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ANN and GMDH Algorithms in QSAR Analyses of Reactivation Potency for Acetylcholinesterase Inhibited by VX Warfare Agent

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Computational Collective Intelligence (ICCCI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10449))

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Abstract

Successful development of novel drugs requires a close cooperation of experimental subjects, such as chemistry and biology, with theoretical disciplines in order to confidently design new chemical structures eliciting the desired therapeutic effects. Herein, especially quantitative structure-activity relationships (QSAR) as correlation models may elucidate which molecular features are significantly associated with enhancing a specific biological activity. In the present study, QSAR analyses of 30 pyridinium aldoxime reactivators for VX-inhibited rat acetylcholinesterase (AChE) were performed using the group method of data handling (GMDH) approach. The self-organizing polynomial networks based on GMDH were compared with multilayer perceptron networks (MPN) trained by 10 different algorithms. The QSAR models developed by GMHD and MPN were critically evaluated and proposed for further utilization in drug development.

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References

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Acknowledgements

This work was supported by the project “Smart Solutions for Ubiquitous Computing Environments” FIM UHK, Czech Republic (under ID: UHK-FIM-SP-2017-2102). This work was also supported by long-term development plan of UHHK, by the IT4Innovations Centre of Excellence project (CZ.1.05/1.1.00/02.0070), and Czech Ministry of Education, Youth and Sports project (LM2011033).

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Authors and Affiliations

  1. Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, 50003, Hradec Kralove, Czech Republic

    Rafael Dolezal, Jiri Krenek, Veronika Racakova, Jan Trejbal & Kamil Kuca

  2. Department of Chemistry, Faculty of Sciences, University of Hradec Kralove, Rokitanskeho 62, 50003, Hradec Kralove, Czech Republic

    Rafael Dolezal, Natalie Karaskova, Michaela Melikova, Karel Kolar & Kamil Kuca

  3. Biomedical Research Center, University Hospital Hradec Kralove, Hradec Kralove, Czech Republic

    Rafael Dolezal & Kamil Kuca

  4. State Budget Professional Education Institution, Kosygina st. 17(3), Moscow, 119334, Russia

    Nadezhda V. Maltsevskaya

Authors
  1. Rafael Dolezal
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  2. Jiri Krenek
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  3. Veronika Racakova
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  4. Natalie Karaskova
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  5. Nadezhda V. Maltsevskaya
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  6. Michaela Melikova
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  7. Karel Kolar
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  8. Jan Trejbal
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  9. Kamil Kuca
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Corresponding author

Correspondence to Rafael Dolezal .

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Editors and Affiliations

  1. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Department of Computer Science, University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  3. Department of Information Systems, Gdynia Maritime University, Gdynia, Poland

    Piotr Jędrzejowicz

  4. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  5. Department of Information Systems, University of Münster, Münster, Germany

    Gottfried Vossen

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Dolezal, R. et al. (2017). ANN and GMDH Algorithms in QSAR Analyses of Reactivation Potency for Acetylcholinesterase Inhibited by VX Warfare Agent. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10449. Springer, Cham. https://doi.org/10.1007/978-3-319-67077-5_17

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  • DOI: https://doi.org/10.1007/978-3-319-67077-5_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67076-8

  • Online ISBN: 978-3-319-67077-5

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