基于代谢差异分析的抑制病毒复制的通用靶点预测方法-《中国医学物理学杂志》

文章信息/Info

Title:: General target prediction method for inhibiting viral replication based on metabolic differential analysis

Author(s):: FENG Ziye; QI Yupeng; ZHENG Haoran; School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China

Keywords:: Keywords: viral disease differential metabolic network metabolic differential analysis target prediction

摘要:: 提出一种基于代谢差异分析的抑制病毒复制的通用靶点预测方法。该方法采用的差异代谢网络模型（DELTA网络）利用感染前后宿主细胞的代谢差异，聚焦于病毒感染诱导的代谢子系统，有效消除病毒感染的不同宿主组织的特异性。该模型基于病毒感染前后宿主细胞的基因表达差异与病毒生物质反应函数进行重构，通过单基因敲除和细胞毒性测试，筛选出候选靶点。结果表明，CTH和DCTD在全部15种病毒的靶点基因集合中单独或组合出现，对于抑制病毒复制具有一定的广谱性。本文方法在预测抑制病毒复制的靶点方面展现出良好的通用性，能有效地挖掘潜在的广谱靶点，有望为病毒性疾病的研究提供新思路，提升病毒感染靶向治疗的效率。

Abstract:: Abstract: A general target prediction method for inhibiting viral replication based on metabolic differential analysis is proposed. This method employs a differential metabolic network model, referred to as the DELTA network, which utilizes metabolic differences in host cells before and after infection to focus on virus-induced metabolic subsystems, thereby effectively eliminating tissue specificity associated with infections in different hosts. The model which is reconstructed by integrating host gene expression differences pre- and post-infection with the viral biomass objective function is used to identify candidate targets through single-gene knockout simulations and cytotoxicity assessments. The results show that CTH and DCTD are present, either alone or in combination, in the predicted target gene sets across all 15 viruses, demonstrating a certain degree of broad-spectrum potential in suppressing viral replication. The proposed method exhibits strong generalizability in predicting antiviral targets, enabling effective identification of potential broad-spectrum candidates and providing new insights into viral disease research, thereby enhancing the efficiency of targeted antiviral therapies.