Skip to main content
SpringerLink
Log in

QSPR models for water solubility of ammonium hexafluorosilicates: analysis of the effects of hydrogen bonds

  • Original Research
  • Published:
Structural Chemistry Aims and scope Submit manuscript

Abstract

In the present study, adequate quantitative structure-activity relationship (QSAR) models were developed to analyze the water solubility of some ammonium hexafluorosilicates. All models were developed using structural descriptors calculated by the SiRMS method based on the simplex representation of the molecular structure and Dragon descriptors. Log P, equalized electronegativity, molecular refraction, and molecular weight were used as integral descriptors in addition to 2D structural descriptors. All QSAR models were obtained using the partial least squares (PLS) method. Model M1 examined the influence of various physicochemical and structural factors on the water solubility of the studied compounds. The interpretation results are consistent with the qualitative data of previous experimental works. It was possible to detail the features of the hydrogen bonds effect on the water solubility for investigated compounds The non-trivial nature of the effect of the hydrogen bond was also shown. QSPR model M2 could predict the solubility of new compounds of the studied type with satisfactory accuracy.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Sun H, Shah P, Nguyen K, Yu KR, Kerns E, Kabir M, Wang Y, Xu X (2019) Predictive models of aqueous solubility of organic compounds built on a large dataset of high integrity. Bioorg Med Chem 27:3110–3114

    Article  CAS  Google Scholar 

  2. Hossain S, Kabedev A, Parrow A, Bergström CAS, Larsson P (2019) Molecular simulation as a computational pharmaceutics tool to predict drug solubility, solubilization processes and partitioning. Eur J Pharm Biopharm 137:46–55

    Article  CAS  Google Scholar 

  3. Avdeef A (2020) Prediction of aqueous intrinsic solubility of druglike molecules using Random Forest regression trained with Wiki-pS0 database. ADMET & DMPK 8:29–77

    Article  Google Scholar 

  4. Klimenko K, Kuz’min V, Ognichenko L, Gorb L, Shukla M, Vinas N, Ed P, Polishchuk P, Artemenko A, Leszczynski J (2016) Novel enhanced applications of QSPR models: Temperature dependence of aqueous solubility. J Comput Chem 37:2045–2051

    Article  CAS  Google Scholar 

  5. Toropova AP, Toropov AA, Carnesecchi E, Benfenati E, Dorne JL (2020) The using of the Index of Ideality of Correlation (IIC) to improve predictive potential of models of water solubility for pesticides. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-020-07820-6

  6. Toropov AA, Toropova AP, Marzo M, Benfenati E (2020) Use of the index of ideality of correlation to improve aquatic solubility model. J Mol Graph Model 96:107525. https://doi.org/10.1016/j.jmgm.2019.107525

    Article  CAS  PubMed  Google Scholar 

  7. Toropov AA, Toropova AP, Benfenati E, Gini G, Leszczynska D, Leszczynski J (2013) CORAL: QSPR model of water solubility based on local and global SMILES attributes. Chemosphere 90:877–880. https://doi.org/10.1016/j.chemosphere.2012.07.035

    Article  CAS  PubMed  Google Scholar 

  8. Raevsky OA, Polianczyk DE, Grigorev VY, Raevskaja OE, Dearden JC (2015) In silico prediction of aqueous solubility: a comparative study of local and global predictive models. Mol Inf 34:417–430

    Article  CAS  Google Scholar 

  9. Raevsky OA, Grigorev VY, Polianczyk DE, Raevskaja OE, Dearden JC (2019) Aqueous drug solubility: What do we measure, calculate and QSPR predict? Mini-Rev Med Chem 19:362–372

    Article  CAS  Google Scholar 

  10. Gelmboldt VO (2009) Effects of hydrogen bonding in the chemistry of onium hexafluorosilicates. Russ J Inorg Chem 54:916–921

    Article  Google Scholar 

  11. Freire MG, Neves CMSS, Ventura SPM, Pratas MJ, Marrucho IM, Oliveira J, Coutinho JAP, Fernandes AM (2010) Solubility of non-aromatic ionic liquids in water and correlation using a QSPR approach. Fluid Phase Equilib 294:234–240

    Article  CAS  Google Scholar 

  12. Tantishaiyakul V (2005) Prediction of the aqueous solubility of benzylamine salts using QSPR model. J Pharm Biomed Anal 37:411–415

    Article  CAS  Google Scholar 

  13. Gelmboldt VO, Kravtsov VC, Fonari MS (2019) Ammonium hexafluoridosilicates: Synthesis, structures, properties, applications. J Fluor Chem 221:91–102

    Article  CAS  Google Scholar 

  14. Suge T, Kawasaki A, Ishikawa K, Matsuo T, Ebisu S (2008) Ammonium hexafluorosilicate elicits calcium phosphate precipitation and shows continuous dentin tubule occlusion. Dent Mater 24:192–198

    Article  CAS  Google Scholar 

  15. Brsikyan NA, Andriasyan LH, Badalyan GR, Harutyunyan АV, Petrosyan АM, Ghazaryan VV (2012) Comparative morphology of dentinal tubules occlusion at the use of different desensitizing agents in experiment. New Armenian Med J 6:52–55

    Google Scholar 

  16. Hosoya Y, Tadokore K, Otani H, Hidaka K, Inoue T, Miyazaki M, Tay FR (2013) Effect of ammonium hexafluorosilicate application for arresting caries treatment on demineralized primary tooth enamel. J Oral Sci 55:115–121

    Article  CAS  Google Scholar 

  17. Suge T, Shibata S, Ishikawa K, Matsuo T (2018) Fluoride activity of antibacterial ammonium hexafluorosilicate solution for the prevention of dentin caries. Am J Dent 31:103–106

    PubMed  Google Scholar 

  18. Gelmboldt VО, Anisimov VY, Shyshkin IO, Fonari MS, Kravtsov VC (2018) Synthesis, crystal structures, properties and caries prevention efficiency of 2-, 3-, 4-carboxymethylpyridinium hexafluorosilicates. J Fluor Chem 205:15–21

    Article  CAS  Google Scholar 

  19. Gelmboldt VO, Anisimov VY, Shyshkin IO, Fonari MS, Kravtsov VC (2018) Synthesis, structure and anticaries activity of 2-amino-4,6-dihydroxypyrimidinium hexafluorosilicate. Pharm Chem J 52:606–610

    Article  CAS  Google Scholar 

  20. Anisimov VY, Shyshkin IO, Levitsky AP, Gelmboldt VO (2019) Cariesprophylactic and periodontoprotective action of octenidine hexafluorosilicate in rats obtained cariesogenic ration. Farm Zh 3:86–95 (in Ukrainian)

    Article  Google Scholar 

  21. Gelmboldt VO, Koroeva LV, Ganin EV, Fonari MS, Botoshansky MM, Ennan AA (2008) Hexafluorosilicates of bis(carboxypyridinium) and bis(2-carboxyquinolinium). J Fluor Chem 129:632–636

    Article  CAS  Google Scholar 

  22. Kukushkin VYu, Kukushkin YuN (1990) Teoriya i praktika sinteza koordinatsionnykh soedinenii (Theory and practice of synthesis of coordination compounds). Nauka, Leningrad

  23. Gelmboldt VO, Ennan AA, Ganin EV, Simonov YA, Fonari MS, Botoshansky MM (2004) Synthesis and structure of fluorosilicic acid compounds with 4-aminobenzoic acid and with 4-aminobenzenesulfonamide. The role of H-bonding in crystal structure formation. J Fluor Chem 125:1951–1957

    CAS  Google Scholar 

  24. Wang A-R (2008) Bis[4-(2-nitrobenzenesulfonamido)pyridinium] hexafluorosilicate. Acta Crystallogr E64:o2405

    Google Scholar 

  25. Gelmboldt VО, Ganin EV, Koroeva LV, Botoshansky MM, Fonari MS (2010) Interaction of fluorosilicic acid with sulfa drugs. Bis(sulfathiazolium) hexafluorosilicate: spectral data and crystal structure. J Fluor Chem 131:719–723

    Article  CAS  Google Scholar 

  26. Steiner T (2002) The hydrogen bond in the solid state. Angew Chem Int Ed 41:48–76

    Article  CAS  Google Scholar 

  27. Gelmboldt VО, Ganin EV, Fonari MS, Koroeva LV, YuEd I, Botoshansky MM (2009) Hexafluorosilicates of bis(aminopyridinium). The relationship between H-bonding system and solubility of salts. J Fluor Chem 130:428–433

    Article  CAS  Google Scholar 

  28. Gelmboldt VO (2012) Effects of hydrogen bonds and the solubility of onium hexafluorosilicates. Russ J Inorg Chem 57:287–291

    Article  CAS  Google Scholar 

  29. European Pharmacopoeia (2010) 7th edition. Council оf Europe, Strasbourg

    Google Scholar 

  30. Gelmboldt VО, Ganin EV, Botoshansky ММ, Anisimov VY, Prodan OV, Kravtsov VC, Fonari MS (2014) Preparation, structure and properties of pyridinium/bipyridinium hexafluorosilicates. J Fluor Chem 160:57–63

    Article  CAS  Google Scholar 

  31. Gelmboldt VO, Shyshkin IO, Fonari MS, Kravtsov VC (2019) Synthesis, crystal structure and some properties of 4-hydroxymethylpyridinium hexafluorosilicate. J Struct Chem 60:1150–1155

    Article  CAS  Google Scholar 

  32. Kuz'min V, Artemenko A, Muratov E (2008) Hierarchical QSAR technology on the base of simplex representation of molecular structure. J Comput Aided Mol Des 22:403–421

    Article  CAS  Google Scholar 

  33. Kuz’min VE, Artemenko AG, Muratov EN, Polischuk PG, Ognichenko LN, Liahovsky AV, Hromov AI, Varlamova EV (2010) Virtual screening and molecular design based on hierarchical QSAR technology. In: Puzyn T, Leszczynski J, Cronin M (eds) Challenges and Advances in Computational Chemistry and Physics, vol 8, pp 127–176

    Google Scholar 

  34. Jolly WL, Perry WB (1973) Estimation of atomic charges by an electronegativity equalization procedure calibration with core binding energies. J Am Chem Soc 95:5442–5450

    Article  CAS  Google Scholar 

  35. Wang R, Fu Y, Lai L (1997) A new atom-additive method for calculating partition coefficients. J Chem Inf Comput Sci 37:615–621

    Article  CAS  Google Scholar 

  36. Ioffe BV (1983) Refraktometricheskiye metody khimii (Refractometric methods of chemistry). Chemistry, Leningrad (In Russian)

  37. Rappe AK, Casewit CJ, Colwell KS, Goddard III WA, Skiff WM (1992) UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations. J Am Chem Soc 114:10024–10035

    Article  CAS  Google Scholar 

  38. Dragon Professional version 5.5 -2007, http://www.talete.mi.it

  39. Rännar S, Lindgren F, Geladi P, Wold S (1994) A PLS kernel algorithm for data sets with many variables and fewer objects. Part 1: theory and algorithm. J Chemom 8:111–125

    Article  Google Scholar 

  40. Carhart RE, Smith DH, Venkataraghavan R (1985) Atom paris as molecular features in structure - activity studies. Definition and application. J Chem Inf Comput Sci 25:64–73

    Article  CAS  Google Scholar 

  41. Rogers D, Hopfinger AJ (1994) Application of genetic function approximation to quantitative structure-activity relationships and quantitative structure-property relationships. J Chem Inf Comput Sci 34:854–866

    Article  CAS  Google Scholar 

  42. Hasegawa K, Miyashita Y, Funatsu K (1997) GA strategy for variable selection in QSAR studies: GA-based PLS analysis of calcium channel antagonists. J Chem Inf Comput Sci 37:306–310

    Article  CAS  Google Scholar 

  43. Gramatica P (2007) Principles of QSAR models validation: internal and external. QSAR & Comb Sci 26:694–701

    Article  CAS  Google Scholar 

  44. Meloun M, Militku J, Hill M (2002) Crucial problems in regression modelling and their solutions. Analyst 127:433–450

    Article  CAS  Google Scholar 

  45. Goreshnik EA, Gelmboldt VO, Koroeva LV, Ganin EV (2011) Synthesis, crystal structure, IR-spectral data and some properties of 3,5-diamino-1,2,4-triazolium tetrafluoroborate and hexafluorosilicate. J Fluor Chem 132:138–142

    Article  CAS  Google Scholar 

Download references

Acknowledgments

Authors greatly appreciate the assistance of PhD Davide Vignati and PhD Mariya Gelmboldt in the preparation of the manuscript and helpful discussion.

Author information

Authors and Affiliations

  1. Department of Pharmaceutical Chemistry, Odessa National Medical University, Odessa, 65082, Ukraine

    Vladimir Gelmboldt & Ivan Shyshkin

  2. Department of Molecular Structures and Chemoinformatics, A. V. Bogatsky Physical-Chemical Institute NAS of Ukraine, Odessa, 65080, Ukraine

    Luidmyla Ognichenko & Victor Kuz’min

Authors
  1. Vladimir Gelmboldt
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Luidmyla Ognichenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ivan Shyshkin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Victor Kuz’min
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Luidmyla Ognichenko.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(XLSX 13 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gelmboldt, V., Ognichenko, L., Shyshkin, I. et al. QSPR models for water solubility of ammonium hexafluorosilicates: analysis of the effects of hydrogen bonds. Struct Chem 32, 309–319 (2021). https://doi.org/10.1007/s11224-020-01652-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11224-020-01652-3

Keywords

Search

Navigation