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Strasbourg Summer School in Chemoinformatics - 2022

Chemoinformatics Strasbourg Summer School, Strasbourg 2022

Chemoinformatics Strasbourg Summer School 2022
University of Strasbourg, 27 June - 1 July 2022

We are happy to announce the 8th Strasbourg Summer School in Chemoinformatics (CS3-2022) to be held in Strasbourg, France, from 27th June to 1st July 2022.

CS3-2022 is a unique school mixing students, young and experienced scientists.

Registration is closed !

The program includes plenary lectures, poster session, oral presentations and hands-on tutorials. It covers the following topics:

· Artificial Intelligence in chemistry:

  • Artificial Intelligence in chemistry
  • Big Data analysis and visualization
  • Chemical Reactions mining
  • New trends in QSAR modeling
  • Materials informatics
  • In silico pharmacology

Among invited speakers, it is our pleasure to acknowledge the participation of many world-class scientists:

  • J. Bajorath (Univ. Bonn, Germany)
  • T. Langer (Univ. Vienna, Austria)
  • G. Schneider (ETH, Zürich, Switzerland)
  • A. Cherkasov (Univ. British Columbia, Canada)
  • A. Tropsha (Univ. North Carolina, Chappel Hill, USA)
  • P. Polishchuk (Palacký University Olomouc, Czech Republic)
  • M. Rarey (Univ. Hamburg, Germany)
  • O. Taboureau (Univ. Paris, France)
  • J. Medina-Franco (Univ. Mexico)
  • J. Kirchmair (Univ. Vienna, Austria)
  • E. Benfenati (Ist. Ricerche Farm. Mario Negri, Milan, Italy)
  • H. Senderowitz (Univ. Bar Ilan, Israel)
  • C. Coley (MTI, USA)
  • N. Stiefl (Novartis, Switzerland)
  • O. Engkvist (ASTRAZENECA).

A pre-conference ”Crash course in Chemoinformatics” for the beginners will be organized on June 27th from 9:00 to 16:00 (for registered participants only).
A pre-conference "Interactive Workshop with SeeSAR" will be organized on June 27th from 14:00 to 16:00.

Please note that the CS3 program also includes several short oral communications (20 min) in order to enable software editors to present their latest developments used in particular scientific projects. The number of communications is limited, a “first come, first served” policy will be applied.

Tiny URL of this page: https://tinyurl.com/CS3-2022
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  • Alexandre VARNEK (Chairman) - University of Strasbourg, France
  • Gilles Marcou - University of Strasbourg, France
  • Dragos Horvath - National Center for Scientific Research (CNRS), France
  • Olga Klimchuk - University of Strasbourg, France
  • Fanny Bonachera - National Center for Scientific Research (CNRS), France

Informations about Strasbourg University


Strasbourg Summer School - Strasbourg, France, 29 June - 3 July 2020

Welcome to Strasbourg !

Its magnificent Cathedral, its fine food, "La Petite France" the typical quarter beloved of the tourists, not to mention the Grande-Ile, a UNESCO World Heritage site, have given it its reputation as a city anchored in History and Tradition.

Located in the "Esplanade" district, the Central Campus is near Strasbourg historical center. Also called "Esplanade Campus", it is the main University of Strasbourg Campus, regrouping University headquarters and many University of Strasbourg elements (including the "Tour de Chimie"), as well as the main part of the research units. Several independant high schools are present as well (Ecole Supérieure des Arts Décoratifs de Strasbourg and INSA).

Conference venue

The conference will be held at the European Doctoral College building in the central campus of the University of Strasbourg (46 Boulevard de la Victoire, 67000 Strasbourg).

Campus map

1 : European Doctoral College (46 Bd de la Victoire, 67000 Strasbourg)
2 : Chemistry Tower (1 Rue Blaise Pascal, 67008 Strasbourg)
3 : Restaurant "le 32" (Boulevard de la Victoire, Strasbourg)

Social program map

Here are 3 proposed routes to get to the European Council (Av. de l’Europe, 67000 Strasbourg)

Route 1 : replacement bus + tram E

Route 2 : walking + bus 72 or L6

Route 3 : walking

Conference dinner map

1 : European Doctoral College (46 Bd de la Victoire, 67000 Strasbourg)
2 : Restaurant "la Bourse" (Place du Maréchal de Lattre de Tassigny, Strasbourg)

How to get to the Conference Venue ?

From the airport

  • Take the shuttle train until the terminus Strasbourg Railway Station (see here)
  • Take the tram line C, direction "Neuhof Rodolphe Reuss" and get off at the stop "Observatoire".

From the train station

Take the tram line C, direction "Neuhof / Rodolphe Reuss" and get off at the stop "Observatoire".

From a bus or tram station

The Central Campus is situated near the tram station "Observatoire" on lines C and E.
Please check the map of the city network Here

By car

Coming from the North, on highway A4:

  • Follow the directions to "Kehl".
  • After the tunnel, stay on the left and follow the direction "Esplanade".
  • Turn left and cross the Pont du Danube.
  • Go straight on Rue d’Ankara and on Rue de Leicester.
  • Turn left to rue de Londres.
  • At traffic light, go straight across avenue du General de Gaulle and the tram rails.
  • Enter the Place d’Athènes, which is in front of the Campus Central.

Coming from the South, on highway A35:

  • Take the Exit "Place de l’Etoile-Neudorf", stay on the left lane.
  • Follow the direction to Kehl.
  • Continue as described above (directions for coming from the North on highway A4).

Important information !

There will be roadworks during the summer school, impacting the tram routes. As a result, there won’t be any tram circulating between the stations "Republique" and "Observatoire". Replacement busses will be put into circulation.

You can read the document below for more details.

The map of the central campus is available here.

Photos by Jonathan Martz and Geneviève Engel.

Program of the School


The program includes plenary lectures, poster session, oral presentations and hands-on tutorials. It covers the following topics:

  • Big Data in chemistry
  • Material Informatics
  • Machine-Learning methods
  • Virtual screening techniques
  • In silico pharmacology
Chemoinformatics Strasbourg Summer School
(University of Strasbourg, 27 June - 1 July 2022)

Monday 27 June

13:40 - 16:40 Registration
9:00 - 16:15 Preconference session “Introduction to Chemoinformatics”
16:45 - 17:00 Opening
17:00 - 18:00 Jürgen BAJORATH

(University of Bonn, Germany)

Rationalizing Molecular Promiscuity through Data Analysis and Explainable Machine Learning


18:00 - 19:45 Welcome Party

Tuesday 28 June

9:00 - 9:40 Gisbert SCHNEIDER

(ETH Zurich, Switzerland)

De Novo Molecular Design with Machine Intelligence



9:40-10:20 Emilio BENFENATI

(Ist. Ricerche Farm. Mario Negri, Milan, Italy)

In silico models for the REACH and the food regulation: perspectives for the near future



10:20-10:40 coffee break
10:40-11:20 Connor COLEY

(Massachusetts Institute of Technology, Cambridge, USA)

Learning patterns of chemical reactivity from experimental data



11:20-12:00 Matthias RAREY

( University of Hamburg, Germany)

Chemoinformatics operating in Chemical Space


12:00-14:00 Lunch
14:00-14:20 Marcus GASTREICH

(BioSolveIT Germany)

Why Everybody Talks About Chemical Space Exploration



14:20-14:40 David RINALDO

(Schrödinger GmbH)

Finding Hits in Large Chemical Spaces by Combining Docking with Deep Learning
14:40-15:00 Brice HOFFMANN

(IKTOS, France)

Representing, predicting, and generating simple and complex peptides



15:00-17:00 Tutorial 1 – Gilles MARCOU
(University of Strasbourg, France)
Tutorial on Generative Topographic Mapping Landscapes
17:00-19:00 Poster session Beer & Bretzel

Wednesday 29 June

9:00-9:40 Alex TROPSHA

(University of North Carolina, USA)

Development of Biomedical Knowledge Graphs and their application to drug discovery


9:40-10:20 Hanoch SENDEROWITZ

(Bar Ilan University, Israel)

Materials Informatics: The marriage of materials and data sciences



10:20-10:40 coffee break
10:40-11:20 Thierry LANGER

(University of Vienna, Austria)

Approaches to Next Generation Pharmacophore Modelling



11:20-12:00 Pavel POLISHCHUK

(Palacky University, Olomouc, Czech Republic)

Explainable artificial intelligence: evolution, achievements and perspectives



12:00-14:00 Lunch
14:00-14:20 Francois BERENGER

(University of Tokyo, Japan)

Molecular Generation by Fast Assembly of (Deep)SMILES Fragments



14:20-14:40 Johanna GIOVANNINI

(University of Caen, France)

Towards DAG-based interactive pharmacophore exploration: application to the BCR-ABL ligand set



14:40-15:00 Nathalie LAGARDE (Replacing Matthieu MONTES)

(HESAM University, Paris, France)

VTX: High-performance molecular structure and dynamics visualization software


15:00-17:00 Tutorial 2 – Célien JACQUEMARD
(University of Strasbourg, France)
Tutorial on protein cavities alignment with ProCare
17:00-19:00 Beer & Bretzel

Thursday 30 June

9:00-9:40 Johannes KIRCHMAIR

(University of Vienna, Austria)

Cheminformatics in Natural Product-based Drug Discovery



09:40-10:00 Yuliana ZABOLOTNA

(University of Strasbourg, France)

ChemSpace Atlas: Multiscale Chemography of Ultra-Large Libraries For Drug Discovery


10:00-10:20 Črtomir PODLIPNIK

(University of Ljubljana, Slovenia)

COVID.SI - A Crowdsourced Drug Discovery Project



10:20-10:40 coffee break
10:40-11:00 Joao AIRES DE SOUSA

(New University of Lisbon, Portugal)

ML prediction of C-H bond energies: calibration of DFT-based models with experimental data


11:00-11:20 Moritz WALTER

(University of Sheffield, United Kingdom)

Interpreting Neural Network Models for Toxicity Prediction by Extracting Learned Chemical Features



11:20-12:00 Ola ENGKVIST

(ASTRAZENECA, Gothenburg, Sweden)

AI for drug design an industrial perspective



12:00-14:00 Lunch
15:00-19:00 Cultural Program
19:00 Conference Dinner

Friday 1 July

9:00-9:40 José L. MEDINA-FRANCO

(National Autonomous University, Mexico)

Advancing epigenetic drug discovery with epi-informatics



9:40-10:20 Artem CHERKASOV

(University of British Columbia, Canada)

Deep Docking – the AI-enabled platform for advanced virtual screening


10:20-10:40 coffee break
10:40-11:20 Olivier TABOUREAU

(Paris Cité University, France)

Cheminformatics and Network science applied with high content screening data



11:20-12:00 Nikolaus STIEFL

(Novartis, Switzerland)

Augmenting Drug Hunters with Generative Chemistry Models



12:00 Closure

no publication

Crash course in Chemoinformatics

The crash-course will take place on Monday, June 27, from 8:30 a.m. to 4:15 p.m.

08:30-09:30 Lecture 1 (Dragos Horvath): In Silico Drug Design
09:30-10:30 Lecture 2 (Gilles Marcou): Introduction to data mining
10:30-10:50 Coffee break
10:50-12:00 Lecture 3 (Esther Kellenberger): Structure-based ligand discovery: when structural bioinformatics meets chemoinformatics
12:00-13:30 Lunch break (Resto 32)
13:30-14:40 Tutorial (Gilles Marcou): From chemical structures to outlier analysis
14:40-15:00 Coffee break
15:00-16:10 Tutorial (Dragos Horvath, Esther Kellenberger, Gilles Marcou): Docking

Contact : Dr. Gilles Marcou

Interactive Workshop with SeeSAR

Advanced 3D Modeling: LO, FBLD, Ph4 - and More

Marcus Gastreich (BioSolveIT Germany)

Beyond the obvious tasks, SeeSAR can also swiftly be used for more advanced tasks. In this workshop that addresses scenarios where the non-obvious is needed or where roads get bumpy: We shall use the tool to overcome hurdles, realize scenarios when NOT to trust the computer blindly, and hunt for good, well-fitting molecules. This for example refers to:

  • My ∆G is far off. What now?
  • That docking does not work. How can I proceed?
  • I am in desperate need for another core here.
  • But I need that interaction with that amino acid up there.
  • The boss wants me to come up with fragments attached that explore this sub-pocket.

Using indexing techniques, pharmacophores in combination with SMARTS expressions, and several other functionalities, we will discuss remedies for such scenarios.

If time permits, we will also navigate through chemical spaces of multi-billion member sizes.

You will use your own computer! Bring it along, and make sure you have:

Sponsors of the event


Tutorials of the school

no publication

Tutorial on GTM Landscapes

The tutorial aims at presenting the Generative Topographic Mapping (GTM) landscapes . For more details about the GTM algorithm, see [Bishop et al, Neural Computation 10, No. 1, 215–234 (1998)]. For details about GTM predictive models and landscapes, see [H.A. Gaspar et al. Mol. Informatics, 2015, 34 (6-7), 348-356]

The GTM is an unsupervised method to map high dimensional data to a two-dimensional representation. In the process, the GTM builds a probabilistic model of the data that can be exploited for data characterization, comparison or classification and regression model building. The GTM approach will be used to analyze a bioconcentration factor dataset and to explore structure-activity relationships. As a result, several property and activity landscapes will be generated and visualized.


The tutorial is based on six pieces of software:

  • xGTMapTool: a graphical user interface frontend for the preparation of a GTM.
  • xGTMview: an application to link the GTM trained on chemical data and the chemical structures.
  • xGTMReSample: an application to improve the resolution of a GTM model.
  • xGTMReg: an application to build and validate a GTM-based regression model.
  • xGTMClass: an application to build and validate a GTM-based classification model.
  • xGTMLandscape: an application to visualize and navigate the activity and property landscapes.

The software are supplied online and can be downloaded for the OS of your choice.:

  • Windows (Win10, 64bits)
  • Mac (for Intel: Monterey 12.4. For M1: BigSur or Monterey 12.4)
  • Linux (Ubuntu 20 64bits or Ubuntu 20 64 bits)

Download link (Contains Software + License - valid until the 1st of August, 2022)

Software available until the 17th of July, 2022

Later, you can ask for updated versions here:

The license of the software is distributed freely and a license file, called "licence.dat_CS32022" (to be renamed to "licence.dat") is distributed with the software for the OS of your choice (Windows, Mac or Linux).

The license file must be installed in a proper location to be found.

  • On Windows: create the directory AppData\local\ISIDAGTM directory at the root of your home directory and copy the file license.dat in it. The absolute path of the file should be similar to this one:


The file and the directory should have read and write permissions.

  • On Mac: create the directory .config/ISIDAGTM directory at the root of your home directory and copy the file license.dat in it. The absolute path of the file should be similar to this one:


  • On Linux: create the directory .config/ISIDAGTM directory at the root of your home directory and copy the file license.dat in it. The absolute path of the file should be similar to this one:


Datasets and Step-by-step instructions

The tutorial uses a dataset of bioconcentration factor Lunghini, F.et al. QSAR & Env. Protection, 30(7), 507-524].

The dataset and instructions can be downloaded here.

Tutorial on protein cavities alignment with ProCare

The tutorial will show you how to use ProCare to align protein cavities. A cavity is described as point clouds in which each point has a pharmacophoric property [J. Desaphy et al. J. Chem. Inf. Model., vol. 52, no 8, p. 2287‑2299 (2012)]. ProCare aligns two point clouds using a Point Cloud Registration algorithm allowing the comparison of cavities of different size (local alignment) [M. Eguida et al. J. Med. Chem., vol. 63, no 13, p. 7127‑7142 (2020)]. In this tutorial, co-crystallized fragmented ligands from the Protein Data Bank will be aligned onto the cavity of a target protein to suggest seed fragments for the de novo construction of a ligand.


The complete tutorial material can be downloaded here:


NB: The exercise will be done on your personal computer. To speed up preparation time, please install all necessary software BEFORE the session begins.


The ProCare software runs only on Linux operating systems. If you use another operating system, it is possible to run ProCare using virtualization software.


First download the “CS3_2022_procare.zip” archive and unzip it. Then follow the instructions given in the output directory to install software and scripts. Be careful! 7 Gb of free space is required!

MacOS or Windows

You will need the VirtualBox software installed on your computer. You can download this software by clicking on the corresponding link:
• Windows: https://download.virtualbox.org/virtualbox/6.1.34/VirtualBox-6.1.34a-150636-Win.exe
• MacOS: https://download.virtualbox.org/virtualbox/6.1.34/VirtualBox-6.1.34-150636-OSX.dmg

NB1: It is possible to use VMware software for this tutorial if you already installed it.
NB2: For Mac users, VirtualBox must has permission to access the computer. After installation, go to the Security and Privacy panel to change the security rule.

Then download the “Ubuntu_CS3_2022.zip” archive and unzip it. Be careful! 14 Gb of free space is required! The output directory contains the virtual machine file named “Ubuntu_CS3_2022.vmdk” in which there is an Ubuntu distribution with everything already installed.

To login use the following credentials:
• username: puser
• password: 1234




Credit photo : Petit Phil Photo