Panda Sandeep Kumar, Mahapatra Rajani Kanta
School of Biotechnology, KIIT University, Bhubaneswar, Odisha, 751024, India.
Parasitol Res. 2017 Apr;116(4):1293-1305. doi: 10.1007/s00436-017-5408-z. Epub 2017 Feb 24.
With the enormous genetic plasticity of malaria parasite, the challenges of developing a potential malaria vaccine candidate with highest efficacy still remain. This study has incorporated a bioinformatics-based screening approach to explore potential vaccine candidates in Plasmodium falciparum proteome. A systematic strategy was defined to screen proteins from the Malaria Parasite Metabolic Pathways (MPMP) database, on the basis of surface exposure, non-homology with host proteome, orthology with related Plasmodium species, and MHC class I and II binding promiscuity. The approach reported PF3D7_1428200, a putative metabolite transporter protein, as a novel vaccine candidate. RaptorX server was used to generate the 3D model of the protein and was validated by PROCHECK. Furthermore, the predicted B cell and T cell epitopes with the highest score were subjected to energy minimization by molecular dynamics simulation to examine their stability within a solvent system. Results from this study could facilitate selection of proteins for entry into vaccine production pipeline in future.
鉴于疟原虫具有巨大的遗传可塑性,开发一种具有最高效力的潜在疟疾疫苗候选物仍然面临挑战。本研究采用了基于生物信息学的筛选方法,以探索恶性疟原虫蛋白质组中的潜在疫苗候选物。定义了一种系统策略,基于表面暴露、与宿主蛋白质组无同源性、与相关疟原虫物种的直系同源性以及MHC I类和II类结合多态性,从疟原虫代谢途径(MPMP)数据库中筛选蛋白质。该方法报告了一种推定的代谢物转运蛋白PF3D7_1428200作为一种新型疫苗候选物。使用RaptorX服务器生成该蛋白质的3D模型,并通过PROCHECK进行验证。此外,对得分最高的预测B细胞和T细胞表位进行分子动力学模拟能量最小化,以检查它们在溶剂系统中的稳定性。本研究结果有助于未来选择进入疫苗生产流程的蛋白质。