Development of multiple QSAR models for consensus predictions and unified mechanistic interpretations of the free-radical scavenging activities of chromone derivatives

Abstract

Antioxidants are important defenders of the human body against nocive free radicals, which are the causative agents of most life-threatening diseases. The immense biomedicinal utility of antioxidants necessitates the development and design of new synthetic antioxidant molecules. The present report deals with the modeling of a series of chromone derivatives, which was done to provide detailed insight into the main structural fragments that impart antioxidant activity to these molecules. Four different quantitative structure-property relationship (QSAR) techniques, namely 3D pharmacophore mapping, comparative molecular similarity indices analysis (CoMSIA 3D-QSAR), hologram QSAR (HQSAR), and group-based QSAR (G-QSAR) techniques, were employed to obtain statistically significant models with encouraging external predictive potentials. Moreover, the visual contribution maps obtained for the different models signify the importance of different structural features in specific regions of the chromone nucleus. Additionally, the G-QSAR models determine the composite influence of pairs of substituent fragments on the overall antioxidant activity profiles of the molecules. Multiple models with different strategies for assessing structure-activity relationships were applied to reach a unified conclusion regarding the antioxidant mechanism and to provide consensus predictions, which are more reliable than values derived from a single model. The structural information obtained from the various QSAR models developed in the present work can thus be effectively utilized to design and predict the activities of new molecules belonging to the class of chromone derivatives.

Computational Studies of Free Radical-Scavenging Properties of Phenolic Compounds

“…Unfortunately, the electrostatic fields did not provide any information about the hydroxyl group-populated region of A ring (positions 5,7,8), or these data points were discarded during the analysis due to insufficient variability. Mitra and co-workers [ 166 ] analysed the same dataset by means of consensus modelling (for details see [ 154 ]), which included two 3D modelling techniques: comparative molecular similarity indices analysis (CoMSIA) and pharmacophore modelling. The importance of the catechol configuration in A ring (positions 7,8) was not outlined by either of the tools.…”

Structure-activity Relationships of Antioxidant Activity in vitro about Flavonoids Isolated from Pyrethrum Tatsienense

“…Some serious diseases such as cardiovascular disease, diabetes, acquired immune deficiency syndrome, neurodegenerative diseases, inflammation, cancer, and aging process are related to oxidative damage caused by free radicals. It has been widely recognized nowadays that lowering oxidative stress can provide clinical benefits to a variety of pathological conditions, and antioxidant treatment as research focus has thus been regarded as a viable therapy to alleviate the oxidative injury in these disorders [ 1 , 2 ]. Under physiological conditions, a number of free radical scavengers in human body can effectively scavenge free radicals, which keeps the organisms healthy under the normal concentrations of free radicals.…”

Ligand-based pharmacophore modeling; atom-based 3D-QSAR analysis and molecular docking studies of phosphoinositide-dependent kinase-1 inhibitors

“…The reliable prediction of a compound is unlikely when it is highly dissimilar to all compounds of modeling set. To avoid such an unjustified exploration of activity predictions we used the concept of AD[1921]. …”