Skip to main content

ChEMBL PostgreSQL



With the aim of providing more options to access the ChEMBL database, a PostgreSQL version of the most recent ChEMBL release is now available on the ChEMBL FTP site, (thanks to the Ora2Pg project for making the conversion process relatively painless). 

The main goal of this project is make it easier for users to integrate the chemical data in the ChEMBL database with freely available chemical cartridges, such as the excellent RDKit and Bingo. Now that we have the PostgreSQL version of the database available, we are in the process of benchmarking the aforementioned chemical cartridges - we will report back soon the results of the benchmarking exercises we are undertaking. We are also looking to build and release a virtual machine, which will come preloaded with ChEMBL, PostgreSQL, RDKit and/or Bingo. When we have more details on this we will let you know.

Right now everyone has the opportunity to download and install the PostgreSQL version of the ChEMBL database and optionally install a chemical cartridge. We hope this will help as many projects as possible and any comments or feedback will be very much appreciated. Enjoy it :)

(You can download the ChEMBL_14 PostgreSQL here, the tarball also comes with some basic install instructions, but does assume you have a PostgreSQL instance up and running).

Comments

greg landrum said…
Nice!

Let me know if there's anything I can do to help with the benchmarking.
Unknown said…
oh yes, you'll hear from us soon
:)
greg landrum said…
Any chance you would be willing/able to share logs of substructures that people have executed against ChEMBL?

That kind of real-world (and public) data would be very helpful for optimizing SSS fingerprints.
jpo said…
Greg - we've been asked this a lot of times, and quite simply it's against our terms of use of the resources here at the EBI. The queries are confidential, and we have written the application, so anything that may be considered confidential is cleared from any caches as soon as is practicable, consistent with reasonable performance, or is only stored client side.

In summary, we don't store the queries.

There have been a few apocryphal cases where in the field of drug discovery, people have gone and mined or shared the queries of their web resources, and it is quite a sad tale......
Kyle Kinney said…
Awesome, this is almost exactly what I needed - I was not looking forward to trying to convert this into postgresql myself. There's only one little issue - I'm running postgresql 9.0, and this is for postgresql 9.1. Any idea what kinds of compatibility issues am I likely to run into? The only noticeable failure I saw on loading was the failure of the CREATE EXTENSION plpgsql, and I may or may not be able to substitute CREATE LANGUAGE there. Not sure how much plpgsql has changed between versions, other than being an extension now.
Push comes to shove, I can migrate, but if it's a matter of changing a couple lines at the top, I'd rather avoid it.

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

New Drug Approvals - Pt. XVII - Telavancin (Vibativ)

The latest new drug approval, on 11th September 2009 was Telavancin - which was approved for the treatment of adults with complicated skin and skin structure infections (cSSSI) caused by susceptible Gram-positive bacteria , including Staphylococcus aureus , both methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) strains. Telavancin is also active against Streptococcus pyogenes , Streptococcus agalactiae , Streptococcus anginosus group (includes S. anginosus, S. intermedius and S. constellatus ) and Enterococcus faecalis (vancomycin susceptible isolates only). Telavancin is a semisynthetic derivative of Vancomycin. Vancomycin itself is a natural product drug, isolated originally from soil samples in Borneo, and is produced by controlled fermentation of Amycolatopsis orientalis - a member of the Actinobacteria . Telavancin has a dual mechanism of action, firstly it inhibits bacterial cell wall synthesis by interfering with the polymerization and cross-linking of peptid

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

Accessing SureChEMBL data in bulk

It is the peak of the summer (at least in this hemisphere) and many of our readers/users will be on holiday, perhaps on an island enjoying the sea. Luckily, for the rest of us there is still the 'sea' of SureChEMBL data that awaits to be enjoyed and explored for hidden 'treasures' (let me know if I pushed this analogy too far). See here and  here for a reminder of SureChEMBL is and what it does.  This wealth of (big) data can be accessed via the SureChEMBL interface , where users can submit quite sophisticated and granular queries by combining: i) Lucene fields against full-text and bibliographic metadata and ii) advanced structure query features against the annotated compound corpus. Examples of such queries will be the topic of a future post. Once the search results are back, users can browse through and export the chemistry from the patent(s) of interest. In addition to this functionality, we've been receiving user requests for  local (behind the

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