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QSAR of antimycobacterial activity of benzoxazoles by optimal SMILES-based descriptors

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Abstract

The CORAL software based on the optimal descriptors calculated with simplified molecular input-line entry system was used to build up quantitatively structure-activity relationship for the minimal inhibition concentrations against (i) Mycobacterium tuberculosis H37RV ATCC 27294 and (ii) M. tuberculosis drug resistant clinical isolate. The predictive potential of these models has been checked up with three random splits into the training, calibration, and validation sets. Although all models are quantitative, it has been found that splitting have apparent influence on the statistical quality of these models. Thus, the thesis “QSAR is a random event” is confirmed in this work.

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Acknowledgements

A.A.T. and A.P.T thank the project LIFE-COMBASE contract (LIFE15 ENV/ES/000416) for financial support. I.Y. and T.E.-B. thank the Research Fund of Ankara University (Grant No: 12B3336002) for the financial support.

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Authors and Affiliations

  1. Department of Analytical Chemistry, Charles University in Prague, Faculty of Science, Hlavova 8, 128 43, Prague 2, Czech Republic

    Karel Nesměrák

  2. IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156, Milano, Italy

    Andrey A. Toropov & Alla P. Toropova

  3. Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Ankara University, Tandogan, 06100, Ankara, Turkey

    Tugba Ertan-Bolelli & Ilkay Yildiz

Authors
  1. Karel Nesměrák
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  2. Andrey A. Toropov
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  3. Alla P. Toropova
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  4. Tugba Ertan-Bolelli
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  5. Ilkay Yildiz
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Correspondence to Alla P. Toropova.

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Nesměrák, K., Toropov, A.A., Toropova, A.P. et al. QSAR of antimycobacterial activity of benzoxazoles by optimal SMILES-based descriptors. Med Chem Res 26, 3203–3208 (2017). https://doi.org/10.1007/s00044-017-2013-8

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  • DOI: https://doi.org/10.1007/s00044-017-2013-8

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