Virtual Screening and Molecular Design Based on Hierarchical Qsar Technology

  • Victor E. Kuz’minEmail author
  • A.G. Artemenko
  • Eugene N. Muratov
  • P.G. Polischuk
  • L.N. Ognichenko
  • A.V. Liahovsky
  • A.I. Hromov
  • E.V. Varlamova
Part of the Challenges and Advances in Computational Chemistry and Physics book series (COCH, volume 8)


This chapter is devoted to the hierarchical QSAR technology (HiT QSAR) based on simplex representation of molecular structure (SiRMS) and its application to different QSAR/QSPR tasks. The essence of this technology is a sequential solution (with the use of the information obtained on the previous steps) of the QSAR paradigm by a series of enhanced models based on molecular structure description (in a specific order from 1D to 4D). Actually, it’s a system of permanently improved solutions. Different approaches for domain applicability estimation are implemented in HiT QSAR. In the SiRMS approach every molecule is represented as a system of different simplexes (tetratomic fragments with fixed composition, structure, chirality, and symmetry). The level of simplex descriptors detailed increases consecutively from the 1D to 4D representation of the molecular structure. The advantages of the approach presented are an ability to solve QSAR/QSPR tasks for mixtures of compounds, the absence of the “molecular alignment” problem, consideration of different physical–chemical properties of atoms (e.g., charge, lipophilicity), and the high adequacy and good interpretability of obtained models and clear ways for molecular design. The efficiency of HiT QSAR was demonstrated by its comparison with the most popular modern QSAR approaches on two representative examination sets. The examples of successful application of the HiT QSAR for various QSAR/QSPR investigations on the different levels (1D–4D) of the molecular structure description are also highlighted. The reliability of developed QSAR models as the predictive virtual screening tools and their ability to serve as the basis of directed drug design was validated by subsequent synthetic, biological, etc. experiments. The HiT QSAR is realized as the suite of computer programs termed the “HiT QSAR” software that so includes powerful statistical capabilities and a number of useful utilities.


HiT QSAR Simplex representation SiRMS 



Automatic/Interactive/Evolutionary Variables Selection


Angiotensin Converting Enzyme




Comparative Molecular Fields Analysis QSAR approach


Comparative Molecular Similarity Indexes Analysis QSAR approach


Applicability Domain




Eigenvalue Analysis QSAR approach


Genetic Algorithm


Hierarchical QSAR Technology


Hologram QSAR approach


Human Rhinovirus


Herpes Simplex Virus


Multiple Linear Regression statistical method


Partial Least Squares or Projection on Latent Structures statistical method


cross-validation determination coefficient


Quantitative Structure-Activity/Property Relationship


determination coefficient for training set


determination coefficient for test set


Simplex Descriptor


Selectivity Index


Simplex Representation of Molecular Structure QSAR approach


Trend-Vector statistical method


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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Victor E. Kuz’min
    • 1
    Email author
  • A.G. Artemenko
    • 1
  • Eugene N. Muratov
    • 1
  • P.G. Polischuk
    • 1
  • L.N. Ognichenko
    • 1
  • A.V. Liahovsky
    • 1
  • A.I. Hromov
    • 1
  • E.V. Varlamova
    • 1
  1. 1.A.V. Bogatsky Physical-Chemical Institute NAS of UkraineOdessaUkraine

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