PubChem 2023 update.

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a popular chemical information resource that serves a wide range of use cases. In the past two years, a number of changes were made to PubChem. Data from more than 120 data sources was added to PubChem. Some major highlights include: the integration of Google Patents data into PubChem, which greatly expanded the coverage of the PubChem Patent data collection; the creation of the Cell Line and Taxonomy data collections, which provide quick and easy access to chemical information for a given cell line and taxon, respectively; and the update of the bioassay data model. In addition, new functionalities were added to the PubChem programmatic access protocols, PUG-REST and PUG-View, including support for target-centric data download for a given protein, gene, pathway, cell line, and taxon and the addition of the 'standardize' option to PUG-REST, which returns the standardized form of an input chemical structure. A significant update was also made to PubChemRDF. The present paper provides an overview of these changes.

PubChem in 2021: new data content and improved web interfaces.

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a popular chemical information resource that serves the scientific community as well as the general public, with millions of unique users per month. In the past two years, PubChem made substantial improvements. Data from more than 100 new data sources were added to PubChem, including chemical-literature links from Thieme Chemistry, chemical and physical property links from SpringerMaterials, and patent links from the World Intellectual Properties Organization (WIPO). PubChem's homepage and individual record pages were updated to help users find desired information faster. This update involved a data model change for the data objects used by these pages as well as by programmatic users. Several new services were introduced, including the PubChem Periodic Table and Element pages, Pathway pages, and Knowledge panels. Additionally, in response to the coronavirus disease 2019 (COVID-19) outbreak, PubChem created a special data collection that contains PubChem data related to COVID-19 and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

PubChem 2019 update: improved access to chemical data.

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a key chemical information resource for the biomedical research community. Substantial improvements were made in the past few years. New data content was added, including spectral information, scientific articles mentioning chemicals, and information for food and agricultural chemicals. PubChem released new web interfaces, such as PubChem Target View page, Sources page, Bioactivity dyad pages and Patent View page. PubChem also released a major update to PubChem Widgets and introduced a new programmatic access interface, called PUG-View. This paper describes these new developments in PubChem.

PubChem BioAssay: 2017 update.

PubChem's BioAssay database (https://pubchem.ncbi.nlm.nih.gov) has served as a public repository for small-molecule and RNAi screening data since 2004 providing open access of its data content to the community. PubChem accepts data submission from worldwide researchers at academia, industry and government agencies. PubChem also collaborates with other chemical biology database stakeholders with data exchange. With over a decade's development effort, it becomes an important information resource supporting drug discovery and chemical biology research. To facilitate data discovery, PubChem is integrated with all other databases at NCBI. In this work, we provide an update for the PubChem BioAssay database describing several recent development including added sources of research data, redesigned BioAssay record page, new BioAssay classification browser and new features in the Upload system facilitating data sharing.

PubChem Substance and Compound databases.

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public repository for information on chemical substances and their biological activities, launched in 2004 as a component of the Molecular Libraries Roadmap Initiatives of the US National Institutes of Health (NIH). For the past 11 years, PubChem has grown to a sizable system, serving as a chemical information resource for the scientific research community. PubChem consists of three inter-linked databases, Substance, Compound and BioAssay. The Substance database contains chemical information deposited by individual data contributors to PubChem, and the Compound database stores unique chemical structures extracted from the Substance database. Biological activity data of chemical substances tested in assay experiments are contained in the BioAssay database. This paper provides an overview of the PubChem Substance and Compound databases, including data sources and contents, data organization, data submission using PubChem Upload, chemical structure standardization, web-based interfaces for textual and non-textual searches, and programmatic access. It also gives a brief description of PubChem3D, a resource derived from theoretical three-dimensional structures of compounds in PubChem, as well as PubChemRDF, Resource Description Framework (RDF)-formatted PubChem data for data sharing, analysis and integration with information contained in other databases.

PubChem BioAssay: 2014 update.

PubChem's BioAssay database (http://pubchem.ncbi.nlm.nih.gov) is a public repository for archiving biological tests of small molecules generated through high-throughput screening experiments, medicinal chemistry studies, chemical biology research and drug discovery programs. In addition, the BioAssay database contains data from high-throughput RNA interference screening aimed at identifying critical genes responsible for a biological process or disease condition. The mission of PubChem is to serve the community by providing free and easy access to all deposited data. To this end, PubChem BioAssay is integrated into the National Center for Biotechnology Information retrieval system, making them searchable by Entrez queries and cross-linked to other biomedical information archived at National Center for Biotechnology Information. Moreover, PubChem BioAssay provides web-based and programmatic tools allowing users to search, access and analyze bioassay test results and metadata. In this work, we provide an update for the PubChem BioAssay resource, such as information content growth, new developments supporting data integration and search, and the recently deployed PubChem Upload to streamline chemical structure and bioassay submissions.

Structural Perspectives on the Evolutionary Expansion of Unique Protein-Protein Binding Sites.

Structures of protein complexes provide atomistic insights into protein interactions. Human proteins represent a quarter of all structures in the Protein Data Bank; however, available protein complexes cover less than 10% of the human proteome. Although it is theoretically possible to infer interactions in human proteins based on structures of homologous protein complexes, it is still unclear to what extent protein interactions and binding sites are conserved, and whether protein complexes from remotely related species can be used to infer interactions and binding sites. We considered biological units of protein complexes and clustered protein-protein binding sites into similarity groups based on their structure and sequence, which allowed us to identify unique binding sites. We showed that the growth rate of the number of unique binding sites in the Protein Data Bank was much slower than the growth rate of the number of structural complexes. Next, we investigated the evolutionary roots of unique binding sites and identified the major phyletic branches with the largest expansion in the number of novel binding sites. We found that many binding sites could be traced to the universal common ancestor of all cellular organisms, whereas relatively few binding sites emerged at the major evolutionary branching points. We analyzed the physicochemical properties of unique binding sites and found that the most ancient sites were the largest in size, involved many salt bridges, and were the most compact and least planar. In contrast, binding sites that appeared more recently in the evolution of eukaryotes were characterized by a larger fraction of polar and aromatic residues, and were less compact and more planar, possibly due to their more transient nature and roles in signaling processes.

National health accounts data from 1996 to 2010: a systematic review.

OBJECTIVE: To collect, compile and evaluate publicly available national health accounts (NHA) reports produced worldwide between 1996 and 2010. METHODS: We downloaded country-generated NHA reports from the World Health Organization global health expenditure database and the Organisation for Economic Co-operation and Development (OECD) StatExtract website. We also obtained reports from Abt Associates, through contacts in individual countries and through an online search. We compiled data in the four main types used in these reports: (i) financing source; (ii) financing agent; (iii) health function; and (iv) health provider. We combined and adjusted data to conform with OECD's first edition of A system of health accounts manual, (2000). FINDINGS: We identified 872 NHA reports from 117 countries containing a total of 2936 matrices for the four data types. Most countries did not provide complete health expenditure data: only 252 of the 872 reports contained data in all four types. Thirty-eight countries reported an average not-specified-by-kind value greater than 20% for all data types and years. Some countries reported substantial year-on-year changes in both the level and composition of health expenditure that were probably produced by data-generation processes. All study data are publicly available at http://vizhub.healthdata.org/nha/. CONCLUSION: Data from NHA reports on health expenditure are often incomplete and, in some cases, of questionable quality. Better data would help finance ministries allocate resources to health systems, assist health ministries in allocating capital within the health sector and enable researchers to make accurate comparisons between health systems.

Large-scale mapping of human protein interactome using structural complexes.

Although the identification of protein interactions by high-throughput (HTP) methods progresses at a fast pace, 'interactome' data sets still suffer from high rates of false positives and low coverage. To map the human protein interactome, we describe a new framework that uses experimental evidence on structural complexes, the atomic details of binding interfaces and evolutionary conservation. The structurally inferred interaction network is highly modular and more functionally coherent compared with experimental interaction networks derived from multiple literature citations. Moreover, structurally inferred and high-confidence HTP networks complement each other well, allowing us to construct a merged network to generate testable hypotheses and provide valuable experimental leads.

IBIS (Inferred Biomolecular Interaction Server) reports, predicts and integrates multiple types of conserved interactions for proteins.

We have recently developed the Inferred Biomolecular Interaction Server (IBIS) and database, which reports, predicts and integrates different types of interaction partners and locations of binding sites in proteins based on the analysis of homologous structural complexes. Here, we highlight several new IBIS features and options. The server's webpage is now redesigned to allow users easier access to data for different interaction types. An entry page is added to give a quick summary of available results and to now accept protein sequence accessions. To elucidate the formation of protein complexes, not just binary interactions, IBIS currently presents an expandable interaction network. Previously, IBIS provided annotations for four different types of binding partners: proteins, small molecules, nucleic acids and peptides; in the current version a new protein-ion interaction type has been added. Several options provide easy downloads of IBIS data for all Protein Data Bank (PDB) protein chains and the results for each query. In this study, we show that about one-third of all RefSeq sequences can be annotated with IBIS interaction partners and binding sites. The IBIS server is available at http://www.ncbi.nlm.nih.gov/Structure/ibis/ibis.cgi and updated biweekly.

PubChem's BioAssay Database.

PubChem (http://pubchem.ncbi.nlm.nih.gov) is a public repository for biological activity data of small molecules and RNAi reagents. The mission of PubChem is to deliver free and easy access to all deposited data, and to provide intuitive data analysis tools. The PubChem BioAssay database currently contains 500,000 descriptions of assay protocols, covering 5000 protein targets, 30,000 gene targets and providing over 130 million bioactivity outcomes. PubChem's bioassay data are integrated into the NCBI Entrez information retrieval system, thus making PubChem data searchable and accessible by Entrez queries. Also, as a repository, PubChem constantly optimizes and develops its deposition system answering many demands of both high- and low-volume depositors. The PubChem information platform allows users to search, review and download bioassay description and data. The PubChem platform also enables researchers to collect, compare and analyze biological test results through web-based and programmatic tools. In this work, we provide an update for the PubChem BioAssay resource, including information content growth, data model extension and new developments of data submission, retrieval, analysis and download tools.

Potential measurement error from vessel reflex and multiple light paths in dual-wavelength retinal oximetry.

PURPOSE: This study aims to characterize the dependence of measured retinal arterial and venous saturation on vessel diameter and central reflex in retinal oximetry, with an ultimate goal of identifying potential causes and suggesting approaches to improve measurement accuracy. METHODS: In 10 subjects, oxygen saturation, vessel diameter and optical density are obtained using Oxymap Analyzer software without diameter correction. Diameter dependence of saturation is characterized using linear regression between measured values of saturation and diameter. Occurrences of negative values of vessel optical densities (ODs) associated with central vessel reflex are acquired from Oxymap Analyzer. A conceptual model is used to calculate the ratio of optical densities (ODRs) according to retinal reflectance properties and single and double-pass light transmission across fixed path lengths. Model-predicted values are compared with measured oximetry values at different vessel diameters. RESULTS: Venous saturation shows an inverse relationship with vessel diameter (D) across subjects, with a mean slope of -0.180 (SE = 0.022) %/µm (20 < D < 180 µm) and a more rapid saturation increase at small vessel diameters reaching to over 80%. Arterial saturation yields smaller positive and negative slopes in individual subjects, with an average of -0.007 (SE = 0.021) %/µm (20 < D < 200 µm) across all subjects. Measurements where vessel brightness exceeds that of the retinal background result in negative values of optical density, causing an artifactual increase in saturation. Optimization of model reflectance values produces a good fit of the conceptual model to measured ODRs. CONCLUSION: Measurement artefacts in retinal oximetry are caused by strong central vessel reflections, and apparent diameter sensitivity may result from single and double-pass transmission in vessels. Improvement in correction for vessel diameter is indicated for arteries however further study is necessary for venous corrections.

The role of comprehensive stress cardiac MRI in autoimmune rheumatic disease: A review.

Cardiovascular disease is the leading cause of morbidity and mortality in patients with autoimmune rheumatic diseases. Much of this may be attributed to systemic inflammation resulting in coronary atherosclerosis and myocarditis. Cardiac magnetic resonance imaging is the gold standard for the evaluation of cardiac structure and function, including tissue characterization, which allows for detection of myocardial edema, inflammation, and fibrosis. Advances in parametric mapping and coronary flow reserve measurement techniques have the potential to change the diagnosis, risk stratification, and management of patients with autoimmune rheumatic diseases. We provide an overview of the current evidence and suggest potential future roles for the use of comprehensive cardiac magnetic resonance in patients with autoimmune rheumatic diseases in the field of cardio-rheumatology.

Clinical Management of Brugada Syndrome: Commentary From the Experts.

Although there is consensus on the management of patients with Brugada Syndrome with high risk for sudden cardiac arrest, asymptomatic or intermediate-risk patients present clinical management challenges. This document explores the management opinions of experts throughout the world for patients with Brugada Syndrome who do not fit guideline recommendations. Four real-world clinical scenarios were presented with commentary from small expert groups for each case. All authors voted on case-specific questions to evaluate the level of consensus among the entire group in nuanced diagnostic and management decisions relevant to each case. Points of agreement, points of controversy, and gaps in knowledge are highlighted.

Adding open spectral data to MassBank and PubChem using open source tools to support non-targeted exposomics of mixtures.

The term "exposome" is defined as a comprehensive study of life-course environmental exposures and the associated biological responses. Humans are exposed to many different chemicals, which can pose a major threat to the well-being of humanity. Targeted or non-targeted mass spectrometry techniques are widely used to identify and characterize various environmental stressors when linking exposures to human health. However, identification remains challenging due to the huge chemical space applicable to exposomics, combined with the lack of sufficient relevant entries in spectral libraries. Addressing these challenges requires cheminformatics tools and database resources to share curated open spectral data on chemicals to improve the identification of chemicals in exposomics studies. This article describes efforts to contribute spectra relevant for exposomics to the open mass spectral library MassBank (https://www.massbank.eu) using various open source software efforts, including the R packages RMassBank and Shinyscreen. The experimental spectra were obtained from ten mixtures containing toxicologically relevant chemicals from the US Environmental Protection Agency (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT). Following processing and curation, 5582 spectra from 783 of the 1268 ENTACT compounds were added to MassBank, and through this to other open spectral libraries (e.g., MoNA, GNPS) for community benefit. Additionally, an automated deposition and annotation workflow was developed with PubChem to enable the display of all MassBank mass spectra in PubChem, which is rerun with each MassBank release. The new spectral records have already been used in several studies to increase the confidence in identification in non-target small molecule identification workflows applied to environmental and exposomics research.

ComSin: database of protein structures in bound (complex) and unbound (single) states in relation to their intrinsic disorder.

Most of the proteins in a cell assemble into complexes to carry out their function. In this work, we have created a new database (named ComSin) of protein structures in bound (complex) and unbound (single) states to provide a researcher with exhaustive information on structures of the same or homologous proteins in bound and unbound states. From the complete Protein Data Bank (PDB), we selected 24 910 pairs of protein structures in bound and unbound states, and identified regions of intrinsic disorder. For 2448 pairs, the proteins in bound and unbound states are identical, while 7129 pairs have sequence identity 90% or larger. The developed server enables one to search for proteins in bound and unbound states with several options including sequence similarity between the corresponding proteins in bound and unbound states, and validation of interaction interfaces of protein complexes. Besides that, through our web server, one can obtain necessary information for studying disorder-to-order and order-to-disorder transitions upon complex formation, and analyze structural differences between proteins in bound and unbound states. The database is available at http://antares.protres.ru/comsin/.

An overview of the PubChem BioAssay resource.

The PubChem BioAssay database (http://pubchem.ncbi.nlm.nih.gov) is a public repository for biological activities of small molecules and small interfering RNAs (siRNAs) hosted by the US National Institutes of Health (NIH). It archives experimental descriptions of assays and biological test results and makes the information freely accessible to the public. A PubChem BioAssay data entry includes an assay description, a summary and detailed test results. Each assay record is linked to the molecular target, whenever possible, and is cross-referenced to other National Center for Biotechnology Information (NCBI) database records. 'Related BioAssays' are identified by examining the assay target relationship and activity profile of commonly tested compounds. A key goal of PubChem BioAssay is to make the biological activity information easily accessible through the NCBI information retrieval system-Entrez, and various web-based PubChem services. An integrated suite of data analysis tools are available to optimize the utility of the chemical structure and biological activity information within PubChem, enabling researchers to aggregate, compare and analyze biological test results contributed by multiple organizations. In this work, we describe the PubChem BioAssay database, including data model, bioassay deposition and utilities that PubChem provides for searching, downloading and analyzing the biological activity information contained therein.

Inferred Biomolecular Interaction Server--a web server to analyze and predict protein interacting partners and binding sites.

IBIS is the NCBI Inferred Biomolecular Interaction Server. This server organizes, analyzes and predicts interaction partners and locations of binding sites in proteins. IBIS provides annotations for different types of binding partners (protein, chemical, nucleic acid and peptides), and facilitates the mapping of a comprehensive biomolecular interaction network for a given protein query. IBIS reports interactions observed in experimentally determined structural complexes of a given protein, and at the same time IBIS infers binding sites/interacting partners by inspecting protein complexes formed by homologous proteins. Similar binding sites are clustered together based on their sequence and structure conservation. To emphasize biologically relevant binding sites, several algorithms are used for verification in terms of evolutionary conservation, biological importance of binding partners, size and stability of interfaces, as well as evidence from the published literature. IBIS is updated regularly and is freely accessible via http://www.ncbi.nlm.nih.gov/Structure/ibis/ibis.html.

Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data.

Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.

Knowledge-based annotation of small molecule binding sites in proteins.

BACKGROUND: The study of protein-small molecule interactions is vital for understanding protein function and for practical applications in drug discovery. To benefit from the rapidly increasing structural data, it is essential to improve the tools that enable large scale binding site prediction with greater emphasis on their biological validity. RESULTS: We have developed a new method for the annotation of protein-small molecule binding sites, using inference by homology, which allows us to extend annotation onto protein sequences without experimental data available. To ensure biological relevance of binding sites, our method clusters similar binding sites found in homologous protein structures based on their sequence and structure conservation. Binding sites which appear evolutionarily conserved among non-redundant sets of homologous proteins are given higher priority. After binding sites are clustered, position specific score matrices (PSSMs) are constructed from the corresponding binding site alignments. Together with other measures, the PSSMs are subsequently used to rank binding sites to assess how well they match the query and to better gauge their biological relevance. The method also facilitates a succinct and informative representation of observed and inferred binding sites from homologs with known three-dimensional structures, thereby providing the means to analyze conservation and diversity of binding modes. Furthermore, the chemical properties of small molecules bound to the inferred binding sites can be used as a starting point in small molecule virtual screening. The method was validated by comparison to other binding site prediction methods and to a collection of manually curated binding site annotations. We show that our method achieves a sensitivity of 72% at predicting biologically relevant binding sites and can accurately discriminate those sites that bind biological small molecules from non-biological ones. CONCLUSIONS: A new algorithm has been developed to predict binding sites with high accuracy in terms of their biological validity. It also provides a common platform for function prediction, knowledge-based docking and for small molecule virtual screening. The method can be applied even for a query sequence without structure. The method is available at http://www.ncbi.nlm.nih.gov/Structure/ibis/ibis.cgi.