Skip to main content

Should CAS numbers be in ChEMBL and/or UniChem?


A very quick survey to add excitement to either your holiday or work-day! None of these sucker links, where there appears a 0.24% complete progress bar on the second page, it's just a simple yes/no question on whether it's a good idea to add CAS registry numbers to ChEMBL and/or UniChem. No promises that we could deliver this, but depending on what you vote for, we will consider our options.

Update: Given the multiple channels out there, there are also comments on this on LinkedIn (in the ChUG - "ChEMBL User Group" group - why not join, if you're not already) and a couple on Google+.

Update 2: I'll let the poll run till the end of the week (Friday 8th 2014) - and then write something up on the results.

Comments

I would argue against this. The CAS registry number is proprietary and not easy to use. Particularly, you are not allowed to collect them, though they have an informal limit at 10k registry numbers. This causes serious licensing issues with ChEMBL: you will have to make it a separate database and release it separate files. CC-BY-SA does not allow further restrictions such as those imposed for the CAS registry number.
jpo said…
I would disagree with the statement that I'm not allowed to collect them. How can anyone stop me from public sources of course. For example, is there a license carve out on the wikipedia CAS numbers? wikipedia content is CC-BY-SA, so perfect alignment with the current ChEMBL license. There are lots of other sources of large sets of CAS RNs - NCI resolver, ChemSpider, PubChem, UNII). There are also many on public, non-copyrighted documents, patents, INN/USAN documents, etc. To say that i'm not allowed to do anything with them, is just bonkers.

There is a formal limit of 10K, if you sign (or your organisation, with relevant scope of the license).

I'm of mixed view myself as to whether it is worth doing something with ChEMBL - hence to poll - see what the community thinks. For some of the stuff I'm currently working on (clinical candidate disclosures) they are required, and I have never seen a statement to say I can't reuse them in any document I've come across). The whole idea is that they (CAS RNs) are useful to cross reference chemical (and biological) objects with systems that choose to use them.

Sorry for briefish reply, holiday, and just back from the beach with wet trunks!
jpo said…
I would disagree with the statement that I'm not allowed to collect them. How can anyone stop me from public sources of course. For example, is there a license carve out on the wikipedia CAS numbers? wikipedia content is CC-BY-SA, so perfect alignment with the current ChEMBL license. There are lots of other sources of large sets of CAS RNs - NCI resolver, ChemSpider, PubChem, UNII). There are also many on public, non-copyrighted documents, patents, INN/USAN documents, etc. To say that i'm not allowed to do anything with them, is just bonkers.

There is a formal limit of 10K, if you sign (or your organisation, with relevant scope of the license).

I'm of mixed view myself as to whether it is worth doing something with ChEMBL - hence to poll - see what the community thinks. For some of the stuff I'm currently working on (clinical candidate disclosures) they are required, and I have never seen a statement to say I can't reuse them in any document I've come across). The whole idea is that they (CAS RNs) are useful to cross reference chemical (and biological) objects with systems that choose to use them.

Sorry for briefish reply, holiday, and just back from the beach with wet trunks!

Popular posts from this blog

New SureChEMBL announcement

(Generated with DALL-E 3 ∙ 30 October 2023 at 1:48 pm) We have some very exciting news to report: the new SureChEMBL is now available! Hooray! What is SureChEMBL, you may ask. Good question! In our portfolio of chemical biology services, alongside our established database of bioactivity data for drug-like molecules ChEMBL , our dictionary of annotated small molecule entities ChEBI , and our compound cross-referencing system UniChem , we also deliver a database of annotated patents! Almost 10 years ago , EMBL-EBI acquired the SureChem system of chemically annotated patents and made this freely accessible in the public domain as SureChEMBL. Since then, our team has continued to maintain and deliver SureChEMBL. However, this has become increasingly challenging due to the complexities of the underlying codebase. We were awarded a Wellcome Trust grant in 2021 to completely overhaul SureChEMBL, with a new UI, backend infrastructure, and new f

A python client for accessing ChEMBL web services

Motivation The CheMBL Web Services provide simple reliable programmatic access to the data stored in ChEMBL database. RESTful API approaches are quite easy to master in most languages but still require writing a few lines of code. Additionally, it can be a challenging task to write a nontrivial application using REST without any examples. These factors were the motivation for us to write a small client library for accessing web services from Python. Why Python? We choose this language because Python has become extremely popular (and still growing in use) in scientific applications; there are several Open Source chemical toolkits available in this language, and so the wealth of ChEMBL resources and functionality of those toolkits can be easily combined. Moreover, Python is a very web-friendly language and we wanted to show how easy complex resource acquisition can be expressed in Python. Reinventing the wheel? There are already some libraries providing access to ChEMBL d

Multi-task neural network on ChEMBL with PyTorch 1.0 and RDKit

  Update: KNIME protocol with the model available thanks to Greg Landrum. Update: New code to train the model and ONNX exported trained models available in github . The use and application of multi-task neural networks is growing rapidly in cheminformatics and drug discovery. Examples can be found in the following publications: - Deep Learning as an Opportunity in VirtualScreening - Massively Multitask Networks for Drug Discovery - Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set But what is a multi-task neural network? In short, it's a kind of neural network architecture that can optimise multiple classification/regression problems at the same time while taking advantage of their shared description. This blogpost gives a great overview of their architecture. All networks in references above implement the hard parameter sharing approach. So, having a set of activities relating targets and molecules we can tra

LSH-based similarity search in MongoDB is faster than postgres cartridge.

TL;DR: In his excellent blog post , Matt Swain described the implementation of compound similarity searches in MongoDB . Unfortunately, Matt's approach had suboptimal ( polynomial ) time complexity with respect to decreasing similarity thresholds, which renders unsuitable for production environments. In this article, we improve on the method by enhancing it with Locality Sensitive Hashing algorithm, which significantly reduces query time and outperforms RDKit PostgreSQL cartridge . myChEMBL 21 - NoSQL edition    Given that NoSQL technologies applied to computational chemistry and cheminformatics are gaining traction and popularity, we decided to include a taster in future myChEMBL releases. Two especially appealing technologies are Neo4j and MongoDB . The former is a graph database and the latter is a BSON document storage. We would like to provide IPython notebook -based tutorials explaining how to use this software to deal with common cheminformatics p

ChEMBL 26 Released

We are pleased to announce the release of ChEMBL_26 This version of the database, prepared on 10/01/2020 contains: 2,425,876 compound records 1,950,765 compounds (of which 1,940,733 have mol files) 15,996,368 activities 1,221,311 assays 13,377 targets 76,076 documents You can query the ChEMBL 26 data online via the ChEMBL Interface and you can also download the data from the ChEMBL FTP site . Please see ChEMBL_26 release notes for full details of all changes in this release. Changes since the last release: * Deposited Data Sets: CO-ADD antimicrobial screening data: Two new data sets have been included from the Community for Open Access Drug Discovery (CO-ADD). These data sets are screening of the NIH NCI Natural Product Set III in the CO-ADD assays (src_id = 40, Document ChEMBL_ID = CHEMBL4296183, DOI = 10.6019/CHEMBL4296183) and screening of the NIH NCI Diversity Set V in the CO-ADD assays (src_id = 40, Document ChEMBL_ID = CHEMBL4296182, DOI = 10.601