Maria Matos

QSAR Model: Prediction of the Clastogenic Potential of 3-Arylcoumarins

Drug discovery is a challenging task for researchers due to the complexity of biomolecules involved in pathologic processes. Design and development of efficient drugs is still urgent for several diseases. Cheminformatics tools are useful to better understand the interaction between new chemical entities and their targets. We studied a selected series of 3-arylcoumarins with antioxidant potential, and determined how their chemical features can contribute for the clastogenic activity. A virtual screening, based on the TOPSMODE approach, using a clastogenic model, was performed. The results suggested that the presence and position of hydroxyl groups in the scaffold is important for the activity. This communication is focused on cheminformatics, and its applications in drug effectiveness and safety.

In silico study of new structural alerts of agents clastogenic

Natural polyphenols and their derivatives from diet have been reported by their pro-oxidant and clastogenic activities. In an aim of elucidating structural alerts for this genotoxicity endpoint, a QSTR study was conducted under the TOPS-MODE approach. It was possible to establish structural alerts from the DNA oxidative damage as an endpoint of clastogenicity at optimum leaders with high probability of being clastogenic. Some important fragments to obviate this activity were also identified. The results constitute a reference system for designing new food or pharmaceutical matrices as an alternative to the experimental toxicology.