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计算机辅助真菌病原体工具和资源:用于毛霉病的反向疫苗学应用。

Computer-Aided Tools and Resources for Fungal Pathogens: An Application of Reverse Vaccinology for Mucormycosis.

机构信息

Informatics and Big Data, Council of Scientific and Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), New Delhi, India.

Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.

出版信息

Monoclon Antib Immunodiagn Immunother. 2022 Oct;41(5):243-254. doi: 10.1089/mab.2021.0039. Epub 2022 Aug 8.

Abstract

Increasing fungal infections in immunocompromised hosts are a growing concern for global public health. Along with treatments, preventive measures are required. The emergence of reverse vaccinology has opened avenues for using genomic and proteomic data from pathogens in the design of vaccines. In this work, we present a comprehensive collection of various computational tools and databases with potential to aid in vaccine development. The ongoing pandemic has directed attention toward the increasing number of mucormycosis infections in COVID-19 patients. As a case study, we developed a computational pipeline for assisting vaccine development for mucormycosis. We obtained 6 proteins from 29,447 sequences from UniProtKB as potential vaccine candidates against mucormycosis, fulfilling multiple criteria. These criteria included potential characteristics, namely adhesin properties, surface or extracellular localization, antigenicity, no similarity to any human proteins, nonallergenicity, stability , and expression in fungal cells. These six proteins were predicted to have B cell and T cell epitopes, proinflammatory inducing peptides, and orthologs in several mucormycosis-causing species. These data could aid in vaccine development against mucormycosis for at-risk individuals.

摘要

免疫功能低下宿主的真菌感染日益受到全球公共卫生的关注。除了治疗方法外,还需要采取预防措施。反向疫苗学的出现为利用病原体的基因组和蛋白质组数据设计疫苗开辟了途径。在这项工作中,我们介绍了一系列全面的计算工具和数据库,这些工具和数据库具有辅助疫苗开发的潜力。正在发生的大流行引起了人们对 COVID-19 患者中毛霉菌病感染数量不断增加的关注。作为一个案例研究,我们开发了一个计算管道,以协助毛霉菌病疫苗的开发。我们从 UniProtKB 中的 29447 个序列中获得了 6 种蛋白质,作为抗毛霉菌病的潜在疫苗候选物,这些候选物满足了多个标准。这些标准包括潜在特性,即黏附素特性、表面或细胞外定位、抗原性、与任何人类蛋白质没有相似性、非变应原性、稳定性和在真菌细胞中的表达。这 6 种蛋白质被预测具有 B 细胞和 T 细胞表位、促炎诱导肽和几种毛霉菌病致病种的同源物。这些数据可能有助于为高危人群开发抗毛霉菌病疫苗。

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