We're recruiting!

Want to join the ChEMBL team?

We are seeking to recruit an experienced Web Application Developer to join the Chemogenomics Team at the European Bioinformatics Institute (EMBL-EBI).

You will develop a series of web-based applications and interfaces for the ChEMBL chemogenomic resources. In collaboration with senior team members you will also have a role in determining and advising on the web development strategy for the chemogenomic resources. In addition you will be involved with the development, maintenance and documentation of these tools and supporting their usage within EMBL-EBI and externally. The position will also involve some requirement gathering and use-case development.

For more information or to apply for this position follow this link:
http://ig14.i-grasp.com//fe/tpl_embl01.asp?newms=jj&id=53807&aid=15470

The ChEMBL team

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New SureChEMBL announcement

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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

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

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

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

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