses. We found that XFZYD enhanced neuroprotection, simultaneously improved learning and memory performances in controlled cortical impact rats. Bioinformatics analysis revealed that the improvements of XFZYD implied the Long-term potentiation relative proteins including NMDAR1, CaMKII and GAP-43. The further confirmation of molecular biological studies confirmed that XFZYD upregulated the mRNA and protein levels of NMDAR1, CaMKII and GAP-43. Pharmacological synaptic regulation of XFZYD could provide a novel therapeutic strategy for cognitive impairment following TBI. PMID:29069769

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bolton, Evan; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Landsman, David; Lipman, David J; Lu, Zhiyong; Madden, Thomas L; Madej, Tom; Maglott, Donna R; Marchler-Bauer, Aron; Miller, Vadim; Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Wang, Yanli; Wilbur, W John; Yaschenko, Eugene; Ye, Jian

2011-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Electronic PCR, OrfFinder, Splign, ProSplign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), IBIS, Biosystems, Peptidome, OMSSA, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach

PubMed Central

Kudisthalert, Wasu

2018-01-01

Machine learning techniques are becoming popular in virtual screening tasks. One of the powerful machine learning algorithms is Extreme Learning Machine (ELM) which has been applied to many applications and has recently been applied to virtual screening. We propose the Weighted Similarity ELM (WS-ELM) which is based on a single layer feed-forward neural network in a conjunction of 16 different similarity coefficients as activation function in the hidden layer. It is known that the performance of conventional ELM is not robust due to random weight selection in the hidden layer. Thus, we propose a Clustering-based WS-ELM (CWS-ELM) that deterministically assigns weights by utilising clustering algorithms i.e. k-means clustering and support vector clustering. The experiments were conducted on one of the most challenging datasets–Maximum Unbiased Validation Dataset–which contains 17 activity classes carefully selected from PubChem. The proposed algorithms were then compared with other machine learning techniques such as support vector machine, random forest, and similarity searching. The results show that CWS-ELM in conjunction with support vector clustering yields the best performance when utilised together with Sokal/Sneath(1) coefficient. Furthermore, ECFP_6 fingerprint presents the best results in our framework compared to the other types of fingerprints, namely ECFP_4, FCFP_4, and FCFP_6. PMID:29652912

Principles for identification of High Potency Category Chemicals for which the Dermal Sensitisation Threshold (DST) approach should not be applied.

PubMed

Roberts, David W; Api, Anne Marie; Safford, Robert J; Lalko, Jon F

2015-08-01

An essential step in ensuring the toxicological safety of chemicals used in consumer products is the evaluation of their skin sensitising potential. The sensitising potency, coupled with information on exposure levels, can be used in a Quantitative Risk Assessment (QRA) to determine an acceptable level of a given chemical in a given product. Where consumer skin exposure is low, a risk assessment can be conducted using the Dermal Sensitisation Threshold (DST) approach, avoiding the need to determine potency experimentally. Since skin sensitisation involves chemical reaction with skin proteins, the first step in the DST approach is to assess, on the basis of the chemical structure, whether the chemical is expected to be reactive or not. Our accompanying publication describes the probabilistic derivation of a DST of 64 μg/cm(2) for chemicals assessed as reactive. This would protect against 95% of chemicals assessed as reactive, but the remaining 5% would include chemicals with very high potency. Here we discuss the chemical properties and structural features of high potency sensitisers, and derive an approach whereby they can be identified and consequently excluded from application of the DST. Copyright © 2015 Elsevier Inc. All rights reserved.

Flame-Resistant Composite Materials For Structural Members

NASA Technical Reports Server (NTRS)

Spears, Richard K.

1995-01-01

Matrix-fiber composite materials developed for structural members occasionally exposed to hot, corrosive gases. Integral ceramic fabric surface layer essential for resistance to flames and chemicals. Endures high temperature, impedes flame from penetrating to interior, inhibits diffusion of oxygen to interior where it degrades matrix resin, resists attack by chemicals, helps resist erosion, and provides additional strength. In original intended application, composite members replace steel structural members of rocket-launching structures that deteriorate under combined influences of atmosphere, spilled propellants, and rocket exhaust. Composites also attractive for other applications in which corrosion- and fire-resistant structural members needed.

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Belianinov, Alex; Ganesh, Panchapakesan; Lin, Wenzhi; Sales, Brian C.; Sefat, Athena S.; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.

2014-12-01

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1-xSex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

Study of chloride ion transport of composite by using cement and starch as a binder

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

Armynah, Bidayatul; Halide, Halmar; Zahrawani,

This study presents the chemical bonding and the structural properties of composites from accelerator chloride test migration (ACTM). The volume fractions between binder (cement and starch) and charcoal in composites are 20:80 and 60:40. The effect of the binder to the chemical composition, chemical bonding, and structural properties before and after chloride ion passing through the composites was determined by X-ray fluorescence (XRF), by Fourier transform infra-red (FTIR), and x-ray diffraction (XRD), respectively. From the XRD data, XRF data, and the FTIR data shows the amount of chemical composition, the type of binding, and the structure of composites are dependingmore » on the type of binder. The amount of chloride migration using starch as binder is higher than that of cement as a binder due to the density effects.« less

Solid State Chemistry of Clathrate Phases: Crystal Structure, Chemical Bonding and Preparation Routes

NASA Astrophysics Data System (ADS)

Baitinger, Michael; Böhme, Bodo; Ormeci, Alim; Grin, Yuri

Clathrates represent a family of inorganic materials called cage compounds. The key feature of their crystal structures is a three-dimensional (host) framework bearing large cavities (cages) with 20-28 vertices. These polyhedral cages bear—as a rule—guest species. Depending on the formal charge of the framework, clathrates are grouped in anionic, cationic and neutral. While the bonding in the framework is of (polar) covalent nature, the guest-host interaction can be ionic, covalent or even van-der Waals, depending on the chemical composition of the clathrates. The chemical composition and structural features of the cationic clathrates can be described by the enhanced Zintl concept, whereas the composition of the anionic clathrates deviates often from the Zintl counts, indicating additional atomic interactions in comparison with the ionic-covalent Zintl model. These interactions can be visualized and studied by applying modern quantum chemical approaches such as electron localizability.

Chemical Probes for Visualizing Intact Animal and Human Brain Tissue.

PubMed

Lai, Hei Ming; Ng, Wai-Lung; Gentleman, Steve M; Wu, Wutian

2017-06-22

Newly developed tissue clearing techniques can be used to render intact tissues transparent. When combined with fluorescent labeling technologies and optical sectioning microscopy, this allows visualization of fine structure in three dimensions. Gene-transfection techniques have proved very useful in visualizing cellular structures in animal models, but they are not applicable to human brain tissue. Here, we discuss the characteristics of an ideal chemical fluorescent probe for use in brain and other cleared tissues, and offer a comprehensive overview of currently available chemical probes. We describe their working principles and compare their performance with the goal of simplifying probe selection for neuropathologists and stimulating probe development by chemists. We propose several approaches for the development of innovative chemical labeling methods which, when combined with tissue clearing, have the potential to revolutionize how we study the structure and function of the human brain. Copyright © 2017 Elsevier Ltd. All rights reserved.

Chemical and thermal stability of core-shelled magnetite nanoparticles and solid silica

NASA Astrophysics Data System (ADS)

Cendrowski, Krzysztof; Sikora, Pawel; Zielinska, Beata; Horszczaruk, Elzbieta; Mijowska, Ewa

2017-06-01

Pristine nanoparticles of magnetite were coated by solid silica shell forming core/shell structure. 20 nm thick silica coating significantly enhanced the chemical and thermal stability of the iron oxide. Chemical and thermal stability of this structure has been compared to the magnetite coated by mesoporous shell and pristine magnetite nanoparticles. It is assumed that six-membered silica rings in a solid silica shell limit the rate of oxygen diffusion during thermal treatment in air and prevent the access of HCl molecules to the core during chemical etching. Therefore, the core/shell structure with a solid shell requires a longer time to induce the oxidation of iron oxide to a higher oxidation state and, basically, even strong concentrated acid such as HCl is not able to dissolve it totally in one month. This leads to the desired performance of the material in potential applications such as catalysis and environmental protection.

Process for forming a porous silicon member in a crystalline silicon member

DOEpatents

Northrup, M. Allen; Yu, Conrad M.; Raley, Norman F.

1999-01-01

Fabrication and use of porous silicon structures to increase surface area of heated reaction chambers, electrophoresis devices, and thermopneumatic sensor-actuators, chemical preconcentrates, and filtering or control flow devices. In particular, such high surface area or specific pore size porous silicon structures will be useful in significantly augmenting the adsorption, vaporization, desorption, condensation and flow of liquids and gasses in applications that use such processes on a miniature scale. Examples that will benefit from a high surface area, porous silicon structure include sample preconcentrators that are designed to adsorb and subsequently desorb specific chemical species from a sample background; chemical reaction chambers with enhanced surface reaction rates; and sensor-actuator chamber devices with increased pressure for thermopneumatic actuation of integrated membranes. Examples that benefit from specific pore sized porous silicon are chemical/biological filters and thermally-activated flow devices with active or adjacent surfaces such as electrodes or heaters.

Imaging Molecular Motion: Femtosecond X-Ray Scattering of an Electrocyclic Chemical Reaction

NASA Astrophysics Data System (ADS)

Minitti, M. P.; Budarz, J. M.; Kirrander, A.; Robinson, J. S.; Ratner, D.; Lane, T. J.; Zhu, D.; Glownia, J. M.; Kozina, M.; Lemke, H. T.; Sikorski, M.; Feng, Y.; Nelson, S.; Saita, K.; Stankus, B.; Northey, T.; Hastings, J. B.; Weber, P. M.

2015-06-01

Structural rearrangements within single molecules occur on ultrafast time scales. Many aspects of molecular dynamics, such as the energy flow through excited states, have been studied using spectroscopic techniques, yet the goal to watch molecules evolve their geometrical structure in real time remains challenging. By mapping nuclear motions using femtosecond x-ray pulses, we have created real-space representations of the evolving dynamics during a well-known chemical reaction and show a series of time-sorted structural snapshots produced by ultrafast time-resolved hard x-ray scattering. A computational analysis optimally matches the series of scattering patterns produced by the x rays to a multitude of potential reaction paths. In so doing, we have made a critical step toward the goal of viewing chemical reactions on femtosecond time scales, opening a new direction in studies of ultrafast chemical reactions in the gas phase.

Imaging Molecular Motion: Femtosecond X-Ray Scattering of an Electrocyclic Chemical Reaction.

PubMed

Minitti, M P; Budarz, J M; Kirrander, A; Robinson, J S; Ratner, D; Lane, T J; Zhu, D; Glownia, J M; Kozina, M; Lemke, H T; Sikorski, M; Feng, Y; Nelson, S; Saita, K; Stankus, B; Northey, T; Hastings, J B; Weber, P M

2015-06-26

Structural rearrangements within single molecules occur on ultrafast time scales. Many aspects of molecular dynamics, such as the energy flow through excited states, have been studied using spectroscopic techniques, yet the goal to watch molecules evolve their geometrical structure in real time remains challenging. By mapping nuclear motions using femtosecond x-ray pulses, we have created real-space representations of the evolving dynamics during a well-known chemical reaction and show a series of time-sorted structural snapshots produced by ultrafast time-resolved hard x-ray scattering. A computational analysis optimally matches the series of scattering patterns produced by the x rays to a multitude of potential reaction paths. In so doing, we have made a critical step toward the goal of viewing chemical reactions on femtosecond time scales, opening a new direction in studies of ultrafast chemical reactions in the gas phase.

General Characteristics of the Changes in the Thermal Stability of Proteins and Enzymes After the Chemical Modification of Their Functional Groups

NASA Astrophysics Data System (ADS)

Kutuzova, G. D.; Ugarova, N. N.; Berezin, Ilya V.

1984-11-01

The principal structural and physicochemical factors determining the stability of protein macromolecules in solution and the characteristics of the structure of the proteins from thermophilic microorganisms are examined. The mechanism of the changes in the thermal stability of proteins and enzymes after the chemical modification of their functional side groups and the experimental data concerning the influence of chemical modification on the thermal stability of proteins are analysed. The dependence of the stabilisation effect and of the changes in the structure of protein macromolecules on the degree of modification and on the nature of the modified groups and the groups introduced into proteins in the course of modification (their charge and hydrophobic properties) is demonstrated. The great practical value of the method of chemical modification for the preparation of stabilised forms of biocatalysts is shown in relation to specific examples. The bibliography includes 178 references.

Combining density functional theory (DFT) and pair distribution function (PDF) analysis to solve the structure of metastable materials: the case of metakaolin.

PubMed

White, Claire E; Provis, John L; Proffen, Thomas; Riley, Daniel P; van Deventer, Jannie S J

2010-04-07

Understanding the atomic structure of complex metastable (including glassy) materials is of great importance in research and industry, however, such materials resist solution by most standard techniques. Here, a novel technique combining thermodynamics and local structure is presented to solve the structure of the metastable aluminosilicate material metakaolin (calcined kaolinite) without the use of chemical constraints. The structure is elucidated by iterating between least-squares real-space refinement using neutron pair distribution function data, and geometry optimisation using density functional modelling. The resulting structural representation is both energetically feasible and in excellent agreement with experimental data. This accurate structural representation of metakaolin provides new insight into the local environment of the aluminium atoms, with evidence of the existence of tri-coordinated aluminium. By the availability of this detailed chemically feasible atomic description, without the need to artificially impose constraints during the refinement process, there exists the opportunity to tailor chemical and mechanical processes involving metakaolin and other complex metastable materials at the atomic level to obtain optimal performance at the macro-scale.

Kohonen and counterpropagation neural networks applied for mapping and interpretation of IR spectra.

PubMed

Novic, Marjana

2008-01-01

The principles of learning strategy of Kohonen and counterpropagation neural networks are introduced. The advantages of unsupervised learning are discussed. The self-organizing maps produced in both methods are suitable for a wide range of applications. Here, we present an example of Kohonen and counterpropagation neural networks used for mapping, interpretation, and simulation of infrared (IR) spectra. The artificial neural network models were trained for prediction of structural fragments of an unknown compound from its infrared spectrum. The training set contained over 3,200 IR spectra of diverse compounds of known chemical structure. The structure-spectra relationship was encompassed by the counterpropagation neural network, which assigned structural fragments to individual compounds within certain probability limits, assessed from the predictions of test compounds. The counterpropagation neural network model for prediction of fragments of chemical structure is reversible, which means that, for a given structural domain, limited to the training data set in the study, it can be used to simulate the IR spectrum of a chemical defined with a set of structural fragments.

Tunable multi-band absorption in metasurface of graphene ribbons based on composite structure

NASA Astrophysics Data System (ADS)

Ning, Renxia; Jiao, Zheng; Bao, Jie

2017-05-01

A tunable multiband absorption based on a graphene metasurface of composite structure at mid-infrared frequency was investigated by the finite difference time domain method. The composite structure were composed of graphene ribbons and a gold-MgF2 layer which was sandwiched in between two dielectric slabs. The permittivity of graphene is discussed with different chemical potential to obtain tunable absorption. And the absorption of the composite structure can be tuned by the chemical potential of graphene at certain frequencies. The impedance matching was used to study the perfect absorption of the structure in our paper. The results show that multi-band absorption can be obtained and some absorption peaks of the composite structure can be tuned through the changing not only of the width of graphene ribbons and gaps, but also the dielectric and the chemical potential of graphene. However, another peak was hardly changed by parameters due to a different resonant mechanism in proposed structure. This flexibily tunable multiband absorption may be applied to optical communications such as optical absorbers, mid infrared stealth devices and filters.

Racemic & quasi-racemic protein crystallography enabled by chemical protein synthesis.

PubMed

Kent, Stephen Bh

2018-04-04

A racemic protein mixture can be used to form centrosymmetric crystals for structure determination by X-ray diffraction. Both the unnatural d-protein and the corresponding natural l-protein are made by total chemical synthesis based on native chemical ligation-chemoselective condensation of unprotected synthetic peptide segments. Racemic protein crystallography is important for structure determination of the many natural protein molecules that are refractory to crystallization. Racemic mixtures facilitate the crystallization of recalcitrant proteins, and give diffraction-quality crystals. Quasi-racemic crystallization, using a single d-protein molecule, can facilitate the determination of the structures of a series of l-protein analog molecules. Copyright © 2018 Elsevier Ltd. All rights reserved.

CSI 3.0: a web server for identifying secondary and super-secondary structure in proteins using NMR chemical shifts.

PubMed

Hafsa, Noor E; Arndt, David; Wishart, David S

2015-07-01

The Chemical Shift Index or CSI 3.0 (http://csi3.wishartlab.com) is a web server designed to accurately identify the location of secondary and super-secondary structures in protein chains using only nuclear magnetic resonance (NMR) backbone chemical shifts and their corresponding protein sequence data. Unlike earlier versions of CSI, which only identified three types of secondary structure (helix, β-strand and coil), CSI 3.0 now identifies total of 11 types of secondary and super-secondary structures, including helices, β-strands, coil regions, five common β-turns (type I, II, I', II' and VIII), β hairpins as well as interior and edge β-strands. CSI 3.0 accepts experimental NMR chemical shift data in multiple formats (NMR Star 2.1, NMR Star 3.1 and SHIFTY) and generates colorful CSI plots (bar graphs) and secondary/super-secondary structure assignments. The output can be readily used as constraints for structure determination and refinement or the images may be used for presentations and publications. CSI 3.0 uses a pipeline of several well-tested, previously published programs to identify the secondary and super-secondary structures in protein chains. Comparisons with secondary and super-secondary structure assignments made via standard coordinate analysis programs such as DSSP, STRIDE and VADAR on high-resolution protein structures solved by X-ray and NMR show >90% agreement between those made with CSI 3.0. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genome scale enzyme–metabolite and drug–target interaction predictions using the signature molecular descriptor

DOE PAGES

Faulon, Jean-Loup; Misra, Milind; Martin, Shawn; ...

2007-11-23

Motivation: Identifying protein enzymatic or pharmacological activities are important areas of research in biology and chemistry. Biological and chemical databases are increasingly being populated with linkages between protein sequences and chemical structures. Additionally, there is now sufficient information to apply machine-learning techniques to predict interactions between chemicals and proteins at a genome scale. Current machine-learning techniques use as input either protein sequences and structures or chemical information. We propose here a method to infer protein–chemical interactions using heterogeneous input consisting of both protein sequence and chemical information. Results: Our method relies on expressing proteins and chemicals with a common cheminformaticsmore » representation. We demonstrate our approach by predicting whether proteins can catalyze reactions not present in training sets. We also predict whether a given drug can bind a target, in the absence of prior binding information for that drug and target. Lastly, such predictions cannot be made with current machine-learning techniques requiring binding information for individual reactions or individual targets.« less

Leaching behavior and chemical stability of copper butyl xanthate complex under acidic conditions.

PubMed

Chang, Yi Kuo; Chang, Juu En; Chiang, Li Choung

2003-08-01

Although xanthate addition can be used for treating copper-containing wastewater, a better understanding of the leaching toxicity and the stability characteristics of the copper xanthate complexes formed is essential. This work was undertaken to evaluate the leaching behavior of copper xanthate complex precipitates by means of toxicity characteristics leaching procedure (TCLP) and semi-dynamic leaching test (SDLT) using 1 N acetic acid solution as the leachant. Also, the chemical stability of the copper xanthate complex during extraction has been examined with the studying of variation of chemical structure using UV-vis, Fourier transform infrared and X-ray photoelectron spectroscopies (XPS). Both TCLP and SDLT results showed that a negligible amount of copper ion was leached out from the copper xanthate complex precipitate, indicating that the complex exhibited a high degree of copper leaching stability under acidic conditions. Nevertheless, chemical structure of the copper xanthate complex precipitate varied during the leaching tests. XPS data suggested that the copper xanthate complex initially contained both cupric and cuprous xanthate, but the unstable cupric xanthate change to the cuprous form after acid extraction, indicating the cuprous xanthate to be the final stabilizing structure. Despite that, the changes of chemical structure did not induce the rapid leaching of copper from the copper xanthate complex.

Study of the Chemical Space of Selected Bacteriostatic Sulfonamides from an Information Theory Point of View.

PubMed

López-Rosa, Sheila; Molina-Espíritu, Moyocoyani; Esquivel, Rodolfo O; Soriano-Correa, Catalina; Dehesa, Jésus S

2016-12-05

The relative structural location of a selected group of 27 sulfonamide-like molecules in a chemical space defined by three information theory quantities (Shannon entropy, Fisher information, and disequilibrium) is discussed. This group is composed of 15 active bacteriostatic molecules, 11 theoretically designed ones, and para-aminobenzoic acid. This endeavor allows molecules that share common chemical properties through the molecular backbone, but with significant differences in the identity of the chemical substituents, which might result in bacteriostatic activity, to be structurally classified and characterized. This is performed by quantifying the structural changes on the electron density distribution due to different functional groups and number of electrons. The macroscopic molecular features are described by means of the entropy-like notions of spatial electronic delocalization, order, and uniformity. Hence, an information theory three-dimensional space (IT-3D) emerges that allows molecules with common properties to be gathered. This space witnesses the biological activity of the sulfonamides. Some structural aspects and information theory properties can be associated, as a result of the IT-3D chemical space, with the bacteriostatic activity of these molecules. Most interesting is that the active bacteriostatic molecules are more similar to para-aminobenzoic acid than to the theoretically designed analogues. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.