• Title of article

    Molecular Docking and QSAR Study of 2-Benzoxazolinone, Quinazoline and Diazocoumarin Derivatives as Anti-HIV-1 Agents

  • Author/Authors

    Faghihi, Kamyar Department of Pharmaceutical Chemistry - Faculty of Pharmaceutical Chemistry - Tehran Medical Sciences, Islamic Azad University, Tehran, Iran , Safakish, Mahdieh Department of Medicinal Chemistry - School of Pharmacy - Shahid Beheshti University of Medical Sciences, Tehran, Iran , Zebardast, Tannaz Department of Pharmaceutical Chemistry - Faculty of Pharmaceutical Chemistry - Tehran Medical Sciences, Islamic Azad University, Tehran, Iran , Hajimahdi, Zahra Department of Medicinal Chemistry - School of Pharmacy - Shahid Beheshti University of Medical Sciences, Tehran, Iran , Zarghi, Afshin Department of Medicinal Chemistry - School of Pharmacy - Shahid Beheshti University of Medical Sciences, Tehran, Iran

  • Pages
    11
  • From page
    1253
  • To page
    1263
  • Abstract
    A series of 2-benzoxazolinone, diazocoumarin and quinazoline derivatives have been shown to inhibit HIV replication in cell culture. To understand the pharmacophore properties of selected molecules and design new anti-HIV agents, quantitative structure–activity relationship (QSAR) study was developed using a descriptor selection approach based on the stepwise method. Multiple linear regression method was applied to relate the anti-HIV activities of dataset molecules to the selected descriptors. Obtained QSAR model was statistically significant with correlation coefficient R2 of 0.84 and leave one out coefficient Q2 of 0.73. The model was validated by test set molecules giving satisfactory prediction value (R2 test) of 0.79. Molecules also were docked on HIV integrase enzyme and showed important interactions with the key residues in enzyme active site. These data might be helpful for design and discovery of novel anti-HIV compounds.
  • Keywords
    Stepwise , Multiple linear regressions , QSAR , Anti-HIV , Docking
  • Journal title
    Astroparticle Physics
  • Serial Year
    2019
  • Record number

    2487127