シドロフパベル

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シドロフパベル
Co-PI (ヴァーネックグループ)
連絡先

pavel.sidorov atmark icredd.hokudai.ac.jp

アレクサンドル・ヴァーネック グループ
主任研究者
教員
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    シドロフパベル
博士研究員

研究紹介

研究テーマ

In silico design of new molecules, materials and reactions

キーワード

Chemical databases, Quantitative Structure-Property Relationships (QSPR), Machine learning
研究概要

My research was focused on exploration and analysis of chemical space, as well as Quantitative Structure-Property Relationships modeling, from redox properties to the biological activity of antimalarial drugs or pairs of anti-cancer drugs. Now, in addition to QSPR modeling of reaction parameters, I study approaches for generation of novel compounds and reactions by Deep neural networks.

経歴

経歴書を参照願います。

代表的な研究成果

  • Mappability of drug-like space: towards a polypharmacologically competent map of drug-relevant compounds
    P. Sidorov, H. Gaspar, G. Marcou, A. Varnek, D. Horvath, J. Comp.Aid. Mol. Des., 2015, 29, 1087-1108
    DOI: 10.1007/s10822-015-9882-z
  • AntiMalarial Mode of Action (AMMA) Database: Data Selection, Verification and Chemical Space Analysis
    P. Sidorov, E. Davioud‐Charvet, G. Marcou, D. Horvath, A. Varnek, Mol. Inf., 2018, 9-10, 1800021
    DOI: 10.1002/minf.201800021
  • Electrochemical Properties of Substituted 2‐Methyl‐1, 4‐Naphthoquinones: Redox Behavior Predictions
    M. Elhabiri, P. Sidorov, E. Cesar‐Rodo, G. Marcou, D.A. Lanfranchi, E. Davioud‐Charvet, D. Horvath, A. Varnek, Chem. Eur. J., 2015, 21, 3415-3424
    DOI: 10.1002/chem.201403703
  • Predicting synergism of cancer drug combinations using NCI-ALMANAC data
    P. Sidorov, S. Naulaerts, J. Ariey-Bonnet, E. Pasquier, P. Ballester, Front. In Chem., 2019, 7, 509
    DOI: 10.3389/fchem.2019.00509
  • Classical scoring functions for docking are unable to exploit large volumes of structural and interaction data
    H. Li, J. Peng, P. Sidorov, Y. Leung, K.-S. Leung, M.-H. Wong, G. Lu, P. Ballester, Bioinformatics, 2019, 35, 3989-3995
    DOI: 10.1093/bioinformatics/btz183