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基于基因组的毛霉病管理解决方案。

Genome-based solutions for managing mucormycosis.

机构信息

Department of Computational Biology, Indraprastha Institute of Information Technology, Delhi, India.

Department of Computational Biology, Indraprastha Institute of Information Technology, Delhi, India.

出版信息

Adv Protein Chem Struct Biol. 2024;139:383-403. doi: 10.1016/bs.apcsb.2023.11.014. Epub 2024 Feb 14.

DOI:10.1016/bs.apcsb.2023.11.014
PMID:38448141
Abstract

An uncommon opportunistic fungal infection known as mucormycosis is caused by a class of molds called mucoromycetes. Currently, antifungal therapy and surgical debridement are the primary treatment options for mucormycosis. Despite the importance of comprehensive knowledge on mucormycosis, there is a lack of well-annotated databases that provide all relevant information. In this study, we have gathered and organized all available information related to mucormycosis that include disease's genome, proteins, diagnostic methods. Furthermore, using the AlphaFold2.0 prediction tool, we have predicted the tertiary structures of potential drug targets. We have categorized the information into three major sections: "genomics/proteomics," "immunotherapy," and "drugs." The genomics/proteomics module contains information on different strains responsible for mucormycosis. The immunotherapy module includes putative sequence-based therapeutics predicted using established tools. Drugs module provides information on available drugs for treating the disease. Additionally, the drugs module also offers prerequisite information for designing computationally aided drugs, such as putative targets and predicted structures. In order to provide comprehensive information over internet, we developed a web-based platform MucormyDB (https://webs.iiitd.edu.in/raghava/mucormydb/).

摘要

一种罕见的机会性真菌感染,称为毛霉病,是由一类称为毛霉的霉菌引起的。目前,抗真菌治疗和手术清创是毛霉病的主要治疗选择。尽管全面了解毛霉病非常重要,但缺乏提供所有相关信息的良好注释数据库。在这项研究中,我们收集并组织了与毛霉病相关的所有可用信息,包括疾病的基因组、蛋白质、诊断方法。此外,我们使用 AlphaFold2.0 预测工具预测了潜在药物靶点的三级结构。我们将信息分为三个主要部分:“基因组学/蛋白质组学”、“免疫疗法”和“药物”。基因组学/蛋白质组学模块包含了不同菌株导致毛霉病的信息。免疫疗法模块包含了使用现有工具预测的基于假定序列的治疗方法。药物模块提供了治疗这种疾病的现有药物的信息。此外,药物模块还提供了设计计算辅助药物的前提信息,例如假定的靶点和预测的结构。为了在互联网上提供全面的信息,我们开发了一个基于网络的平台 MucormyDB(https://webs.iiitd.edu.in/raghava/mucormydb/)。

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