ZANKOV, Dmitry

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ZANKOV, Dmitry
Postdoctoral Fellow
Contact

zankov atmark icredd.hokudai.ac.jp

VARNEK, Alexandre Group
Principal Investigator
Faculty Members
Postdoctoral Fellows
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    ZANKOV, Dmitry

About the Research

Research Theme

Computer-aided synthesis planning

Keyword

Chemoinformatics, Machine learning

Research Outline

My projects focus on the development of tools for computer-aided retro- and forward-synthesis. These tools combine search algorithms and deep learning methods.

Representative Research Achievements

  • QSAR modeling based on conformation ensembles using a multi-instance learning approach
    D. Zankov, M. Matveieva, A. Nikonenko, R. Nugmanov, I. Baskin, A. Varnek, P. Polishchuk, T. Madzhidov. J. Chem. Inf. Model., 2021, 61(10), 4913–23.
    DOI: 10.1021/acs.jcim.1c00692
  • Conjugated Quantitative Structure-Property Relationship Models: Application to Simultaneous Prediction of Tautomeric Equilibrium Constants and Acidity of Molecules
    D. Zankov, T. Madzhidov, T. Gimadiev, R. Nugmanov, M. Kazymova, I. Baskin, A. Varnek.
    J. Chem. Inf. Model., 2019, 59(11), 4569–4576.
    DOI: 10.1021/acs.jcim.9b00722
  • Multi-Instance Learning Approach to Predictive Modeling of Catalysts Enantioselectivity
    D. Zankov, P Polishchuk, T. Madzhidov, A. Varnek. Synlett., 2021, 18, 1833-1836.
    DOI: 10.1055/a-1553-0427<

Publications

2023

  • 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