Updated project metadata. Coronavirus disease 2019 (COVID-19) has been threatening public health for the last 3 years globally. So far, the pathophysiology of the disease and therapeutic strategies have not clearly known yet. In this project, performing label-free plasma proteomics analysis, we aimed at identifying severity biomarkers for COVID-19 prognosis and proposing potential drugs against the disease symptoms by building the signaling network of significantly regulated proteins and finding the corresponding virus-host interactions. A total of 38 plasma samples from 13 COVID-19 PCR positive individuals and 5 plasma samples from healthy individuals were collected for the analysis. According to the WHO criteria, the severity of our patients was categorized as moderate (n=4), severe (n=3), and critical (n=6). Also, blood samples were collected in different time points after the symptom onset: (1) 1-5 day (± 2 days); early infection, (2) 5-15 days (± 2 days); inflammatory response, and after 15 days (± 2 days); recovery which shows the first PCR negative result from a nasal swab. In summary, we found significantly regulated proteins between COVID-19 patients and uninfected individuals and proposed some critical patient-specific prognostic biomarkers, which can be used as an early predictor of the disease severity. Also, we created a COVID-19 related plasma protein network modulated by SARS-CoV2 viral proteins and indicated clinically significant targets for the disease symptoms.