In silico identification and validation of a novel hypothetical protein in Cryptosporidium hominis and virtual screening of inhibitors as therapeutics

Computational approaches to predict structure/function and other biological characteristics of proteins are becoming more common in comparison to the traditional methods in drug discovery. Cryptosporidiosis is a major zoonotic diarrheal disease particularly in children, which is caused primarily by Cryptosporidium hominis and Cryptosporidium parvum. Currently, there are no vaccines for cryptosporidiosis and recommended drugs are ineffective. With the availability of complete genome sequence of C. hominis, new targets have been recognized for the development of effective and better drugs and/or vaccines. We identified a unique hypothetical protein (TU502HP) in the C. hominis genome from the CryptoDB database. A three-dimensional model of the protein was generated using the Iterative Threading ASSEmbly Refinement server through an iterative threading method. Functional annotation and phylogenetic study of TU502HP protein revealed similarity with human transportin 3. The model is further subjected to a virtual screening study form the ZINC database compound library using the Dock Blaster server. A docking study through AutoDock software reported N-(3-chlorobenzyl)ethane-1,2-diamine as the best inhibitor in terms of docking score and binding energy. The reliability of the binding mode of the inhibitor is confirmed by a complex molecular dynamics simulation study using GROMACS software for 10 ns in the water environment. Furthermore, antigenic determinants of the protein were determined with the help of DNASTAR software. Our findings report a great potential in order to provide insights in the development of new drug(s) or vaccine(s) for treatment and prophylaxis of cryptosporidiosis among humans and animals.