非洲猪瘟病毒 蛋白质-蛋白质相互作用 预测
Jacob A Fenster1,2,3, Paul A Azzinaro2,3, Mark Dinhobl2,3
1Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN 37830, USA.
Viruses
|July 27, 2024
概括
研究人员使用人工智能预测非洲猪瘟病毒 (ASFV) 蛋白质-蛋白质相互作用 (PPI),确定了十七种对理解ASFV病变和开发干预措施至关重要的新型相互作用.
科学领域:
- 病毒学 病毒学
- 生物信息学是一种生物信息学.
- 结构生物学 结构生物学
背景情况:
- 非洲猪瘟病毒 (ASFV) 对全球猪健康和经济构成重大威胁.
- 由于ASFV的复杂基因组和人们对蛋白质功能的了解不足,阻碍了疫苗的开发.
- 识别病毒蛋白-蛋白相互作用 (PPI) 对于理解ASFV复制和宿主相互作用至关重要.
研究的目的:
- 使用人工智能驱动的结构预测来识别新的ASFV-ASFV蛋白质-蛋白质相互作用 (PPI).
- 使用已知的病毒 (Vaccinia病毒) 验证PPI识别的计算工作流.
- 通过确定关键ASFV蛋白相互作用来发现潜在的治疗点.
主要方法:
- 利用人工智能驱动的蛋白质结构预测工具来识别ASFV PPI.
- 基准测试了PPI识别工作流程的Vaccinia病毒,一个特征很好的DNA病毒.
- 通过计算选了18000多种ASFV蛋白质的对对组合.
主要成果:
- 人工智能工作流程成功识别了已知的 Vaccinia 病毒 PPI,验证了其有效性.
- 确定了17种新的ASFV-ASFV PPI.
- 确定了两种新的PPI (I267L__I8L和B175L__DP79L),涉及调节宿主免疫反应的病毒蛋白.
结论:
- 人工智能驱动的蛋白质结构预测是发现病毒蛋白-蛋白相互作用的强大工具.
- 发现的新型ASFV PPI为病毒机制提供了新的见解,并为控制策略提供了潜在的目标.
- 进一步对这些新型PPI进行实验验证是有必要的,以推进ASFV疫苗和治疗开发.
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