Intrinsic factors behind long COVID: exploring the role of nucleocapsid protein in thrombosis

Abstract

COVID-19, caused by the SARS-CoV-2, poses significant global health challenges. A key player in its pathogenesis is the nucleocapsid protein (NP), which is crucial for viral replication and assembly. While NPs from other coronaviruses, such as SARS-CoV and MERS-CoV, are known to increase inflammation and cause acute lung injury, the specific effects of the SARS-CoV-2 NP on host cells remain largely unexplored. Recent findings suggest that the NP acts as a pathogen-associated molecular pattern (PAMP) that binds to Toll-like receptor 2 (TLR2), activating NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) and MAPK (mitogen-activated protein kinase) signaling pathways. This activation is particularly pronounced in severe COVID-19 cases, leading to elevated levels of soluble ICAM-1 (intercellular adhesion molecule 1) and VCAM-1 (vascular cell adhesion molecule 1), which contribute to endothelial dysfunction and multiorgan damage. Furthermore, the NP is implicated in hyperinflammation and thrombosis-key factors in COVID-19 severity and long COVID. Its potential to bind with MASP-2 (mannan-binding lectin serine protease 2) may also be linked to persistent symptoms in long COVID patients. Understanding these mechanisms, particularly the role of the NP in thrombosis, is essential for developing targeted therapies to manage both acute and chronic effects of COVID-19 effectively. This comprehensive review aims to elucidate the multifaceted roles of the NP, highlighting its contributions to viral pathogenesis, immune evasion, and the exacerbation of thrombotic events, thereby providing insights into potential therapeutic targets for mitigating the severe and long-term impacts of COVID-19.

Keywords: Endothelial cells; Long COVID; Nucleocapsid protein; SARS-CoV-2; Thrombosis.

Figure 1. Structural and functional characterization of SARS-CoV-2 N protein.

(A) Per-residue intrinsic disorder profile generated for the SARS-CoV-2 N protein (UniProt ID: P0DTC9) generated by the RIDAO platform that assembles the outputs of several commonly used per-residue intrinsic disorder predictors in one plot (Dayhoff & Uversky, 2022). In addition to showing the outputs of PONDR^® VLXT, PONDR^® VL3, PONDR^® VSL2, PONDR^® FIT, IUPred_long and IUPred_short, RIDAO represents the mean disorder profile (MDP), which is calculated by averaging the disorder profiles of individual predictors. The light pink shade represents the MDP error distribution. The thin black line at the disorder score of 0.5 is the threshold between order and disorder, where residues/regions above 0.5 are disordered, and residues/regions below 0.5 are ordered. The dashed line at the disorder score of 0.15 is the threshold between order and flexibility, where residues/regions above 0.15 are flexible, and residues/regions below 0.15 are highly ordered. (B) 3D structure of the full-length protein modeled by AlphaFold (Jumper et al., 2023). Regions with low per-residue confidence scores (red) are expected to be disordered in isolation, whereas the two known domains are predicted with a high confidence (blue). (C) 3D structure of the dimeric form of the CTD of SARS-CoV-2 nucleocapsid protein (residues 247-364) (PDB: 6WZO) generated using PyMol (Schrödinger, 2015; Ye et al., 2020). (D) Protein-protein interaction network centered at the SARS-CoV-2 N protein. This network was generated by IntAct, which is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions (Orchard et al., 2014). The network represents both viral and host proteins with established physical associations.