OBJECTIVE: The current study aimed to model and verify the anti-Smo activity of berberine and its derivatives using a novel automated script.
METHOD: Based on the patented inventions filed on ADMET modelling until 2016, which also predicts ADMET parameters and binding efficiency indices for all molecules, a script was developed to run automated molecular docking for a large number of small molecules.
RESULTS: Berberine was found to interact with Lys395 of Smo receptor via hydrogen bonding and cation-π interactions. In addition, π-π interactions between berberine aromatic rings and two aromatic residues in the Smo transmembrane domain, Tyr394 and Phe484, were noted. Binding efficiency indices using an in silico approach to plot the Smo-specific binding potency of each ligand was performed. The mRNA level of Gli1 was studied as the outcome of Hh signalling pathway to show the effect of berberine on hedgehog signalling.
CONCLUSION: This study predicted the role of berberine as an inhibitor of Smo receptor, suggesting its effectiveness in hedgehog signalling during cancer treatment.
METHODS: In an attempt to visualize the aggregation behavior of GA and its subsequent association with PTX, 100 ns molecular dynamics simulation of a 5 mM aqueous solution of GA with 10 molecules of PTX was conducted using GROMACS and an all-atom forcefield.
RESULTS: Aggregation of GA molecules was found to occur quickly at this level of saturation leading to two stable aggregates of 13 and 17 GA molecules with an effective radius of 10.17 nm to 10.92 nm. These aggregates form not in isolation, but together with PTX molecule embedded within the structures, which reduces the number of interactions and hydrogen-bonding with water.
CONCLUSION: GA aggregation occurs around PTX molecules in solution, forming co-joined GA-PTX cluster units at a ratio of 3:1. These clusters remain stable for the remainder of the 100ns simulation and serve to isolate and protect PTX from the aqueous environment.