Identifying co-targets to fight drug resistance based on a random walk model

Abstract- Drug resistance has now posed more severe and emergent threats to human health and infectious disease treatment. However, the wet-lab approaches alone to counter drug resistance have so far achieved limited success in understanding the underlying mechanisms and pathways of drug resistance. Our approach applied A * heuristic search algorithm in order to extract drug response pathways from protein-protein interaction networks and to identify the co-target for effective antibacterial drugs. In this paper, we chose one of the killer infectious diseases, Mycobacterium Tuberculosis as our test bed. The results showed that the acetyl-CoA carboxylase is believed to be involved in fatty acid and mycolic acid biosynthesis and is strongly associated with the drug resistance mechanisms. Our analysis are consistent with the recent experimental results and also found alanine and glycine rich membrane and cell wall-associated lipoproteins to be potential co-targets for countering drug resistance. keywords: Drug resistance, Co-target, Random walk, Mycobacterium Tuberculosi

Overcoming drug resistance by co-targeting

10.1109/BIBM.2010.5706562Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010198-20