Computational protein subgraph analysis provides insights into effective therapeutic management of psoriasis and its comorbidities
D. Subhashini, Alex Anand Daniel · Research Journal of Biotechnology · 2022
Computational biology is a flourishing domain in which the functions of biomolecules can be easily predicted in seconds. A plethora of differentially expressed genes using distinct, customized platforms had been deposited by various researchers from their deep wet lab investigations worldwide. These genes can be predicted for their biological functions using the strategy of computational biology. We have used this fast method to assess a bunch of genes from psoriatic patients, reported in previous studies of experimenters. The constructed protein subgraph analysis revealed 16 of them and they were associated with various types of comorbid diseases. Protein nodes namely ALDH1A3, CYP2E1, HSD11B1 and ALDH3A2 were identified as significant hubs for the second subgraph. Altogether, 53 drugs were found for subgraphs 2, 3, 4, 7, 9, 11, 12, 13, 14 and 15. These findings help us manage psoriasis sufferers and treat them in a much better way.