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Cambridge Cheminformatics Newsletter, 1 February 2023

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 8 February the next Cambridge Cheminformatics Meeting, and on 15 February the next Berlin Digital Science for Drug Discovery Seminar will take place, both in hybrid mode, so they can be attended from any location worldwide. See below for further information, and hope to see you there!

So here we go…


7 February 2023
Quantum Computing: What are the Pharma Use Cases?
Virtual Event

8 February 2023
Cambridge Cheminformatics Network Meeting
Cambridge, UK and Online (Hybrid)


InChIng Towards Better Molecular Identifiers
Jonathan Goodman, University of Cambridge and Ian Bruno, CCDC

Huge Chemical Space Exploration Using 3D-Hydrophobic Profiles
Javier Vazquez, Pharmacelera

Fragment-Based Hit Discovery via Unsupervised Learning of Fragment-Protein Complexes
Will McCorkindale, University of Cambridge

In Person at the CCDC (see for details)
Zoom registration at

15 February 2023
Berlin Digital Science for Drug Discovery Seminar
Berlin, Germany and Online (Hybrid)


Integrating Physical Modeling and Machine Learning to Enable Rational Kinase Inhibitor Polypharmacology
John Chodera, Memorial Sloan Kettering Cancer Center

Molecular Dynamics of GPCR-Gprotein complexes
Guillermo Pérez Hernández, Charite

In Person at Free University, Berlin (see for details)
Zoom registration at

17 February 2023
What is a Chemical? Part IV: Innovation in Chemical Descriptions
IUPAC WorldFAIR Chemistry Webinar

3-5 May 2023
Schrodinger 21st European User Group Meeting 2023
Lisbon, Portugal

5 May 2023 (paper deadline 10 Feb)
Machine Learning for Drug Discovery Workshop (part of ICLR2023)
Virtual Event

19-21 June 2023 (abstract deadline 3 Feb)
Ninth Joint Sheffield Conference on Chemoinformatics
Sheffield, UK

5 July 2023
2023 Milner Therapeutics Symposium
Cambridge, UK and Online


Senior Computational Drug Designer, Director Computational Drug Design
Oxford, UK

Distinguished Scientist, Modeling and Informatics
Boston, MA

Senior Scientist Cheminformatics
Stevenage, UK

PhD Research Fellow in de novo drug design
Bergen University
Bergen, Norway

Assistant Professor in Machine Learning in the Life Sciences
Uppsala University
Uppsala, Sweden

Senior Lecturer/Reader (Associate Professor) in Bioinformatics
Bath University
Bath, UK

PhD and Postdoc position in AI for ligand/structure-based drug discovery
TU Eindhoven
Eindhoven, The Netherlands

Research Fellow in Self-Writing Code for Chemical Dynamics Simulations
University of Warwick
Warwick, UK

PhD Studentships: Machine learning for chemistry
Nottingham University
Nottingham, UK

In Silico Biology Scientist
Aachen, Germany

Pangea Botanica
Berlin, Germany or London, UK

Principal Data Scientist, Bioinformatics and AI-driven Precision Medicine
Chilly-Mazarin, France

Scientific Programmer/Web Developer
Cambridge, UK

Computational Chemist / Biophysicist
Planegg, Germany

Computational Chemist
Amsterdam, The Netherlands

Principal Scientist, Cheminformatics
Cambridge, MA

Computational Chemist
Bughausen, Germany

Computational Chemist
Glasgow, UK

Software Developer, Scientific Software Developer, Machine Learning Researchers and Engineers
D. E. Shaw Research
New York, USA


Q-raKtion: A Semiautomated KNIME Workflow for Bioactivity Data Points Curation
Might be helpful to some

DrugApp: A Method for Machine Learning-based Prediction of Drug Approval
Several approaches exist, this is one with public code (I am quite surprised how well this works – does it hold prospectively?)

AI in Drug Discovery 2022 – A Highly Opinionated Literature Review
by Pat Walters

Quite a lot was happening in AI in Synthesis recently:

AiZynthTrain: robust, reproducible, and extensible pipelines for training synthesis prediction models

CoPriNet: Graph Neural Networks provide accurate and rapid compound price prediction for molecule prioritisation

Merging enzymatic and synthetic chemistry with computational synthesis planning

“exmol is a package to explain black-box predictions of molecules. The package uses model agnostic explanations to help users understand why a molecule is predicted to have a property”
(beware biases in your underlying data though!)

EFMC² – Computational Chemistry Initiative
We are planning various events in the future, please let me know if you are interested

… beyond cheminformatics …

“A short thread on de novo hit generation in small molecule drug discovery”
An opinion by David Grainger

Cracking the black box of deep sequence-based protein-protein interaction prediction
“We found that overlaps between training and test sets resulting from random splitting lead to strongly overestimated performances, giving a false impression of the field. […] When data leakage is avoided by minimizing sequence similarities between training and test, performances become random, leaving this research field wide open.”

Talking About Large Language Models
“The more adept LLMs become at mimicking human language, the more vulnerable we become to anthropomorphism, to seeing the systems in which they are embedded as more human-like than they really are.”

“A thread of the most beautiful paintings of winter”
Quite beautiful indeed

Things You Should Never Do, Part I
So should you rewrite your code from scratch? 20 years old (Netscape 6.0!), yet still current

Trouble in High-Dimensional Land
How higher dimensions behave counter to intuition – relevant for sampling parameters, chemical space, …

The basics of quantum computing for chemists
As the title says

Probabilistic Machine Learning: Advanced Topics
by Kevin Patrick Murphy, draft PDF freely accessible online

… and clearly beyond cheminformatics

Web3, the Metaverse, and the Lack of Useful Innovation
I would tend to agree with many of the points made

Monty Hall and the ‘Leibniz Illusion’
Many of you will have heard of the “Three Doors problem”, this is a nice write-up of the societal aspects surrounding it, and ways to approach and comprehend its answer

70th Birthday Bhante Bodhidhamma’s Life story
From Pete from Manchester to Bhante in Burma. I can very much recommend Bhante’s retreats if you look to meditate in the future

“Introducing EctoLife, the world’s first Artificial Womb Facility, which can incubate up to 30,000 babies a year”
Progress everywhere

Philip Glass, Etudes No 6 (Vikingur Olafsson)
Maybe a bit too bombastic at times, I still quite like the richness of this piece

Froukje – Heb Ik Dat Gezegd?
Of recent interest in particular in the Netherlands (as recommended by my daughter)

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, cheers!

Best wishes,


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