Prediction of Potential Drug Targets for Cutaneous Leishmaniasis By Leishmania major and Leishmania tropica: A Quantitative Proteomics and Bioinformatics Approach

Nasrin Amiri-Dashatan, Marzieh Ashrafmansouri, Mostafa Rezaei-Tavirani, Mehdi Koushki, Nayebali Ahmadi
2021 Current Science  
Leishmania spp. cause life-threatening infectious diseases which affect universal health. Novel treatments for leishmaniasis are crucially needed since those available are limited by emerging drug-resistant species, low efficacy and side effects. In this study, we have employed a quantitative shotgun proteomics and bioinformatics method to identify differentially expressed proteins (DEPs) between Leishmania major and Leishmania tropica and to detect novel potential drug targets for cutaneous
more » ... shmaniasis, which may aid in the future drug discovery process. A total of 57 proteins were differentially expressed between the studied species. Based on KEGG pathway analysis, the more upregulated proteins in L. major are clearly related to proteasome and metabolic pathways. In L. tropica, most of the upregulated proteins are related to the metabolic pathway and carbon metabolism. According to gene ontology analysis based on biological process, the upregulated proteins mainly participated in translation and carbohydrate metabolism in L. tropica and L. major respectively. We have constructed a protein-protein interaction network that is common for the two species. We detected the top 10 potential targets for drug design by topology analysis of the protein network. Additional in vivo studies are needed to confirm these targets. We have identified several new DEPs between the species which would help in the understanding of pathogenesis mechanisms, and offer potential drug targets and vaccine candidates. Analysis of the predicted protein network provides a catalogue of key proteins, which can be considered in future studies to be validated as druggable targets against cutaneous leishmaniasis.
doi:10.18520/cs/v120/i6/1040-1049 fatcat:xx6coj42s5cjjp27nea25yyyby