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Scopus Indexed Publications

Title: Mining and predicting protein-drug interaction network of breast cancer risk genes

Author: Muhammad Nahidul Islam, Bikash Kumar Paul, Shams Shah Shaolin, Touhid Bhuiyan,

Abstract: Background and objective
The increasing number of patients of Breast Cancer (BC) is a matter of concern all around the world. There isn't any specific reason behind this disease to be occurred in the human body. But there are such diseases which are counted as a risk factor of BC. Atypical Hyperplasia (AH) and Lobular Carcinoma in SITU (LCIS) are two of them. In this research we have collected the gene list of BC, AH and LCIS from the NCBI gene database and then our target was to find out the common genes among them by implementing an intersecting program.
Method
Then we used those intersected data to construct and analyze the Protein-Protein Interaction Network (PPIN), Protein-drug interaction network and so on. After the end of this we have got the most common fundamental genes associated with these diseases, the interrelated interaction networks of this 3 disease that will help us to better understand the common gene structure of them.
Results
We have got a drug signature suggestion for the hub proteins in the PDI network. From PPIN, 9 most responsible hub genes are obtained. Finally, following the PDI network, 4 of those hub genes were selected where several drug molecules from DRUGBANK were suggested for each hub gene.
Conclusions
In future by implementing further studies and analyzing those gene structures, it may be able to notify us to take precautionary steps to reduce the risk of BC.

Keywords: Breast cancer Atypical hyperplasia Lobular carcinoma in SITU Bioinformatics Data mining methods Drug-protein interaction network