Leishmaniasis is an infectious disease caused by parasites of the genus Leishmania and transmitted by the bite of a sand fly. The current available drugs for treatment are toxic and beyond the economic means of those affected by the disease. This study utilized a computer-aided approach to design a series of inhibitors for Leishmania major protein disulfide isomerase (LmPDI), a chaperone protein that plays a major role in the folding of newly synthesized proteins, specifically assisting in disulfide bond formation, breakage, or rearrangement in all non-native proteins. In previous work, we demonstrated that LmPDI has an essential role in pathogen virulence, and inhibition of LmPDI further blocked parasite infection in macrophages. Fragment-based virtual screening allowed for the understanding of the inhibitors’ modes of action on LmPDI active sites. By combining protein modeling, docking simulation, virtual screening and rational design, the generated compounds significantly inhibited target LmPDI reductase activity and were shown to decrease in vitro parasite growth in human monocyte-derived macrophages. 

Ben Khalaf is an Associate Professor at the Life Sciences Department and Vice-Dean of Research and Innovation at the College of Graduate Studies at the Arabian Gulf University. He has over 18 years of research and development experience in translational research and health biotechnology. In 2009 he was an Invited Scientist at the University of California in San Francisco, in the Center for Discovery and Innovation in Parasitic Diseases (CDIPD) and Small Molecules Discovery Center (SMDC). After completing his Ph.D. in Biochemistry in 2012 from Institute Pasteur, he started a Postdoctoral Fellowship at the Molecular Medicine Department of the College of Medicine at The Arabian Gulf University in Bahrain. Dr. Ben Khalaf has published several papers and supervised several theses in the field of infectious and inflammatory diseases' drug discovery. Dr. Ben Khalaf's research interests cover different aspects of translational research involving Computational- and Molecular- based approaches.