Skip to main content

A Dating Site For Chemists and Biologists


Probably everyone who reads the ChEMBL-og will have world-changing ideas - but it's really difficult to find someone to screen a few compounds for you - of course there are CROs who will want to meet, then prepare a quote for you, set up a CDA, receive payment, etc., but cash is difficult to get hold of, and the process will be slow. There are no grant mechanisms for this sort of thing either - imagine - "I'd like funds to test four compounds as potential inhibitors of snoraze" - no chance (at least with the panels I've sat on) too small, too speculative.... The bigger problem though is finding someone with the assay or the compounds.

But, there's a lot of people with compounds to test, and a lot of biologists with assays that are easy to run in their labs, and they have expertise in, but who can't assemble sets of interesting compounds to profile. Why not just use the paradigm of a dating site to matchmake mutually compatible biologists and chemists - if there is a spark, it could develop into a long lasting (collaborative) relationship!

Imagine something like:

Biologist with HMGCoA reductase assay and expertise in cholesterol homeostasis would like to meet chemist with non-statin compounds likely to be brain penetrant to test a cool idea.

Anyway, there's a toy FaceBook group that I've set up - just to get the idea across. I've pitched this as a national thing (so for me that means to the UK, for you somewhere different maybe) - not least that it's a lot easier to ship compounds around within a country than between - and also there's a clear match to downstream funding opportunities. I chose FaceBook, since most of the open LinkedIn groups I'm involved in are train-wrecks of spam and flame-wars.

I think this idea is worth trying, or at least getting some discussion started over - huge thanks to Tom Heightman for our recent discussion on things that needed to be done in Chemical Biology in the UK.

Maybe Google+ is another alternative.

Comments

Bio to Chem said…
1) Couldn't agree more re LinkedIN. My 2-cent whinge from last year (below) got zero responses "@cdsouthan exasperated that many of his LinkedIN groups show no moderation. Hence valuable discussions are contaminated with spurious comments or plugs
12:15 PM - 19 Nov 11 via LinkedIn"

2) Have asked to join dating agency. I have nothing to broker lab-wise but I might be able to help someone "find" something e.g. by patent ferreting.
Unknown said…
Great idea, John.
The French have something similar to that they call it La Chimiothèque Nationale (see the article Hilbert 2009). But from what I understood it isn't very open, in the sense that you don't know who is sending you the compounds and even what compounds are in each well. I hope I am wrong but to create an open library or a dating agency is a difficult job as there are many interests from both sides of the wall.

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

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

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

Using ChEMBL activity comments

We’re sometimes asked what the ‘activity_comments’ in the ChEMBL database mean. In this Blog post, we’ll use aspirin as an example to explain some of the more common activity comments. First, let’s review the bioactivity data included in ChEMBL. We extract bioactivity data directly from   seven core medicinal chemistry journals . Some common activity types, such as IC50s, are standardised  to allow broad comparisons across assays; the standardised data can be found in the  standard_value ,  standard_relation  and  standard_units  fields. Original data is retained in the database downloads in the  value ,  relation  and  units  fields. However, we extract all data from a publication including non-numerical bioactivity and ADME data. In these cases, the activity comments may be populated during the ChEMBL extraction-curation process  in order to capture the author's  overall  conclusions . Similarly, for deposited datasets and subsets of other databases (e.g. DrugMatrix, PubChem), th