ABSTRACT
Forty anthraquinone derivatives have been downloaded from PubChem database and investigated in a quantitative structure-activity relationships (QSAR) study. The models describing log P and LD50 of this set were built up on the hypermolecule scheme that mimics the investigated receptor space; the models were validated by the leave-one-out procedure, in the external test set and in a new version of prediction by using similarity clusters. Molecular docking approach using Lamarckian Genetic Algorithm was made on this class of anthraquinones with respect to 3Q3B receptor. The best scored molecules in the docking assay were used as leaders in the similarity clustering procedure. It is demonstrated that the LD50 data of this set of anthraquinones are related to the binding energies of anthraquinone ligands to the 3Q3B receptor.
Subject(s)
Anthraquinones/chemistry , Anthraquinones/pharmacology , Glycogen Synthase Kinase 3/antagonists & inhibitors , Molecular Docking Simulation , Quantitative Structure-Activity Relationship , Algorithms , Databases, Chemical , Glycogen Synthase Kinase 3/chemistry , Glycogen Synthase Kinase 3/metabolism , Glycogen Synthase Kinase 3 beta , Ligands , Molecular StructureABSTRACT
A study of 30 flavonoid derivatives, taken from PubChem database and docked on flavonoid 3-O-glucosyltransferase 3HBF, next submitted to a QSAR study, performed within a hypermolecule frame, to model their LD50 values, is reported. The initial set of molecules was split into a training set and the test set (taken from the best scored molecules in the docking test); the predicted LD50 values, computed on similarity clusters, built up for each of the molecules of the test set, surpassed in accuracy the best model. The binding energies to 3HBF protein, provided by the docking step, are not related to the LD50 of these flavonoids, more protein targets are to be investigated in this respect. However, the docking step was useful in choosing the test set of molecules.
Subject(s)
Enzyme Inhibitors/chemistry , Enzyme Inhibitors/pharmacology , Flavonoids/chemistry , Flavonoids/pharmacology , Glucosyltransferases/metabolism , Databases, Pharmaceutical , Fabaceae/enzymology , Glucosyltransferases/antagonists & inhibitors , Molecular Docking Simulation , Quantitative Structure-Activity RelationshipABSTRACT
Quantitative Structure-Activity Relationships based on molecular descriptors calculated with correlation weights within the hypermolecule, considered to mimic the investigated correlational space, was performed on a set of 40 flavonoids (PubChem database). The best models describing log P and LD50 of this set of flavonoids were validated by the leave-one-out procedure, in the external test set and in a new version of prediction by using clusters of similar molecules. The best prediction was provided by the similarity cluster procedure.
