scholarly journals QUANTITATIVE STRUCTURE AND ACTIVITY RELATIONSHIP ANALYSIS OF 1,2,4-THIADIAZOLINE FUNGICIDES BASED ON MOLECULAR STRUCTURE CALCULATED BY AM1 METHOD

2010 ◽  
Vol 3 (1) ◽  
pp. 39-47 ◽  
Author(s):  
Mudasir Mudasir ◽  
Iqmal Tahir ◽  
Ida Puji Astuti Maryono Putri
Keyword(s):  
Molecular Structure ◽  
Semiempirical Method ◽  
Quantitative Structure Activity Relationship ◽  
Molecular Properties ◽  
Activity Relationship ◽  
Am1 Method ◽  
Log P ◽  
Quantitative Structure ◽  
Qsar Analysis ◽  
Relationship Analysis

Quantitative structure-Activity relationship (QSAR) analysis of fungicides having 1,2,4-thiadiazoline structure based on theoretical molecular properties have been done. Calculation of the properties was conducted by semiempirical method AM1 and the activity of the compounds was taken from literature. Relationship analysis between fungicides activity (pEC50) and molecular properties was done using SPSS program. The QSAR analysis gave the best model as follows: pEC50 = 3.842 + (1.807x10-4) ET + (5.841x10-3) Eb - (5.689x10-2) DHf  -0.770 log P + 1.144 a - 0.671 m + 9.568 GLOB - (5.54x10-2) MR. n=19   r=0.917   SE=0.216   Fcal/Ftable=2.459   PRESS=0.469. The best model obtained was then used to design and predict the fungicides activity of new compounds derived from 1,2,4-thiadiazoline.   Keywords: QSAR, QSPR, fungicide, molecular structure, 1,2,4-thiadiazoline

Biological Activity, Physical Properties, and Toxicity

2021 ◽  
Vol 6 (3) ◽  
pp. 25-34
Author(s):  
Ranita Pal ◽  
Pratim Kumar Chattaraj
Keyword(s):  
Molecular Structure ◽  
Biological Activity ◽  
Molecular Biology ◽  
Drug Design ◽  
Physical Properties ◽  
Quantitative Structure Activity Relationship ◽  
Molecular Properties ◽  
Quantitative Structure ◽  
Qsar Analysis ◽  
Structure Activity

In the current pandemic-stricken world, quantitative structure-activity relationship (QSAR) analysis has become a necessity in the domain of molecular biology and drug design, realizing that it helps estimate properties and activities of a compound, without actually having to spend time and resources to synthesize it in the laboratory. Correlating the molecular structure of a compound with its activity depends on the choice of the descriptors, which becomes a difficult and confusing task when we have so many to choose from. In this mini-review, the authors delineate the importance of very simple and easy to compute descriptors in estimating various molecular properties/toxicity.

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 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.  

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