Drug Designing: Open Access
Open Access
ISSN: 2169-0138
+44 1223 790975
ISSN: 2169-0138
+44 1223 790975
Tilahun Melak and Sunita Gakkhar
Posters-Accepted Abstracts: Drug Des
Background: Tuberculosis (TB) is overwhelmingly a serious global public health problem by being the cause of mortality and
morbidity of millions every year. This is mainly due to the emergence of drug-resistance varieties of TB. In spite of the implementations
of several strategies, the resistance forms are still in rise and drug resistance remains the main threat for management, control and
eradication programs of TB. As a result one approach to deal with the problem is protecting the emergence of resistance. In this
analysis, maximum flow approach has been used to identify potential co-targets for isonisid which is one of the most widely used
drug for the treatment of TB.
Results: A weighted proteome interaction network for Mycobacterium tuberculosis H37Rv was constructed using a dataset from
STRING database. Drug targets of isonisid have been taken as source node and a curated list of set of genes involved in intrinsic and
extrinsic drug resistance mechanisms was taken as a sink node. Then, the flows from drug targets to resistance genes were calculated.
The proteins were ranked according to their maximum flow value to the sink node.
Conclusion: List of proteins which have strong influence on the resistance genes were proposed as potential co-targets for isonisid.
It has been implemented with maximum flow approach through identifying the flow of all proteins to resistance genes from the drug
target proteins. Through this, we will be able to tackle the problem of the emergence of resistance at the initial phase of rational drug
discovery process. We believe that the identified co-targets will be an important input to experimental study which in the way could
save considerable amount of time and cost of drug discovery.