Study on Anti-Tumor Activity of Novel 3-Substituted 4 Anilino-Coumarin Derivatives Using Quantitative Structure-Activity Relationship (QSAR)

2019 ◽  
Vol 948 ◽  
pp. 101-108 ◽  
Author(s):  
Daratu E.K. Putri ◽  
Harno Dwi Pranowo ◽  
Winarto Haryadi
Keyword(s):  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Linear Regression Method ◽  
Coumarin Derivatives ◽  
Quantitative Structure ◽  
Activity Data ◽  
Qsar Analysis ◽  
Structure Activity ◽  
Anti Tumor Activity

Study on anti breast cancer activity of 3-substituted 4-anilino coumarin derivatives by using quantitative structure-activity relationship (QSAR) has been performed. The structures and the activity data were literatured from Guoshun et al. experiment. The molecular and electronic molecule properties were obtained from DFT/BPV86 6-31G method calculation after was through methods validation. The QSAR analysis were shown by Multi Linear Regression method (MLR). The best model of obtained for 3-substituted 4-anilino coumarin derivatives is: Log IC50 = 5.905 + (0.936 x qC1) + (-8.225 x qC8) + (-0.582 x qC13) + (11.273 x qC15) + (0.869 x ∆E) ; n = 26; r2= 0.704; Fcal/Ftab = 2.462; SEE = 0.184.

scholarly journals Quantitative structure-activity relationship to elucidate human CYP2A6 inhibition by organosulfur compounds

ADMET & DMPK ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 196-209
Author(s):  
Daniela Andrea Ramirez ◽  
Eduardo Marchevsky ◽  
Juan Maria Luco ◽  
Alejandra Camargo
Keyword(s):  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
The Body ◽  
Activity Relationship ◽  
Organosulfur Compounds ◽  
Quantitative Structure ◽  
Activity Data ◽  
Qsar Analysis ◽  
Future Design ◽  
Structure Activity

CYP2A6 is a human enzyme responsible for the metabolic elimination of nicotine, and it is also involved in the activation of procarcinogenic nitrosamines, especially those present in tobacco smoke. Several investigations have reported that reducing this enzyme activity may contribute to anti-smoking therapy as well as reducing the risk of promutagens in the body. For these reasons, several authors investigate selective inhibitors molecules toward this enzyme. The aim of this study was to evaluate the interactions between a set of organosulfur compounds and the CYP2A6 enzyme by a quantitative structure-activity relationship (QSAR) analysis. The present work provides a better understanding of the mechanisms involved, with the final goal of providing information for the future design of CYP2A6 inhibitors based on dietary compounds. The reported activity data were modeled by means of multiple regression analysis (MLR) and partial least-squares (PLS) techniques. The results indicate that hydrophobic and steric factors govern the union, while electronic factors are strongly involved in the case of monosulfides.

scholarly journals QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP ANALYSIS (QSAR) OF VINCADIFFORMINE ANALOGUES AS THE ANTIPLASMODIAL COMPOUNDS OF THE CHLOROQUINOSENSIBLE STRAIN

2010 ◽  
Vol 5 (3) ◽  
pp. 255-260
Author(s):  
Iqmal Tahir ◽  
Mudasir Mudasir ◽  
Irza Yulistia ◽  
Mustofa Mustofa
Keyword(s):  
Molecular Orbital ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Activity Data ◽  
Qsar Analysis ◽  
Relationship Analysis ◽  
Structure Activity

Quantitative Structure-Activity Relationship (QSAR) analysis of vincadifformine analogs as an antimalarial drug has been conducted using atomic net charges (q), moment dipole (), LUMO (Lowest Unoccupied Molecular Orbital) and HOMO (Highest Occupied Molecular Orbital) energies, molecular mass (m) as well as surface area (A) as the predictors to their activity. Data of predictors are obtained from computational chemistry method using semi-empirical molecular orbital AM1 calculation. Antimalarial activities were taken as the activity of the drugs against chloroquine-sensitive Plasmodium falciparum (Nigerian Cell) strain and were presented as the value of ln(1/IC50) where IC50 is an effective concentration inhibiting 50% of the parasite growth. The best QSAR model has been determined by multiple linier regression analysis giving QSAR equation: Log (1/IC50) = 9.602.qC1 -17.012.qC2 +6.084.qC3 -19.758.qC5 -6.517.qC6 +2.746.qC7 -6.795.qN +6.59.qC8 -0.190. -0.974.ELUMO +0.515.EHOMO -0.274. +0.029.A -1.673 (n = 16; r = 0.995; SD = 0.099; F = 2.682)   Keywords: QSAR analysis, antimalaria, vincadifformine.  

scholarly journals Quantitative Structure Activity Relationship (QSAR) Based on Electronic Descriptors and Docking Studies of Quinazoline Derivatives for Anticancer Activity

2018 ◽  
Vol 34 (5) ◽  
pp. 2361-2369
Author(s):  
Herlina Rasyid ◽  
Bambang Purwono ◽  
Ria Armunanto
Keyword(s):  
External Validation ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Docking Studies ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Qsar Analysis ◽  
Structure Activity ◽  
B3lyp Method ◽  
Quinazoline Derivatives

Quantitative structure-activity relationship (QSAR) based on electronic descriptors had been conducted on 2,3-dihydro-[1,4]dioxino[2,3-f]quinazoline analogues as anticancer using DFT/B3LYP method. The best QSAR equation described as follow: Log IC50 = -11.688 + (-35.522×qC6) + (-21.055×qC10) + (-85.682×qC12) + (-32.997×qO22) + (-85.129 EHOMO) + (19.724×ELUMO). Statistical value of R2 = 0.8732, rm2 = 0.7935, r2-r02/r2 = 0.0118, PRESS = 1.5727 and Fcalc/Ftable = 2.4067 used as external validation. Atomic net charge showed as the most important descriptor to predict activity and design new molecule. Following QSAR analysis, Lipinski rules was applied to filter the design compound due to physicochemical properties and resulted that all filtered compounds did not violate the rules. Docking analysis was conducted to determine interaction between proposed compounds and EGFR protein. Critical hydrogen bond was found in Met769 residue suggesting that proposed compounds could be used to inhibit EGFR protein.

scholarly journals Quantitative Structure-Activity Relationship Studies for Potential Rho-Associated Protein Kinase Inhibitors

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Giovanna Cardoso Gajo ◽  
Tamiris Maria de Assis ◽  
Letícia Cristina Assis ◽  
Teodorico Castro Ramalho ◽  
Elaine Fontes Ferreira da Cunha
Keyword(s):  
Protein Kinase ◽  
Kinase Inhibitors ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Protein Kinase Inhibitors ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Qsar Analysis ◽  
Structure Activity ◽  
New Compounds

A series of pyridylthiazole derivatives developed by Lawrence et al. as Rho-associated protein kinase inhibitors were subjected to four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis. The models were generated applying genetic algorithm (GA) optimization combined with partial least squares (PLS) regression. The best model presented validation values ofr2=0.773,qCV2=0.672,rpred2=0.503,Δrm2=0.197,rm test2⁡⁡=0.520,rY-rand2=0.19, andRp2=0.590. Furthermore, analyzing the descriptors it was possible to propose new compounds that predicted higher inhibitory concentration values than the most active compound of the series.

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