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毒药研究中的计算免疫学:对表位预测和验证方法的系统审查

Razana Zegrari^1,2, Abderrahim Ait Ouchaoui^1,2, Zainab Gaouzi^1,2

¹Mohammed VI University of Sciences and Health (UM6SS), Boulevard Mohammed taïeb Naciri, Commune Hay Hassani 82 403, 20100, Casablanca, Morocco.

Briefings in bioinformatics

|October 3, 2025

概括

免疫信息学加速了毒素表位的发现,超过了传统方法. 将计算预测与实验验证相结合显示出有希望的结果,但需要标准化的框架才能获得可靠的结果.

科学领域:

* 计算生物学和免疫学.
* 药物发现和毒理学.

背景情况:

* 传统的毒素毒素的发现是缓慢而昂贵的.
* 免疫信息学提供了一种更有效的方法,但对毒素蛋白质未得到充分利用.

研究的目的:

*系统地审查有关毒毒素表位的计算预测和实验验证研究.
*评估免疫信息学工具的有效性,并确定影响预测成功的因素.

主要方法:

* 按照PRISMA-2020指南进行系统性文献审查.
*包括11篇文章,这些文章通过计算预测和实验验验证了毒毒素表位.
*使用自定义检查清单进行偏差风险评估.

主要成果:

*多工具预测策略,特别是结合序列和基于结构的模型,优于单个工具.
*实验验证证证实了表位免疫性,但由于不一致的报告和有限的负面数据而面临挑战.
* 毒素家族和结构数据的可用性显著影响了预测的准确性.

结论:

* In silico表位预测与实验验证相结合,是毒药研究进步的有力策略.
* 评估计算方法和验证严格性的标准化框架至关重要.
*解决数据稀缺问题和标准化协议将增强免疫信息学在毒素发现中的应用.

关键词:

在 silico 验证中.在B细胞中,B细胞是这就是T细胞.开发抗毒药的发展.标本预测预测的预测标志性表现物 (Epitopes) 是一种表现物.免疫信息学是一种免疫信息学.毒液毒素有毒物质的毒素

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