Structural Chemistry

, Volume 24, Issue 5, pp 1665–1679 | Cite as

QSAR analysis of poliovirus inhibition by dual combinations of antivirals

  • E. N. Muratov
  • E. V. Varlamova
  • A. G. Artemenko
  • P. G. Polishchuk
  • L. Nikolaeva-Glomb
  • A. S. Galabov
  • V. E. Kuz’min
Original Research


We have applied Hierarchical QSAR Technology (HiT QSAR) to the prediction of antiviral effects of paired combinations of picornavirus replication inhibitors against poliovirus 1 (Mahoney) in vitro. The inhibition from all binary combinations of eight antivirals were investigated. Simplex representation of molecular structure (SiRMS) was used for the generation of molecular descriptors of both pure compounds and all dual mixture combinations. Predictive QSAR models were obtained using the partial least squares (PLS) method. Predictive power of the developed models was validated using eightfold external cross-validation (CV, \(Q_{\text{ext}}^{ 2}\) = 0.67–0.93). Adequate models (\(Q_{\text{ext}}^{ 2}\) = 0.53–0.97) were obtained in the same way for predicting measured inhibitory concentrations at other levels (i.e., IC30, IC40, IC60, IC70). The usage of predicted values of these concentrations in the framework of the feature net (FN) approach led to an insignificant increase in the quality of the obtained QSAR models (\(Q_{\text{ext}}^{ 2}\) = 0.71–0.94). Developed QSAR models were analyzed and interpreted so that structural fragments and components of the combination promoting the antiviral activity were determined (e.g., 2-(4-methoxyphenyl)-4,5-dihydrooxazole or the combination of N-hydroxybenzimidoyl and 3-methylisoxasole). Then the resulting consensus model was used to predict novel potent combinations of drugs. Combinations of enviroxime with pleconaril, WIN52084, and rupintrivir and the mixture of rupintrivir with disoxaril were predicted to cause the most inhibition of poliovirus 1 replication. HiT QSAR proved itself as an adequate tool for QSAR analysis of mixtures and, although the method described here is suitable only for binary mixtures, it can be easily extended for more complex combinations.


Dual combinations SiRMS Mixture descriptors Poliovirus 



The authors are very thankful to Ms. Jessica Wignall for her help in editing this manuscript. E. Muratov gratefully acknowledges the financial support from NIH (Grant GM66940) and EPA (RD 83382501 and R832720).

Conflict of interest

  The authors declare that they have no conflict of interest.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • E. N. Muratov
    • 1
    • 2
  • E. V. Varlamova
    • 1
  • A. G. Artemenko
    • 1
  • P. G. Polishchuk
    • 1
  • L. Nikolaeva-Glomb
    • 3
  • A. S. Galabov
    • 3
  • V. E. Kuz’min
    • 1
  1. 1.Department of Molecular Structure and Cheminformatics, A.V. Bogatsky Physical-Chemical InstituteNAS of UkraineOdessaUkraine
  2. 2.Laboratory for Molecular Modeling, Eshelman School of PharmacyUniversity of North CarolinaChapel HillUSA
  3. 3.The Stephan Angeloff Institute of MicrobiologyBulgarian Academy of SciencesSofiaBulgaria

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