Ilyas Sidra, Manan Abdul, Lee Donghun
Department of Herbal Pharmacology, College of Korean Medicine, Gachon University, 1342 Seongnamdae-ro, Sujeong-gu, Seongnam-si 13120, Republic of Korea.
Department of Molecular Science and Technology, Ajou University, Suwon 16499, Republic of Korea.
Int J Mol Sci. 2025 Apr 5;26(7):3411. doi: 10.3390/ijms26073411.
This study explores the role of intrinsically disordered regions (IDRs) in the SARS-CoV-2 proteome and their potential as targets for small-molecule drug discovery. Experimentally validated intrinsic disordered regions from the literature were utilized to assess the prediction of intrinsic disorder across a selection of SARS-CoV-2 proteins. The disorder propensities of proteins using four deep learning-based disorder prediction models: ADOPT, PONDRVLXT, PONDRVSL2, and flDPnn, were analyzed. ADOPT, VSL2, and VLXT identified a flexible linker (129-147), while VSL2 and VLXT predicted disorder in the Cu(II) binding region (163-167) of NSP1. ADOPT did not predict disordered regions in NSP11; however, VSL2 and VLXT identified disorder in the experimentally validated regions. The IDR in ORF3a is crucial for protein localization and immune modulation, affecting inflammatory pathways. VSL2 predicted significant disorder in the N-terminal domain (18-23), which aligns with experimental data (1-41), overlapping with the TRAF-binding motif, while ADOPT indicated high disorder in the C-terminal domain (255-275), consistent with VSL2 and flDPnn. All tools identified disorder in the N-terminal (1-68), central linker (181-248), and C-terminal (370-419) regions of the nucleocapsid (N) protein, suggesting flexibility and accuracy. The S2 subunit of the spike protein displayed more predicted disorder than the S1 subunit across ADOPT, VSL2, and flDPnn. These IDRs are essential for viral functions, like protein localization, immune modulation, receptor binding, and membrane fusion. This study highlights the importance of IDR in modulating key inflammatory pathways, suggesting that they could serve as promising targets for small-molecule drug development to combat COVID-19.
本研究探讨了内在无序区域（IDR）在严重急性呼吸综合征冠状病毒2（SARS-CoV-2）蛋白质组中的作用及其作为小分子药物发现靶点的潜力。利用文献中经过实验验证的内在无序区域来评估一系列SARS-CoV-2蛋白的内在无序预测情况。分析了使用四种基于深度学习的无序预测模型（ADOPT、PONDRVLXT、PONDRVSL2和flDPnn）的蛋白质的无序倾向。ADOPT、VSL2和VLXT识别出一个柔性连接子（129 - 147），而VSL2和VLXT预测了非结构蛋白1（NSP1）的铜（II）结合区域（163 - 167）存在无序。ADOPT未预测到NSP11中的无序区域；然而，VSL2和VLXT在经过实验验证的区域中识别出了无序。开放阅读框3a（ORF3a）中的IDR对于蛋白质定位和免疫调节至关重要，会影响炎症途径。VSL2预测N端结构域（18 - 23）存在显著无序，这与实验数据（1 - 41）相符，且与肿瘤坏死因子受体相关因子（TRAF）结合基序重叠，而ADOPT表明C端结构域（255 - 275）存在高度无序，这与VSL2和flDPnn一致。所有工具都识别出核衣壳（N）蛋白的N端（1 - 68）、中央连接子（181 - 248）和C端（370 - 419）区域存在无序，表明具有灵活性和准确性。在ADOPT、VSL2和flDPnn中，刺突蛋白的S2亚基比S1亚基显示出更多预测的无序。这些IDR对于病毒功能至关重要，如蛋白质定位、免疫调节、受体结合和膜融合。本研究强调了IDR在调节关键炎症途径中的重要性，表明它们可能成为对抗2019冠状病毒病（COVID - 19）的小分子药物开发的有希望的靶点。
