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在抗击恶性疟原虫方面,一种新型候选疫苗的计算机模拟筛选、鉴定及验证

In-silico screening, identification and validation of a novel vaccine candidate in the fight against Plasmodium falciparum.

作者信息

Panda Sandeep Kumar, Mahapatra Rajani Kanta

机构信息

School of Biotechnology, KIIT University, Bhubaneswar, Odisha, 751024, India.

出版信息

Parasitol Res. 2017 Apr;116(4):1293-1305. doi: 10.1007/s00436-017-5408-z. Epub 2017 Feb 24.

Abstract

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.

摘要

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。

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