Poster Presentation ANZOS-Breakthrough Discoveries Joint Annual Scientific Meeting 2018

Molecular docking study of cassia seed compounds to identify amylase and lipase inhibitors for weight management (#260)

Heidi Yuen 1 , George Lenon 1 , Andrew Hung 2 , Angela Yang 1
  1. School of Health and Biomedical sciences, RMIT University, bundoora, Vic, Australia
  2. School of Science, RMIT University, Melbourne, Vic, Australia

Background: The epidemic of obesity has become a major challenge to health globally. Current pharmacological treatments for obesity are limited by their efficacy and side effects. Cassia seed (CS) is an herb commonly used for weight management in China. However, the bioactive compounds in CS with anti-obesity properties have not been identified and the relevant mechanisms of action are not clear.

Aim: To identify promising active compounds in CS as amylase and lipase inhibitors for weight management with molecular modelling and docking studies.

Methods: Autodock Vina [1] was the molecular docking software used in this study. The selected ligands were orlistat (a drug designed to treat obesity) and 27 compounds reported to be present in CS. Seven amylases and lipases were used as protein targets. Every ligand was docked against each target and the binding affinity of the pair was calculated by Autodock Vina. The binding affinity indicates the strength of interaction between the ligand and target.

Results: The preliminary molecular docking study has shown that CS compounds emodin, alaternin, rubrofusarin gentiobioside and ononitol are comparable, in terms of binding affinity and efficiency, to orlistat. Predicted binding affinity values suggest that rubrofusarin exhibits similar affinity to lipase compared to orlistat; while emodin has substantially (> 20%) higher affinity, indicative of the latter's potential to act as an inhibitor with greater efficacy than orlistat.

Conclusion: The results suggest that some chemical compounds in CS may interact with amylase and lipase via a similar mechanism to orlistat. Further studies, with Biovia Discovery Studio [2], are recommended to identify ligand-receptor interactions at the binding sites to confirm if there is any inhibitory action.

  1. Trott, O. and A.J. Olson, AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry. 31(2): p. 455-461.
  2. BIOVIA, D.S. BIOVIA Discovery Studio. 2017 [cited 2018 23 Aug]; Available from: http://accelrys.com/products/collaborative-science/biovia-discovery- studio/.