Webinar 3: Chemistry data: Challenges and opportunities. 7 December 2023

We will explore ongoing and planned initiatives developing standards and tools, research infrastructures, and cultures to support FAIR chemistry data as well as its preparation, publication, and reuse.

Webinar 3: Challenges and opportunities

7 December 2023, 15.00-16.00 (GMT)

Register now  

Speakers

Sonja Herres Pawlis
“How to initiate the cultural change towards digital chemistry”
Sonja Herres-Pawlis
Chair of Bioinorganic Chemistry, RWTH Aachen

Samantha Kanza
“How can we combat heterogeneous, unfair and disparate data in digital chemistry? ”
Samantha Kanza
Senior Enterprise Fellow, University of Southampton
Pathfinder Lead, Physical Sciences Data Infrastructure (PSDI)

Guy Jones
“How data journals can support (chemistry) data sharing and discovery”
Guy Jones
Chief Editor of Scientific Data, Springer Nature

Register now for webinar 3


Sponsored by Revvity

Revvity Signals Software, formerly PerkinElmer Informatics, has over three decades of experience providing support for scientific workflows.

logo of Revvity Signals

Our powerful informatics solutions are used in R&D across disciplines from drug discovery to materials development. Now under our Signals Research Suite, our end-to-end SaaS solution integrates workflows to accelerate innovation and help scientists collaborate. In addition, our solution powered by TIBCO® Spotfire® can transform clinical trials.

From our flagship ChemDraw® and E-Notebook applications, to our Signals Research Suite, to our TIBCO® Spotfire® partnership for data analytics, Revvity Signals offers a powerful suite of scientific solutions.

Supported by



 

 

About ChemSpider

Explore more than 128 million structures on the ChemSpider database. Including over 200 data sources, ChemSpider is a valuable source of information for chemical scientists working with data.

Freely accessible and comprehensive, this rich source of structure-based chemistry information is a fundamental resource for chemical scientists working with data everywhere.

Learn more about ChemSpider

Webinar 2: What does the future hold? 17 November 2023

We will explore ongoing and planned initiatives developing standards and tools, research infrastructures, and cultures to support FAIR chemistry data as well as its preparation, publication, and reuse.

Webinar 2: What does the future hold?

Held on 17 November 2023 – recording available on-demand. Register now to watch the recording  

Speakers

Lynn Kamerlin
“Data explosion in chemistry: what are we going to do with all the data, and what will it do to us?” SLIDES
Lynn Kamerlin
Professor and Georgia Research Alliance Vasser Woolley Chair in Molecular Design, Georgia Tech


“Will an AI win a chemistry Nobel Prize and replace us?” SLIDES
Simon Coles
Professor of Structural Chemistry, University of Southampton

Anna Rulka
“Data sharing at the RSC” SLIDES
May Copsey
Executive Editor, Chemical Science, RSC
Anna Rulka
Executive Editor, Digital Discovery, RSC


Sponsored by Revvity

Revvity Signals Software, formerly PerkinElmer Informatics, has over three decades of experience providing support for scientific workflows.

logo of Revvity Signals

Our powerful informatics solutions are used in R&D across disciplines from drug discovery to materials development. Now under our Signals Research Suite, our end-to-end SaaS solution integrates workflows to accelerate innovation and help scientists collaborate. In addition, our solution powered by TIBCO® Spotfire® can transform clinical trials.

From our flagship ChemDraw® and E-Notebook applications, to our Signals Research Suite, to our TIBCO® Spotfire® partnership for data analytics, Revvity Signals offers a powerful suite of scientific solutions.

Supported by



 

 

About ChemSpider

Explore more than 128 million structures on the ChemSpider database. Including over 200 data sources, ChemSpider is a valuable source of information for chemical scientists working with data.

Freely accessible and comprehensive, this rich source of structure-based chemistry information is a fundamental resource for chemical scientists working with data everywhere.

Learn more about ChemSpider

Webinar 1: Where are we with digital chemistry data? Watch the recording

 

 

These webinars will explore how digital chemistry data is enabling research – existing models, current challenges and exemplars, and what’s needed to evolve towards a better future using chemistry data.

We will focus on how data is enabling research – existing models, current challenges and exemplars, and what’s needed to evolve a better future using chemistry data.

Webinar 1: Where are we with digital chemistry data?

Watch on-demand: Register now to watch the recording

Webinar recorded on 17 October 2023

Speakers

Leah McEwen
“WANTED: standard notation for reusable chemical data” SLIDES
Leah McEwen
Chemistry Librarian, Cornell University

Kevin Jablonka
Kevin Jablonka
Research Group Leader, University of Jena

Pierre Morieux

Pierre Morieux
Chemistry Product Marketing Manager, Revvity Signals

 


Sponsored by Revvity

Revvity Signals Software, formerly PerkinElmer Informatics, has over three decades of experience providing support for scientific workflows.

logo of Revvity Signals

Our powerful informatics solutions are used in R&D across disciplines from drug discovery to materials development. Now under our Signals Research Suite, our end-to-end SaaS solution integrates workflows to accelerate innovation and help scientists collaborate. In addition, our solution powered by TIBCO® Spotfire® can transform clinical trials.

From our flagship ChemDraw® and E-Notebook applications, to our Signals Research Suite, to our TIBCO® Spotfire® partnership for data analytics, Revvity Signals offers a powerful suite of scientific solutions.

Supported by


 

About ChemSpider

Explore more than 128 million structures on the ChemSpider database. Including over 200 data sources, ChemSpider is a valuable source of information for chemical scientists working with data.

Freely accessible and comprehensive, this rich source of structure-based chemistry information is a fundamental resource for chemical scientists working with data everywhere.

Learn more about ChemSpider

ChemSpider webinars – helping you embrace digital chemistry data with expert insights

How can you learn about chemistry data trends and best practices happening right now? Elevate your knowledge for future success with leading experts in our three-part webinar series.

The webinar series will focus on how data is enabling research – the current challenges and examples and how a better future can be created using chemistry data. It will showcase current and planned initiatives to develop standards and tools, research infrastructures, and developing cultures to support Findable Accessible Interoperable Reusable (FAIR) chemistry data preparation, publication and reuse.

Elevate your data practices  

Created as a free, three-part series for chemical scientists working with data, learn more about chemistry data today, what the future holds, and the current challenges and opportunities of digital chemistry data. Make the most of this opportunity to discover insights from the experts in the field – register for all three webinars.

Webinar 3: Challenges and opportunities

7 December 2023, 15.00-16.00 (GMT)

Register now  

Speakers

Sonja Herres Pawlis
“How to initiate the cultural change towards digital chemistry”
Sonja Herres-Pawlis
Chair of Bioinorganic Chemistry, RWTH Aachen

Samantha Kanza
“How can we combat heterogeneous, unfair and disparate data in digital chemistry?”
Samantha Kanza
Senior Enterprise Fellow, University of Southampton
Pathfinder Lead, Physical Sciences Data Infrastructure (PSDI)

Guy Jones

“How data journals can support (chemistry) data sharing and discovery”
Guy Jones
Chief Editor of Scientific Data, Springer Nature

Register now for webinar 3


Webinar 1: Where are we with digital chemistry data?

Held on 17 October 2023 – recording available on-demand. Register now to watch the recording

Speakers

Leah McEwen
“Wanted – standard notation for reusable chemistry data” SLIDES
Leah McEwen
Chemistry Librarian, Cornell University

Kevin Jablonka
Kevin Jablonka
Research Group Leader, University of Jena

Pierre Morieux

Pierre Morieux
Chemistry Product Marketing Manager, Revvity Signals


Webinar 2: What does the future hold?

Held on 17 November 2023 – recording available on-demand. Register now to watch the recording  

Speakers

Lynn Kamerlin
“Data explosion in chemistry: what are we going to do with all the data, and what will it do to us?” SLIDES
Lynn Kamerlin
Professor and Georgia Research Alliance Vasser Woolley Chair in Molecular Design, Georgia Tech


“Will an AI win a chemistry Nobel Prize and replace us?” SLIDES
Simon Coles
Professor of Structural Chemistry, University of Southampton

Anna Rulka
“Data sharing at the RSC” SLIDES
May Copsey
Executive Editor, Chemical Science, RSC
Anna Rulka
Executive Editor, Digital Discovery, RSC


Sponsored by Revvity

Revvity Signals Software, formerly PerkinElmer Informatics, has over three decades of experience providing support for scientific workflows.

logo of Revvity Signals

Our powerful informatics solutions are used in R&D across disciplines from drug discovery to materials development. Now under our Signals Research Suite, our end-to-end SaaS solution integrates workflows to accelerate innovation and help scientists collaborate. In addition, our solution powered by TIBCO® Spotfire® can transform clinical trials.

From our flagship ChemDraw® and E-Notebook applications, to our Signals Research Suite, to our TIBCO® Spotfire® partnership for data analytics, Revvity Signals offers a powerful suite of scientific solutions.

Supported by



 

About ChemSpider

Explore more than 128 million structures on the ChemSpider database. Including over 200 data sources, ChemSpider is a valuable source of information for chemical scientists working with data.

Freely accessible and comprehensive, this rich source of structure-based chemistry information is a fundamental resource for chemical scientists working with data everywhere.

Learn more about ChemSpider

Tips and tricks: generating machine-readable structural data from a structure

Interested in making your article more discoverable and usable? As a reader, you have probably spent a lot of time re-drawing structures from an image in a PDF, or have struggled to find all relevant articles because your compound of interest is called by different names in different articles (IUPAC name, trivial name, registry number, drug development ID, generic name, brand name, revised trivial name etc etc etc…).

If you’re already drawing a structure for an article you are preparing to submit, it only takes a few seconds to generate machine-readable mol files or structure identifiers like SMILES or InChI. Including these files or identifiers in your article or supplementary information helps make your article indexable and structure-searchable, and is a great way to make your article stand out.

Save as MOL fileSave as mol file

 

All major structure drawing packages can save structures as MOL files. They generally follow the same steps:

Choose File > Save As from the top menu OR press Ctrl+Shift+S.

Select “MDL Molfile”, “MDL SDFile”, or “.mol” or “.sdf” in the dropdown.

Please note: There may be more than one molfile format listed in the dropdown. If there is more than one option, please be aware that V2000 mol format is more common and is supported by all cheminformatics software packages. The V3000 mol file has some extra features, but is not universally supported, so it is advised that you use V2000 mol format to ensure maximum interoperability.


Copy as SMILES or InChI

Start by selecting the structure you would like to copy as SMILES or InChI.

Avogadro

Copy as - Avogadro

From the top menu, choose Edit > Copy As > SMILES or InChI

ChemDoodle

Copy as - chemdoodle

From the top menu, choose Edit > Copy As > Daylight SMILES or IUPAC InChI

OR

To copy as SMILES, press Ctrl+Alt+C

ChemDraw

Copy as InChI

From the top menu, choose Edit > Copy As > SMILES or InChI

OR

Right click, and choose Molecule > Copy As > SMILES or InChI

OR

To copy as SMILES, press Alt+Ctrl+C

ChemSketch

machine readable copy as - chemsketch

From the top menu, choose Tools > Generate > SMILES Notation or InChI for Structure

MarvinSketch

Copy as - Marvin

Press Ctrl+K, then select SMILES or InChI from the Copy As pop-up

OR

From the top menu, choose Edit > Copy As and select SMILES or InChI from the pop-up

OR

To copy as SMILES, press Ctrl+L

Finally, paste your SMILES or InChI into your document or spreadsheet.


The less time we have to spend re-drawing structures from pdfs, the more time we can devote to doing science. Luckily, it really couldn’t be quicker or easier to improve the discoverability and reusability of your article by including machine-readable structure files or identifiers. Let’s work together to make chemistry articles easier to find and use.

ChemSpider Mobile app

ChemSpider Mobile was an app developed by Molecular Materials Informatics Inc1 on behalf of the Royal Society of Chemistry to allow users to explore the benefits of ChemSpider on mobile devices. Since its launch we have made improvements to ChemSpider.com, including responsive design elements to allow it to work better on smart phones and tablets2 and upgrades to the ChemSpider web services3 that power it. As a result of these developments we felt it was timely to review the community’s need for the app and have taken the decision to discontinue support for the services that power the app from 31st October. We would like to thank everyone who used and provided feedback on the app to aid its development and encourage you to switch to using ChemSpider.com for future mobile use.

1. http://molmatinf.com/

2. http://blogs.rsc.org/chemspider/2015/05/21/introduction-to-the-new-chemspider-website/

3. https://developer.rsc.org/

Chemical Validation and Standardization Platform (CVSP)

The Chemical Validation and Standardization Platform (CVSP)1 was developed during the Open PHACTS IMI project2 to process chemical structure files through tested validation and standardization protocols. The aim was to provide the community with rigorous analysis of their chemical structure files to ensure that data released into the public domain via online databases was pre-validated. The online CVSP site provided a useful means to test the rulesets and allow users to validate their structure files, but the standalone website was taken offline in November 2018. As a legacy, the codebase and ruleset has been evolved and applied to the ChemSpider deposition system at deposit.chemspider.com3 and the community discussions around appropriate standardisation of chemical structure files continue. The original code is also available from GitHub.4

  1. The Chemical Validation and Standardization Platform (CVSP): large-scale automated validation of chemical structure datasets, J. Cheminf., 2015, 7:30, https://doi.org/10.1186/s13321-015-0072-8
  2. https://www.openphacts.org
  3. https://deposit.chemspider.com/
  4. https://github.com/openphacts/ops-crs/tree/master/CVSP

ChemSpider Pre-Deposition Filters

Written by Mark Archibald.

In a previous post (Behind the Scenes at ChemSpider) we discussed some of the challenges in upholding data quality across one of the largest chemical databases in the world. We identified automated filtering as a key tool when dealing with far more records than a human could reasonably handle. In this post we’ll go into more detail about how that filtering works, what the challenges are, and the role played by human intervention.

To perform this filtering we use KNIME, an open-source data processing platform. The wide range of KNIME nodes developed by the active cheminformatics community allows us to ask chemistry-specific questions of the data we process. In simple terms, input chemical structures that match our criteria are passed on to the next node, while those that don’t are written out to an error file. After processing all structures, the result is a file of structures that have successfully passed through all the filters and several (usually smaller) files of structures rejected for various reasons.

Structures are filtered. Flagged structures are reviewed, and passed structures are added to ChemSpider.

It’s not possible to review all of the generated files in full, as this would eliminate the time-saving advantages of automated processing. However, output files of all types are spot checked for accuracy and to iteratively improve the filtering criteria. Certain output files have high potential for false positives and so we review them in full.

Formats and identifiers

Submitted files can be in one of several different formats. The most common is SDF (structure data file, a chemical structure format containing multiple structures with associated data fields). The advantage of this format is that it contains 2- or 3-dimensional structures, so we can immediately start processing the file without having to convert an identifier to a structure. This means that the final structure we deposit is more likely to exactly match the original. The disadvantage of the SDF format is that it is specialised – many users will be unfamiliar with it or won’t have software to create and display the files.

We also receive different spreadsheet formats (excel, csv, tsv) with structures encoded in text-based notation systems like SMILES  or InChI. The advantage of this format is that it doesn’t require specialised software (provided the submitter has SMILES or InChIs for the compounds).The disadvantage is that the structures require conversion to SDF before processing and deposition to ChemSpider. Additionally, these formats contain information about atoms and their connectivity but lack layout information. This can introduce errors as different structure drawing packages can parse these structures slightly differently, resulting in alterations to the final deposited structure.

Filtering criteria

The criteria by which we judge chemical structures are a mixture of definitive chemical rules and less well-defined ‘rules of thumb’ based on our experience and chemical knowledge. Examples of both follow.

Empty structures, query atoms and incorrect valences

The first filter is the simplest – ChemSpider is a structure-centric database, so it’s not possible to deposit any input entries that lack a structure.

Similarly, each ChemSpider record requires a single defined chemical structure, so we exclude anything using a query atom to represent a variable atom or attachment point.

Another simple filter is to exclude structures in which atoms have invalid valences.

Charge imbalance

In general, entries in ChemSpider should represent a real-world, isolable compound. This means that we filter out structures with a non-zero overall charge. However, we make exceptions for certain examples where a counterion is generally unimportant and it’s useful to consider the charged species alone, such as choline (ChemSpider record).

Structures containing undefined stereocentres

Undefined stereocentres alone don’t represent a chemical error. However, structures like that shown below (cholesterol without any defined stereocentres) occur frequently and, although chemically valid, it’s extremely unlikely that they represent the intended structure.

Cholesterol skeleton with no defined stereochemistry

Cholesterol skeleton without stereochemistry

As a result we have a rule of thumb that excludes structures containing more than two undefined stereocentres. This is not a hard-and-fast rule, but rather an attempt to strike a balance between excluding structures like the one above and including structures where the undefined stereocentres are intentional and correct.

The count of undefined stereocentres (as determined by examining the InChI) sometimes includes cases where it is conventional to exclude stereochemical wedges. Examples include nucleic acids with no wedges on the phosphate and adamantyl groups without explicit stereochemistry – it’s unusual to draw these compounds with wedges, and users will rarely use wedges in their search. These potential false positives are filtered out and reviewed manually. A curator can then decide whether to include them in the deposition, improving the overall accuracy of the filter.

Structures containing many components

This is another rule of thumb – there’s no upper limit on how many separate components a correctly depicted chemical substance can have. However, from experience we find that excluding structures with more than four separate components removes most obviously nonsensical entries (e.g.  attempts to depict alloys) while retaining the majority of correct entries.

When applying this rule, pharmaceutical molecules represent a major source of false positives because they are often multiple hydrates and/or salts with multiple counterions (e.g. Irinotecan hydrochloride trihydrate). Excluded structures that are hydrates or contain common pharmaceutical salts are flagged for human review.

Synonym filter

This filter compares the synonyms assigned to a given structure with its molecular formula and performs some ‘common sense’ checks. For example, a relatively frequent error is associating the name of a salt form (e.g., mozavaptan hydrochloride) with the structure of the free base (mozavaptan). In this case, the filter removes synonyms containing ‘hydrochloride’ because the molecular formula does not contain Cl.

SMARTS

SMARTS (Wikipedia page) is a way of describing general chemical structures. It’s based on SMILES, but has additional features allowing the specification of variable chain lengths, number of bonds, number of hydrogens, variable bond orders, or more than one potential element at a site.

We use SMARTS to identify common erroneous features in a structure. These include:

  • Azides and diazo groups depicted with a pentavalent nitrogen
  • A ‘floating’ alkane unconnected to the main structure (probably caused by an accidental click in a drawing program)
  • Metal carboxylates depicted as a protonated carboxylic acid with an elemental metal atom
  • Hexafluorophosphates (and similar species) depicted as phosphorous pentafluoride and a separate fluoride ion

SMIRKS

SMIRKS is a further extension of SMILES to depict reactions. We don’t use it to represent real reactions, but to define structural transformations – allowing us to fix simple structural errors that can be resolved by breaking and creating bonds.

One example is connecting charge-separated Grignard reagents to give a more accurate depiction:

Reconnecting disconnected Grignard reagents

Reconnecting Grignards

Organometallics

The difficulties of encoding organometallic structures in machine-readable formats are well documented (J. Chem. Inf. Model. 51, 12, 3149-3157). There is an ongoing IUPAC project to extend the InChI’s functionality, but for now, the challenges remain.

Every ChemSpider record is fundamentally based on an InChI, and so we are bound by the current limitations. This means that we can’t depict coordination bonds or bonds with non-integer order – any bond drawn is interpreted as a standard covalent bond with one electron contributed by each atom.

Although we generally can’t represent organometallic structures in the manner a human chemist would prefer, we still attempt to choose the ‘least wrong’ structure from various possible compromises.

Ferrocene is a classic example of this problem and illustrates several of the issues we have to consider. A few common ways to draw ferrocene are shown below (there are many more).

Common depictions of ferrocene lose bonding information when converted to mol files

Converting ferrocene structures to mol format can introduce errors in molecular formula, bond orders or valence

 

Most of the structures shown take advantage of extended features of chemical drawing packages in order to represent ferrocene’s bonding in a way that’s attractive and easily understandable to a human chemist. Unfortunately, once transferred to the simplified but universal mol format, some of those features are lost, resulting in nonsensical structures. Although structure D is unchanged, this representation has other problems: incorrect valence on Fe and no representation of the aromaticity of the cyclopentadienyl ligands.

We have a limited number of ways in which we can depict ferrocene and related structures in ChemSpider, none of which give an accurate representation of the bonding or a view that would satisfy an inorganic chemist. However, we can choose the ‘least bad’ of the possible compromises and allow machine readability:

Fe2+ and (C5H5-)2

Our compromise

Although this structure (ChemSpider record) doesn’t capture the hapticity of ferrocene and the charge localisation on a single carbon is inaccurate, it retains correct overall charges and valences and doesn’t show the ligands as sigma-bonded.

More generally, we apply some rules and transformations to standardise representations of organometallic structures. Many of these rules involve choosing whether to depict a metal–carbon (or metal–heteroatom) as covalent or ionic, depending on the nature of the metal and the ligand. Again, compromises are necessary when working within the limitations of machine-readable structures, but we attempt to classify ‘more ionic’ and ‘more covalent’ bonds. Some examples follow:

  • Disconnect oxygen from group 1 and 2 metals
  • Connect oxygen to all other metals
  • Disconnect carbon from sodium, potassium and calcium
  • Connect carbon to group 11 and 12 metals, p-block metals and some metalloids

As expected, general rules like these fail in certain cases. Therefore we have additional, more specific rules to cover exceptions, which we iteratively refine.

But these errors still appear in ChemSpider!

At present the filtering described only applies to new data coming into ChemSpider. The full ChemSpider database, built up over many years, certainly contains examples of every error described here. To fix these legacy errors, we intend to run the entire database through the same quality filters. This is a significant task with some specific challenges: the files requiring human review become orders of magnitude larger, the processing time and memory/CPU overhead is high, and the larger the data set the more likely we will run into false positives. In order to manage these challenges, we are taking the time to refine our processes on new depositions, and periodically checking our progress by running subsets of the full ChemSpider database through our filters. We know you need access to data you can trust, so we want to make sure we get this right. We’ll continue to update you as this project progresses, so stay tuned!

Royal Society of Chemistry Renews Partnership with ACD/Labs to Continue Providing Industry-Leading Data to Worldwide Research Community

ACD/Labs algorithms will continue to equip ChemSpider with physicochemical property values and chemical nomenclature following ten year milestone.

Toronto, CANADA (July 26, 2018)ACD/Labs, an informatics company that develops and commercializes solutions in support of R&D, today announced the continued collaboration with ChemSpider, a leading chemical database owned by the Royal Society of Chemistry, to continue furnishing predicted physicochemical properties and chemical nomenclature to the ever-expanding platform. For over ten years, scientists have accessed this publically-available free resource to gather information on chemical compounds in preparation of research or experimentation.

As the industry standard for physicochemical prediction software, ACD/Labs was chosen to generate property information including logP, logD (at various pHs), Lipinski rule-of-5 values, and boiling point, and to provide Name-to-structure (and vice-versa) capabilities. The renewal of the partnership further reflects the success of the platform and its continued importance as one of the most robust online chemical structure databases for the scientific community. As the platform advances, ChemSpider will continue to use ACD/Labs algorithms to provide quality insights to researchers.

“We set out with the mission of empowering researchers with a comprehensive view of chemical data to inform R&D initiatives,” said Richard Kidd, Publisher, Royal Society of Chemistry. “By working with ACD/Labs and utilizing its property information, we’ve been able to meet our users’ need for knowledge, which is reflected in our rapid growth since the Royal Society of Chemistry acquired ChemSpider ten years ago. To-date, property information populated by ACD/Labs’ algorithms has been among the most accessed on ChemSpider, and remains a key driver in our service.”

While ChemSpider has doubled the size of its database, it has remained committed to maintaining high quality data from selective sources. As the platform continues to grow, ChemSpider will use ACD/Percepta prediction algorithms and ACD/Name tools in a batch-wise fashion to populate the database and enhance publicly available chemical intelligence.

“Enabling the dissemination of chemical knowledge and providing solutions to accelerate R&D are among our top priorities at ACD/Labs,” said Gabriela Cimpan, Senior Director Sales, Europe, ACD/Labs. “ChemSpider is empowering knowledge throughout the chemical community and we feel privileged to be able to support learning worldwide.”

For more information on ACD/Percepta, visit https://www.acdlabs.com/percepta

For more information on ACD/Labs Chemical Nomenclature tools, visit https://www.acdlabs.com/name

For more information on ChemSpider, visit http://www.chemspider.com

About Advanced Chemistry Development, Inc.

ACD/Labs is a leading provider of scientific informatics technologies to R&D organizations that rely on analytical data and molecular information for decision-making, problem-solving, and product lifecycle control. Our software automates and accelerates molecular characterization, product development, and knowledge management. We integrate with existing informatics systems and undertake custom projects including enterprise-level automation.

ACD/Labs solutions are used globally in a variety of industries including pharma/biotech, chemicals, consumer goods, agrochemicals, petrochemicals, and academic/government institutions. We provide worldwide sales and support, and more than 20 years of experience and success helping organizations accelerate R&D and leverage corporate intelligence. For more information, please visit www.acdlabs.com. Follow us on Twitter @ACDLabs.

About the Royal Society of Chemistry

The Royal Society of Chemistry is the world’s leading chemistry community, advancing excellence in the chemical sciences. With over 50,000 members and a knowledge business that spans the globe, we are the UK’s professional body for chemical scientists; a not-for-profit organisation with 175 years of history and an international vision for the future. We promote, support and celebrate chemistry. We work to shape the future of the chemical sciences – for the benefit of science and humanity.

Behind the Scenes at ChemSpider

A peek at who we are, how we run the site, and how we manage data quality.

What is ChemSpider and who runs the service?

ChemSpider is one of the largest chemical databases in the world, containing data on over 65 million chemical structures. This data is freely available to the public at ChemSpider.com, a website published by the Royal Society of Chemistry.

How does the Royal Society of Chemistry support ChemSpider?

ChemSpider.com is an independent service that does not rely on direct or research grant funding. The Royal Society of Chemistry supports the website using the surplus generated by our publishing activities, allowing us to provide a sustainable and reliable service. We also generate revenue from advertising and by providing paid for web services, such as our APIs, for non-academic users. These activities help keep ChemSpider financially sustainable and help support our server costs, staff hours and development.

These services enable us to make the site available free anyone in the world, and we reached over six million unique users in 2017. These users range from school students looking for help with their homework, to researchers working in academia and industry, to general users who want to keep their chemical knowledge up to date. They come from every continent except Antarctica, and just about every country on Earth.

What goes into ChemSpider?

ChemSpider data comes from the chemical sciences community itself – submitted by researchers, databases, publishers, chemical vendors and many more.

We have two main inclusion criteria for ChemSpider data:

  1. Machine readability – Depositors must provide structures in a machine-readable format, typically a .mol file that is interpretable by InChI – the open-source chemical structure representation algorithm.The .mol format describes how a compound is arranged, atom-by-atom and bond-by-bond. This means that it can only accurately depict small molecules with defined structures. For ChemSpider, “small” means structures up to 4000 daltons, including short peptides, oligonucleotides, and other structures. Large proteins, extended crystal lattices or long nucleotides are too big to describe sensibly in ChemSpider, but are available from other databases suited for larger molecules.

    We also only accept ‘defined structures’ – compounds with exact chain lengths, fully expressed functional groups, and integer bond orders – due to the requirement to describe every heavy atom in a molecule. This means we can only accept structures for which we can generate a valid InChI.

    Most ChemSpider structures are organic molecules. However, we do accept some inorganic and organometallic compounds, with specific methods for curating these.

  2. Real compounds – We do not accept virtual or prophetic compounds.

As far as possible, we only accept compounds that have been synthesised or isolated in physical form. This means we do not accept transition states, theoretically predicted compounds, virtual compounds from vendors or prophetic compounds from patents.

Who are our data sources?

We have received data from almost 250 unique data sources, including data from chemical vendors, specialist databases, individuals, research groups and publishers. These sources cross the breadth of the chemical sciences – including biochemistry, pharmacology and toxicology, natural products, spectroscopy and crystallography. Each ChemSpider record includes links to all of the data sources for the compound, enabling users to find and to check the provenance of the data.

Our data source list is continually changing, as we find new sources of data to add and remove outdated or low-quality data sources.

We no longer accept data from other data aggregators. We have taken this step to match our quality requirements with other databases and reduce the propagation of algorithmically generated errors that can arise from prophetic sources. One example of this is Chessboardane, which originated from an optical structure recognition program interpreting a data table contained within a patent as a chemical structure. The result was an 81-carbon grid structure, erroneously identified as a complex cyclic alkane, which was deposited in a public repository and shared between multiple aggregators.

Because of this, we only seek data directly from the original sources, where we have greater certainty about the data’s provenance and accuracy, and are working to curate legacy data still within ChemSpider.

Because of examples like Chessboardane, we are cautious about accepting data from text-and-data-mined sources that depositors have programmatically extracted from text or encoded images in patents or scientific literature. After review, we have added some of the highest quality data mined sources. We will continue to review potential new data-mined sources on a case-by-case basis to ensure that their data meet our quality standards.

Automated filters

A manual check of every one the 65 million records in ChemSpider would take an individual more than 600 years to complete working round the clock – even if we only invested five minutes of curation time per record.

Instead, we run each deposition through a series of automated filters to pick out unsuitable structures, such as those with incorrect valences, unbalanced charges, or missing stereochemistry. In addition to structure filters, we also apply basic name and synonym filtering and regularly review the processed files so that we can improve our filters.

We have provided a simplified overview of this process below, and will provide a more detailed description of our filters in a separate blog post:

Structures are run through filters in KNIME. Those that fail the filters are removed and reviewed. Passed structures are deposited to ChemSpider

Curation by ChemSpider staff

ChemSpider is run by a small team of full-time curators, who work to add new compounds, remove errors, and respond to user feedback. Our staff have extensive experience of both chemical data and practical chemistry, with backgrounds in fields such as organic synthesis and art conservation, and a wealth of experience working on other Royal Society of Chemistry databases, such as The Merck Index* Online and Analytical Abstracts.

Community curation

Because we cannot review every record ourselves, we really appreciate comments or corrections from our users.  The easiest way to help us improve ChemSpider is to leave feedback or email us when you spot an error. We try to act on user feedback within a few days – sooner for simpler queries. Please let us know if you find an error by leaving a comment on the relevant ChemSpider record, or by emailing us (chemspider@rsc.org).

Users wishing to get more involved can directly deposit structures and curate synonyms related to their research or work, without having to email the ChemSpider team.

We are extremely grateful for all the contributions our community curators have made over the years.

Keep using and contributing to ChemSpider

To access information on over 65 million chemical structures, go to ChemSpider.com, which is fully searchable by structure, name, or advanced query, from any device, anywhere, for free.

To deposit data, tell us about an error, become a curator, or for any other query, please do not hesitate to email us at chemspider@rsc.org

*The name THE MERCK INDEX is owned by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Whitehouse Station, N.J., U.S.A., and is licensed to The Royal Society of Chemistry for use in the U.S.A. and Canada.