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Twitter is in turmoil and the scholarly community on the platform is once again starting to migrate. As with the early internet, scholarly organizations are at the forefront of developing and implementing a decentralized alternative to Twitter, Mastodon. Both historically and conceptually, this is not a new situation for the scholarly community. Historically, scholars were forced to leave social media platform FriendFeed after it was bought by Facebook in 2006. Conceptually, the problems associated with public scholarly discourse subjected to the whims of corporate owners are not unlike those of scholarly journals owned by monopolistic corporations: in both cases the perils associated with a public good in private hands are palpable. For both short form (Twitter/Mastodon) and longer form (journals) scholarly discourse, decentralized solutions exist, some of which are already enjoying some institutional support. Here we argue that scholarly organizations, in particular learned societies, are now facing a golden opportunity to rethink their hesitations towards such alternatives and support the migration of the scholarly community from Twitter to Mastodon by hosting Mastodon instances. Demonstrating that the scholarly community is capable of creating a truly public square for scholarly discourse, impervious to private takeover, might renew confidence and inspire the community to focus on analogous solutions for the remaining scholarly record-encompassing text, data and code-to safeguard all publicly owned scholarly knowledge., Competing Interests: We declare we have no competing interests., (© 2023 The Authors.)

Bioactive molecules such as drugs, pesticides and food additives are produced in large numbers by many commercial and academic groups around the world. Enormous quantities of data are generated on the biological properties and quality of these molecules. Access to such data - both on licensed and commercially available compounds, and also on those that fail during development - is crucial for understanding how improved molecules could be developed. For example, computational analysis of aggregated data on molecules that are investigated in drug discovery programmes has led to a greater understanding of the properties of successful drugs. However, the information required to perform these analyses is rarely published, and when it is made available it is often missing crucial data or is in a format that is inappropriate for efficient data-mining. Here, we propose a solution: the definition of reporting guidelines for bioactive entities - the Minimum Information About a Bioactive Entity (MIABE) - which has been developed by representatives of pharmaceutical companies, data resource providers and academic groups.

We have produced an open source, freely available, algorithm (Open Parser for Systematic IUPAC Nomenclature, OPSIN) that interprets the majority of organic chemical nomenclature in a fast and precise manner. This has been achieved using an approach based on a regular grammar. This grammar is used to guide tokenization, a potentially difficult problem in chemical names. From the parsed chemical name, an XML parse tree is constructed that is operated on in a stepwise manner until the structure has been reconstructed from the name. Results from OPSIN on various computer generated name/structure pair sets are presented. These show exceptionally high precision (99.8%+) and, when using general organic chemical nomenclature, high recall (98.7-99.2%). This software can serve as the basis for future open source developments of chemical name interpretation.

Chemistry text mining tools should be interoperable and adaptable regardless of system-level implementation, installation or even programming issues. We aim to abstract the functionality of these tools from the underlying implementation via reconfigurable workflows for automatically identifying chemical names. To achieve this, we refactored an established named entity recogniser (in the chemistry domain), OSCAR and studied the impact of each component on the net performance. We developed two reconfigurable workflows from OSCAR using an interoperable text mining framework, U-Compare. These workflows can be altered using the drag-&-drop mechanism of the graphical user interface of U-Compare. These workflows also provide a platform to study the relationship between text mining components such as tokenisation and named entity recognition (using maximum entropy Markov model (MEMM) and pattern recognition based classifiers). Results indicate that, for chemistry in particular, eliminating noise generated by tokenisation techniques lead to a slightly better performance than others, in terms of named entity recognition (NER) accuracy. Poor tokenisation translates into poorer input to the classifier components which in turn leads to an increase in Type I or Type II errors, thus, lowering the overall performance. On the Sciborg corpus, the workflow based system, which uses a new tokeniser whilst retaining the same MEMM component, increases the F-score from 82.35% to 84.44%. On the PubMed corpus, it recorded an F-score of 84.84% as against 84.23% by OSCAR.

This work presents thermochemical data for possible gas phase intermediate species in an industrial rutile chlorinator. An algorithm developed for previous work is employed to ensure that all possible species are considered, reducing the number of important species neglected. Thermochemical data and enthalpies of formation are calculated for 22 new species using density functional theory, post Hartree-Fock coupled cluster calculations, and statistical mechanics. Equilibrium calculations are performed to identify whether any Ti/C intermediates are likely to be important to the high temperature industrial process. These new species are not present at high concentration in the exit stream. It is therefore likely that the two chemical processes do not interact. Rather, the Cl₂ rapidly reacts with the solid TiO₂ to form TiCl₄ and O₂. The latter then reacts with the solid C to form CO and CO₂ and provide the heat. Data for all the new species is provided as Supporting Information. Finally, a new methodology for data collaboration is investigated in which the data is made openly accessible using the resource description framework. Example scripts are provided to demonstrate how to query and retrieve the data automatically.

Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.

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.

Polymers are among the most important classes of materials but are only inadequately supported by modern informatics. The paper discusses the reasons why polymer informatics is considerably more challenging than small molecule informatics and develops a vision for the computer-aided design of polymers, based on modern semantic web technologies. The paper then discusses the development of Polymer Markup Language (PML). PML is an extensible language, designed to support the (structural) representation of polymers and polymer-related information. PML closely interoperates with Chemical Markup Language (CML) and overcomes a number of the previously identified challenges.

The SPECTRa (Submission, Preservation and Exposure of Chemistry Teaching and Research Data) project has investigated the practices of chemists in archiving and disseminating primary chemical data from academic research laboratories. To redress the loss of the large amount of data never archived or disseminated, we have developed software for data publication into departmental and institutional Open Access digital repositories (DSpace). Data adhering to standard formats in selected disciplines (crystallography, NMR, computational chemistry) is transformed to XML (CML, Chemical Markup Language) which provides added validation. Context-specific chemical metadata and persistent Handle identifiers are added to enable long-term data reuse. It was found essential to provide an embargo mechanism, and policies for operating this and other processes are presented.

CMLSpect is an extension of Chemical Markup Language (CML) for managing spectral and other analytical data. It is designed to be flexible enough to contain a wide variety of spectral data. The paper describes the CMLElements used and gives practical examples for common types of spectra. In addition it demonstrates how different views of the data can be expressed and what problems still exist.

Background: There is a need for software applications that provide users with a complete and extensible toolkit for chemo- and bioinformatics accessible from a single workbench. Commercial packages are expensive and closed source, hence they do not allow end users to modify algorithms and add custom functionality. Existing open source projects are more focused on providing a framework for integrating existing, separately installed bioinformatics packages, rather than providing user-friendly interfaces. No open source chemoinformatics workbench has previously been published, and no successful attempts have been made to integrate chemo- and bioinformatics into a single framework., Results: Bioclipse is an advanced workbench for resources in chemo- and bioinformatics, such as molecules, proteins, sequences, spectra, and scripts. It provides 2D-editing, 3D-visualization, file format conversion, calculation of chemical properties, and much more; all fully integrated into a user-friendly desktop application. Editing supports standard functions such as cut and paste, drag and drop, and undo/redo. Bioclipse is written in Java and based on the Eclipse Rich Client Platform with a state-of-the-art plugin architecture. This gives Bioclipse an advantage over other systems as it can easily be extended with functionality in any desired direction., Conclusion: Bioclipse is a powerful workbench for bio- and chemoinformatics as well as an advanced integration platform. The rich functionality, intuitive user interface, and powerful plugin architecture make Bioclipse the most advanced and user-friendly open source workbench for chemo- and bioinformatics. Bioclipse is released under Eclipse Public License (EPL), an open source license which sets no constraints on external plugin licensing; it is totally open for both open source plugins as well as commercial ones. Bioclipse is freely available at http://www.bioclipse.net.

The Blue Obelisk Movement (http://www.blueobelisk.org/) is the name used by a diverse Internet group promoting reusable chemistry via open source software development, consistent and complimentary chemoinformatics research, open data, and open standards. We outline recent examples of cooperation in the Blue Obelisk group: a shared dictionary of algorithms and implementations in chemoinformatics algorithms drawing from our various software projects; a shared repository of chemoinformatics data including elemental properties, atomic radii, isotopes, atom typing rules, and so forth; and Web services for the platform-independent use of chemoinformatics programs.

A set of components (CMLReact) for managing chemical and biochemical reactions has been added to CML. These can be combined to support most of the strategies for the formal representation of reactions. The elements, attributes, and types are formally defined as XMLSchema components, and their semantics are developed. New syntax and semantics in CML are reported and illustrated with 10 examples.

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.

Chemical information is now seen as critical for most areas of life sciences. But unlike Bioinformatics, where data is openly available and freely re-usable, most chemical information is closed and cannot be re-distributed without permission. This has led to a failure to adopt modern informatics and software techniques and therefore paucity of chemistry in bioinformatics. New technology, however, offers the hope of making chemical data (compounds and properties) free during the authoring process. We argue that the technology is already available; we require a collective agreement to enhance publication protocols.

Molecules, as defined by connectivity specified via the International Chemical Identifier (InChI), are precisely indexed by major web search engines so that Internet tools can be transparently used for unique structure searches.

We present an overview of the current state of public semantic chemistry and propose new approaches at a strategic and a detailed level. We show by example how a model for a Chemical Semantic Web can be constructed using machine-processed data and information from journal articles.

Automatically extracting chemical information from documents is a challenging task, but an essential one for dealing with the vast quantity of data that is available. The task is least difficult for structured documents, such as chemistry department web pages or the output of computational chemistry programs, but requires increasingly sophisticated approaches for less structured documents, such as chemical papers. The identification of key units of information, such as chemical names, makes the extraction of useful information from unstructured documents possible.

Bioinformatics involves both the automatic processing of large amounts of existing data and the creation of new types of information resource. Both will be required if the data are to be transformed into information and used to help in the discovery of drugs.

In the development of a treatment for AIDS, the HIV-1 protease has been identified as a good target enzyme for inhibitor design. We previously reported a series of dimeric penicillin-derived C2-symmetric HIV-1 protease inhibitors [Humber, D., et al. (1993) J. Med. Chem. 36, 3120-3128]. In an attempt to reduce the size and optimize the binding of these C2-symmetric inhibitors, molecular modeling studies led to a novel series of monomeric penicillin-derived inhibitors of HIV-1 protease. The binding modes of these monomeric inhibitors have been characterized by X-ray crystallographic and NMR studies. Crystal structures of HIV-1 protease complexed to three inhibitors (GR123976, GR126045, and GR137615) from this series identify the molecular details of the interactions. The binding of GR123976 (IC50 = 2.3 microM) exhibits good hydrophobic contacts but few electrostatic interactions. A strategy of structure-based design and chemical synthesis led to the elaboration of GR123976 to optimize interactions with the protein. Crystallographic analysis of HIV-1 protease complexed to GR126045 and GR137615 identified these interactions with the catalytic aspartates and the protein binding pockets. The crystal structures of the three complexes confirm the presence of the major interactions modeled in order to optimize potency and reveal details of the molecular recognition by HIV-1 protease of this novel series of nonpeptidic inhibitors.

A comparison has been made between the homology and hydrophobicity profiles of six interleukin amino acid sequences and that of the human interleukin 1 beta (IL-1 beta) for which a crystal structure exists. The resulting sequence alignment was used to build model structures for the sequences for three IL-1 alpha, two IL-1 beta and an interleukin receptor antagonist. Analysis of these structures demonstrates that the interleukin molecule has a strong electric dipole which is generated by the topological position of the amino acids in the sequence. Electrostatic surface calculations implicate a particular residues (Lys145) as being fundamental to interleukin activity and this supports site-directed mutation evidence that this residue is required for activity.

The binding modes of a series of penicillin-derived C2 symmetric dimer inhibitors of HIV-1 proteinase were investigated by NMR, protein crystallography, and molecular modeling. The compounds were found to bind in a symmetrical fashion, tracing and S-shaped course through the active site, with good hydrophobic interactions in the S1/S1' and S2/S2' pockets and hydrogen bonding of inhibitor amide groups. Interactions with the catalytic aspartates appeared poor and the protein conformation was very similar to that seen in complexes with peptidomimetics, in spite of the major differences in ligand structure.

An analysis of the stereochemistry of hydrogen bonding and metal binding to some nitrogen-containing heterocycles found in crystal structure determinations has shown that the interacting atom will generally lie in the plane of the heterocyclic ring system in a direction that approximately bisects the C-N-C angle of the heterocycle. The Cambridge Structural Database (CSD) of crystal structures of small molecules was used for this analysis because stereochemical data are available at high resolution and are amendable to comparative analysis. It was found that, for hydrogen bonding, a slight out-of-plane deviation of the binding atom is marginally more likely than an in-plane deviation. Metal ions appear to bind in a manner that is similar to that of hydrogen bonding to a protonated heterocycle, no matter what the chemical identity of the metal. The binding is more rigid, with less in-plane or out-of-plane deviation of the metal ion compared to the interaction with a hydrogen-bonding group. Some ab initio molecular orbital energy calculations give a measure of the energies involved when metal ions or hydrogen-bonding groups deviate from the plane of the ring system or from the line bisecting the C-N-C angle of the heterocycle. These results are compared with reported structural data (at lower resolution) for some acridine-oligonucleotide complexes and the surroundings of histidine rings in some protein crystal structures.

The solution structure of the fibrinogen antagonist, echistatin, has been determined by a combination of NMR and simulated annealing methods. While the structure of the disulphide-linked core is well-defined by the NMR data, the N- and C-termini and the loop bearing the RGD sequence (which is responsible for the fibrinogen antagonist properties) are poorly defined. The pattern of disulphide bridges, which could not be determined by classical methods, was predicted by a statistical analysis of the simulated annealing structures. This pattern is distinct from that for the homologous protein kistrin, leading to the novel suggestion that homologous proteins possess non-conserved patterns of disulphide bridges.

The 1H-NMR spectrum of the snake toxin echistatin has been assigned using homonuclear two-dimensional methods. Consideration of the NOE patterns, coupling constants and putative hydrogen bonds enabled two regular features of secondary structure to be deduced: a beta-sheet/turn between residues 8 and 13 and a small anti-parallel beta-sheet and bulge linking residues 16-20 with residues 30-33. The recognition region of the protein containing the residues RGD lies in a loop joining the two strands of the beta-sheet. The beta-bulge and the loop containing the RGD sequence undergo pH-dependent conformational interconversion, modulated by the side chain of Asp29.