PhD Studentship at Babraham - Systems Pharmacology Models of Druggable Targets and Disease Mechanisms

Our friendly neighbours at The Babraham Institute are looking for a PhD candidate to work on systems pharmacology models, as part of a collaboration between the Le Novère (Babraham), the Hermjakob (EMBL-EBI) and the pharmaceutical company GlaxoSmithKline. The Le Novère group uses quantitative computational models to understand cellular and molecular processes, and develop community services that facilitate research in computational systems biology (http://lenoverelab.org).

One of the major challenges of drug discovery is to demonstrate the efficacy of a potential new drug. This goes beyond the development of a potent molecule - it also implies a good understanding of the biological context, how it relates to a particular disease, and the drug's mechanism of action. The availability of relevant Systems Pharmacology models can therefore have a significant impact. The most comprehensive repository of Systems Biology models in machine readable language is BioModels Database, created by Le Novère and maintained at the EBI. In spite of its extensive collection, BioModels Database only covers a fraction of the Systems Pharmacology models described in the literature. In addition, no analysis has been performed on how they map to druggable targets and/or disease mechanisms.

The candidate will:

Use state-of-the-art text-mining methods to extract and analyse the space of Systems Pharmacology models currently described in the literature, with particular emphasis to their relevance to druggable targets and disease mechanisms;
Identify the models offering the best opportunities for the discovery of new drugs, and incorporate them into BioModels Database;
Explore and assess the applicability of those models to real drug development cases, evaluating their quality, advantages, caveats, overlaps, gaps and impact on the demonstration of drug efficacy against specific indications.

The candidate must have an extensive knowledge of molecular biology and pharmacology, and solid basis in numerical analysis and statistics. Advanced familiarity with data representation and programming skills will also be desirable.

Thiele I et al. A community-driven global reconstruction of human metabolism. Nat Biotechnol. 2013 Mar 3. Online advance publication.
Cucurull-Sanchez L et al. Relevance of systems pharmacology in drug discovery. Drug Discov Today. 2012 17: 665-670
Le Novère N et al. BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. Nucleic Acids Res. 2006 34: D689-D691.

For any further information or to express interest, please contact Nicolas Le Novère (n.lenovere (at) gmail.com)

Comments

ChEMBL 34 is out!

We are delighted to announce the release of ChEMBL 34, which includes a full update to drug and clinical candidate drug data. This version of the database, prepared on 28/03/2024 contains: 2,431,025 compounds (of which 2,409,270 have mol files) 3,106,257 compound records (non-unique compounds) 20,772,701 activities 1,644,390 assays 15,598 targets 89,892 documents Data can be downloaded from the ChEMBL FTP site: https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/ Please see ChEMBL_34 release notes for full details of all changes in this release: https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/chembl_34_release_notes.txt New Data Sources European Medicines Agency (src_id = 66): European Medicines Agency's data correspond to EMA drugs prior to 20 January 2023 (excluding ...

SureChEMBL gets a facelift

Dear SureChEMBL users, Over the past year, we’ve introduced several updates to the SureChEMBL platform, focusing on improving functionality while maintaining a clean and intuitive design. Even small changes can have a big impact on your experience, and our goal remains the same: to provide high-quality patent annotation with a simple, effective way to find the data you need. What’s Changed? After careful consideration, we’ve redesigned the landing page to make your navigation smoother and more intuitive. From top to bottom: - Announcements Section: Stay up to date with the latest news and updates directly from this blog. Never miss any update! - Enhanced Search Bar: The main search bar is still your go-to for text searches, still with three pre-filter radio buttons to quickly narrow your results without hassle. - Improved Query Assistant: Our query assistant has been redesigned and upgraded to help you craft more precise queries. It now includes five operator options: E...

Here's a nice Christmas gift - ChEMBL 35 is out!

Use your well-deserved Christmas holidays to spend time with your loved ones and explore the new release of ChEMBL 35! This fresh release comes with a wealth of new data sets and some new data sources as well. Examples include a total of 14 datasets deposited by by the ASAP ( AI-driven Structure-enabled Antiviral Platform) project, a new NTD data se t by Aberystwyth University on anti-schistosome activity, nine new chemical probe data sets, and seven new data sets for the Chemogenomic library of the EUbOPEN project. We also inlcuded a few new fields that do impr ove the provenance and FAIRness of the data we host in ChEMBL: 1) A CONTACT field has been added to the DOCs table which should contain a contact profile of someone willing to be contacted about details of the dataset (ideally an ORCID ID; up to 3 contacts can be provided). 2) In an effort to provide more detailed information about the source of a deposited dat...

Improvements in SureChEMBL's chemistry search and adoption of RDKit

Dear SureChEMBL users, If you frequently rely on our "chemistry search" feature, today brings great news! We’ve recently implemented a major update that makes your search experience faster than ever. What's New? Last week, we upgraded our structure search engine by aligning it with the core code base used in ChEMBL . This update allows SureChEMBL to leverage our FPSim2 Python package , returning results in approximately one second. The similarity search relies on 256-bit RDKit -calculated ECFP4 fingerprints, and a single instance requires approximately 1 GB of RAM to run. SureChEMBL’s FPSim2 file is not currently available for download, but we are considering generating it periodicaly and have created it once for you to try in Google Colab ! For substructure searches, we now also use an RDKit -based solution via SubstructLibrary , which returns results several times faster than our previous implementation. Additionally, structure search results are now sorted by...

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 ChEM...

The ChEMBL-og

Search This Blog