Turn off MathJax
Article Contents
Abdulla Al Mamun, Zheng Mei, Ling Qiu, Xue-hai Ju. Theoretical investigation on the QSAR of (2-methyl-3-biphenylyl) methanol (MBPM) analogs as PD-L1 inhibitor[J]. Chinese Journal of Chemical Physics .
Citation: Abdulla Al Mamun, Zheng Mei, Ling Qiu, Xue-hai Ju. Theoretical investigation on the QSAR of (2-methyl-3-biphenylyl) methanol (MBPM) analogs as PD-L1 inhibitor[J]. Chinese Journal of Chemical Physics .

Theoretical investigation on the QSAR of (2-methyl-3-biphenylyl) methanol (MBPM) analogs as PD-L1 inhibitor

  • Accepted Date: 2020-07-02
  • Available Online: 2019-12-01
  • Cancer is one of the most serious issues in human life. Blocking Programmed cell death protein 1 (PD-1) and programmed death ligand-1 (PD-L1) pathway is one of the great innovation on last few years, but a few numbers of inhibitors can be able to block it. (2-methyl-3-biphenylyl) methanol (MBPM) derivative is one of them. Here, the quantitative structure-activity relationship (QSAR) established twenty (2-methyl-3-biphenylyl) methanol (MBPM) derivatives as the programmed death ligand-1 (PD-L1) inhibitors. Density functional theory (DFT) at the B3LPY/6-31+G (d, p) level was employed to study the chemical structure and properties of the chosen compounds. Highest occupied molecular orbital energy EHOMO, lowest unoccupied molecular orbital energy ELUMO, total energy ET, dipole moment DM, absolute hardness η, absolute electronegativity χ, softness S, electrophilicity ω, energy gap ΔE, etc, properties were observed and determine. Principal component analysis (PCA), multiple linear regression (MLR) and multiple non-linear regression (MNLR) analysis were carried out to establish the QSAR. The proposed quantitative models and interpreted outcomes of the compounds were based on statistical analysis. Statistical results of MLR and MNLR exhibited the coefficient was 0.661 and 0.758, respectively. Leave-one-out cross-validation (LOO-CV), r2m metric, r2m test and “Golbraikh & Tropsha’s criteria” analyses were applied for the validation of MLR and MNLR, which indicate two models are statistically significant and well stable with data variation in the external validation towards PD-L1. The obtained values specified that the two different modelings can predict the bioactivity and may be helpful and supporting for evaluation of the biological activity of PD-L1 inhibitor.

     

  • loading
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (612) PDF downloads(10) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return