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

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.

2011 ◽  
Vol 66 (3-4) ◽  
pp. 136-142
Author(s):  
Rodrigo Octavio M. A. de Souza ◽  
José C. Barros ◽  
Joaquim F. M. da Silva ◽  
Octavio A. C. Antunes

A quantitative structure-activity relationship model for Morita-Baylis-Hillman adducts with leishmanicidal activities was developed which correlates molecular orbital energy and dipole with percentage in the promastigote stage


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

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.


Molekul ◽  
2016 ◽  
Vol 11 (1) ◽  
pp. 143
Author(s):  
Isnatin Miladiyah ◽  
Iqmal Tahir ◽  
Jumina Jumina ◽  
Sofia Mubarika ◽  
Mustofa Mustofa

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.


Author(s):  
Rosmahaida Jamaludin ◽  
Mohamed Noor Hasan

The increase in resistance to older drugs and the emergence of new types of infection have created an urgent need for discovery and development of new compounds with antimalarial activity. Quantitative-Structure Activity Relationship (QSAR) methodology has been performed to develop models that correlate antimalarial activity of artemisinin analogs and their molecular structures. In this study, the data set consisted of 197 compounds with their activities expressed as log RA (relative activity). These compounds were randomly divided into training set (n=157) and test set (n=40). The initial stage of the study was the generation of a series of descriptors from three-dimensional representations of the compounds in the data set. Several types of descriptors which include topological, connectivity indices, geometrical, physical properties and charge descriptors have been generated. The number of descriptors was then reduced to a set of relevant descriptors by performing a systematic variable selection procedure which includes zero test, pairwisecorrelation analysis and genetic algorithm (GA). Several models were developed using different combinations of modelling techniques such as multiple linear regression (MLR) and partial least square (PLS) regression. Statistical significance of the final model was characterized by correlation coefficient, r2 and root-mean-square error calibration, RMSEC. The results obtained were comparable to those from previous study on the same data set with r2 values greater than 0.8. Both internal and external validations were carried out to verify that the models have good stability, robustness and predictive ability. The cross-validated regression coefficient (r2cv) and prediction regression coefficient (r2 test) for the external test set were consistently greater than 0.7. The QSAR models developed in this study should facilitate the search for new compounds with antimalarial activity.


2011 ◽  
Vol 11 (1) ◽  
pp. 31-36 ◽  
Author(s):  
Ponco Iswanto ◽  
Mochammad Chasani ◽  
Harjono Harjono ◽  
Iqmal Tahir ◽  
Muhammad Hanafi ◽  
...  

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).


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