The Natural Products Atlas: An Open Access Knowledge Base for Microbial Natural Products Discovery | ACS Central Science

Abstract:  Despite rapid evolution in the area of microbial natural products chemistry, there is currently no open access database containing all microbially produced natural product structures. Lack of availability of these data is preventing the implementation of new technologies in natural products science. Specifically, development of new computational strategies for compound characterization and identification are being hampered by the lack of a comprehensive database of known compounds against which to compare experimental data. The creation of an open access, community-maintained database of microbial natural product structures would enable the development of new technologies in natural products discovery and improve the interoperability of existing natural products data resources. However, these data are spread unevenly throughout the historical scientific literature, including both journal articles and international patents. These documents have no standard format, are often not digitized as machine readable text, and are not publicly available. Further, none of these documents have associated structure files (e.g., MOL, InChI, or SMILES), instead containing images of structures. This makes extraction and formatting of relevant natural products data a formidable challenge. Using a combination of manual curation and automated data mining approaches we have created a database of microbial natural products (The Natural Products Atlas, www.npatlas.org) that includes 24?594 compounds and contains referenced data for structure, compound names, source organisms, isolation references, total syntheses, and instances of structural reassignment. This database is accompanied by an interactive web portal that permits searching by structure, substructure, and physical properties. The Web site also provides mechanisms for visualizing natural products chemical space and dashboards for displaying author and discovery timeline data. These interactive tools offer a powerful knowledge base for natural products discovery with a central interface for structure and property-based searching and presents new viewpoints on structural diversity in natural products. The Natural Products Atlas has been developed under FAIR principles (Findable, Accessible, Interoperable, and Reusable) and is integrated with other emerging natural product databases, including the Minimum Information About a Biosynthetic Gene Cluster (MIBiG) repository, and the Global Natural Products Social Molecular Networking (GNPS) platform. It is designed as a community-supported resource to provide a central repository for known natural product structures from microorganisms and is the first comprehensive, open access resource of this type. It is expected that the Natural Products Atlas will enable the development of new natural products discovery modalities and accelerate the process of structural characterization for complex natural products libraries.

The Natural Products Atlas: An Open Access Knowledge Base for Microbial Natural Products Discovery | ACS Central Science

Abstract:  Despite rapid evolution in the area of microbial natural products chemistry, there is currently no open access database containing all microbially produced natural product structures. Lack of availability of these data is preventing the implementation of new technologies in natural products science. Specifically, development of new computational strategies for compound characterization and identification are being hampered by the lack of a comprehensive database of known compounds against which to compare experimental data. The creation of an open access, community-maintained database of microbial natural product structures would enable the development of new technologies in natural products discovery and improve the interoperability of existing natural products data resources. However, these data are spread unevenly throughout the historical scientific literature, including both journal articles and international patents. These documents have no standard format, are often not digitized as machine readable text, and are not publicly available. Further, none of these documents have associated structure files (e.g., MOL, InChI, or SMILES), instead containing images of structures. This makes extraction and formatting of relevant natural products data a formidable challenge. Using a combination of manual curation and automated data mining approaches we have created a database of microbial natural products (The Natural Products Atlas, www.npatlas.org) that includes 24?594 compounds and contains referenced data for structure, compound names, source organisms, isolation references, total syntheses, and instances of structural reassignment. This database is accompanied by an interactive web portal that permits searching by structure, substructure, and physical properties. The Web site also provides mechanisms for visualizing natural products chemical space and dashboards for displaying author and discovery timeline data. These interactive tools offer a powerful knowledge base for natural products discovery with a central interface for structure and property-based searching and presents new viewpoints on structural diversity in natural products. The Natural Products Atlas has been developed under FAIR principles (Findable, Accessible, Interoperable, and Reusable) and is integrated with other emerging natural product databases, including the Minimum Information About a Biosynthetic Gene Cluster (MIBiG) repository, and the Global Natural Products Social Molecular Networking (GNPS) platform. It is designed as a community-supported resource to provide a central repository for known natural product structures from microorganisms and is the first comprehensive, open access resource of this type. It is expected that the Natural Products Atlas will enable the development of new natural products discovery modalities and accelerate the process of structural characterization for complex natural products libraries.

OPEN SCHOLARSHIP position statement from the Biochemical Society and Portland Press

“Currently: ? We publish two fully-OA journals, and one of these is currently sustained by article publishing charges (APC) at an article-by-article level; in addition, we publish five hybrid journals where authors may opt to pay an APC to have their article published OA. ? For titles on the hybrid model we avoid ‘double dipping’ (charging twice for the same articles) through two routes: APCs are discounted for corresponding authors based at subscribing institutions; in addition, subscription prices are set, each year, based on the number of paywalled articles in the preceding years to account for OA content published in hybrid titles. ? There are a variety of mechanisms employed by different publishers to avoid double-dipping. We are supportive of efforts to standardize and agree common principles around transparent pricing of hybrid journals that demonstrate, objectively, the avoidance of double dipping….

Looking ahead: ? We are seeking to transition our hybrid journals to full-OA in a way that supports researchers and keeps the Society financially viable. ? We strongly believe that the ability to publish research should not be linked to individual researchers’ ability to pay; we are enthusiastic about all opportunities to remove author-facing invoices from OA publishing. To enable a transition away from paywalls, we seek to offer as much APC-free OA as possible that will be supported though continuing and new partnerships with institutions, consortia and funders….

Open Science – Symposia – Beilstein-Institut zur Förderung der Chemischen Wissenschaften

“This symposium addresses the interfaces between the laboratory and the new infrastructures currently being set up. Open Science aims to make research and development more effective by better supporting collaboration. The advantages of making data open will be critically reviewed and the development of highly interconnected, collaborative research in data driven laboratories of the future will be discussed. Adoption of the FAIR data principles is an important step to support this.

In chemistry, biochemistry and neighbouring areas, funding agencies and national and supranational bodies are strongly advocating the sharing and depositing of data. To make this work the incentive structures for academics need to be realigned, investment in infrastructure and new technologies increased, and the awareness of the advantages of making data available for AI and similar technologies heightened….”

Has the Time Come for Preprints in Chemistry? | ACS Omega

Abstract:  Chemistry is among the last of the core natural sciences to embrace preprints, namely, the publication of non peer-reviewed scientific articles on the Internet. After a brief insight into the origins and the purpose of preprints in science, we conducted a concrete analysis of the concrete situation, aiming at providing an answer to several questions. Why has the chemistry community been late in embracing preprints? Is this in relation with the slow acceptance of open-access publishing by the same community? Will preprints become a common habit also for chemistry scholars?

Repositioning the Chemical Information Science… | F1000Research

Abstract:  The Chemical Information Science Gateway (CISG) of F1000Research was originally conceptualized as a forum for high-quality publications in chemical information science (CIS) including chemoinformatics. Adding a publication venue with open access and open peer review to the CIS field was a prime motivation for the introduction of CISG, aiming to support open science in this area. Herein, the CISG concept is revisited and the development of the gateway over the past four years is reviewed. In addition, opportunities are discussed to better position CISG within the publication spectrum of F1000Research and further increase its visibility and attractiveness for scientific contributions.

Researchers reject APC-based OA publishing as promoted by Plan S – For Better Science

“Lynn Kamerlin, Bas de Bruin and their colleagues have been the most vocal critics of Plan S from the very beginning, braving continuous opposition from certain OA leaders. Now that final Plan S guidelines were released, the chemists publish this Open Letter expressing their worry about a possible dystopian OA future….”

Researchers warn open access Plan S may still be too rushed, despite one-year delay | News | Chemistry World

The funders behind Plan S – an ambitious set of policies that aims to speed up the transition to open access publishing – have released updated guidelines that delay implementing the plan for a year and provide more clarity on transformative publishing agreements.

The revisions have attracted mixed reactions from chemists, some of whom welcome the clarity while others worry it will harm their careers.

COAlition S – the group of funders behind Plan S – has said the plan will now come into effect in 2021 rather than the proposed 2020 date to give publishers more time to shift their business models. While many researchers agree this is necessary, some say it still does not allow enough time for the scientific community to adapt….”

Envisioning data sharing for the biocomputing community | Interface Focus

Abstract:  The scientific community is facing a revolution in several aspects of its modus operandi, ranging from the way science is done—data production, collection, analysis—to the way it is communicated and made available to the public, be that an academic audience or a general one. These changes have been largely determined by two key players: the big data revolution or, less triumphantly, the impressive increase in computational power and data storage capacity; and the accelerating paradigm switch in science publication, with people and policies increasingly pushing towards open access frameworks. All these factors prompt the undertaking of initiatives oriented to maximize the effectiveness of the computational efforts carried out worldwide. Taking the moves from these observations, we here propose a coordinated initiative, focusing on the computational biophysics and biochemistry community but general and flexible in its defining characteristics, which aims at addressing the growing necessity of collecting, rationalizing, sharing and exploiting the data produced in this scientific environment.

novel open access web portal for integrating mechanistic and toxicogenomic study results | Toxicological Sciences | Oxford Academic

Abstract:  Applying toxicogenomics to improving the safety profile of drug candidates and crop protection molecules is most useful when it identifies relevant biological and mechanistic information that highlights risks and informs risk mitigation strategies. Pathway-based approaches, such as GSEA, integrate toxicogenomic data with known biological process and pathways. Network methods help define unknown biological processes and offer data reduction advantages. Integrating the two approaches would improve interpretation of toxicogenomic information. Barriers to the routine application of these methods in genome-wide transcriptomic studies include a need for “hands-on” computer programming experience, the selection of one or more analysis methods (e.g. pathway analysis methods), the sensitivity of results to algorithm parameters, and challenges in linking differential gene expression to variation in safety outcomes. To facilitate adoption and reproducibility of gene expression analysis in safety studies, we have developed Collaborative Toxicogenomics (CTox), an open-access integrated web portal using the Django web framework. The software, developed with the Python programming language, is modular, extensible and implements “best-practice” methods in computational biology. New study results are compared to over 4,000 rodent liver experiments from Drug Matrix and open TG-GATEs. A unique feature of the software is the ability to integrate clinical chemistry and histopathology-derived outcomes with results from gene expression studies, leading to relevant mechanistic conclusions. We describe its application by analyzing the effects of several toxicants on liver gene expression and exemplify application to predicting toxicity study outcomes upon chronic treatment from expression changes in acute-duration studies.