In Silico Identification Of New Targets For Diagnosis, Vaccine, And Drug Candidates Against Trypanosoma Cruzi

DISEASE MARKERS(2020)

引用 5|浏览7
暂无评分
摘要
Chagas disease is a neglected tropical disease caused by the parasite Trypanosoma cruzi. Despite the efforts and distinct methodologies, the search of antigens for diagnosis, vaccine, and drug targets for the disease is still needed. The present study is aimed at identifying possible antigens that could be used for diagnosis, vaccine, and drugs targets against T. cruzi using reverse vaccinology and molecular docking. The genomes of 28 T. cruzi strains available in GenBank (NCBI) were used to obtain the genomic core. Then, subtractive genomics was carried out to identify nonhomologous genes to the host in the core. A total of 2630 conserved proteins in 28 strains of T. cruzi were predicted using OrthoFinder and Diamond software, in which 515 showed no homology to the human host. These proteins were evaluated for their subcellular localization, from which 214 are cytoplasmic and 117 are secreted or present in the plasma membrane. To identify the antigens for diagnosis and vaccine targets, we used the VaxiJen software, and 14 nonhomologous proteins were selected showing high binding efficiency with MHC I and MHC II with potential for in vitro and in vivo tests. When these 14 nonhomologous molecules were compared against other trypanosomatids, it was found that the retrotransposon hot spot (RHS) protein is specific only for T. cruzi parasite suggesting that it could be used for Chagas diagnosis. Such 14 proteins were analyzed using the IEDB software to predict their epitopes in both B and T lymphocytes. Furthermore, molecular docking analysis was performed using the software MHOLline. As a result, we identified 6 possible T. cruzi drug targets that could interact with 4 compounds already known as antiparasitic activities. These 14 protein targets, along with 6 potential drug candidates, can be further validated in future studies, in vivo, regarding Chagas disease.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要