[논문]Quantitative Structure-Activity Relationships for Radical Scavenging Activities of Flavonoid Compounds by GA-MLR Technique

Om, Ae-Son; Ryu, Jae-Chun; Kim, Jae-Hyoun

Quantitative Structure-Activity Relationships for Radical Scavenging Activities of Flavonoid Compounds by GA-MLR Technique 원문보기

Molecular & cellular toxicology, v.4 no.2, 2008년, pp.170 - 176

Om, Ae-Son (Department of Food & Nutrition, College of Human Ecology, Hanyang University) , Ryu, Jae-Chun (Laboratory of Cellular and Molecular Toxicology, Korea Institute of Science and Technology) , Kim, Jae-Hyoun (Department of Health Science, School of Natural Science, Dongduk Women's University)

Abstract ▼ AI-Helper

The quantitative structure-activity relationship (QSAR) of a set of 35 flavonoid compounds presenting antioxidant activity was established by means of Genetic Algorithm-Multiple Linear Regression (GA-MLR) technique. Four-parametric models for two sets of data, the 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging activity $(R^2=0.788,\;Q^2_{cv}=0.699\;and\;Q^2_{ext}=0.577)$ and scavenging activity of reactive oxgen species (ROS) induced by $H_2O_2 (R^=0.829,\;Q^2_{cv}=0.754\;and\;Q^2_{ext}=0.573)$ were obtained with low external predictive ability on a mass basis, respectively. Each model gave some different mechanistic aspects of the flavonoid compounds tested in terms of the radical scavenging activity. Topological charge, H-bonding complex and deprotonation processes were likely to be involved in the radical scavenging activity.

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문제 정의

The aim of the research is to construct the predictive QSAR model for two different radical scavenging activity data on structurally diverse flavonoid compounds using GA-MRL analysis, and to understand the different mechanistic features for the radical scavenging activity.

제안 방법

The model obtained on the first chemicals selected is used to predict the values for the excluded sample, then Qeloo is calculated for each model. The proposed model was also checked for reliability and robustness by permutation test- in_흥: new models were recalculated for randomly reordered response (Y-scrambling). These chemometric validation techniques are well described in literature24.
To establish a r_이iable QSAR model, an external test set consisting of ten molecules was used to measure the external predictivity. The overall external prediction accuracy for the 94 modeling set ranged from 0 to 0.

대상 데이터

QSAR model. Following descriptor pruning procedures, four descriptors were selected to build the final QSAR model for the data set, consisting of 29 compounds. In order to investigate the possible existence of outhers from the 35 compounds which constitute the entire data sets.
Following descriptor pruning procedures, four descriptors were selected to build the final QSAR model for the data set, consisting of 29 compounds. In order to investigate the possible existence of outhers from the 35 compounds which constitute the entire data sets. The LOO procedure indicated that chemicals, no.

이론/모형

For the validation of the model, the combination GA-MLRA technique was utilized to select, the ap- propriate descriptors and to generate different QSAR models as implemented in the Mobydigs program23. This algorithm allows to construct the models with the following statistical characteristics: high squared correlation coefficient Rlow standard deviation S, the least number of descriptors, Fisher coefficient F, Predictive Residual Error Sum of Squares (PRESS), Standard error of calibration (SEC), standard error of prediction (SEP), explained variance (R) as additional statistical parameters.
and Q2ev. The predictive power, Q2CV, of the equations was confirmed by LOO cross-validation method. Table 1 shows a comparison of the experimental (Y- Exp), calculated (Y-Calc), LOO-predicted (Y-Pred), HAT and standardized error predicted values based on Eq.

성능/효과

No QSAR models with less than fo_니]'descriptors were proposed because and Q2ext significantly decreased to 0.653 and 0.391 with three descriptors and 0.514 and 0.335 with two descriptors, indicating a poor internal and external predictivity.
models. The regression analyses showed that the final QSAR models for two different types of scavenging activities produced statistically significant predic- tivities with four Dragon descriptors. The appearance of different outhers and descriptors in both types of models implies that each model may be acting by an obviously different mechanism or elicit changes in the scavenging activity.
The resultant final model obtained shows high flexibility and the predicting ability with mostly 2D descriptors, which is confirmed by the close values of R2adj and Q2ev. The predictive power, Q2CV, of the equations was confirmed by LOO cross-validation method.

후속연구

In this study, it was possible to consider some mechanistic aspects of the struct_니re of the flavonoid compounds studied that are associated with the free radical scavenging activity of ROS and DPPH radical scavenging activity on a mass basis. However, MLR regression models performed with external validation on a molar basis by a random sampling method yielded no prediction power, due to high multi-collinearity in both data sets.

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