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Cambridge Cheminformatics Newsletter, 17 November 2022

Dear All,

I would like to circulate some current Cheminformatics- (and related) news to everyone as follows. If you have information from your side for distribution please just let me know, and I am happy to include it on the next occasion!

Please note in particular that on 30 November the first ‘Cambridge/Oxford/Berlin Joint Digital Drug Discovery Meeting’ will take place, simultaneously in person at all locations as well as remote! Please see below and for further information. Hope to see you there!

So here we go…


17 November 2022
Modeller Stammtisch
Berlin, Germany

17 November 2022
4th NovAliX Virtual Conference
Virtual Event

28 November 2022
ELLIS Machine Learning for Molecule Discovery Workshop
Virtual Event

30 November 2022
Cambridge/Oxford/Berlin Cheminformatics & Digital Drug Discovery Meeting (hybrid)
Cambridge, UK; Oxford, UK; Berlin, Germany; Remote


Why is it so Hard to Search Ultra-Large Chemical Libraries?
Roger Sayle, NextMove Software, Cambridge

Fragmenstein: Stitching Compounds Together Like a Reanimated Corpse
Matteo Ferla, Oxford Protein Informatics Group, Department of Statistics

Data-Driven Methods for Active Compound Design and Risk Assessment
Andrea Volkamer, Charité Berlin and Saarland University

Please come and join us! More details at:

1 December 2022
Computation in Drug Discovery An Insider’s View
Virtual Event

8 December 2022
NeurIPS @ Cambridge
Cambridge, UK

31 March 2023
Molecular Dynamics in Pharma
London, UK


AI/ML Specialist – Computational Chemistry
Cambridge, UK—Cambridge/Senior-Data-Scientist_R-151885-2

Sr. Scientist/Scientist, Computational Chemistry
Berlin, Germany/Hybrid
HotSpot Therapeutics

The Unilever Professorship of Molecular Sciences Informatics
University of Cambridge
Cambridge, UK

Principal Research Scientist – Computational Chemistry – Technical
Eli Lilly
Alcobendas, Spain

Director of Computational Biology
Barcelona, Spain

Lead Computational Chemist
Wren Therapeutics
Cambridge, UK

Machine Learning Engineer
Warsaw, Poland / Remote

Computational Chemistry Lead
LifeMine Therapeutics
Basel, Switzerland

Director Computational Molecular Design, Director Machine Learning Research
Berlin, Germany

Postdoctoral Fellow Cheminformatics Data Scientist
Stein, Switzerland

Eric and Wendy Schmidt AI in Science Postdoctoral Fellowships
Imperial College
London, UK wendy schmidt postdoctoral

Global Head R&D, Artificial Intelligence & Deep Analytics
Chilly-Mazarin, France

Cheminformatics/Bioinformatics Scientist
Skills Alliance
Cambridge, UK

Job Seekers

I have a scientist from our area looking for a position:

– M.Sc. in Biostatistics,
– 3+ years of experience as acting manager of a Bioinformatics and Computational Biology lab
– Extensive experience in Data Science, Machine and Deep Learning tools and frameworks (Python, R, SQL; Pytorch, Tensorflow, etc.)
– Research experience and publications in the field of genomics and computational biology

– Familiar with Git, Linux, visualization, PostgreSQL, etc.

Please let me know in case this matches a vacancy in your organization and I will bring you in touch:


Virtual Screening’s Latest
Docking to identify biased partial agonists against 5-HT2A

Mol* (/’molstar/) is a modern web-based open-source toolkit for visualisation and analysis of large-scale molecular data

Matcher: An Open-Source Application for Translating Large Structure/Property Datasets into Insights for Drug Design

One Transformer Can Understand Both 2D & 3D Molecular Data
I find this focus on ‘better than SOTA’ more and more tedious (how about practical relevance?) but the integration of 2D and 3D information in a single model is probably still worth a read

Open Systems Pharmacology Software Suite 11

Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design

AI4SD Conference Report 2022
by Wendy Warr

… beyond cheminformatics …

JUMP Cell Painting Datasets (for 116k compounds)
Let’s now find out now about predictivity for in vivo relevant endpoints!

Reviving an R&D pipeline: a step change in the Phase II success rate
From Pfizer; seems to be mostly related to exiting certain disease areas though

To TabPFN…

Or not to TabPFN?

Biopharmaceutical R&D outsourcing: Short-term gain for long-term pain?
From the start-up side: Be careful how to build a platform (either develop your own assets, or avoid economy of scope and spillover)

Drug Development Dashboard for Oncology

#Unshackled: The evolving definition of asset-centricity
David Grainger’s blog, on asset-centricity in drug discovery and development (and investing)

BIOS — Top 100 TechBio VC Funds
… might save you some time running around

Computer Science ‘cheat sheets’
for AI, ML, deep learning, …

To cloud or not to cloud?
… or not to cloud anymore

“AI critic Gary Marcus: Meta’s LeCun is finally coming around to the things I said years ago”
Bit of recent AI gossip between Gary Marcus and Yann LeCun

Mental Illness Is Not in Your Head
There are various societal and economic drivers behind it as well

… and clearly beyond cheminformatics

This is what a true liberation military force looks like

Pubs shutting down in Britain

“The best parallel for what Musk, Flynn, and Sachs are trying to do is the Pinochet coup in Chile on 9/11/1973”
Interesting developments in the US (and worldwide) these days

20 climate photographs that changed the world

“Belfast in the 70s”

I believe this is all from my side for now – if you have any information for me to circulate, or wish to present at one of our next Cambridge Cheminformatics or Digital Science for Drug Discovery Meetings, please just let me know; and hope to see you on 30 November in Cambridge, Oxford or Berlin – cheers!

Best wishes,


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