ChEMBL is medicinal chemistry database by the team of dr. J. Overington at the EBI: http://www.ebi.ac.uk/chembl/ It is detailed in this paper (doi:10.1093/nar/gkr777): http://nar.oxfordjournals.org/content/early/2011/09/22/nar.gkr777.short This project develops, releases, and hosts a RDF version of ChEMBL, independent from the ChEMBL team who make their own RDF version. The main SPARQL end point is available from Uppsala University at: http://rdf.farmbio.uu.se/chembl/sparql

The MNXref reconciliation of metabolites and biochemical reactions namespace

ChEBI dataset in Turtle, N-Triples, JSON-LD, and RDF/XML. https://www.ebi.ac.uk/chebi/

NBDC NikkajiRDF is RDF data of Japan Chemical Substance Dictionary (Nikkaji), which is one of the largest chemical substance databases in Japan.

This RDF data contains the core information of chemical substances such as NIkkaji Number, English/Japanese label, Type, Chemical structure diagram, and same object which were extracted extracted from the Basic Information RDF. We recommend using this RDF together with the 'InChI and InChIKey' 'Canonical SMILES' or 'MOL/SDF' RDF.

Present chemical data storage methodologies place many restrictions on the use of the stored data. The absence of sufficient high-quality metadata prevents intelligent computer access to the data without human intervention. This creates barriers to the automation of data mining in activities such as quantitative structure−activity relationship modelling. The application of Semantic Web technologies to chemical data is shown to reduce these limitations. The use of unique identifiers and relationships (represented as uniform resource identifiers, URIs, and resource description framework, RDF) held in a triplestore provides for greater detail and flexibility in the sharing and storage of molecular structures and properties.

The Molecular Entities in Linked Data (MEiLD) dataset comprises data of distinct atoms, molecules, ions, ion pairs, radicals, radical ions, and others that can be identifiable as separately distinguishable chemical entities. The dataset is provided in a JSON-LD format and was generated by the SDFEater, a tool that allows parsing atoms, bonds, and other molecule data. MEiLD contains 349,960 of 'small' chemical entities. Our dataset is based on the SDF files and is enriched with additional ontologies and line notation data. As a basis, the Molecular Entities in Linked Data dataset uses the Resource Description Framework (RDF) data model. Saving the data in such a model allows preserving the semantic relations, like hierarchical and associative, between them. To describe chemical molecules, vocabularies such as Chemical Vocabulary for Molecular Entities (CVME) and Simple Knowledge Organization System (SKOS) are used. The dataset can be beneficial, among others, for people concerned with research and development tools for cheminformatics and bioinformatics. In this paper, we describe various methods of access to our dataset. In addition to the MEiLD dataset, we publish the Shapes Constraint Language (SHACL) schema of our dataset and the CVME ontology. The data is available in Mendeley Data.

The files contain knots and coefficients of third order (quadratic) B-spline representation approximating the structure factor S(q) appearing in the equation for power spectral density of particle or cavity monolayer. The structure factor depends on the radial distribution function (RDF) of objects forming the monolayer. In our computations, we used a B-spline representation of the RDF computed for a hard disk system of surface coverage 0.85. The representation, averaged over 26 replicas of RDF, was calculated as described at http://dx.doi.org/10.17632/3csw4wmjnr.1. With the RDF representation, we numerically computed the structure factor using the procedure DBFQAD of SLATEC library. This way we got 1E5 values of the structure factor at equidistant wavenumbers in the interval from 1E-3 to 1E2. Finally, we fit a B-spline representation to the discrete function S(q). For that, we used the B-spline fitting procedure splrep of the package SciPy.interpolate included in the Python-based open-source library SciPy. We used a forth order (cubic) B-spline with the default knot vector generated by the procedure splrep, i.e., with the knot separation distance equal about 1E-3. To calculate the structure factor with the B-spline you can use the procedures splev or BSpline of the module SciPy.interpolate of SciPy library v. 1.7.1. The knot vector in the attached files begins and ends with three improper knots, in accordance with the requirements of the procedures. For details, see the paper: P. Weroński & K. Pałka, "Roughness spectroscopy of particle monolayer: Implications for spectral analysis of the monolayer image", Measurement 196 (2022) 111263.

This is the trajectory file meant to work with the rdf2d-example example folder of d-SEAMS. Check Github to navigate the source code in the browser. The filename needs to be preserved to run without any changes.

.alpha.-Hexachlorocyclohexane at IL_EPA_WQX-RDF-1

This RDF data contains the URL-encoded content of MOL/SDF files of chemical substances registered in Nikkaji by using CHEMINF, SIO and other ontologies. We recommend using this RDF together with the Core RDF.

This is the dataset used in the publication of "Resource Description Framework (RDF) Modeling of Named Entity Co-occurrences in Biomedical Literature and Its Integration with PubChemRDF"

Project that developed an open access discovery platform, called Open Pharmacological Space (OPS), via a semantic web approach, integrating pharmacological data from a variety of information resources and tools and services to question this integrated data to support pharmacological research. The project is based upon the assimilation of data already stored as triples, in the form subject-predicate-object. The software and data are available for download and local installation, under an open source and open access model. Tools and services are provided to query and visualize this data, and a sustainability plan will be in place, continuing the operation of the Open PHACTS Discovery Platform after the project funding ends. Throughout the project, a series of recommendations will be developed in conjunction with the community, building on open standards, to ensure wide applicability of the approaches used for integration of data.

In this paper, we have investigated the chemical adsorption behavior of O2 on five types of organic sulfur (thiol, sulfoxide, thioether, sulfone, and thiophene) in polycyclic aromatic hydrocarbon (PAH) sheets using density functional theory (DFT) calculations. Here, the adsorption energy of O2-organic sulfur exceeds that of O2-PAH. Sulfone tends to be more favorable for oxidation reactions than other organic sulfur compounds and PAH by energy gap and deformation charge density analyses. A large charge transfer occurs between O2 and organic sulfur compounds by charge analysis. A radical distribution function (RDF) analysis shows that O2/CO2/N2 is preferentially adsorbed on nitrogen/sulfur/oxygen-containing functional groups in coal. To inhibit the reaction of sulfur-containing coal with oxygen, the physical adsorption of pure gas (CO2/O2/N2) and binary mixed gases (CO2 + O2/N2 + O2/CO2 + N2) is conducted at different temperatures and geological depths using molecular dynamics (MD) and grand canonical Monte Carlo (GCMC) simulations. The adsorption capacities of five types of organic sulfur with respect to the pure gases decrease with increasing temperature and increase with increasing depth. For O2/CO2, CO2/N2, and O2/N2 binary gas systems, the order with respect to adsorption amount is CO2 > O2 > N2. The factor of adsorption capacities is also evaluated, and the results show that pore volume plays a key role in adsorption behavior.

Ammonia-nitrogen at IL_EPA_WQX-RDF-3

Beryllium at IL_EPA-RDF-4

Pendimethalin at IL_EPA-RDF-1

Depth at IL_EPA-RDF-2

This data set accompanies the manuscript Differential-Mobility Spectrometry of 1-deoxysphingosine Isomers: New Insights into the Gas Phase Structures of Ionized Lipids by Berwyck L. J. Poad, Alan T. Maccarone, Haibo Yu, Todd W. Mitchell, Essa M. Saied, Christoph Arenz, Thorsten Hornemann, James N. Bull, Evan J. Bieske, Stephen J. Blanksby.

ABSTRACT: Separation and structural identification of lipids remains a major challenge for contemporary lipidomics. Regioisomeric lipids differing only in position(s) of unsaturation are not differentiated by conventional liquid chromatography-mass spectrometry approaches leading to the incomplete, or sometimes incorrect, assignation of molecular structure. Here we describe an investigation of the gas phase separations by differential mobility spectrometry (DMS) of a series of synthetic analogues of the recently described 1-deoxysphingosine. The dependence of the DMS behavior on the position of the carbon-carbon double bond within the ionized lipid is systematically explored and compared to trends from complementary investigations, including collision cross sections measured by drift tube ion mobility, reaction efficiency with ozone, and molecular dynamics simulations. Consistent trends across these modes of interrogation point to the importance of direct, through-space interactions between the charge site and the carbon-carbon double bond. Differences in the geometry and energetics of this intra-molecular interaction underpin DMS separations and influence reactivity trends between regioisomers. Importantly, the disruption and reformation of these intra-molecular solvation interactions during DMS are proposed to be the causative factor in the observed separations of ionized lipids which are shown to have otherwise identical collision cross sections. These findings provide key insights into the strengths and limitations of current ion-mobility technologies for lipid isomer separations and can thus guide a more systematic approach to improved analytical separations in lipidomics.