Viira, B.; Garcia-Sosa, A. T.; Maran, U. Chemical Structure and Correlation Analysis of HIV-1 NNRT and NRT Inhibitors and Database-Curated, Published Inhibition Constants with Chemical Structure in Diverse Datasets. J. Mol. Graph. Model. 2017, 76, 205-223.

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Viira, B.; Garcia-Sosa, A. T.; Maran, U. Chemical Structure and Correlation Analysis of HIV-1 NNRT and NRT Inhibitors and Database-Curated, Published Inhibition Constants with Chemical Structure in Diverse Datasets. J. Mol. Graph. Model. 2017, 76, 205-223.

QDB archive DOI: 10.15152/QDB.202   DOWNLOAD

QsarDB content

Property pKi: Antiviral binding affinity equilibrium constant as p(Ki) [-log(mol/L)]

Eq.1: Antiviral binding affinity for NNRTIs

Regression model (regression)

Open in:QDB ExplorerQDB Predictor

NameTypen

R2

σ

trainingtraining310.7080.448
validationexternal validation80.7250.510
Eq.3: Antiviral binding affinity for NRTIs

Regression model (regression)

Open in:QDB ExplorerQDB Predictor

NameTypen

R2

σ

trainingtraining260.7000.579
validationexternal validation60.7450.542

Citing

When using this QDB archive, please cite (see details) it together with the original article:

  • Viira, B.; Garcia-Sosa, A. T.; Maran, U. Data for: Chemical Structure and Correlation Analysis of HIV-1 NNRT and NRT Inhibitors and Database-Curated, Published Inhibition Constants with Chemical Structure in Diverse Datasets. QsarDB repository, QDB.202. 2017. http://dx.doi.org/10.15152/QDB.202

  • Viira, B.; Garcia-Sosa, A. T.; Maran, U. Chemical Structure and Correlation Analysis of HIV-1 NNRT and NRT Inhibitors and Database-Curated, Published Inhibition Constants with Chemical Structure in Diverse Datasets. J. Mol. Graph. Model. 2017, 76, 205-223. http://dx.doi.org/10.1016/j.jmgm.2017.06.019

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Title: Viira, B.; Garcia-Sosa, A. T.; Maran, U. Chemical Structure and Correlation Analysis of HIV-1 NNRT and NRT Inhibitors and Database-Curated, Published Inhibition Constants with Chemical Structure in Diverse Datasets. J. Mol. Graph. Model. 2017, 76, 205-223.
Abstract:Human immunodeficiency virus (HIV-1) reverse transcriptase is a major target for designing anti-HIV drugs. Developed inhibitors are divided into non-nucleoside analog reverse-transcriptase inhibitors (NNRTIs) and nucleoside analog reverse-transcriptase inhibitors (NRTIs) depending on their mechanism. Given that many inhibitors have been studied and for many of them binding affinity constants have been calculated, it is beneficial to analyze the chemical landscape of these families of inhibitors and correlate these inhibition constants with molecular structure descriptors. For this, the HIV-1 RT data was retrieved from the ChEMBL database, carefully curated, and original literature verified, grouped into NRTIs and NNRTIs, analyzed using a hierarchical scaffold classification method and modelled with best multi-linear regression approach. Analysis of the HIV-1 NNRTIs subset results in ten different common structural parent types of oxazepanone, piperazinone, pyrazine, oxazinanone, diazinanone, pyridine, pyrrole, diazepanone, thiazole, and triazine. The same analysis for HIV-1 NRTIs groups structures into four different parent types of uracil, pyrimide, pyrimidione, and imidazole. Each scaffold tree corresponding to the parent types has been carefully analyzed and examined, and changes in chemical structure favorable to potency and stability are highlighted. For both subsets, descriptive and predictive QSAR models are derived, discussed and externally validated, revealing general trends in relationships between molecular structure and binding affinity constants in structurally diverse datasets.
URI:http://hdl.handle.net/10967/202
http://dx.doi.org/10.15152/QDB.202
Date:2017-06-16


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