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使用ANDSystem认知平台,图形神经网络和分子建模来预测SARS-CoV-2ORF3a蛋白和小分子体之间的相互作用

T V Ivanisenko¹, P S Demenkov², M A Kleshchev²

¹Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, RussiaInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, RussiaInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.

Vavilovskii zhurnal genetiki i selektsii

|January 16, 2026

概括

人工智能,特别是图形神经网络 (GNN),可以预测分子相互作用. 这项研究使用GNN来识别SARS-CoV-2ORF3a蛋白质的潜在候选药物,其中bictegravirum显示出有前途的抑制潜力.

科学领域:

生物医学信息学是生物医学信息学.
计算生物学是一种计算生物学.
人工智能在药物发现中的作用

背景情况:

生物医学网络对于理解分子相互作用至关重要.
图形神经网络 (GNN) 有效地预测生物网络中的缺失边缘.
ANDSystem是一个用于提取分子相互作用和重建基因网络的AI平台.

研究的目的:

将基于注意的GNN应用于ANDSystem知识图.
为了预测新的蛋白质 - 连接体相互作用.
为了识别SARS-CoV-2ORF3a蛋白的潜在连接体.

主要方法:

使用基于注意力的图形神经网络 (GNN).
在ANDSystem知识图中训练有素的GNN,包含超过1亿次交互.
采用分子对接和MM/GBSA用于亲和度估计和结合点分析.

主要成果:

预测有五种可能与ORF3a相互作用的小分子 (N-乙-D-葡萄糖胺,4---胺) 酸,奥斯托西斯D,比克特格拉维,L-氨酸).
确定了每个分子的特定结合点,其中一些位于暴露于溶剂的区域.
比克特格拉维表现出最有利的结合能量,这表明它是潜在的ORF3a抑制剂.

结论:

GNN是预测分子相互作用和识别候选药物的强大工具.
ORF3a是一种潜在的药理性标,因此可以探索其抑制.
比克特格拉维是作为SARS-CoV-2ORF3a的抑制剂的有希望的候选人.

关键词:

4 - () 胺基) 酸是酸中的一种.安德斯系统 ANDS 系统在ORF3a中,ORF3a是指ORF3a.这就是SARS-CoV-2病毒.这就是bictegravirum的意思.基因网络基因网络图形神经网络的神经网络分子对接的分子对接.有潜在的治疗药物.蛋白联体相互作用预测和预测.

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