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Updated: Jun 10, 2026

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples
Published on: October 25, 2018
Multivariate QSAR study on the antimutagenic activity of flavonoids against 3-NFA on Salmonella typhimurium TA98
Eduardo Borges de Melo1, João Paulo Ataide Martins, Teresa Cristina Marinho Jorge
1Curso de Farmácia, Centro de Ciências Médicas e Farmacêuticas, Universidade Estadual do Oeste do Paraná - Unioeste, Cascavel, PR, Brazil.
Abstract:
A quantitative structure-activity relationship (QSAR) study of twenty flavonoid derivatives with antimutagenic activity against 3-nitrofluoranthene (3-NFA) was performed by Partial Least Squares (PLS), using Ordered Predictors Selection (OPS) algorithm for variable selection. Four descriptors (PJI2, Mor27m, G1e and R4u+) were selected and a good model (n = 19; R(2) = 0.747; SEC = 0.332; PRESS(cal) = 1.768; F((2,27)) = 23.585; Q(LOO)(2) = 0.590; SEV = 0.388; PRESS(val) = 2.858; R(pred)(2) = 0.591; SEP = 0.394; ARE(pred) = 5.230%; k = 1.005; k' = 0.990; |R(02) - R'(02)| = 0.109) was built with two latent variables describing 83.410% of the original information. Leave-N-out cross validation (LNO) and y-randomization were performed in order to confirm the robustness of the model. The topological descriptors selected indicate that the antimutagenic activity against 3-NFA depends on molecular size, shape and Sanderson electronegativity of flavonoids. The proposed model may provide a better understanding of the antimutagenic activity of flavonoids and can be used as a guidance for proposition of new chemopreventive agents.
Insights
This study developed a quantitative structure-activity relationship (QSAR) model to predict the antimutagenic activity of flavonoid derivatives against 3-nitrofluoranthene (3-NFA). The model highlights molecular size, shape, and electronegativity as key factors for designing new chemopreventive agents.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Toxicology
Background:
- Flavonoids exhibit diverse biological activities, including antimutagenic properties.
- Mutagenic compounds like 3-nitrofluoranthene (3-NFA) pose health risks.
- Understanding structure-activity relationships is crucial for developing effective chemopreventive agents.
Purpose of the Study:
- To develop a quantitative structure-activity relationship (QSAR) model for flavonoid derivatives.
- To identify key molecular descriptors influencing antimutagenic activity against 3-NFA.
- To guide the design of novel chemopreventive agents.
Main Methods:
- Partial Least Squares (PLS) regression was employed for QSAR modeling.
- Ordered Predictors Selection (OPS) algorithm was used for descriptor selection.
- Leave-N-out cross-validation and y-randomization assessed model robustness.
Main Results:
- A robust QSAR model was built using four topological descriptors (PJI2, Mor27m, G1e, R4u+).
- The model explained 83.410% of the original information with two latent variables.
- Antimutagenic activity against 3-NFA was correlated with molecular size, shape, and Sanderson electronegativity.
Conclusions:
- The developed QSAR model provides insights into the structural requirements for antimutagenic activity of flavonoids.
- The findings can aid in the rational design of new flavonoid-based chemopreventive agents.
- This study contributes to understanding the mechanisms of antimutagenicity and developing safer chemical agents.
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