INTRODUCTION

Since its discovery in the year 1909, the Chagas disease (CD) or American Sleeping Sickness or American Trypanosomiasis has been deemed as a serious public health concern that continues to plague individuals across the globe. With no proper therapeutic drug (offering a good prognosis post-treatment) and clinically approved vaccine in the market, it ranks 17th among the top 20 Neglected Tropical Disease (NTD) of the world. From being an endemic disease restricted to the poor communities of Latin America, it has spread to globally through intra-continental and intercontinental migration. The potential individuals at risk of contracting the disease is an estimated 25 million while the approximately 20,000 patients succumb to the same annually. The causative agent of CD is a parasitic protozoan called Trypanosoma cruzi that requires an insect (Triatomine bug) and a vertebrate mammalian (Human) host to complete its life cycle. Transmission from primary to secondary host occurs mainly through the feces of the former.

Our team of professionals have attempted to identity potential vaccine candidates (PVC) and design in-silico multiple subunit vaccines using a computational framework constituting immunoinformatics, Reverse-Vaccinology (RV) and AI-based methodologies developed by us. The entire proteome of TC-CLB (T. cruzi CL Brener) was screened through a computational pipeline to identify sets of PVCs. Next, the B-Cell and T-Cell epitopes were analysed for various parameters and the highest scoring ones were shortlisted based off on their antigenicities. To study the cross protection potential of the selected epitopes, cross-protection studies with other species and strain of Trypanosoma, was also conducted. Combining the various shortlisted epitopes with appropriate adjuvant and linker sequences, a few vaccine constructs were made. These were then evaluated for for their physicochemical properties, & subjected to structural studies, codon optimization and immune modulations studies.