VARNEK, Alexandre

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VARNEK, Alexandre
Principal Investigator, Professor
University of Strasbourg
Research Areas
Chemoinformatics, Artificial Intelligence in Chemistry
Related Website

varnek atmark

VARNEK, Alexandre Group
Principal Investigator
  • thumbnail image
    VARNEK, Alexandre
Faculty Members
Postdoctoral Fellows

About the Research

Research Theme

In silico design of new molecules, materials and reactions


Chemoinformatics, Quantitative Structure-Activity Relationships, Synthesis design, Condensed Graph of Reaction, Chemical Space analysis, Big Data, Artificial Intelligence
Research Outline

Our research group deals with development of new methodology of computer-aided design of new molecules, materials and reactions using chemoinformatics approaches. In particularly, this concerns property adaptive ISIDA descriptors for structure-activity relationships, Condensed Graph of Reaction approach for chemical reactions mining, chemical cartography methods for Big Data analysis and de novo design using deep learning techniques.

For details on MANABIYA course topics, please follow this link. To learn more about MANABIYA in general, please click here.

Representative Research Achievements

  • QSAR modeling: where have you been? Where are you going to?
    A Cherkasov, EN Muratov, D Fourches, A Varnek, II Baskin, M Cronin, J. Med. Chem., 2014, 57, 4977-5010
    DOI : 10.1021/jm4004285
  • Critical assessment of QSAR models of environmental toxicity against Tetrahymena pyriformis: focusing on applicability domain and overfitting by variable selection
    I. Tetko, I Sushko, A. Pandey, H. Zhu, A Tropsha, E Papa, T Oberg, A. Varnek et al., J. Chem. Inf. Mod., 2008, 48, 1733-1746
    DOI : 10.1021/ci800151m
  • T Oberg, Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis
    H Zhu, A Tropsha, D Fourches, A Varnek, E Papa, P Gramatica, J. Chem. Inf. Mod., 2008, 48, 766-784
    DOI : 10.1021/ci700443v
  • Substructural fragments: an universal language to encode reactions, molecular and supramolecular structures
    A Varnek, D Fourches, F Hoonakker, VP Solov’ev, J. Comput. Aid. Mol. Des., 2005, 19, 693-703
    DOI : 10.1007/s10822-005-9008-0
  • ISIDA-Platform for virtual screening based on fragment and pharmacophoric descriptors
    A Varnek, D Fourches, D Horvath, O Klimchuk, C Gaudin, P Vayer, et al., Current Comput. Aid. Mol. Des., 2008, 4
    DOI : 10.2174/157340908785747465

Related Research



  • Chemical Complexity Challenge: Is Multi-Instance Machine Learning a Solution?
    D. Zankov, T. Madzhidov, A. Varnek, P. Polishchuk, Wiley Interdisciplinary Reviews-Computational Molecular Science, 2023, ,
    DOI: 10.1002/wcms.1698
  • Multi-Instance Learning Approach to the Modeling of Enantioselectivity of Conformationally Flexible Organic Catalysts
    D. Zankov, T. Madzhidov, P. Polishchuk, P. Sidorov, A. Varnek, J. Chem. Inf. Model., 2023, 63, 21, 6629–6641
    DOI: 10.1021/acs.jcim.3c00393
  • Challenges for Kinetics Predictions via Neural Network Potentials: A Wilkinson's Catalyst Case
    R. Staub, P. Gantzer, Y. Harabuchi, S. Maeda, A. Varnek, Molecules, 2023, 28 (11), 4477
    DOI: 10.3390/molecules28114477
  • Predicting Highly Enantioselective Catalysts Using Tunable Fragment Descriptors
    N. Tsuji, P. Sidorov, C. D. Zhu, Y. Nagata, T. Gimadiev, A. Varnek, B. List, Angew. Chem., Int. Ed., 2023, ,
    DOI: 10.1002/anie.202218659


  • CGRdb2.0: A Python Database Management System for Molecules, Reactions, and Chemical Data
    T. Gimadiev, R. Nugmanov, A. Khakimova, A. Fatykhova, T. Madzhidov, P. Sidorov, A. Varnek, J. Chem. Inf. Model., 2022, 62, 2015-2020
    DOI: 10.1021/acs.jcim.1c01105
  • SynthI: A New Open-Source Tool for Synthon-Based Library Design
    Y. Zabolotna, D. M. Volochnyuk, S. V. Ryabukhin, K. Gavrylenko, D. Horvath, O. Klimchuk, O. Oksiuta, G. Marcou, A. Varnek, J. Chem. Inf. Model., 2022, 62, 2151-2163
    DOI: 10.1021/acs.jcim.1c00754
  • Prediction of Optimal Conditions of Hydrogenation Reaction Using the Likelihood Ranking Approach
    V. A. Afonina, D. A. Mazitov, A. Nurmukhametova, M. D. Shevelev, D. A. Khasanova, R. I. Nugmanov, V. A. Burilov, T. I. Madzhidov, A. Varnek, International Journal of Molecular Sciences, 2022, 23,
    DOI: 10.3390/ijms23010248
  • Exploration of the Chemical Space of DNA-Encoded Libraries
    R. Pikalyova, Y. Zabolotna, D. M. Volochnyuk, D. Horvath, G. Marcou, A. Varnek, Molecular Informatics, 2022, 41,
    DOI: 10.1002/minf.202100289


  • A Close-up Look at the Chemical Space of Commercially Available Building Blocks for Medicinal Chemistry
    Y. Zabolotna, D. M. Volochnyuk, S. V. Ryabukhin, D. Horvath, K. S. Gavrilenko, G. Marcou, Y. S. Moroz, O. Oksiuta, A. Varnek, J. Chem. Inf. Model., 2021, 62, 2171-2185
    DOI: 10.1021/acs.jcim.1c00811
  • Machine Learning Modelling of Chemical Reaction Characteristics: Yesterday, Today, Tomorrow
    T. I. Madzhidov, A. Rakhimbekova, V. A. Afonina, T. R. Gimadiev, R. N. Mukhametgaleev, R. I. Nugmanov, I. Baskinc, A. Varnekkd, Mendeleev Communications, 2021, 31, 769-780
    DOI: 10.1016/j.mencom.2021.11.003
  • Atom-to-Atom Mapping: A Benchmarking Study of Popular Mapping Algorithms and Consensus Strategies
    A. Lin, N. Dyubankova, T. I. Madzhidov, R. I. Nugmanov, J. Verhoeven, T. R. Gimadiev, V. A. Afonina, Z. Ibragimova, A. Rakhimbekova, P. Sidorov, A. Gedich, R. Suleymanov, R. Mukhametgaleev, J. Wegner, H. Ceulemans, A. Varnek, Molecular Informatics, 2021, 41,
    DOI: 10.1002/minf.202100138
  • Reaction Data Curation I: Chemical Structures and Transformations Standardization
    T. R. Gimadiev, A. Lin, V. A. Afonina, D. Batyrshin, R. I. Nugmanov, T. Akhmetshin, P. Sidorov, N. Duybankova, J. Verhoeven, J. Wegner, H. Ceulemans, A. Gedich, T. I. Madzhidov, A. Varnek, Molecular Informatics, 2021, 40,
    DOI: 10.1002/minf.202100119
  • Multi-Instance Learning Approach to Predictive Modeling of Catalysts Enantioselectivity
    D. Zankov, P. Polishchuk, T. Madzhidov, A. Varnek, Synlett, 2021, 32, 1833-1836
    DOI: 10.1055/a-1553-0427
  • A Critical Overview of Computational Approaches Employed for COVID-19 Drug Discovery
    E. N. Muratov, R. Amaro, C. H. Andrade, N. Brown, S. Ekins, D. Fourches, O. Isayev, D. Kozakov, J. L. Medina-Franco, K. M. Merz, T. I. Oprea, V. Poroikov, G. Schneider, M. H. Todd, A. Varnek, D. A. Winkler, A. V. Zakharov, A. Cherkasov, A. Tropsha, Chemical Society Reviews, 2021, 50, 9121-9151
    DOI: 10.1039/d0cs01065k
  • Computer-Aided Design of New Physical Solvents for Hydrogen Sulfide Absorption
    A. A. Orlov, G. Marcou, D. Horvath, A. E. Cabodevilla, A. Varnek, F. de Meyer, Industrial & Engineering Chemistry Research, 2021, 60, 8588-8596
    DOI: 10.1021/acs.iecr.0c05923
  • NP Navigator: A New Look at the Natural Product Chemical Space
    Y. Zabolotna, P. Ertl, D. Horvath, F. Bonachera, G. Marcou, A. Varnek, Molecular Informatics, 2021, 40,
    DOI: 10.1002/minf.202100068
  • Cross-Validation Strategies in QSPR Modelling of Chemical Reactions
    A. Rakhimbekova, T. N. Akhmetshin, G. I. Minibaeva, R. I. Nugmanov, T. R. Gimadiev, T. I. Madzhidov, I. Baskin, A. Varnek, Sar and Qsar in Environmental Research, 2021, 32, 207-219
    DOI: 10.1080/1062936x.2021.1883107
  • Discovery of Novel Chemical Reactions by Deep Generative Recurrent Neural Network
    W. Bort, I. Baskin, T. Gimadiev, A. Mukanov, R. Nugmanov, P. Sidorov, G. Marcou, D. Horvath, O. Klimchuk, T. Madzhidov, A. Varnek, Scientific Reports, 2021, 11, 15
    DOI: 10.1038/s41598-021-81889-y
  • Combined Graph/Relational Database Management System for Calculated Chemical Reaction Pathway Data
    T. Gimadiev, R. Nugmanov, D. Batyrshin, T. Madzhidov, S. Maeda, P. Sidorov, A. Varnek, J. Chem. Inf. Model., 2021, 61, 554-559
    DOI: 10.1021/acs.jcim.0c01280


  • Comprehensive Analysis of Applicability Domains of QSPR Models for Chemical Reactions
    A. Rakhimbekova, T. I. Madzhidov, R. I. Nugmanov, T. R. Gimadiev, I. Baskin, A. Varnek, International Journal of Molecular Sciences, 2020, 21, 20
    DOI: 10.3390/ijms21155542
  • QSAR Without Borders (vol 10, Pg 531, 2020)
    E. N. Muratov, J. Bajorath, R. P. Sheridan, I. V. Tetko, D. Filimonov, V. Poroikov, T. I. Oprea, I. Baskin, A. Varnek, A. Roitberg, O. Isayev, S. Curtarolo, D. Fourches, Y. Cohen, A. Aspuru-Guzik, D. A. Winkler, D. Agrafiotis, A. Cherkasov, A. Tropsha, Chemical Society Reviews, 2020, 49, 3716-3716
    DOI: 10.1039/d0cs90041a
  • Application of the Mol2vec Technology to Large-Size Data Visualization and Analysis
    S. Shibayama, G. Marcou, D. Horvath, I. Baskin, K. Funatsu, A. Varnek, Molecular Informatics, 2020, 39, 10
    DOI: 10.1002/minf.201900170


  • Conjugated Quantitative Structure-Property Relationship Models: Application to Simultaneous Prediction of Tautomeric Equilibrium Constants and Acidity of Molecules
    DV. Zankov, TI. Madzhidov, A. Rakhimbekova, TR. Gimadiev, RI. Nugmanov, MA. Kazymova, II. Baskin, A. Varnek, J. Chem. Inf. Model., 2019, 59, 4569-4576
    DOI: 10.1021/acs.jcim.9b00722