Search

Abstract The chemical sciences are producing an unprecedented amount of large, high-dimensional data sets containing chemical structures and associated properties. However, there are currently no algorithms to visualize such data while preserving both global and local features with a sufficient level of detail to allow for human inspection and interpretation. Here, we propose a solution to this problem with a new data visualization method, TMAP, capable of representing data sets of up to millions of data points and arbitrary high dimensionality as a two-dimensional tree ( http://tmap.gdb.tools ). Visualizations based on TMAP are better suited than t-SNE or UMAP for the exploration and interpretation of large data sets due to their tree-like nature, increased local and global neighborhood and structure preservation, and the transparency of the methods the algorithm is based on. We apply TMAP to the most used chemistry data sets including databases of molecules such as ChEMBL, FDB17, the Natural Products Atlas, DSSTox, as well as to the MoleculeNet benchmark collection of data sets. We also show its broad applicability with further examples from biology, particle physics, and literature.

The chemical sciences are producing an unprecedented amount of large, high-dimensional data sets containing chemical structures and associated properties. However, there are currently no algorithms to visualize such data while preserving both global and local features with a sufficient level of detail to allow for human inspection and interpretation. Here, we propose a solution to this problem with a new data visualization method, TMAP, capable of representing data sets of up to millions of data points and arbitrary high dimensionality as a two-dimensional tree (http://tmap.gdb.tools). Visualizations based on TMAP are better suited than t-SNE or UMAP for the exploration and interpretation of large data sets due to their tree-like nature, increased local and global neighborhood and structure preservation, and the transparency of the methods the algorithm is based on. We apply TMAP to the most used chemistry data sets including databases of molecules such as ChEMBL, FDB17, the Natural Products Atlas, DSSTox, as well as to the MoleculeNet benchmark collection of data sets. We also show its broad applicability with further examples from biology, particle physics, and literature. [ABSTRACT FROM AUTHOR]

The Open Chemistry Database (OChemDb) is a new free online portal which uses an appropriately designed database of already solved crystal structures. It makes freely available computational and graphical tools for searching and analysing crystal‐chemical information of organic, metal–organic and inorganic structures, and providing statistics on desired bond distances, bond angles, torsion angles and space groups. Atom types have been classified by an identifier code containing information about the chemical topology and local environment. The crystallographic data used by OChemDb are acquired from the CIFs contained in the free small‐molecule Crystallography Open Database (COD). OChemDb offers easy‐to‐use and intuitive options for searching. It is updated by following the continuous growth of information stored in the COD. It can be of great utility for structural chemistry, in particular in the process of determination of a new crystal structure, and for any discipline involving crystalline structure knowledge. The use of OChemDb requires only a web browser and an internet connection. Every device (mobile or desktop) and every operating system is able to use OChemDb by accessing its web page. Examples of application of OChemDb are reported. [ABSTRACT FROM AUTHOR]

The Nain ophiolites crop out along the western border of the central East Iran Microcontinent (CEIM) and consist of an ophiolitic mélange in which pargasite-bearing spinel and plagioclase mantle lherzolites are largely represented. Whole-rock and mineral chemistry data suggest that these rocks record the complex history of the asthenospheric and lithospheric mantle evolution. The spinel lherzolites have experienced low-degree (~5%) partial melting and contain clinopyroxenes with positive Eu anomalies (Eu/Eu ⁎  = 1.10–1.48) suggesting that the partial melting occurred under oxidized conditions (fayalite–magnetite–quartz −0.8 to +1.3). The pargasite and coexisting clinopyroxene in these rocks are depleted in light rare earth elements (LREE) (mean chondrite-normalized Ce N /Sm N  = 0.045). The depleted chemistry of this amphibole reflects metasomatism during interaction with H 2 O-rich subalkaline mafic melts, most likely concurrently with or after the partial melting of the spinel lherzolites. The plagioclase lherzolites were subsequently formed by the subsolidus recrystallization of spinel lherzolites under plagioclase facies conditions as a result of mantle uprising, as evidenced by: (1) the development of plagioclase rims around the spinels; (2) plagioclase + orthopyroxene exsolution textures within some clinopyroxene grains; (3) an increase in plagioclase modal content coupled with an increase in modal olivine and a decrease in modal pyroxene and pargasite; (4) coincident decreases in Al, Mg, and Ni, and increases in Cr, Ti, and Fe in spinel, as well as decreases in Al and Ca, and increases in Cr and Ti in pyroxene and pargasite; and (5) the identical whole rock compositions of the spinel and plagioclase lherzolites, which rules out a magmatic origin for the plagioclase in these units. The Nain lherzolites have similar whole-rock and mineral geochemical compositions to subcontinental peridotites that are typically representative of Iberia-type rifted continental margins and ocean–continent transition zones (OCTZ), suggesting that they formed during the early stages of the evolution of the Nain oceanic basin. This means that the Nain lherzolites represent the Triassic–Jurassic western border of the CEIM or alternatively an associated OCTZ. [ABSTRACT FROM AUTHOR]

The influence of a N heteroatom on the ring conformations of six- and seven-membered aliphatic rings in six new C(O)NHP(O)-based phosphoric triamide structures (analysed by X-ray crystallography) is investigated. Additionally the influence of steric and crystal packing effects is also studied by the analysis of Hirshfeld surfaces. The results are compared to analogous structures with three- to seven- aliphatic membered rings deposited in the Cambridge Structural Database. In the newly determined structures, the six-membered rings only show the near-chair conformation with a maximum deviation of the θ puckering parameter of 4.4° from the ideal chair value of 0°/180°, while the seven-membered rings are found in different conformations such as near-chair, twist chair and twist sofa. [ABSTRACT FROM AUTHOR]

High-throughput in vitro assays and exposure prediction efforts are paving the way for modeling chemical risk; however, the utility of such extensive datasets can be limited or misleading when annotation fails to capture current chemical usage. To address this data gap and provide context for food-use in the United States (US), manual curation of food-relevant chemicals in ToxCast was conducted. Chemicals were categorized into three food-use categories: (1) direct food additives, (2) indirect food additives, or (3) pesticide residues. Manual curation resulted in 30% of chemicals having new annotation as well as the removal of 319 chemicals, most due to cancellation or only foreign usage. These results highlight that manual curation of chemical use information provided significant insight affecting the overall inventory and chemical categorization. In total, 1211 chemicals were confirmed as current day food-use in the US by manual curation; 1154 of these chemicals were also identified as food-related in the globally sourced chemical use information from Chemical/Product Categories database (CPCat). The refined list of food-use chemicals and the sources highlighted for compiling annotated information required to confirm food-use are valuable resources for providing needed context when evaluating large-scale inventories such as ToxCast. [ABSTRACT FROM AUTHOR]

Background: Patents are an important source of information for effective decision making in drug discovery. Encouragingly, freely accessible patent-chemistry databases are now in the public domain. However, at present there is still a wide gap between relatively low coverage-high quality manually-curated data sources and high coverage data sources that use text mining and automated extraction of chemical structures. To secure much needed funding for further research and an improved infrastructure, hard evidence is required to demonstrate the significance of patent-derived information in drug discovery. Surprisingly little such evidence has been reported so far. To address this, the present study attempts to quantify the relevance of patents for formulating and substantiating hypotheses for compound-target interactions. Results: A manually-curated set of 130 compound-target interaction pairs annotated with what are considered to be the earliest patent and publication has been produced. The analysis of this set revealed that in stark contrast to what has been reported for novel chemical structures, only about 10% of the compound-target interaction pairs could be found in publications in the scientific literature within one year of being reported in patents. The average delay across all interaction pairs is close to 4 years. In an attempt to benchmark current capabilities, it was also examined how much of the benefit of using patent-derived information can be retained when a bioannotated version of SureChEMBL is used as secondary source for the patent literature. Encouragingly, this approach found the patents in the annotated set for 72% of the compound-target interaction pairs. Similarly, the effect of using the bioactivity database ChEMBL as secondary source for the scientific literature was studied. Here, the publications from the annotated set were only found for 46% of the compound-target interaction pairs. Conclusion: Patent-derived information is a significant enabler for formulating compound-target interaction hypotheses even in cases where the respective interaction is later reported in the scientific literature. The findings of this study clearly highlight the significance of future investments in the development and provision of databases and tools that will allow scientists to search patent information in a comprehensive, reliable, and efficient manner. [ABSTRACT FROM AUTHOR]

The article offers information on use of analytical chemistry data in order accreditation and certification to fulfill conformity assessment role. Topics discussed include importance of quality infrastructure system for industry and market function stress; Environmental Management Systems certification; and manufacturers along with service providers' products and services should deliver on customer expectations.

Background: Visualization of large molecular datasets is a challenging yet important topic utilised in diverse fields of chemistry ranging from material engineering to drug design. Especially in drug design, modern methods of high-throughput screening generate large amounts of molecular data that call for methods enabling their analysis. One such method is classification of compounds based on their molecular scaffolds, a concept widely used by medicinal chemists to group molecules of similar properties. This classification can then be utilized for intuitive visualization of compounds. Results: In this paper, we propose a scaffold hierarchy as a result of large-scale analysis of the PubChem Compound database. The analysis not only provided insights into scaffold diversity of the PubChem Compound database, but also enables scaffold-based hierarchical visualization of user compound data sets on the background of empirical chemical space, as defined by the PubChem data, or on the background of any other user-defined data set. The visualization is performed by a web based client-server application called Scaffvis. It provides an interactive zoomable tree map visualization of data sets up to hundreds of thousands molecules. Scaffvis is free to use and its source codes have been published under an open source license. [ABSTRACT FROM AUTHOR]

Background: 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. Results: 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 . Moreover, a Ruby API version is available at , 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. Conclusion: 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. [ABSTRACT FROM AUTHOR]

Background: PubChem is a public repository for biological activities of small molecules. For the efficient use of its vast amount of chemical information, PubChem performs 2-dimensional (2-D) and 3-dimensional (3-D) neighborings, which precompute 'neighbor' relationships between molecules in the PubChem Compound database, using the PubChem subgraph fingerprints-based 2-D similarity and the Gaussian-shape overlay-based 3-D similarity, respectively. These neighborings allow PubChem to provide the user with immediate access to the list of 2-D and 3-D neighbors (also called 'Similar Compounds' and 'Similar Conformers', respectively) for each compound in PubChem. However, because 3-D neighboring is much more time-consuming than 2-D neighboring, how different the results of the two neighboring schemes are is an important question, considering limited computational resources. Results: The present study analyzed the complementarity between the PubChem 2-D and 3-D neighbors. When all compounds in PubChem were considered, the overlap between 2-D and 3-D neighbors was only 2% of the total neighbors. For the data sets containing compounds with annotated information, the overlap increased as the data sets became smaller. However, it did not exceed 31% and substantial fractions of neighbors were still recognized by either PubChem 2-D or 3-D similarity, but not by both. The Neighbor Preference Index (NPI) of a molecule for a given data set was introduced, which quantified whether a molecule had more 2-D or 3-D neighbors in the data set. The NPI histogram for all PubChem compounds had a bimodal shape with two maxima at NPI = ±1 and a minimum at NPI = 0. However, the NPI histograms for the subsets containing compounds with annotated information had a greater fraction of compounds with a strong preference for one neighboring method to the other (at NPI = ±1) as well as compounds with a neutral preference (at NPI = 0). Conclusion: The results of our study indicate that, for the majority of the compounds in PubChem, their structural similarity to other compounds can be recognized predominantly by either 2-D or 3-D neighborings, but not by both, showing a strong complementarity between 2-D and 3-D neighboring results. Therefore, despite its heavy requirements for computational resources, 3-D neighboring provides an alternative way in which the user can instantly access structurally similar molecules that cannot be detected if only 2-D neighboring is used. [ABSTRACT FROM AUTHOR]

Intermetallic crystal structures offer an enormous structural diversity, with an endless array of structural motifs whose connection to stability and physical properties are often mysterious. Making sense of the often complex crystal structures that arise here, developing a clear structural description, and identifying connections to other phases can be laborious and require an encyclopedic knowledge of structure types. In this Article, we present PRINCEPS, an algorithm based on a new coordination environment projection scheme that facilitates the structural analysis and comparison of such crystal structures. We demonstrate the potential of this approach by applying it to the complex Ce-Ni-Si ternary system, whose 17 binary and 21 ternary phases would present a daunting challenge to one seeking to understand the system by manual inspection (but has nonetheless been well-described through the heroic efforts of previous researchers). With the help of PRINCEPS, most of the ternary phases in this system can be rationalized as intergrowths of simple structural fragments, and grouped into a handful of structural series (with some outliers). These results illustrate how the PRINCEPS approach can be used to organize a vast collection of crystal structures into structurally meaningful families, and guide the description of complex atomic arrangements. [ABSTRACT FROM AUTHOR]

Critical thinking and analytical problem-solving skills in research involves using different search strategies. A proposed concept for an "Imploded Boolean Search" combines three unique identifiable field types to perform a search: keyword(s), numerical value(s), and a chemical structure or reaction. The object of this type of search is to help refine, narrow, and speed the searching process for finding relevant information, which would otherwise yield humanly unmanageable result sets. This search strategy is introduced to third year chemistry students in an information literacy workshop using SciFinder, Reaxys, and Web of Science Structure Search. The aim of the workshop is to help students develop hands-on familiarity on the use of chemistry databases and search strategies for scientific information retrieval. The "Imploded Boolean Search" adds a new skill set to a student's arsenal of search strategies. A survey and training exercise are used to assess the workshop. [ABSTRACT FROM AUTHOR]

The interest and possible contents of a structural database for homoleptic metal complexes (HCD) is analyzed with the help of a set of some 1400 crystal and gas-phase structural data sets. Some examples of stereochemical and bonding trends that can be obtained from such a data collection are given. Attention is paid also to pseudohomoleptic complexes. These are defined as compounds which are formally homoleptic, in the sense that all the ligands around a metal are chemically equivalent, but in one case two very different bonding situations are found, notably due to Jahn-Teller distortions. Another case of pseudohomoleptic complexes correspond to those molecules that are described as homoleptic but that show short intra- or intermolecular contacts to extra donor groups, making it effectively heteroleptic. [ABSTRACT FROM AUTHOR]

A combined search, which joins a slow molecule structure search with a fast compound property search, results in more accurate search results and has been applied in several chemistry databases. However, the problems of search speed differences and combining the two separate search results are two major challenges. In this paper, two kinds of search strategies, synchronous search and asynchronous search, are proposed to solve these problems in the heterogeneous structure database and the property database found in ChemDB, a chemistry database owned by the Institute of Process Engineering, CAS. Their advantages and disadvantages under different conditions are discussed in detail. Furthermore, we applied these two searches to ChemDB and used them to screen for potential molecules that can work as CO2 absorbents. The results reveal that this combined search discovers reasonable target molecules within an acceptable time frame. [ABSTRACT FROM AUTHOR]

Covering: 1984 to end 2014 Using both library paper copies and modern electronic copies, every known, published, English-language journal paper that employs either countercurrent or centrifugal partition chromatography solvent systems for natural product purifications has been studied and the solvent systems classified in a comprehensive database. Papers were studied from the earliest found examples containing natural product separations in 1984 until the end of 2014. In total, 2594 solvent systems have been classified, of which 272 are gradient systems. To observe any trends or patterns in the data, the natural product solutes were divided into 21 classes and the solvent systems into 7 different types. The complete database, sorted according to natural product class, is available for download to assist separation scientists in future liquid–liquid chromatography purifications. [ABSTRACT FROM AUTHOR]

Background: First public disclosure of new chemical entities often takes place in patents, which makes them an important source of information. However, with an ever increasing number of patent applications, manual processing and curation on such a large scale becomes even more challenging. An alternative approach better suited for this large corpus of documents is the automated extraction of chemical structures. A number of patent chemistry databases generated by using the latter approach are now available but little is known that can help to manage expectations when using them. This study aims to address this by comparing two such freely available sources, SureChEMBL and IBM SIIP (IBM Strategic Intellectual Property Insight Platform), with manually curated commercial databases. Results: When looking at the percentage of chemical structures successfully extracted from a set of patents, using SciFinder as our reference, 59 and 51 % were also found in our comparison in SureChEMBL and IBM SIIP, respectively. When performing this comparison with compounds as starting point, i.e. establishing if for a list of compounds the databases provide the links between chemical structures and patents they appear in, we obtained similar results. SureChEMBL and IBM SIIP found 62 and 59 %, respectively, of the compound-patent pairs obtained from Reaxys. [ABSTRACT FROM AUTHOR]

We simulated washout/rainout ratios of non-sea-salt (nss)- SO 4 2 − and NO 3 − using a chemical transport model and compared the estimates with precipitation measurements sampled at 0.5/1 mm intervals at sites located in Kobe (urban), Toyo-oka (suburban), and Tamba (rural) cities, Japan. The 25th and 75th percentile range of the simulated washout contributions was 30–70%. The simulated washout contribution range of NO 3 − (40–70%) was greater than that of nss- SO 4 2 − (30–60%). There was good agreement between the simulated and observed values, and the observed washout contribution of NO 3 − was also greater than that of SO 4 2 − . The simulated washout contribution range was higher (60–75%) in emission source regions and lower (40–55%) in downwind areas. The wet deposition process is one of the key causes of uncertainty in chemical transport modeling. Comparing model results with such high-frequency precipitation chemistry data has been extremely rare. Thus the current study is providing useful information for evaluating and improving wet deposition modeling and for the better understanding of the wet deposition mechanism. [ABSTRACT FROM AUTHOR]

There are compelling needs from a variety of camps for more chemistry data to be available. While there are funder and government mandates for depositing research data in the United States and Europe, this does not mean it will be done well or expediently. Chemists themselves do not appear overly engaged at this stage and chemistry librarians who work directly with chemists and their local information environments are interested in helping with this challenge. Our unique understanding of organizing data and information enables us to contribute to building necessary infrastructure and establishing standards and best practices across the full research data cycle. As not many support structures focused on chemistry currently exist, we are initiating explorations through a few case studies and focused pilot projects presented here, with an aim of identifying opportunities for increased collaboration among chemists, chemistry librarians, cheminformaticians and other chemistry professionals. [ABSTRACT FROM AUTHOR]

Since 2009 the Royal Society of Chemistry (RSC) has been delivering access to chemistry data and cheminformatics tools via the ChemSpider database and has garnered a significant community following in terms of usage and contribution to the platform. ChemSpider has focused only on those chemical entities that can be represented as molecular connection tables or, to be more specific, the ability to generate an InChI from the input structure. As a structure centric hub ChemSpider is built around the molecular structure with other data and links being associated with this structure. As a result the platform has been limited in terms of the types of data that can be managed, and the flexibility of its searches, and it is constrained by the data model. New technologies and approaches, specifically taking into account a shift from relational to NoSQL databases, and the growing importance of the semantic web, has motivated RSC to rearchitect and create a more generic data repository utilizing these new technologies. This article will provide an overview of our activities in delivering data sharing platforms for the chemistry community including the development of the new data repository expanding into more extensive domains of chemistry data. [ABSTRACT FROM AUTHOR]

Matched molecular pair analysis (MMPA)has become a major toolfor analyzing large chemistry data sets for promising chemical transformations.However, the dependence of MMPA predictions on data constraints suchas the number of pairs involved, experimental uncertainty, sourceof the experiments, and variability of the true physical effect hasnot yet been described. In this contribution the statistical basicsfor judging MMPA are analyzed. We illustrate the connection betweenoverall MMPA statistics and individual pairs with a detailed comparisonof average CHEMBL hERG MMPA results versus pairs with extreme transformationeffects. Comparing the CHEMBL results to Novartis data, we find thatsignificant transformation effects agree very well if the experimentaluncertainty is considered. This indicates that caution must be exercisedfor predictions from insignificant MMPAs, yet highlights the robustnessof statistically validated MMPA and shows that MMPA on public databasescan yield results that are very useful for medicinal chemistry. [ABSTRACT FROM AUTHOR]

Background: Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results: This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions: Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain. [ABSTRACT FROM AUTHOR]

Background: Sound statistical validation is important to evaluate and compare the overall performance of (Q)SAR models. However, classical validation does not support the user in better understanding the properties of the model or the underlying data. Even though, a number of visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allow the investigation of model validation results are still lacking. Results: We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. The approach applies the 3D viewer CheS-Mapper, an open-source application for the exploration of small molecules in virtual 3D space. The present work describes the new functionalities in CheS-Mapper 2.0, that facilitate the analysis of (Q)SAR information and allows the visual validation of (Q)SAR models. The tool enables the comparison of model predictions to the actual activity in feature space. The approach is generic: It is model-independent and can handle physico-chemical and structural input features as well as quantitative and qualitative endpoints. Conclusions: Visual validation with CheS-Mapper enables analyzing (Q)SAR information in the data and indicates how this information is employed by the (Q)SAR model. It reveals, if the endpoint is modeled too specific or too generic and highlights common properties of misclassified compounds. Moreover, the researcher can use CheS-Mapper to inspect how the (Q)SAR model predicts activity cliffs. The CheS-Mapper software is freely available at . Graphical abstract: Comparing actual and predicted activity values with CheS-Mapper. [ABSTRACT FROM AUTHOR]

UniChem is a low-maintenance, fast and freely available compound identifier mapping service, recently made available on the Internet. Until now, the criterion of molecular equivalence within UniChem has been on the basis of complete identity between Standard InChIs. However, a limitation of this approach is that stereoisomers, isotopes and salts of otherwise identical molecules are not considered as related. Here, we describe how we have exploited the layered structural representation of the Standard InChI to create new functionality within UniChem that integrates these related molecular forms. The service, called `Connectivity Search' allows molecules to be first matched on the basis of complete identity between the connectivity layer of their corresponding Standard InChIs, and the remaining layers then compared to highlight stereochemical and isotopic differences. Parsing of Standard InChI sub-layers permits mixtures and salts to also be included in this integration process. Implementation of these enhancements required simple modifications to the schema, loader and web application, but none of which have changed the original UniChem functionality or services. The scope of queries may be varied using a variety of easily configurable options, and the output is annotated to assist the user to filter, sort and understand the difference between query and retrieved structures. A RESTful web service output may be easily processed programmatically to allow developers to present the data in whatever form they believe their users will require, or to define their own level of molecular equivalence for their resource, albeit within the constraint of identical connectivity. [ABSTRACT FROM AUTHOR]

Background: The large increase in the number of scientific publications has fuelled a need for semi- and fully automated text mining approaches in order to assist in the triage process, both for individual scientists and also for larger-scale data extraction and curation into public databases. Here, we introduce a document classifier, which is able to successfully distinguish between publications that are `ChEMBL-like' (i.e. related to small molecule drug discovery and likely to contain quantitative bioactivity data) and those that are not. The unprecedented size of the medicinal chemistry literature collection, coupled with the advantage of manual curation and mapping to chemistry and biology make the ChEMBL corpus a unique resource for text mining. Results: The method has been implemented as a data protocol/workflow for both Pipeline Pilot (version 8.5) and KNIME (version 2.9) respectively. Both workflows and models are freely available at: . These can be readily modified to include additional keyword constraints to further focus searches. Conclusions: Large-scale machine learning document classification was shown to be very robust and flexible for this particular application, as illustrated in four distinct text-mining-based use cases. The models are readily available on two data workflow platforms, which we believe will allow the majority of the scientific community to apply them to their own data. Abstract: [ABSTRACT FROM AUTHOR]

Background: The design of chemical libraries, an early step in agrochemical discovery programs, is frequently addressed by means of qualitative physicochemical and/or topological rule-based methods. The aim of this study is to develop quantitative estimates of herbicide- (QEH), insecticide- (QEI), fungicide- (QEF), and, finally, pesticide-likeness (QEP). In the assessment of these definitions, we relied on the concept of desirability functions. Results: We found a simple function, shared by the three classes of pesticides, parameterized particularly, for six, easy to compute, independent and interpretable, molecular properties: molecular weight, logP, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bounds and number of aromatic rings. Subsequently, we describe the scoring of each pesticide class by the corresponding quantitative estimate. In a comparative study, we assessed the performance of the scoring functions using extensive datasets of patented pesticides. Conclusions: The hereby-established quantitative assessment has the ability to rank compounds whether they fail well-established pesticide-likeness rules or not, and offer an efficient way to prioritize (class-specific) pesticides. These findings are valuable for the efficient estimation of pesticide-likeness of vast chemical libraries in the field of agrochemical discovery. [ABSTRACT FROM AUTHOR]

A bibliometric analysis of publications selected according to involvement of the term 'nanocatalysis' from the Chemical Abstracts Plus database on the SciFinder search platform and from the Web of Science database on the Web of Knowledge platform has been carried out. The results indicate the appearance of the new subject domain 'nanocatalysis,' which pertains both to nanoscience and nanotechnology and to catalysis science. [ABSTRACT FROM AUTHOR]

The Analytical Quality by Design (AQbD) concept is demonstrated in the development of a stability-indicating HPLC method for an immediate release dosage form. The AQbD workflow is discussed and demonstrated with a systematic three stage liquid chromatograph method development (wave 1 through wave 3), risk assessment (RA), design of experiments (DOEs), and assessment of the data to provide a method operable design region (MODR) and center point for the method. The use of AQbD workflows streamlines the development of methods as compared to traditional approaches. With the addition of systematic RAs and DOEs, robust and rugged analytical methods result. These methods will have fewer issues and failures throughout the lifecycle due to the knowledge gained via the AQbD process and defining chromatographic set points away from the edges of failure. [ABSTRACT FROM AUTHOR]

The article discusses the Gene Ontology (GO) biological dataset, an informatics tool to combine chemical and biological analysis in order to promote drug research. Topics include collaboration between the GO and the Chemical Entities of Biological Interest (ChEBI) ontology developers, information science in genetic research, and the development of computable definitions for GO terms with semantic relationships correlating with chemical terms in ChEBI.

Liquid chromatography coupled with multistage accurate mass spectrometry (LC-MSn) can generate comprehensive spectral information of metabolites in crude extracts. To support structural characterization of the many metabolites present in such complex samples, we present a novel method (http://www.emetabolomics.org/magma) to automatically process and annotate the LC-MSn data sets on the basis of candidate molecules from chemical databases, such as PubChem or the Human Metabolite Database. Multistage MSn spectral data is automatically annotated with hierarchical trees of in silico generated substructures of candidate molecules to explain the observed fragment ions and alternative candidates are ranked on the basis of the calculated matching score. We tested this method on an untargeted LC-MSn (n ⩽ 3) data set of a green tea extract, generated on an LC-LTQ/Orbitrap hybrid MS system. For the 623 spectral trees obtained in a single LC-MSn run, a total of 116 240 candidate molecules with monoisotopic masses matching within 5 ppm mass accuracy were retrieved from the PubChem database, ranging from 4 to 1327 candidates per molecular ion. The matching scores were used to rank the candidate molecules for each LC-MSn component. The median and third quartile fractional ranks for 85 previously identified tea compounds were 3.5 and 7.5, respectively. The substructure annotations and rankings provided detailed structural information of the detected components, beyond annotation with elemental formula only. Twenty-four additional components were putatively identified by expert interpretation of the automatically annotated data set, illustrating the potential to support systematic and untargeted metabolite identification. [ABSTRACT FROM AUTHOR]

The "small molecule universe" (SMU), the set of all synthetically feasible organic molecules of 500 Da molecular weight or less, is estimated to contain over 1060 structures, making exhaustive searches for structures of interest impractical. Here, we describe the construction of a "representative universal library" spanning the SMU that samples the full extent of feasible small molecule chemistries. This library was generated using the newly developed Algorithm for Chemical Space Exploration with Stochastic Search (ACSESS). ACSESS makes two important contributions to chemical space exploration: it allows the systematic search of the unexplored regions of the small molecule universe, and it facilitates the mining of chemical libraries that do not yet exist, providing a near-infinite source of diverse novel compounds. [ABSTRACT FROM AUTHOR]

The article presents statistical calculations to understand the application of mineral geooxometers of high-magnesium magmas. It estimated the composition of magma for intrusive formations by computer modeling of crystallization differentiation. It informs that spinel appear at the onset of magmatic crystallization together with olivine. It analyzed the experimental database on subliquidus equilibria in the silicate systems to conclude results of experiments with products containing spinel. Several equations related to apply the data on the equilibrium of spinel are also presented.

Abstract: In the search of new cost-effective theoretical approximations, broadly applicable to a large variety of electronic structure problems, a new parameter-free double-hybrid (DH) density functional denominated PBE0-DH was recently launched. Previous successful applications to molecular properties have prompted us to further extend its range of applicability to weak interactions through the addition of a dispersion interaction term (–D). Calculations on some databases for weak interaction energies have confirmed the accuracy of the whole approach, thus giving support to the quality and reliability of the method, as already showed before for other double-hybrid density functionals. [Copyright &y& Elsevier]

Food ingredient fraud and economically motivated adulteration are emerging risks, but a comprehensive compilation of information about known problematic ingredients and detection methods does not currently exist. The objectives of this research were to collect such information from publicly available articles in scholarly journals and general media, organize into a database, and review and analyze the data to identify trends. The results summarized are a database that will be published in the US Pharmacopeial Convention's Food Chemicals Codex, 8th edition, and includes 1305 records, including 1000 records with analytical methods collected from 677 references. Olive oil, milk, honey, and saffron were the most common targets for adulteration reported in scholarly journals, and potentially harmful issues identified include spices diluted with lead chromate and lead tetraoxide, substitution of Chinese star anise with toxic Japanese star anise, and melamine adulteration of high protein content foods. High-performance liquid chromatography and infrared spectroscopy were the most common analytical detection procedures, and chemometrics data analysis was used in a large number of reports. Future expansion of this database will include additional publically available articles published before 1980 and in other languages, as well as data outside the public domain. The authors recommend in-depth analyses of individual incidents. Practical Application: This report describes the development and application of a database of food ingredient fraud issues from publicly available references. The database provides baseline information and data useful to governments, agencies, and individual companies assessing the risks of specific products produced in specific regions as well as products distributed and sold in other regions. In addition, the report describes current analytical technologies for detecting food fraud and identifies trends and developments. [ABSTRACT FROM AUTHOR]

Chemistry databases of the largest international scientific and technical information network, STN International, are characterized in detail. The searching and analytical facilities of STN International and their use in chemical research are considered. [ABSTRACT FROM AUTHOR]

The article presents a research study which examines different categories of structural classes in chemistry and presents a list of patterns for features found in class definitions. The study compares these patterns of class definition to tools which allow for automation of hierarchy construction within cheminformatics and within logic-based ontology technology.

The development of the Molecular Gas-Phase Documentation database is briefly described. It has been developed from a unique literature compilation via the first client programs on computer mainframes and personal computers to a versatile HTML-based version, which can be run platform-independently by common Web browsers. In the database, the structural parameters for about 9200 organic, metalorganic, and inorganic compounds studied in the gas phase mainly by electron diffraction and microwave spectroscopy are given numerically, and the molecular structures can be visualized in many ways, particularly in three-dimensional representation. Moreover, the spectroscopic parameters (such as rotational and centrifugal distortion constants, dipole moments, nuclear quadrupole coupling constants, and barriers of hindered rotation) can be retrieved by keywords. [ABSTRACT FROM AUTHOR]

Confident identification of unknown chemicals in high resolution mass spectrometry (HRMS) screening studies requires cohesive workflows and complementary data, tools, and software. Chemistry databases, screening libraries, and chemical metadata have become fixtures in identification workflows. To increase confidence in compound identifications, the use of structural fragmentation data collected via tandem mass spectrometry (MS/MS or MS2) is vital. However, the availability of empirically collected MS/MS data for identification of unknowns is limited. Researchers have therefore turned to in silico generation of MS/MS data for use in HRMS-based screening studies. This paper describes the generation en masse of predicted MS/MS spectra for the entirety of the US EPA's DSSTox database using competitive fragmentation modelling and a freely available open source tool, CFM-ID. The generated dataset comprises predicted MS/MS spectra for ~700,000 structures, and mappings between predicted spectra, structures, associated substances, and chemical metadata. Together, these resources facilitate improved compound identifications in HRMS screening studies. These data are accessible via an SQL database, a comma-separated export file (.csv), and EPA's CompTox Chemicals Dashboard. Design Type(s) chemical structure classification objective • modeling and simulation objective • mass spectrometry data analysis objective Measurement Type(s) tandem mass spectrometry Technology Type(s) digital curation Factor Type(s) chemical entity Sample Characteristic(s) Machine-accessible metadata file describing the reported data (ISA-Tab format) [ABSTRACT FROM AUTHOR]

The article reviews the web site ChemSpider: The Free Chemical Database, available at www.chemspider.com.