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通过自动化计算流程HitList发现重要人类和植物真菌病原体的新靶点。

Discovery of novel targets for important human and plant fungal pathogens via an automated computational pipeline HitList.

作者信息

Condon David E, Schroeder Brenda K, Rowley Paul A, Ytreberg F Marty

机构信息

Institute for Modeling Collaboration and Innovation, University of Idaho, Moscow, Idaho, United States of America.

Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.

出版信息

PLoS One. 2025 Jun 3;20(6):e0323991. doi: 10.1371/journal.pone.0323991. eCollection 2025.

Abstract

Fungi are a major threat to human health and agricultural productivity, causing 1.7 million human deaths and billions of dollars in crop losses and spoilage annually. While various antifungal compounds have been developed to combat these fungi in medical and agricultural settings, there are concerns that effectiveness is waning due to the emergence of acquired drug resistance and novel pathogens. Effectiveness is further hampered due to the limited number of modes of action for available antifungal compounds. To develop new strategies for the control and mitigation of fungal disease and spoilage, new antifungals are needed with novel fungal-specific protein targets that can overcome resistance, prevent host toxicity, and can target fungi that have no effective control measures. The increasing availability of complete genomes of pathogenic and spoilage fungi has enabled identification of novel protein targets essential for viability and not found in host plants or humans. In this study, an automated bioinformatics pipeline utilizing BLAST, Clustal [Formula: see text], and subtractive genomics was created and used to identify potential new targets for any combination of hosts and pathogens with available genomic or proteomic data. This pipeline called HitList allows in silico screening of thousands of possible targets. HitList was then used to generate a list of potential antifungal targets for the World Health Organization fungal priority pathogens list and the top 10 agricultural fungal pathogens. Known antifungal targets were found, validating the approach, and an additional eight novel protein targets were discovered that could be used for the rational design of antifungal compounds.

摘要

真菌是对人类健康和农业生产力的重大威胁,每年导致170万人死亡以及造成农作物损失和变质达数十亿美元。虽然已开发出各种抗真菌化合物用于在医学和农业环境中对抗这些真菌,但人们担心由于获得性耐药性的出现和新型病原体的出现,其有效性正在下降。由于现有抗真菌化合物的作用方式数量有限,有效性进一步受到阻碍。为了制定控制和减轻真菌疾病及变质的新策略,需要具有新型真菌特异性蛋白质靶点的新型抗真菌药物,这些靶点可以克服耐药性、防止宿主毒性,并能针对尚无有效控制措施的真菌。致病和变质真菌完整基因组的可得性不断提高,使得能够鉴定出对生存至关重要且在宿主植物或人类中不存在的新型蛋白质靶点。在本研究中,创建了一个利用BLAST、Clustal [公式:见正文] 和减法基因组学的自动化生物信息学流程,并用于为任何具有可用基因组或蛋白质组数据的宿主和病原体组合识别潜在的新靶点。这个名为HitList的流程允许对数千个可能的靶点进行计算机筛选。然后,HitList被用于为世界卫生组织真菌重点病原体清单和十大农业真菌病原体生成潜在抗真菌靶点列表。发现了已知的抗真菌靶点,验证了该方法,并发现了另外八个可用于合理设计抗真菌化合物的新型蛋白质靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8550/12132981/69fe9dd5cead/pone.0323991.g001.jpg

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