The Sidorov Group


Welcome to the Sidorov group at ICReDD, Hokkaido University!

Our lab is interested in the development of methods and tools for analysis and management of chemical data, as well as quantitative structure-property relationship models for molecules and reactions. Currently, both computational and experimental data are generated in abundance, and it is imperative to use special tools for its management and analysis, especially considering perspectives for automatization. On the other hand, modern Machine Learning methods including Deep learning and generative models allow us to rationalize the existing knowledge and build predictive models for various properties. Our research is currently focused on prediction of properties of catalysts, such as reactivity and selectivity, as well as automatization of experimental and computational data analysis for various applications.


2022.02 Our lab is established in Sapporo!


Institute for Chemical Reaction Design and Discovery (ICReDD), Hokkaido University
Kita 21 Nishi 10, Kita-ku, Sapporo, Hokkaido, 001-0021, Japan

About Pavel

Pavel was born in Kazan, Russia in 1989. After graduating from the inorganic chemistry department of the Institute of Chemistry in Kazan Federal University, he went to study Chemoinformatics as M.Sc. student in University of Strasbourg (France). He then joined Prof Varnek’s laboratory in the same university for his PhD thesis work, which was focused on the development of methods for analysis of chemical space and their application for modeling of anti-malarial drug properties. Having completed his PhD in 2017, he moved to Cancer Research Center of Marseille (France) to work as a postdoc with Dr Ballester, where he developed models for synergistic effects of anti-cancer drugs.  In 2019, he came to the Institute for Chemical Reaction Design and Discovery (ICReDD) of Hokkaido University in Sapporo, Japan, as a Co-PI of Prof Varnek and then began his independent career there in 2021.

CV (updated August 2022)

Email: pavel.sidorov AT



•Tsuji, N.*; Sidorov, P.*; Zhu, C.; Nagata, Y.; Gimadiev, T.; Varnek, A.*; List, B.* Predicting Highly Enantioselective Catalysts Using Tunable Fragment Descriptors. Angew. Chem. Int. Ed. 2023, 62, e202218659.
DOI: 10.1002/anie.202218659
•Gimadiev, T; Nugmanov, R; Khakimova, A; Fatykhova, A; Madzhidov, T*; Sidorov, P*; Varnek A*. “CGRdb2. 0: A Python Database Management System for Molecules, Reactions, and Chemical Data”, J. Chem. Inf. Model., 2021, DOI:10.1021/acs.jcim.1c01105.
•Gimadiev, T; Nugmanov, R; Batyrshin, D; Madzhidov, T; Maeda, S; Sidorov, P*; Varnek, A*. “Combined graph/relational database management system for calculated chemical reaction pathway data”, J. Chem. Inf. Model., 2021, 61(2), 554-559.
•Bort, W; Baskin, I; Gimadiev, T; Mukanov, A; Nugmanov, R; Sidorov, P; Marcou, G; Horvath, D; Klimchuk, O; Madzhidov, T; Varnek, A*. “Discovery of novel chemical reactions by deep generative recurrent neural network”, Sci. Rep., 2021, 11, 3178.

Previous works

•Sidorov, P; Naulaerts, S; Ariey-Bonnet, J; Pasquier, E; Ballester, P. “Predicting synergism of cancer drug combinations using NCI-ALMANAC data”, Frontiers in Chemistry, 2019, 509.
•Sidorov, P; Viira, B; Davioud-Charvet, E; Maran, U; Marcou, G; Horvath, D; Varnek, A. “QSAR modeling and chemical space analysis of antimalarial compounds”, J. Comp. Aid. Mol. Des., 2017, 31(5), 441-451.
•Sidorov, P; Gaspar, H; Marcou, G; Varnek, A; Horvath, D. “Mappability of drug-like space: towards a polypharmacologically competent map of drug-relevant compounds”, J. Comp. Aid. Mol. Des., 2015, 29(12), 1087-1108.
•Elhabiri, M; Sidorov, P; Cesar‐Rodo, E; Marcou, G; Lanfranchi, D A; Davioud‐Charvet, E; Horvath, D; Varnek, A. “Electrochemical Properties of Substituted 2‐Methyl‐1, 4‐Naphthoquinones: Redox Behavior Predictions”,  Chem. Eur. J., 2015, 21(8), 3415-3424.


We welcome enthusiastic researchers to join our team!  Please contact Pavel for more details.

For researchers outside of Japan, please refer to JSPS postdoctoral fellowship.