Skip to main content
SpringerLink
Log in

Algebraic Modeling as One of the Methods for Solving Organic Chemistry Problems

  • Conference paper
  • First Online:
Information and Communication Technologies in Education, Research, and Industrial Applications (ICTERI 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1698))

  • 134 Accesses

Abstract

A brief review of molecular modeling methods and specialized software and their use for creating and researching molecular models was considered. The authors considered the algebraic approach to modeling molecular interactions in some environments to determine the triggering of the studied properties. In particular, the article describes the results of the first steps of building a tool for the study of molecular, and in particular, biomolecular interaction, based on the formalism of behavioral algebra and insertion modeling. The experiment’s results of applying the proposed approach to modeling atoms interaction (creating of atomic bonds - valence method), constructing the electronic configuration of the molecule/substance (molecular orbitals method), and calculating their main parameters are given. The formalization and properties analysis is considered using the insertion modeling platform.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Gettys, N.S.: Challenges for chemistry in the 21st century: report on the American chemical society presidential event. J. Chem. Educ. 75(6), 665 (1998). https://doi.org/10.1021/ed075p665

    Article  Google Scholar 

  2. Manley, J.B., Anastas, P.T., Cue Jr, B.W.: Frontiers in green chemistry: meeting the grand challenges for sustainability in R&D and manufacturing. J. Cleaner Prod. 16(6), 743–750 (2008)

    Google Scholar 

  3. James, T.D.: Specialty grand challenges in supramolecular chemistry. Front. Chem. 5, 83 (2017)

    Article  Google Scholar 

  4. Li, J., Peng, Z., Wang, E.: Tackling grand challenges of the 21st century with electroanalytical chemistry. J. Am. Chem. Soc. 140(34), 10629–10638 (2018). https://doi.org/10.1021/jacs.8b01302

    Article  Google Scholar 

  5. Peplow, M.: Chemistry’s grand challenges. https://www.chemistryworld.com/features/chemistrys-grand-challenges/6500.article. Accessed 21 Jan 2022

  6. The website of the Dial-a-Molecule EPSRC Grand Challenge Network. http://generic.wordpress.soton.ac.uk/dial-a-molecule/. Accessed 21 Jan 2022

  7. https://www.ccdc.cam.ac.uk/Community/initiatives/cspblindtests/. Accessed 21 Jan 2022

  8. The Cambridge Crystallographic Data Centre (CCDC). https://www.ccdc.cam.ac.uk/. Accessed 21 Jan 2022

  9. The Carbon Dioxide Utilisation Network. http://co2chem.co.uk/. Accessed 21 Jan 2022

  10. The Human Epigenome Consortium. https://www.epigenome.org/index.php. Accessed 21 Jan 2022

  11. Letichevsky, A., Letychevskyi, O., Peschanenko, V., Poltorackij, M.: An algebraic approach for analyzing of legal requirements. In: 2017 IEEE 25th International Requirements Engineering Conference Workshops (REW), pp. 209–212, IEEE. (2017)

    Google Scholar 

  12. Letychevskyi, O., Peschanenko, V., Radchenko, V., Poltoratskiy, M., Tarasich, Y.: Formalization and algebraic modeling of tokenomics projects. In: Proceedings of the 15th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops, pp. 577–584 (2019)

    Google Scholar 

  13. Letychevsky, O., Peschanenko, V., Radchenko, V., Hryniuk, Y., Yakovlev, V..: Algebraic patterns of vulnerabilities in binary code. In: Conference Proceedings of 2019 10th International Conference on Dependable Systems, Services and Technologies, DESSERT 2019, 8770033, pp. 70–73 (2019)

    Google Scholar 

  14. Kolchin, A., Letichevsky, A., Peschanenko, V., Drobintsev, P., Kotlyarov, V.: An approach to creating concretized test scenarios within test automation technology for industrial software projects. Autom. Control. Comput. Sci. 47(7), 433–442 (2013). https://doi.org/10.3103/S0146411613070213

    Article  Google Scholar 

  15. Letychevsky, O., Peschanenko, V., Radchenko, V., Orlovsky, M., Sobol A.: Algebraic approach to verification and testing of distributed application. PervasiveHealth: Pervasive Comput. Technol. Healthc. 37–43 (2019)

    Google Scholar 

  16. Letychevskyi, O., Peschanenko, V., Poltoratskyi, M., Tarasich, Y.: Platform for modeling of algebraic behavior: experience and conclusions. In: Proceedings of the 16th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops, vol. 2732, pp. 42–57 (2020)

    Google Scholar 

  17. Letichevsky, A., Letychevskyi, O., Peschanenko, V., Weigert, T.: Insertion modeling and symbolic verification of large systems. In: Fischer, J., Scheidgen, M., Schieferdecker, I., Reed, R. (eds.) SDL 2015. LNCS, vol. 9369, pp. 3–18. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24912-4_1

    Chapter  Google Scholar 

  18. Lengauer, T., Rarey, M.: Computational methods for biomolecular docking. Curr. Opin. Struct. Biol. 6(3), 402–406 (1996). https://doi.org/10.1016/S0959-440X(96)80061-3

    Article  Google Scholar 

  19. Haile, J.M.: Molecular Dynamics Simulation. John Wiley, New York (1992)

    Google Scholar 

  20. Rapaport, D.C.: The Art of Molecular Dynamics Simulation. Cambridge University Press (2004). https://doi.org/10.1017/CBO9780511816581

    Book  MATH  Google Scholar 

  21. Metropolis, N., Stanislaw, U.: The monte carlo method. J. Am. Stat. Assoc. 44(247), 335–341 (1949)

    Article  MATH  Google Scholar 

  22. Rubinstein, R.Y., Kroese, D.P.: Simulation and the monte carlo method. John Wiley, Hoboken, New Jersey (2016)

    Book  MATH  Google Scholar 

  23. Barbosa, N.S.V., de Almeida Lima, E.R., Tavares, F.W.: Molecular modeling in chemical engineering. In: Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier (2017). https://doi.org/10.1016/B978-0-12-409547-2.13915-0

    Chapter  Google Scholar 

  24. THE BioSPI PROJECT. http://www.wisdom.weizmann.ac.il/~biospi/index_main.html. Accessed 21 Jan 2022

  25. Phillips, A., Cardelli, L.: A correct abstract machine for the stochastic pi-calculus. Bioconcur 2004, ENTCS (2004)

    Google Scholar 

  26. Sneha ,T., Georrge, J.J.: In silico protein engineering: methods and tools. In: Proceedings of 10th National Science Symposium on Recent Trends in Science and Technology. Gujarat, India: Christ Publications, Gujara, pp. 73–80 (2018)

    Google Scholar 

  27. Blinov, M.L., Faeder, J.R., Goldstein, B., Hlavacek, W.S.: BioNetGen: software for rule-based modeling of signal transduction based on the interactions of molecular domains. Bioinf. (Oxford, England) 20(17), 3289–3291 (2004). https://doi.org/10.1093/bioinformatics/bth378

    Article  Google Scholar 

  28. Harris, L.A., et al.: BioNetGen 2.2: advances in rule-based modeling. Bioinformatics 32(21), 3366–3368 (2016). https://doi.org/10.1093/bioinformatics/btw469

    Article  Google Scholar 

  29. Jones, B.: Clinical radiobiology of proton therapy: modeling of RBE. Acta oncologica (Stockholm, Sweden) 56(11), 1374–1378 (2017). https://doi.org/10.1080/0284186X.2017.1343496

    Article  Google Scholar 

  30. Letichevsky, A., Letychevskyi, O., Peschanenko, V.: Insertion modeling and its applications. Comput. Sci. J. Moldova 24(3), 357–370 (2016)

    MathSciNet  MATH  Google Scholar 

  31. APS & IMS. http//www.apsystem.org.ua. Accessed 21 Jan 2022

    Google Scholar 

  32. Letichevsky, A., Gilbert, D.: A model for interaction of agents and environments. In: Bert, D., Choppy, C., Mosses, P.D. (eds.) WADT 1999. LNCS, vol. 1827, pp. 311–328. Springer, Heidelberg (2000). https://doi.org/10.1007/978-3-540-44616-3_18

    Chapter  Google Scholar 

  33. Baranov, S., Jervis, C., Kotlyarov, V., Letichevsky, A., Weigert T. Leveraging: UML to deliver correct telecom applications. In: Lavagno, L., Martin, G., Selic, B., (eds.) UML for Real: Design of Embedded Real-Time Systems. Kluwer Academic Publishers, Amsterdam, (2003)

    Google Scholar 

  34. Letichevsky, A., et al.: System specification with basic protocols. Cybern. Syst. Anal. 41, 479–493 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  35. Letichevsky, A., Godlevsky, A., Letychevsky, A., Potiyenko, S., Peschanenko, V.: Properties of a predicate transformer of the VRS system. Cybern. Syst. Anal. 46(4), 521–532 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  36. Letichevsky, A., Kapitonova, J., Letichevsky, A., Jr., Volkov, V., Baranov, S., Weigert, T.: Basic protocols, message sequence charts, and the verification of requirements specifications. Comput. Netw. 49(5), 661–675 (2005)

    Article  MATH  Google Scholar 

  37. Omega: a solver for quantifier-free problems in Presburger Arithmetic. https://coq.inria.fr/refman/addendum/omega.html. Accessed 21 Jan 2022

  38. CVC3. https://cs.nyu.edu/acsys/cvc3/. Accessed 21 Jan 2022

  39. Z3Prover. https://github.com/Z3Prover/z3. Accessed 21 Jan 2022

  40. Mathsat. http://mathsat.fbk.eu. Accessed 21 Jan 2022

  41. Richard F.W.; Bader, Atoms in Molecules. A Quantum Theory, Oxford University Press, Oxford, (1990)

    Google Scholar 

  42. Kumar, P.S.V., Raghavendra, V., Subramanian, V.: Bader’s theory of atoms in molecules (AIM) and its applications to chemical bonding. J. Chem. Sci. 128(10), 1527–1536 (2016). https://doi.org/10.1007/s12039-016-1172-3

    Article  Google Scholar 

  43. Jiang, C., Jin, X, Dong, Y., Chen, M.: Kekule.js: an open source javascript chemoinformatics toolkit . J. Chem. Inf. Model. 56(6), 1132–1138 (2016) https://doi.org/10.1021/acs.jcim.6b00167

  44. Private Enterprise LitSoft. http://litsoft.com.ua/ Accessed 21 Jan 2022

Download references

Acknowledgements

We would like to thank the company Private Enterprise LitSoft [44] for the opportunity to work with the platform for modeling, formal verification and testing of Blockchain / DLT systems behavior and cybersecurity research for our research and experiments in the modeling area. We are also grateful to the Glushkov Institute of Cybernetics of NAS of Ukraine for the theoretical and practical results in the field of verification that were used as a basis for our studies of formalization and algebraic modeling in the tokenomics projects area and to the Kherson State University for the active supporting of Insertion Modeling System.

Author information

Authors and Affiliations

  1. Private Enterprise LitSoft, Ap. 27, 83 Mykhailivska Str, Kherson, 73000, Ukraine

    Oleksandr Letychevskyi, Yuliia Tarasich, Volodymyr Peschanenko & Maksym Poltoratskyi

  2. V.M.Glushkov Institute of Cybernetics, NAS of Ukraine, 54 Volodymyrska Str, Kyiv, 01030, Ukraine

    Vladislav Volkov

  3. Kherson State University, 27University Str, Kherson, 73003, Ukraine

    Hanna Sokolova

Authors
  1. Oleksandr Letychevskyi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuliia Tarasich
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Volodymyr Peschanenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vladislav Volkov
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hanna Sokolova
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Maksym Poltoratskyi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuliia Tarasich .

Editor information

Editors and Affiliations

  1. Zaporizhzhia National University, Zaporizhzhia, Ukraine

    Vadim Ermolayev

  2. Techforce Infotech Pvt. Ltd., Barcelona, Spain

    David Esteban

  3. University of Warmia and Mazury in Olsztyn, Olsztyn, Poland

    Vitaliy Yakovyna

  4. University of Klagenfurt, Klagenfurt, Austria

    Heinrich C. Mayr

  5. V. N. Karazin Kharkiv National University, Kharkiv, Ukraine

    Grygoriy Zholtkevych

  6. Taras Shevchenko National University of Kyiv, Kyiv, Ukraine

    Mykola Nikitchenko

  7. Kherson State University, Kherson, Ukraine

    Aleksander Spivakovsky

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Letychevskyi, O., Tarasich, Y., Peschanenko, V., Volkov, V., Sokolova, H., Poltoratskyi, M. (2022). Algebraic Modeling as One of the Methods for Solving Organic Chemistry Problems. In: Ermolayev, V., et al. Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2021. Communications in Computer and Information Science, vol 1698. Springer, Cham. https://doi.org/10.1007/978-3-031-20834-8_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-20834-8_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20833-1

  • Online ISBN: 978-3-031-20834-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation