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Journal of Computer-Aided Molecular Design

, Volume 19, Issue 4, pp 229–242 | Cite as

Quantitative Structure–activity Relationship Analysis of Pyridinone HIV-1 Reverse Transcriptase Inhibitors using the k Nearest Neighbor Method and QSAR-based Database Mining

  • Jose Luis Medina-Franco
  • Alexander Golbraikh
  • Scott Oloff
  • Rafael Castillo
  • Alexander Tropsha
Article

Summary

We have developed quantitative structure–activity relationship (QSAR) models for 44 non-nucleoside HIV-1 reverse transcriptase inhibitors (NNRTIs) of the pyridinone derivative type. The k nearest neighbor (kNN) variable selection approach was used. This method utilizes multiple descriptors such as molecular connectivity indices, which are derived from two-dimensional molecular topology. The modeling process entailed extensive validation including the randomization of the target property (Y-randomization) test and the division of the dataset into multiple training and test sets to establish the external predictive power of the training set models. QSAR models with high internal and external accuracy were generated, with leave-one-out cross-validated R2 (q2) values ranging between 0.5 and 0.8 for the training sets and R2 values exceeding 0.6 for the test sets. The best models with the highest internal and external predictive power were used to search the National Cancer Institute database. Derivatives of the pyrazolo[3,4-d]pyrimidine and phenothiazine type were identified as promising novel NNRTIs leads. Several candidates were docked into the binding pocket of nevirapine with the AutoDock (version 3.0) software. Docking results suggested that these types of compounds could be binding in the NNRTI binding site in a similar mode to a known non-nucleoside inhibitor nevirapine.

Keywords:

database mining docking HIV-1 kNN-QSAR non-nucleoside inhibitors reverse transcriptase 

Abbreviations

AIDS

Acquired immunodeficiency syndrome

HIV

Human immunodeficiency virus

kNN

k Nearest neighbor

MZ

MolConnZ

NNRTIs

Non-nucleoside reverse transcriptase inhibitors

QSAR

Quantitative structure–activity relationships

RT

Reverse transcriptase

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Copyright information

© Springer 2005

Authors and Affiliations

  • Jose Luis Medina-Franco
    • 1
  • Alexander Golbraikh
    • 2
  • Scott Oloff
    • 2
  • Rafael Castillo
    • 1
  • Alexander Tropsha
    • 2
  1. 1.Departamento de Farmacia, Facultad de QuímicaUniversidad Nacional Autónoma de MéxicoMexico CityMexico
  2. 2.Division of Medicinal Chemistry and Natural Products, School of PharmacyUniversity of North CarolinaChapel HillUSA

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