Abstract:  ERBB4 is a member of the HER/ERBB family of receptors, which are important in the development of breast cancer. ERBB4 has dual roles—it can either promote or suppress tumour growth. As per our objective, we implemented methodologies from systems biology and network pharmacology. Initially, we examined the kinase domain and homologs of ERBB4, followed by a detailed search for ERBB4 inhibitors in publicly available databases. 14 inhibitors of ERBB4 were mined, and associated biological pathways were analyzed using Reactome, KEGG, and BioModels databases followed by Swiss Target Prediction. For all the 14 inhibitors a (PPIN) protein-protein interaction network (PPIN) was reconstructed using STRING, and ensemble of PPIN reconstructed using CytoScape and hub genes were identified. Protein modeling, validation, drug-protein docking and MD simulations were carried out.  These hub genes were modeled into an extended network, resulting in the identification of 46 protein kinases and 4 non-kinase proteins as potential therapeutic targets associated with various cancers, including breast carcinoma. Structural data for selected non-kinase targets (MCL1, PTGS2, PLCG1, and HSP90AA1) were done. All the 14 compounds docked 04 target revealed the binding affinity and pharmacophoric interactions with stable conformations.  This comprehensive computational framework supports drug repurposing towards non-kinase targets in cancer treatment.

Keywords: ERBB4, Kinase, Non-kinase, Systems Biology, and Network Pharmacology.