Computational investigation of inhibitory mechanism of flavonoids as bovine serum albumin anti-glycation agents

Background: Glycation of serum albumin and its consequence products were considered as an important factor in drug distribution and diabetic complications, therefore finding the glycation inhibitors and their inhibitory mechanisms became a valuable field of study. In this work, bovine serum albumin (BSA) became a subject as a model protein for analyzing the inhibitory mechanism of flavonoids, known as natural BSA glycation inhibitors in the early stage of glycation. Methods: Firstly, for theoretical study, the three-dimensional model of BSA structure was generated by homology modeling and refined through molecular dynamic simulation. Secondly, several validation methods (statistical assessment methods and also neural network methods) by simultaneous docking study were employed for insurance about accuracy of our simulation. Then docking studies were performed for visualizing the relation between flavonoids’ binding sites and BSA glycation sites besides, the correlation analyzes between calculated binding energy and reported experimental inhibitory IC50 values of the flavonoids set, was considered to explore their molecular inhibitory mechanism. Results: The quality assessment methods and simultaneous docking studies on interaction of quercetin (as the most studied flavonoids) with BSA and Human serum albumin (HAS), confirm the accuracy of simulation and the second stage of docking results which were in close agreement with experimental observations, suggest that the potential residues in flavonoids binding sites (which were place neighbor of tryptophan 212 within 5Ǻ) cannot be considered as one of glycation sites. Conclusions: Based on the results, flavonoids don’t participate in inhibitory interference mechanism, and also, the differentiation between complexes of flavonoids with BSA and HSA could destroy the speculation of using them as an exchangeable model protein in study of serum albumin and flavonoids interactions.