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https://www.arca.fiocruz.br/handle/icict/25606
SAR, QSAR AND DOCKING OF ANTICANCER FLAVONOIDS AND VARIANTS: A REVIEW
Autor(es)
Afiliação
Federal University of Paraíba. Centre for Biotechnology. João Pessoa, PB, Brazil
State University of Paraiba. Laboratory of Synthesis and Drug Delivery. Biological Science Department. João Pessoa, PB, Brazil
Fundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil
Federal University of Paraíba. Centre for Biotechnology. João Pessoa, PB, Brazil
Federal University of Pernambuco. Departamento de Antibióticos. Recife, PE, Brazil
Federal University of Paraíba. Department of Engineering and the Environment. Rio Tinto, PB, Brazil
State University of Paraiba. Laboratory of Synthesis and Drug Delivery. Biological Science Department. João Pessoa, PB, Brazil
Fundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil
Federal University of Paraíba. Centre for Biotechnology. João Pessoa, PB, Brazil
Federal University of Pernambuco. Departamento de Antibióticos. Recife, PE, Brazil
Federal University of Paraíba. Department of Engineering and the Environment. Rio Tinto, PB, Brazil
Resumo em Inglês
Flavonoids are phenolic compounds, secondary metabolites of plants that cause several benefits to our health,
including helping the treatment against cancer. These pharmacological properties are associated with the ability of flavonoids
in attenuating the generation of reactive oxygen species, acting as chelate compounds or affecting the oxi-redox cycle.
In spite of the large number of information in term of SAR and QSAR, no recent review has tabulated and discussed
in detail these data. In view of this, we bring here a detailed discussion of the structure-activity relationships (SAR) and
quantitative structure-activity relationships (QSAR) models. We have also analyzed the correlation between the chemical
structure of flavonoids and analogues to their anticancer activities. A large number of methodologies have been used to
identify the characteristics of these compounds with their potential anticancer: multiple linear regression, principal components
analysis, comparative molecular field analysis, comparative molecular similarity indices analysis, partial least
squares, neural networks, configuration of classification and regression trees, Free-Wilson, docking; using topological,
structural and enthalpies’ descriptors. We also discussed the use of docking models, together with QSAR models, for the
virtual screening of anticancer flavonoids. The importance of docking models to the medicinal chemistry of anticancer
flavonoids has increased in the last decade, especially to help in identifying the structural determinants responsible for the
activity. We tabulated here the most important examples of virtual screening determined for anticancer flavonoids and we
highlighted the structural determinants. The mode of action, the most potent anticancer flavonoids and hints for the structural
design of anticancer flavonoids are revised in details and provided here.
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