ChEMBL Resources

The SARfaris: GPCR, Kinase, ADME

Tuesday, 28 October 2014

Paper: PPDMs – A resource for mapping small molecule bioactivities from ChEMBL to Pfam-A protein domains

We've just published a Open Access paper in Bioinformatics on an approach to annotate the region of ligand binding within a target protein. This has a lot of applications in the use of ChEMBL, in particular providing greater accuracy in mapping functional effects, improving ligand-based target prediction approaches, and reducing false positives in sequence/target searching of ChEMBL. Where next for this work - well annotating to a site-specific level would be a good thing to implement (think about HIV-1 RT with the distinct nucleoside and non-nucleoside sites).

Here's the abstract...

Summary: PPDMs is a resource that maps small molecule bioactivities to protein domains from the Pfam-A collection of protein families. Small molecule bioactivities mapped to protein domains add important precision to approaches that use protein sequence searches alignments to assist applications in computational drug discovery and systems and chemical biology. We have previously proposed a mapping heuristic for a subset of bioactivities stored in ChEMBL with the Pfam-A domain most likely to mediate small molecule binding. We have since refined this mapping using a manual procedure. Here, we present a resource that provides up-to-date mappings and the possibility to review assigned mappings as well as to participate in their assignment and curation. We also describe how mappings provided through the PPDMs resource are made accessible through the main schema of the ChEMBL database.

Availability: The PPDMs resource and curation interface is available at

The source-code for PPDMs is available under the Apache license at

Source code is available at to demonstrate the integration process with the main schema of ChEMBL.

Monday, 27 October 2014

Django model describing ChEMBL database.

TL;DR: We have just open sourced our Django ORM Model, which describes the ChEMBL relational database schema. This means you no longer need to write another line of SQL code to interact with ChEMBL database. We think it is pretty cool and we are using it in the ChEMBL group to make our lives easier. Read on to find out more....

It is never a good idea to use SQL code directly in python. Let's see some basic examples explaining why:

Can you see what is wrong with the code above? SQL keyword `JOIN` was misspelled as 'JION'. But it's hard to find it quickly because most of code highlighters will apply Python syntax rules and ignore contents of strings. In our case the string is very important as it contains SQL statement.

The problem above can be easily solved using some simple Python SQL wrapper, such as edendb. This wrapper will provide set of functions to perform database operations for example 'select', 'insert', 'delete':

Now it's harder to make a typo in any of SQL keywords because they are exposed to python so IDE should warn you about mistake.

OK, time for something harder, can you find what's wrong here, assuming that this query is executed against chembl_19 schema:

Well, there are two errors: first of all `molecule_synonyms` table does not have a `synonims` column. The proper name is `synonyms`. Secondly, there is table name typo  `molecule_synonyms`.

This kind of error is even harder to find because we are dealing with python and SQL code that is syntactically correct. The problem is semantic and in order to find it we need to have a good understanding of the underlying data model, in this case the chembl_19 schema. But the ChEMBL database schema is fairly complicated (341 columns spread over 52 tables), are we really supposed to know it all by heart? Let's leave this rhetorical question and proceed to third example: how to query for compounds containing the substructure represented by 'O=C(Oc1ccccc1C(=O)O)C' SMILES:

For Oracle this would be:

And for Postgres:

As you can see both queries are different, reasons for these differences are:
  1. Differences in Oracle and Postgres dialects
  2. Different chemical cartridges (Accelrys Direct and RDKit)
  3. Different names of auxiliary tables containing binary molecule objects
These queries are also more complicated than the previous examples as they require more table joins and they make calls to the chemical cartridge-specific functions.

The example substructure search queries described above are similar to those used by the ChEMBL web services, which are available on EBI servers (Oracle backend) and in the myChEMBL VM (PostgreSQL backend). Still, the web services work without any change to their code. How?

All of the problems highlighted in this blogpost can be solved by the use of a technique known as Object Relational Mapping (ORM). ORM converts every table from database (for example 'molecule_dictionary') into Python class (MoleculeDictionary). Now it's easy to create a list of all available classes in Python module (by using 'dir' function) and check all available fields in class which corresponds to columns from SQL tables. This makes database programming easier and less error prone. The ORM also allows the code to work in a database agnostic manner and explains how we use the same codebase with Oracle and PostgreSQL backends.

If this blogpost has convinced you to give the ORM approach a try, please take a look at our ChEMBL example also included in myChEMBL:

Wednesday, 22 October 2014

myChEMBL 19 Released

We are very pleased to announce that the latest myChEMBL release, based on the ChEMBL 19 database,  is now available to download. In addition to the extra data, you will also find a number a great new features. So what's new then?

More core chemoinformatics tools

We have included OSRA (Optical Structure Recognition), which is useful for extracting compound structures from images. OSRA can be accessed from the command line or by very convenient web interface, provided by Beaker (described below). We've also added OpenBabel - another great open source cheminformatics toolkit. This means you can now experiment with both RDKit and OpenBabel and use whichever you prefer.

ChEMBL Beaker

myChEMBL now ships with a local instance the ChEMBL Beaker service. For those not familiar with Beaker, the service provides users with an array of chemoinformatics utilities via a RESTful API. Under the hood, Beaker is using RDKit and OSRA to carry out its methods. With the addition of Beaker in myChEMBL, users can now carry out the following tasks in secure local environment:
  • Convert chemical structure bewteen multiple formats
  • Extract compound information from images and pdfs
  • Generate compound images in raster (png) and vector (svg) forms
  • Generate HTML5 ready representation of compound structure
  • Generate compound fingerprints
  • Generate compound descriptors
  • Identify Maximum Common Substructure
  • Compound standardisation
  • Lots of more calculations


New IPython notebooks

We have written a number of new IPyhthon notebooks, which focus on a range of cheminformatics and bioinformatic topics. The topics covered by the new notebooks include:
  • Introduction on how to use ChEMBL Beaker
  • Using the Django ORM to query the ChEMBL database
  • Introduction to BLAST and creation of a simple Druggability Score
  • Introduction to machine learning
  • Analysis of SureChEMBL data, focused on identifying the MCS core identified in a patent 
  • Extraction and analysis of ChEMBL ADME data 

We have also updated the underlying Ubuntu VM to 14.04 LTS, which also required us to make a number of changes the myChEMBL installation. To see how these changes and new additions have effected a bare metal installation of myChEMBL, head over the myChEMBL github repository.



There are 2 different ways we recommend for installing myChEMBL:
  1. Follow the instructions in the INSTALL file on the ftpsite. This will import the myChEMBL VM into VirtualBox
  2. Use Vagrant to install myChEMBL. See this earlier blogpost for more details, but the command to run is:
vagrant init chembl/myChEMBL && vagrant up

   If you already have myChEMBL_18 installed via Vagrant, instead of running 'vagrant box update', we strongly recommend running: 

vagrant box remove chembl/myChEMBL
vagrant init chembl/myChEMBL && vagrant up

Future plans

The myChEMBL resource is an evolving system and we are always looking to add new open source projects, tools and notebooks. We would be really interested to hear from users about what they would like to see in future myChEMBL releases, so please get in touch if you have any suggestions. (Just so you know, we already have a couple of ideas for myChEMBL 20).

We hope you find this myChEMBL update useful and if you spot any issues or have any questions let us know.

The myChEMBL Team

Thursday, 16 October 2014

New Drug Approvals 2014 - Pt. XII - Naloxegol (Movantik™)

ATC Code: A06AH03
Wikipedia: Naloxegol

On September 16th FDA approved Movantik (naloxegol, AZ-13337019), as an oral treatment for patients with opioid-induced constipation and chronic non-cancer pain.

Naloxegol is an opioid receptor antagonistDue to its similarity to noroxymorphone, a main metabolite of oxycodone, naloxegol is classed as a controlled substance. However, the FDA analysed its abuse potential and concluded that there was no risk of dependency.

Mode of Action
Opioids are a class of drugs which are used to manage pain, but have a common side effect of reducing the motility of the gastrointestinal tract, making bowel movements difficult. Opioids work by binding to the mu-receptors (CHEMBL233, UniProt:P35372) in the central nervous system, thereby reducing pain. However, they are also able to bind to the mu-receptors in the gastrointestinal tract, hence causing opioid-induced constipation. 
Movantik is a peripherally-acting opioid receptor antagonist, which is able to prevent constipation by reducing this specific side effect of the opioids without affecting the efficacy of the pain management.

Clinical Trials
The clinical trials for this drug were carried out on a KODIAC clinical programme, comprising of four studies. Tests showed that 44% and 41% of patients receiving 25mg and 12.5mg, respectively, experienced increased bowel movements, compared to just 29% who took the placebo. [Paper]

Indication and Warnings
This drug is for non-cancer related pain. Side effects have been abdominal pain, diarrhea, headache and excessive gas in the stomach and/or intestinal area. 
When used in conjunction with another peripherally-acting opioid antagonist, there is the chance of gastrointestinal perforation.
There is also the chance of withdrawal symptoms.
This is contraindicated for anyone who is also taking CYP3A4 (CHEMBL5792, UniProt:Q9HB55) inhibitors, such as clarithromycin (CHEMBL1741), as this will increase the exposure to naloxegol and could precipitate opioid withdrawal symptoms. [FDA]

Trade Names
Naloxegol was developed by AstraZeneca and is marketed under the trade name of Movantik. It is due for release during the first quarter of 2015.

New Drug Approvals 2014 - Pt. XI - Idelalisib (Zydelig™)

ATC Code: L01XX47
Wikipedia: Idelalisib

On July 23rd the FDA approved Zydelig (idelalisib, GS-1101), as an orally-delivered drug to treat patients with three types of blood cancers.
Relapsed chronic lymphocytic leukemia (CLL)
Relapsed follicular B-cell, non-Hodgkin lymphoma  (FL)
Relapsed small lymphocytic lymphoma (SLL)

Blood cancer
The three main categories of blood cancer are leukemia, lymphoma and myeloma. Lymphoma is also split into two types: Hodgkin lymphoma and non-Hodgkin lymphoma. Both leukemia and myeloma occur in the bone marrow, whilst lymphoma is a cancer that is isolated to the lymphatic system. Acute leukemia is where there is an abundance of underdeveloped white blood cells that can’t function properly and chronic leukemia is where there are just far too many white blood cells, which is just as bad as having too few. Myeloma is where the plasma cells form tumours in the bone marrow.

This drug is a phosphoinositide 3-kinase inhibitor, which works by blocking P110σ (CHEMBL3130, Uniprot:O00329), the delta isoform of the phosphoinositide 3-kinase enzyme, encoded in humans by the PIK3CD gene. This isoform plays a role in B-cell development, proliferation and function and is expressed predominantly in leukocytes.

Mode of action
Idelalisib works on patients by inhibiting the PI3 kinase delta isoform (PI3Kδ), which plays an important role in malignant lymphocyte survival. It is the delta and gamma forms that are specific to the hematopoietic system. This treatment impairs the normal tracking of CLL lymph nodes. It can be used in conjunction with Rituxan (rituximab), an existing blood cancer treatment, for relapsed CLL and on its own for FL and SLL.

Clinical trials
Clinical trials were carried out on 220 patients, with relapsed CLL, who were not healthy enough, due to co-existing medical conditions or damage from previous chemotherapy, to receive cytotoxic therapy. Patients were administered either idelalisib plus rituximab or a placebo and rituximab. Most of these patients were 65 years of age or older.
After 24 weeks, 93% of the group who had taken the combination treatment were disease progression-free, compared to only 46% of the group who had received the placebo and rituximab combination.
After 12 months, 90% of the dual drug combination group were alive, compared to 80% of the placebo-containing group. [NCI]

Indication and Warnings
This drug can be used in combination with rituximab or on its own, indicated for patients with relapsed conditions. There are several warnings for idelalisib, including hepatotoxicity, pneumonitis (fatal and serious), intestinal perforation and embyro-fetal toxicity. [FDA]

Trade Names
Idelalisib was developed by Gildead Sciences and is marketed under the name Zydelig.