The main cause of mortality globally is cancer and despite there being a number of therapies available to treat cancer, the success in finding one is like finding a needle in haystack. Immunotherapy emerges to be the one of the needles in this haystack of cancer treatment. Immunotherapeutic agents enhance the immune response of patient’s body to tumor cells One of the immunotherapeutic targets, Cluster of Differentiation 47 (CD47), releases the “don’t eat me” signal when it binds to its receptor, Signal Regulatory Protein (SIRPα). Tumour cells use this signal to circumvent the immune system, rendering it ineffective. In order to stop tumour cells from releasing the “don’t eat me” signal, the CD47-SIRPα interaction is specifically targeted in this study. In order to do so, in silico peptides were designed based on the structural analysis of the interaction between two proteins using point mutations on the interacting residues with the other amino acids. The peptide library was designed and docked on SIRPα using computational tools. Later on, after analysing the docked complex, best of them were selected for MD simulation studies of 100 nanoseconds. Peptides were further analysed after MD studies to narrow down to the possible potential anti-SIRPα peptides.

Haemophilus influenzae, a gram-negative, facultative anaerobic coccobacillus, is a member of Pasteurellaceae family. It causes a variety of invasive and non-invasive bacterial infections known as H. influenzae infections. The rise in antibiotic resistance alarms for the identification of novel therapeutic targets for treating H. influenzae infections. The emerging trends in the field of Pharmacoinformatics have aided in the prediction of novel putative therapeutic targets. Subtractive Genomics is a simple yet powerful approach for the identification of novel therapeutic targets for a bacterial pathogen. The purpose of the current study is to identify novel putative therapeutic targets for the treatment of H. influenzae infections. In this study, the core proteome of 72 strains of H. influenzae was analysed, and 115 proteins were found to be unique and non-homologous to the human proteome. Further screening of these proteins led to identification of 25 proteins involved in the 29 unique metabolic pathways of bacteria. We have identified five novel putative therapeutic targets for H. influenzae bacteria that are unique, non-homologous to the human proteome, essential for the bacterial survival, and involved in the unique metabolic pathways of bacteria.