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…
Events
7 February 2023
Quantum Computing: What are the Pharma Use Cases?
Virtual Event
https://www.pistoiaalliance.org/eventdetails/quantum-computing-what-are-the-pharma-use-cases
8 February 2023
Cambridge Cheminformatics Network Meeting
Cambridge, UK and Online (Hybrid)
http://www.c-inf.net
Programme
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 http://www.c-inf.net for details)
Zoom registration at https://zoom.us/meeting/register/tJUrde2orTorHdT1PhFAuGspeCmf5tGXe4UX
15 February 2023
Berlin Digital Science for Drug Discovery Seminar
Berlin, Germany and Online (Hybrid)
http://www.digidrug.net
Programme
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 http://www.digidrug.net for details)
Zoom registration at https://zoom.us/meeting/register/tJEqdu-rqzIpHNNN2jZCZtmvYNkuD8i1r2BB
17 February 2023
What is a Chemical? Part IV: Innovation in Chemical Descriptions
IUPAC WorldFAIR Chemistry Webinar
https://tamusa.zoom.us/meeting/register/tZIlduuhqz8jGdaEo4gSpnJyl6WiFrLh1TdS
3-5 May 2023
Schrodinger 21st European User Group Meeting 2023
Lisbon, Portugal
https://events.bizzabo.com/417429
5 May 2023 (paper deadline 10 Feb)
Machine Learning for Drug Discovery Workshop (part of ICLR2023)
Virtual Event
https://sites.google.com/view/mldd-2023
19-21 June 2023 (abstract deadline 3 Feb)
Ninth Joint Sheffield Conference on Chemoinformatics
Sheffield, UK
https://cisrg.shef.ac.uk/shef2023
5 July 2023
2023 Milner Therapeutics Symposium
Cambridge, UK and Online
https://www.milner.cam.ac.uk/milner-symposium-2023
Vacancies
Senior Computational Drug Designer, Director Computational Drug Design
ExScientia
Oxford, UK
https://www.linkedin.com/jobs/view/3429562822
https://apply.workable.com/exscientia/j/2AF2C653DE
Distinguished Scientist, Modeling and Informatics
Merck
Boston, MA
https://www.linkedin.com/jobs/view/3457298449
Senior Scientist Cheminformatics
LifeArc
Stevenage, UK
https://www.linkedin.com/jobs/view/3398615222
PhD Research Fellow in de novo drug design
Bergen University
Bergen, Norway
https://www.jobbnorge.no/en/available-jobs/job/237094/phd-research-fellow-in-de-novo-drug-design
Assistant Professor in Machine Learning in the Life Sciences
Uppsala University
Uppsala, Sweden
https://www.uu.se/en/about-uu/join-us/details/?positionId=556674
Senior Lecturer/Reader (Associate Professor) in Bioinformatics
Bath University
Bath, UK
https://www.linkedin.com/jobs/view/3417540107
PhD and Postdoc position in AI for ligand/structure-based drug discovery
TU Eindhoven
Eindhoven, The Netherlands
https://jobs.tue.nl/en/vacancy/phd-on-artificial-intelligence-for-drug-discovery-977491.html
https://jobs.tue.nl/en/vacancy/postdoc-in-ai-for-protein-structurebased-drug-discovery-977511.html
Research Fellow in Self-Writing Code for Chemical Dynamics Simulations
University of Warwick
Warwick, UK
https://www.jobs.ac.uk/job/CWR788/research-fellow-in-self-writing-code-for-chemical-dynamics-simulations-106983-0123
PhD Studentships: Machine learning for chemistry
Nottingham University
Nottingham, UK
https://jobs.nottingham.ac.uk/Vacancy.aspx?ref=SCI2151
In Silico Biology Scientist
Grunenthal
Aachen, Germany
https://www.linkedin.com/jobs/view/3388426876
Cheminformatician
Pangea Botanica
Berlin, Germany or London, UK
https://www.pangeabotanica.com/people/careers#vacancies
Principal Data Scientist, Bioinformatics and AI-driven Precision Medicine
Sanofi
Chilly-Mazarin, France
https://www.linkedin.com/jobs/view/3399694546
Scientific Programmer/Web Developer
Astex
Cambridge, UK
https://www.linkedin.com/jobs/view/3446942376
Computational Chemist / Biophysicist
Leukocare
Planegg, Germany
https://www.linkedin.com/jobs/view/3433973823
Computational Chemist
C2CAT
Amsterdam, The Netherlands
https://www.linkedin.com/jobs/view/3436462805
Principal Scientist, Cheminformatics
Pfizer
Cambridge, MA
https://www.linkedin.com/jobs/view/3450694918
Computational Chemist
Wacker
Bughausen, Germany
https://www.linkedin.com/jobs/view/3437359878
Computational Chemist
BioAscent
Glasgow, UK
https://www.linkedin.com/jobs/view/3452062545
Software Developer, Scientific Software Developer, Machine Learning Researchers and Engineers
D. E. Shaw Research
New York, USA
https://www.linkedin.com/jobs/view/software-developers-for-drug-discovery-at-d-e-shaw-research-3415670561/
https://www.linkedin.com/jobs/view/scientific-software-developers-at-d-e-shaw-research-at-d-e-shaw-research-3430038796/
https://www.linkedin.com/jobs/view/3429048132
Cheminformatics…
Q-raKtion: A Semiautomated KNIME Workflow for Bioactivity Data Points Curation
https://pubs.acs.org/doi/10.1021/acs.jcim.2c01199
Might be helpful to some
DrugApp: A Method for Machine Learning-based Prediction of Drug Approval
https://github.com/HUBioDataLab/DrugApp
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
http://practicalcheminformatics.blogspot.com/2023/01/ai-in-drug-discovery-2022-highly.html
by Pat Walters
Quite a lot was happening in AI in Synthesis recently:
AiZynthTrain: robust, reproducible, and extensible pipelines for training synthesis prediction models
https://chemrxiv.org/engage/chemrxiv/article-details/6380bd380949e12fc255cfea
CoPriNet: Graph Neural Networks provide accurate and rapid compound price prediction for molecule prioritisation
https://doi.org/10.26434/chemrxiv-2022-gvk2k-v6
Merging enzymatic and synthetic chemistry with computational synthesis planning
https://www.nature.com/articles/s41467-022-35422-y
https://github.com/itai-levin/chemoenzymatic-askcos
“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”
https://github.com/ur-whitelab/exmol
(beware biases in your underlying data though!)
EFMC² – Computational Chemistry Initiative
https://www.efmc.info/computational-chemistry
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”
https://twitter.com/sciencescanner/status/1603706278236372994
An opinion by David Grainger
Cracking the black box of deep sequence-based protein-protein interaction prediction
https://www.biorxiv.org/content/10.1101/2023.01.18.524543v1
“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
https://arxiv.org/abs/2212.03551
“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”
https://twitter.com/culturaltutor/status/1605612578255798272
Quite beautiful indeed
Things You Should Never Do, Part I
https://www.joelonsoftware.com/2000/04/06/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
https://dibyaghosh.com/blog/probability/highdimensionalgeometry.html
How higher dimensions behave counter to intuition – relevant for sampling parameters, chemical space, …
The basics of quantum computing for chemists
https://onlinelibrary.wiley.com/doi/10.1002/qua.26990
As the title says
Probabilistic Machine Learning: Advanced Topics
https://probml.github.io/pml-book/book2.html
by Kevin Patrick Murphy, draft PDF freely accessible online
… and clearly beyond cheminformatics
Web3, the Metaverse, and the Lack of Useful Innovation
https://americanaffairsjournal.org/2022/11/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’
https://chance.amstat.org/2022/11/monty-hall
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
https://www.youtube.com/watch?v=13_U9VMqFRA
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”
https://www.linkedin.com/posts/hashem-al-ghaili-1b30679b_science-research-biology-activity-7007347552115118080-mL5U
Progress everywhere
Philip Glass, Etudes No 6 (Vikingur Olafsson)
https://music.youtube.com/watch?v=sZffgf4GoMQ
Maybe a bit too bombastic at times, I still quite like the richness of this piece
Froukje – Heb Ik Dat Gezegd?
https://music.youtube.com/watch?v=AVZnbRdtf3g&list=OLAK5uy_nBVQ7HwLsAFsinkI2XaPVcXQofz7GD0EU
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,
Andreas