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模糊优化用于识别用于治疗心脏中SARS-CoV-2感染的抗病毒点

Sz-Wei Chu¹, Feng-Sheng Wang²

¹Department of Chemical Engineering, National Chung Cheng University, Chiayi, 621301, Taiwan.

BMC bioinformatics

|September 27, 2023

概括

这项研究引入了一个模糊的优化框架,以找到SARS-CoV-2心脏感染的抗病毒点. 它确定了关键的代谢途径和酶,对于抑制病毒生长和最大限度地减少副作用至关重要.

科学领域:

生物化学生化学
计算生物学计算生物学
病毒学病毒学

背景情况:

严重急性呼吸道综合征冠状病毒2 (SARS-CoV-2) 构成重大威胁,心脏参与是一个严重的问题.
确定有效的抗病毒点对于开发针对SARS-CoV-2的治疗方法至关重要,特别是在心脏并发症方面.

研究的目的:

提出一个模糊的等级优化框架,用于识别潜在的抗病毒点对抗心脏中的SARS-CoV-2.
通过四个关键目标来评估病毒生物质消除和治疗副作用.

主要方法:

开发一个模糊的等级优化框架.
应用框架使用杜尔贝科的修饰介质 (DMEM) 和汉姆的介质作为营养来源.
在特定代谢途径内发现病毒点中的酶作用的分析.

主要成果:

大多数已识别的抗病毒酶都参与脂肪酸和氨基酸代谢.
哈姆介质中的六种胆固醇生物合成酶和DMEM中的三种糖解酶未能消除SARS-CoV-2生物质.
在DMEM中,特定的糖解酶 (BPGM,GAPDH,ENO1),与L-氨酸一起,改善了细胞活力和代谢偏差.
胆固醇生物合成酶的有效性取决于培养基中的胆固醇吸收.

结论:

该框架通过分析代谢途径有效预测抗病毒点.
糖解和胆固醇生物合成途径与SARS-CoV-2复制和治疗疗效存在复杂的相互作用.
针对特定的酶和了解营养吸收对于开发有效的抗病毒策略来对抗SARS-CoV-2心脏感染至关重要.

关键词:

基于约束的建模.药物发现药物发现流量平衡分析分析流量平衡分析基因组规模的代谢模型混合差异进化是混合的差异进化.多级优化多层次优化

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