scholarly journals QSAR and QSPR study of derivatives 4-arylaminocoumarin

2003 ◽  
Vol 3 (3) ◽  
pp. 59-63
Author(s):  
Davorka Završnik ◽  
Samija Muratović ◽  
Selma Špirtović
Keyword(s):  
Inhibition Zone ◽  
Wiener Index ◽  
Quantitative Structure Activity Relationship ◽  
Connectivity Index ◽  
Activity Relationship ◽  
Log P ◽  
Structure Activity ◽  
Hiv Virus ◽  
Coumarin Compounds ◽  
Structure Properties

Coumarin and its derivatives are reactive compounds, suitable for many syntheses. They are used as anticoagulants, antibacterial, animistic compounds. The interest in coumarins has increased because it was found that they reduce the HIV virus activity. The synthesis of 4-arylaminocoumarin derivatives from 4-hydroxycoumarin, has been carried out, and their antimycotic effects were tested. In the QSAR (quantitative structure-activity relationship) QSPR (quantitativestructure-property-activity relationship) study we have used physicochemical properties and topological indices (Balaban index J(G), Wiener index W(G), information-theoretical index I(G), and valence connectivity index (G), to predict bioactivity of the newly synthesized coumarin compounds. By using methods of molecular modelling, the relationships between structure, properties and activity of coumarin compounds have been investigated. The best QSPR models were obtained using valence connectivity index or combination indices. According Rekker's method the best correlation of calculated values log P, has been obtained with the model based on the inhibition zone (I) 4-arylaminocoumarin derivatives expressed in mm. The results obtained in this study enable further synthesis of new coumarin derivatives and predict their biological activity and properties.

QSAR AND MOLECULAR DESIGN OF BENZO[B]ACRONYCINE DERIVATIVES AS ANTITUMOR AGENTS

2007 ◽  
Vol 06 (02) ◽  
pp. 223-231 ◽  
Author(s):  
WEN JUAN WU ◽  
JIN CAN CHEN ◽  
LI QIAN ◽  
KANG CHENG ZHENG
Keyword(s):  
Molecular Orbital ◽  
Antitumor Agents ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Log P ◽  
Quantitative Structure ◽  
Antitumor Activities ◽  
Structure Activity ◽  
New Compounds

Quantitative structure-activity relationship (QSAR) studies of a series of benzo[b]acronycine derivatives as a novel class of antitumor agents have been carried out using the density functional theory (DFT), molecular mechanics (MM+) and statistical methods. Some calculated parameters of geometric structures, electronic structures and molecular properties of the compounds were adopted as generalized descriptors (variables). Via a stepwise regression analysis, some main independent factors affecting the activities of the compounds were selected out, and then the quantitative structure-activity relationship (QSAR) equation was established. The results suggest that the energy difference (Δ εL-H) between the lowest unoccupied molecular orbital and the highest occupied molecular orbital, the net charges of the nitrogen atom N 11 and the first atom of the substituent R2, and the hydrophobic parameter (log P1) of the substituent R1 are the main independent factors contributing to the antitumor activities of the compounds. The fitting correlation coefficient (r2) and the cross-validation coefficient (q2) for the model established by this study are 0.865 and 0.721, respectively, showing this model with a good predictability. The QSAR equation can be used to estimate unknown antitumor activity of this kind of compound, and thus design new compounds with high antitumor activities. Here, based on this QASR study, 4 new compounds with predicted high antitumor activities have been theoretically designed and they are expecting experimental verification.

scholarly journals Quantitative Structure-Activity Relationship Analysis of Xanthone Derivates as Cytotoxic Agents in Liver Cancer Cell Line HepG2

Molekul ◽  
2016 ◽  
Vol 11 (1) ◽  
pp. 143
Author(s):  
Isnatin Miladiyah ◽  
Iqmal Tahir ◽  
Jumina Jumina ◽  
Sofia Mubarika ◽  
Mustofa Mustofa
Keyword(s):  
Latent Variables ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Cytotoxic Agents ◽  
Activity Relationship ◽  
Log P ◽  
Quantitative Structure ◽  
Data Set ◽  
Relationship Analysis ◽  
Structure Activity

The study of xanthone derivatives as cytotoxic agents in cancer is increasing. This study was conducted to explore the Quantitative Structure-Activity Relationship (QSAR) of xanthones as cytotoxic agents in HepG2 cells, to find compounds with better potency. The data set were taken from the previous study, involving 26 xanthone derivates and their cytotoxic activities in Inhibitory Concentration 50% (IC50). The parameters (descriptors) were obtained from quantum mechanics calculation using semiempirical AM1 method and QSAR models determined with principle component regression, with log (1/IC50) as a dependent variable and five latent variables as independent variables. From the 26 main descriptors, PCR reduced them to five latent variables (1st– 5th LV). The QSAR analysis gave the best model as follows: log (1/IC50) = 4.592 – 0.204 LV1 + 0.295 LV2 + 0.028 LV3 (n = 26, r = 0.571, SE = 0.234, Fcount/Ftable ratio = 1.165, PRESS value = 3.766). The study concluded that the descriptors contributed to anticancer activity were volume, mass, surface area, log P, dipole moment, HOMO energy, LUMO energy, and atomic net charge of some atoms. Modifications of substitution that would contribute to cytotoxic activity can be performed at phenyl ring A and C, but not at B.

scholarly journals NOVEL DESIGN OF CALANONE DERIVATIVES AS ANTI-LEUKEMIA COMPOUNDS BASED ON QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP ANALYSIS

2011 ◽  
Vol 11 (1) ◽  
pp. 31-36 ◽  
Author(s):  
Ponco Iswanto ◽  
Mochammad Chasani ◽  
Harjono Harjono ◽  
Iqmal Tahir ◽  
Muhammad Hanafi ◽  
...  
Keyword(s):  
Leukemia Cell ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Pcr Analysis ◽  
Log P ◽  
Quantitative Structure ◽  
Activity Data ◽  
Relationship Analysis ◽  
Structure Activity

Leukemia drug discovery based on calanone compound was conducted in previous research and produced 6 calanone derivatives. Most of them have lower activities against leukemia cell L1210 than pure calanone. A Quantitative Structure-Activity Relationship (QSAR) analysis is conducted in this work to find more active calanone derivatives. Six compounds were used as the material of the research because they already have anti-leukemia activity data expressed in Inhibitory Concentration of Fifty Percent Cell Lethal (IC50, in mg/mL). Calculation of predictors was performed by AM1 semiempirical method. QSAR equation is determined using Principle Component Regression (PCR) analysis, with Log IC50 as dependent variable. Independent variables (predictors) are atomic net charges, dipole moment (m), and coefficient partition of n-octanol/water (Log P). This work recommends 3 novel designs of calanone derivatives that may have higher activities (in mg/mL) than those already available, i.e. gemdiol calanone (57.78), 2,4-dinitrophenylhydrazone calanone (30.94) and 2,4,6-trinitrophenylhydrazone calanone (18.96).

scholarly journals The 4-arylaminocoumarin derivatives log P values calculated according to Rekker's method

2003 ◽  
Vol 3 (4) ◽  
pp. 37-40 ◽  
Author(s):  
Davorka Završnik ◽  
Selma Špirtović ◽  
Samija Muratović
Keyword(s):  
Partition Coefficient ◽  
Quantitative Structure Activity Relationship ◽  
Activity Relationship ◽  
Log P ◽  
Quantitative Structure ◽  
Structure Property ◽  
Method Of Calculation ◽  
Numeric Characteristic ◽  
Coumarin Compounds ◽  
Experimental Values

In the QSAR (quantitative structure-activity relationship) and QSPR (quantitative structure-property-activity relationship) study physico-chemical property, lipophilicity is used, to predict bioactivity of the newly synthesized coumarin compounds. Lipophilicity is a property of a molecule which depends on and can be changed by modifications in molecular structure. The parameter of the lipophilicity, partition coefficient (log P), is commonly used in drug designing and it is a numeric characteristic of lipophilicity of the examined substance, potential drug. The synthesis of 4-arylaminocoumarins derivatives from 4-hydroxycoumarin, has been carried out. In this work we described the fragmental method of calculation of partition coefficient according to the Rekker's method, because the best correlation between calculated and experimental values log P was determined according to the Rekker model. 4-Arylaminocoumarin has negative value of log P, but substitution with alkyl or allyl groups on the position 3 increases lipofilicity. Introduction of methyl or ethyl group into position 3 increases lipofilicity, suggesting that by increasing the chain length the values of log P become higher. The influence of allyl substituent in position three increases lipophilicity similar to methyl group. The aryl supstitent decreases lipoflicity, but a general relationship among them could not be established. The results obtained in this study enable further synthesis of new coumarin derivatives and predict their biological activity and properties.

Pemodelan dan Analisis QSAR Turunan Aminosulfenil Metilkarbamat sebagai Insektisida menggunakan Metode Semiempirik Austin Model 1

2017 ◽  
Vol 1 (1) ◽  
pp. 43-49
Author(s):  
Dwi Siswanta ◽  
Gerry Nugraha
Keyword(s):  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Log P ◽  
Quantitative Structure ◽  
Structure Activity

Telah diteliti pemodelan insektisida turunan aminosulfenil metilkarbamat berdasarkan model QSAR (Quantitative Structure Activity Relationship). Senyawa turunan aminosulfenil metilkarbamat dan data aktivitas inhibitor asetilkolinesterasenya diperoleh dari literatur. Perhitungan deskriptor elektronik, polaritas dan pemodelan struktur senyawa turunan aminosulfenil metilkarbamat dilakukan dengan metode semiempirik Austin Model 1 (AM1). Analisis QSAR dilakukan dengan analisis regresi multilinier untuk memperoleh persamaan QSAR terbaik untuk memprediksi aktivitas inhibitor asetilkolinesterase pada serangga dan mamalia, persamaan tersebut adalah: Serangga Log LD50 = 28,655 + 409,682 qC2 + 111,990 qO4 – 68,932 qC5 + 79,603 qC9 + 36,628 qO12 + 14,228 qO15 + 18,116 qC16 – 15,488 qS17 + 5,022 qN18 – 0,105 dipol – 0,044 Log P + 0,054 Polarisabilitas (n= 43, R= 0,928, SD= 0,176, Fhitung/Ftabel= 6,865, PRESS= 0,242) Mamalia Log LD50 = 6,984 + 28,671 qO15 - 6,986 qN18 - 0,091 dipol -0,180 Log P + 0,053 Polarisabilitas (n = 13, R = 0,977, SD = 0,042, Fhitung/Ftabel= 7,326, PRESS = 0,006) Berdasarkan model diatas, dirancang senyawa insektisida baru turunan aminosulfenil metilkarbamat dengan aktivitas inhibitor asetilkolinesterase yang tinggi terhadap serangga tapi rendah terhadap mamalia. Senyawa yang tersubstitusi ganda dengan kurkumin dan – (CH2)2COOC2H5 yaitu etil 3-((((((2,2- dimetil-2,3-dihidrobenzofuran-7-il)oksi)karbonil) (metil)amino)tio) ((4-((1E,6E)-7-(4–hidroksi-3-metoksifenil)- 3,5- dioksohepta- 1,6-dien-1il) -2-metoksifenoksi) metil)amino) propanoat memiliki aktivitas inhibitor asetilkolinesterase yang tinggi terhadap serangga (LD50=0,71 µg/g) dan aktivitas inhibitor asetilkolinesterase yang rendah terhadap mamalia (LD50=20.769,86 g/kg). Senyawa ini direkomendasikan untuk disintesis di laboratorium sebagai senyawa insektisida baru.

Prediction of Lipophilicity of some Quinolone Derivatives by using Quantitative Structure- Activity Relationship

2019 ◽  
Vol 16 ◽  
Author(s):  
Meysam Shirmohammadi ◽  
Zakiyeh Bayat ◽  
Esmat Mohammadinasab
Keyword(s):  
Partition Coefficient ◽  
Principal Component ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Selection Methods ◽  
Qsar Study ◽  
Structure Activity ◽  
Descriptor Selection

: Quantitative structure activity relationship (QSAR) was used to study the partition coefficient of some quinolones and their derivatives. These molecules are broad-spectrum antibiotic pharmaceutics. First, data were divided into two categories of train and test (validation) sets using random selection method. Second, three approaches including stepwise selection (STS) (forward), genetic algorithm (GA), and simulated annealing (SA) were used to select the descriptors, with the aim of examining the effect feature selection methods. To find the relation between descriptors and partition coefficient, multiple linear regression (MLR), principal component regression (PCR) and partial least squares (PLS) were used. QSAR study showed that the both regression and descriptor selection methods have vital role in the results. Different statistical metrics showed that the MLR-SA approach with (r2=0.96, q2=0.91, pred_r2=0.95) gives the best outcome. The proposed expression by MLR-SA approach can be used in the better design of novel quinolones and their derivatives.

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