Computational proteomics to enhance personalized treatment of COVID-19 and Long COVID

Published Abstract (Verbatim Bibliographic Record)

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to significant global health burden, including both acute infections and persistent post-acute sequelae, also known as Long COVID (LC) in survivors. While clinical management has reduced case-fatality rates, a substantial proportion of patients develop LC, a heterogeneous syndrome with long-term symptoms. This complex continuum requires therapeutic strategies for both the acute and chronic phases. Plasma proteomics has emerged as a powerful tool in precision medicine, offering insights into systemic molecular changes and disease trajectories. Using targeted and untargeted proteomic analyses, researchers can identify disease-relevant pathways, perform cellular deconvolution to assess tissue-specific contributions, and pinpoint therapeutic targets for both acute infection and persistent symptoms. Combined with bioinformatics and machine learning, these proteomic insights support biomarker discovery and drug repurposing strategies.

Bibliographic Metadata

Journal / Book

Clinical Proteomics

Publication Date / Volume

2026;23(1):18

Digital Object Identifier (DOI)

https://doi.org/10.1186/s12014-026-09601-8

PubMed ID (PMID)

41947042

Leadership Authorship

First Author (Debasis Sahu, PhD) · ORCID 0000-0003-1720-2680