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Application of ligand- and receptor-based approaches for prediction of the HIV-RT inhibitory activity of fullerene derivatives

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Abstract

Fullerene and its derivatives have potential to be utilized in many biomedical applications. In the present study, we investigated the role of fullerene derivatives as inhibitors of HIV-RT by combined protein–ligand docking approach and QSAR methods. The study shows the best predictive QSAR model that represents a two-variable model. It has a good ratio of the number of descriptors and predictive ability. The main contributions to the inhibitory activity are provided by signal JhetZ descriptor and μ (dipole moment, as a measure of the polarity of a compound). The developed GA-MLRA-based model demonstrates a good performance, confirmed by statistics \(\left( {R^{2}_{\text{training}} = 0.867,\;Q^{2} = 0.788,\;R^{2}_{\text{test}} = 0.902} \right).\) The structure–activity analysis of these fullerene analogues allowed us to design and suggest for synthesis a set of new potentially active fullerenes. Finally, the molecular docking analysis was carried out to understand the details of interactions between HIV-RT and fullerene-C60 derivatives.

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Acknowledgments

This work was financially supported by The Scientific and Technological Research Council of Turkey (TÜBİTAK) and by NSF CREST Interdisciplinary Nanotoxicity Center NSF-CREST—Grant # HRD-0833178. The authors also thank the Extreme Science and Engineering Discovery Environment (XSEDE) for the award allocations (TG-DMR110088 and CHE140005) and the Mississippi Center for Supercomputer Research (Oxford, MS) for a generous allotment of a computer time. B.R. gratefully acknowledges support from the North Dakota State University Center for Computationally Assisted Science and Technology and the U.S. Department of Energy through Grant No. DE-SC0001717.

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Authors and Affiliations

  1. Department of Biomedical Devices and Technology, Kayseri Vocational School, Erciyes University, 38039, Kayseri, Turkey

    Hayriye Yilmaz

  2. Department of Chemistry and Biochemistry, Interdisciplinary Center for Nanotoxicity, Jackson State University, Jackson, MS, 39217, USA

    Hayriye Yilmaz, Lucky Ahmed, Bakhtiyor Rasulev & Jerzy Leszczynski

  3. Center for Computationally Assisted Science and Technology (CCAST), North Dakota State University, 1805 NDSU Research Park Dr, PO Box 6050, Fargo, ND, 58108, USA

    Bakhtiyor Rasulev

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  1. Hayriye Yilmaz
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Correspondence to Hayriye Yilmaz.

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Yilmaz, H., Ahmed, L., Rasulev, B. et al. Application of ligand- and receptor-based approaches for prediction of the HIV-RT inhibitory activity of fullerene derivatives. J Nanopart Res 18, 123 (2016). https://doi.org/10.1007/s11051-016-3429-7

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