Molecular parameters and the antimicrobial activity of some n-substituted amino acids


  • M. Yu. Golik National University of Pharmacy, Ukraine
  • O. S. Kryskiv National University of Pharmacy, Ukraine
  • A. M. Komissarenko National University of Pharmacy, Ukraine
  • O. V. Kolisnyk National University of Pharmacy, Ukraine



correlation, antimicrobial activity, N-substituted amino acids


The concept of “drug likeness” is used when developing drugs for a potential biologically active substance, which must meet some specific criteria, in particular it should be bioavailable. The traditional method of “drug likeness” assessment is verification of compliance with Lipinski’s rule.
Aim. To determine the compliance of the “drug likeness” concept for some N-substituted amino acids and identify the quantitative “structure – microbiological activity” relationships.
Materials and methods. Using ChemOffice 2016 software the physicochemical parameters determining the bioavailability of some N-substituted amino acids were calculated. Determination of the possible correlations and quantitative ratios of the biological activity data experimentally obtained with the molar refraction (MR) values calculated was conducted using STATISTIKA 8 program.
Results and discussion. All compounds studied in their physicochemical properties meet the requirements for new BAS at the stage of testing their biological activity (correspond to Lipinski’s rule). The dependence of the microbiological action of some N-substituted amino acids on MR is maximal for compounds, which MR value is in the range of 2.13-4.53. The growth of all microorganisms was observed for unsubstituted amino acids (MR < 2.8). The maximum activity of all compounds studied was observed against gram-positive (B. subtilis and S. aureus), and the less activity was against gram-negative microorganisms (E. coli, P. vulgaris, P. aeruginosa) and fungi (C. albicans). It may be associated with the structural peculiarities of the cellular wall. The MR values calculated correlate satisfactorily with the experimental data of the antimicrobial activity of compounds.
Conclusions. Statistically significant values of MR correlation with the values of the antimicrobial activity of some N-substituted amino acids against the microorganisms studied have been determined. It quantitatively confirms the presence of the “structure – activity” relationship in this series of compounds.

Author Biographies

M. Yu. Golik, National University of Pharmacy

Candidate of Chemistry (Ph.D.), associate professor of the Analytical Chemistry Department

O. S. Kryskiv, National University of Pharmacy

Candidate of Pharmacy (Ph.D.), associate professor of the Inorganic Chemistry Department

A. M. Komissarenko, National University of Pharmacy

Doctor of Pharmacy (Dr. habil.), professor of the Chemistry of Natural Compounds Department

O. V. Kolisnyk, National University of Pharmacy

Candidate of Pharmacy (Ph.D.), associate professor of the Pharmaceutical Chemistry Department


Bickerton, G. R., Paolini, G. V., Besnard, J., Muresan, S., Hopkins, A. L. (2012). Quantifying the chemical beauty of drugs. Nature

Chemistry, 4 (2), 90–98. doi: 10.1038/nchem.1243

Srivastava, K., Mishra, R., Khan, A. (2014). Molar refractivity based SAR/QSPR study of benzoic acid derivatives against mice in terms of median lethal dose. IJRPC, 4 (4), 898–905.

Sun, Y. Z., Yan, X. L., Li, Z. J., Meng, F. H. (2007). Application of Chemical Models in Toxicological study. Chinese J. Environ. Health,

, 734–736.

Putz, M. V., Lacrămă, A.–M. (2007). Introducing Spectral Structure Activity Relationship (S–SAR) Analysis. Application to Ecotoxicology. International Journal of Molecular Sciences, 8 (5), 363–391. doi: 10.3390/i8050363

Putz, M. V., Putz, A.–M., Lazea, M., Ienciu, L., Chiriac, A. (2009). Quantum–SAR Extension of the Spectral–SAR Algorithm. Application to Polyphenolic Anticancer Bioactivity. International Journal of Molecular Sciences, 10 (3), 1193–1214. doi: 10.3390/ijms10031193

Meng, F. H., Sun, Y. Z., Li, Z. J., Yan, X. L. (2007). The Application of QSAR in the Study of Chemicals Toxicity. Chem. Bioeng., 24, 5–7.

Lipinski, C. A. (2004). Lead– and drug–like compounds: the rule–of–five revolution. Drug Discovery Today: Technologies, 1 (4), 337–341. doi: 10.1016/j.ddtec.2004.11.007

Padrón, J. A., Carrasco, R., Pellón, R. F. (2002). Molecular descriptor based on a molar refractivity partition using Randic–type graph–theoretical invariant. J. Pharm. Pharmaceut. Sci., 5 (3), 258–266.

Komissarenko, A. N., Golik, М. Yu., Osolodchenko, O. P., Leonova, S. G., Dudka, K. I. (2017). The search of compounds with the

antimicrobial activity among derivatives of aliphatic б–amino acids. The scientific heritage, 1 (8), 68–71.

Golik, M. Y., Kryskiv, O. S., Komissarenko, A. M., Kolisnyk, O. V., Dudka, K. I. (2017). The quantitative “structure – antibacterial

activity” relationships in a series of N–substituted amino acids. Vìsnik Farmacìï, 1(89), 14–20. doi: 10.24959/nphj.17.2153

ChemOffice Professional. Available at:

Statistica. Available at:–Features

Biuiul, А., Tcefel, P. (2005). SPSS: Iskusstvo obrabotki informatcii. Analiz statisticheskikh dannykh i vosstanovlenie skrytykh zakonomernostei. SPb.: DiaSoftUP, 608.

Gubler, E. V., Genkin, A. A. (1973). Primenenie neparametricheskikh kriteriev statistiki v mediko–biologicheskikh issledovaniyakh. L.: Meditcina, 141.

Madigan, M., Martinko, J., Stahl, D., Clark, D. (2012). Brock Biology of Microorganisms, 13th Ed. New York: Pearson Education, 1155.






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