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Int. J. Mol. Sci. 2011, 12(12), 9533-9569; doi:10.3390/ijms12129533
Article

Introducing Catastrophe-QSAR. Application on Modeling Molecular Mechanisms of Pyridinone Derivative-Type HIV Non-Nucleoside Reverse Transcriptase Inhibitors

1,* , 1
, 1,2,*  and 1
Received: 27 October 2011; in revised form: 28 November 2011 / Accepted: 12 December 2011 / Published: 20 December 2011
(This article belongs to the Special Issue Advances in Molecular Electronic Structure Calculations)
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Abstract: The classical method of quantitative structure-activity relationships (QSAR) is enriched using non-linear models, as Thom’s polynomials allow either uni- or bi-variate structural parameters. In this context, catastrophe QSAR algorithms are applied to the anti-HIV-1 activity of pyridinone derivatives. This requires calculation of the so-called relative statistical power and of its minimum principle in various QSAR models. A new index, known as a statistical relative power, is constructed as an Euclidian measure for the combined ratio of the Pearson correlation to algebraic correlation, with normalized t-Student and the Fisher tests. First and second order inter-model paths are considered for mono-variate catastrophes, whereas for bi-variate catastrophes the direct minimum path is provided, allowing the QSAR models to be tested for predictive purposes. At this stage, the max-to-min hierarchies of the tested models allow the interaction mechanism to be identified using structural parameter succession and the typical catastrophes involved. Minimized differences between these catastrophe models in the common structurally influential domains that span both the trial and tested compounds identify the “optimal molecular structural domains” and the molecules with the best output with respect to the modeled activity, which in this case is human immunodeficiency virus type 1 HIV-1 inhibition. The best molecules are characterized by hydrophobic interactions with the HIV-1 p66 subunit protein, and they concur with those identified in other 3D-QSAR analyses. Moreover, the importance of aromatic ring stacking interactions for increasing the binding affinity of the inhibitor-reverse transcriptase ligand-substrate complex is highlighted.
Keywords: Thom’s catastrophe polynomials; statistical factors; minimum statistical paths; QSAR structural domains; HIV-1 inhibitory activity Thom’s catastrophe polynomials; statistical factors; minimum statistical paths; QSAR structural domains; HIV-1 inhibitory activity
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Putz, M.V.; Lazea, M.; Putz, A.-M.; Duda-Seiman, C. Introducing Catastrophe-QSAR. Application on Modeling Molecular Mechanisms of Pyridinone Derivative-Type HIV Non-Nucleoside Reverse Transcriptase Inhibitors. Int. J. Mol. Sci. 2011, 12, 9533-9569.

AMA Style

Putz MV, Lazea M, Putz A-M, Duda-Seiman C. Introducing Catastrophe-QSAR. Application on Modeling Molecular Mechanisms of Pyridinone Derivative-Type HIV Non-Nucleoside Reverse Transcriptase Inhibitors. International Journal of Molecular Sciences. 2011; 12(12):9533-9569.

Chicago/Turabian Style

Putz, Mihai V.; Lazea, Marius; Putz, Ana-Maria; Duda-Seiman, Corina. 2011. "Introducing Catastrophe-QSAR. Application on Modeling Molecular Mechanisms of Pyridinone Derivative-Type HIV Non-Nucleoside Reverse Transcriptase Inhibitors." Int. J. Mol. Sci. 12, no. 12: 9533-9569.


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