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A quantitative structure-activity relationship study of anti-HIV activity of substituted HEPT using nonlinear models.

ABSTRACT: We performed studies on extended series of 79 HEPT ligands (1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine), inhibitors of HIV reverse-transcriptase with anti-HIV biological activity, using quantitative structure-activity relationship (QSAR) methods that imply analysis of correlations and representation of models. A suitable set of molecular descriptors was calculated, and the genetic algorithm was employed to select those descriptors which resulted in the best-fit models. The kernel partial least square and Levenberg-Marquardt artificial neural network were utilized to construct the nonlinear QSAR models. The proposed methods will be of great significance in this research, and would be expected to apply to other similar research fields.

SUBMITTER: Noorizadeh H

PROVIDER: S-EPMC3785711 | biostudies-other | 2013

REPOSITORIES: biostudies-other

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A quantitative structure-activity relationship study of anti-HIV activity of substituted HEPT using nonlinear models.

Noorizadeh Hadi H Sajjadifar Sami S Farmany Abbas A

Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents 20130227

We performed studies on extended series of 79 HEPT ligands (1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine), inhibitors of HIV reverse-transcriptase with anti-HIV biological activity, using quantitative structure-activity relationship (QSAR) methods that imply analysis of correlations and representation of models. A suitable set of molecular descriptors was calculated, and the genetic algorithm was employed to select those descriptors which resulted in the best-fit models. The kernel partial ...[more]

PMID: 24098069

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Project description:BackgroundAlthough substantial concerns about the inflammatory effects of engineered nanomaterial (ENM) have been raised, experimentally assessing toxicity of various ENMs is challenging and time-consuming. Alternatively, quantitative structure-activity relationship (QSAR) models have been employed to assess nanosafety. However, no previous attempt has been made to predict the inflammatory potential of ENMs.ObjectivesBy employing metal oxide nanoparticles (MeONPs) as a model ENM, we aimed to develop QSAR models for prediction of the inflammatory potential by their physicochemical properties.MethodsWe built a comprehensive data set of 30 MeONPs to screen a proinflammatory cytokine interleukin (IL)-1 beta (IL-1β) release in THP-1 cell line. The in vitro hazard ranking was validated in mouse lungs by oropharyngeal instillation of six randomly selected MeONPs. We established QSAR models for prediction of MeONP-induced inflammatory potential via machine learning. The models were further validated against seven new MeONPs. Density functional theory (DFT) computations were exploited to decipher the key mechanisms driving inflammatory responses of MeONPs.ResultsSeventeen out of 30 MeONPs induced excess IL-1β production in THP-1 cells. In vivo disease outcomes were highly relevant to the in vitro data. QSAR models were developed for inflammatory potential, with predictive accuracy (ACC) exceeding 90%. The models were further validated experimentally against seven independent MeONPs (ACC=86%). DFT computations and experimental results further revealed the underlying mechanisms: MeONPs with metal electronegativity lower than 1.55 and positive ζ-potential were more likely to cause lysosomal damage and inflammation.ConclusionsIL-1β released in THP-1 cells can be an index to rank the inflammatory potential of MeONPs. QSAR models based on IL-1β were able to predict the inflammatory potential of MeONPs. Our approach overcame the challenge of time- and labor-consuming biological experiments and allowed for computational assessment of MeONP inflammatory potential by characterization of their physicochemical properties. https://doi.org/10.1289/EHP6508.

Dataset Information

A quantitative structure-activity relationship study of anti-HIV activity of substituted HEPT using nonlinear models.

Publications

A quantitative structure-activity relationship study of anti-HIV activity of substituted HEPT using nonlinear models.

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