Volume 33 Issue 4
Sep.  2020
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Abdulla Al Mamun, Zheng Mei, Ling Qiu, Xue-hai Ju. Theoretical Investigation on QSAR of (2-Methyl-3-biphenylyl) methanol Analogs as PD-L1 Inhibitor[J]. Chinese Journal of Chemical Physics , 2020, 33(4): 459-467. doi: 10.1063/1674-0068/cjcp1909168
 Citation: Abdulla Al Mamun, Zheng Mei, Ling Qiu, Xue-hai Ju. Theoretical Investigation on QSAR of (2-Methyl-3-biphenylyl) methanol Analogs as PD-L1 Inhibitor[J]. Chinese Journal of Chemical Physics , 2020, 33(4): 459-467.

# Theoretical Investigation on QSAR of (2-Methyl-3-biphenylyl) methanol Analogs as PD-L1 Inhibitor

##### doi: 10.1063/1674-0068/cjcp1909168
• Corresponding author: Ling Qiu. E-mail:lingqiu@jsinm.org; Xue-hai Ju. E-mail:xhju@njust.edu.cn
• Accepted Date: 2019-10-31
• Publish Date: 2020-08-27
• Cancer is one of the most serious issues in human life. Blocking programmed cell death protein 1 and programmed death ligand-1 (PD-L1) pathway is one of the great innovations in the last few years, a few numbers of inhibitors can be able to block it. (2-Methyl-3-biphenylyl) methanol derivative is one of them. Here, the quantitative structure-activity relationship (QSAR) established twenty (2-methyl-3-biphenylyl) methanol derivatives as the programmed death ligand-1 inhibitors. Density functional theory 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 $E_{\rm{HOMO}}$, lowest unoccupied molecular orbital energy $E_{\rm{LUMO}}$, total energy $E_{\rm{T}}$, dipole moment DM, absolute hardness $\eta$, absolute electronegativity $\chi$, softness $S$, electrophilicity $\omega$, energy gap $\Delta E$, etc., were observed and determined. 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 $R^2$ was 0.661 and 0.758, respectively. Leave-one-out cross-validation, $r^2_{\rm{m}}$ metric, $r^2_{\rm{m}}$ 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 results showed that the MNLR model predicts the bioactivity more accurately than MLR, and it may be helpful and supporting for evaluation of the biological activity of PD-L1 inhibitors.
###### 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

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## Theoretical Investigation on QSAR of (2-Methyl-3-biphenylyl) methanol Analogs as PD-L1 Inhibitor

##### doi: 10.1063/1674-0068/cjcp1909168
###### Corresponding author:Ling Qiu. E-mail:lingqiu@jsinm.org; Xue-hai Ju. E-mail:xhju@njust.edu.cn

Abstract: Cancer is one of the most serious issues in human life. Blocking programmed cell death protein 1 and programmed death ligand-1 (PD-L1) pathway is one of the great innovations in the last few years, a few numbers of inhibitors can be able to block it. (2-Methyl-3-biphenylyl) methanol derivative is one of them. Here, the quantitative structure-activity relationship (QSAR) established twenty (2-methyl-3-biphenylyl) methanol derivatives as the programmed death ligand-1 inhibitors. Density functional theory 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 $E_{\rm{HOMO}}$, lowest unoccupied molecular orbital energy $E_{\rm{LUMO}}$, total energy $E_{\rm{T}}$, dipole moment DM, absolute hardness $\eta$, absolute electronegativity $\chi$, softness $S$, electrophilicity $\omega$, energy gap $\Delta E$, etc., were observed and determined. 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 $R^2$ was 0.661 and 0.758, respectively. Leave-one-out cross-validation, $r^2_{\rm{m}}$ metric, $r^2_{\rm{m}}$ 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 results showed that the MNLR model predicts the bioactivity more accurately than MLR, and it may be helpful and supporting for evaluation of the biological activity of PD-L1 inhibitors.

Abdulla Al Mamun, Zheng Mei, Ling Qiu, Xue-hai Ju. Theoretical Investigation on QSAR of (2-Methyl-3-biphenylyl) methanol Analogs as PD-L1 Inhibitor[J]. Chinese Journal of Chemical Physics , 2020, 33(4): 459-467. doi: 10.1063/1674-0068/cjcp1909168
 Citation: Abdulla Al Mamun, Zheng Mei, Ling Qiu, Xue-hai Ju. Theoretical Investigation on QSAR of (2-Methyl-3-biphenylyl) methanol Analogs as PD-L1 Inhibitor[J]. Chinese Journal of Chemical Physics , 2020, 33(4): 459-467.
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