Citicoline for COVID-19

c19early.org

COVID-19 Treatment Clinical Evidence

COVID-19 involves the interplay of 400+ viral and host proteins and factors, providing many therapeutic targets. c19early analyzes 6,000+ studies for 210+ treatments—over 17 million hours of research. Only three high-profit early treatments are approved in the US. In reality, many treatments reduce risk, with 25 low-cost treatments approved across 163 countries.

Naso/oropharyngeal treatment Effective Treatment directly to the primary source of initial infection.
Healthy lifestyles Protective Exercise, sunlight, a healthy diet, and good sleep all reduce risk.
Immune support Effective Vitamins A, C, D, and zinc show reduced risk, as with other viruses.
Thermotherapy Effective Methods for increasing internal body temperature, enhancing immune system function.
Systemic agents Effective Many systemic agents reduce risk, and may be required when infection progresses.
High-profit systemic agents Conditional Effective, but with greater access and cost barriers.
Monoclonal antibodies Limited Utility Effective but rarely used—high cost, variant dependence, IV/SC admin.
Acetaminophen Harmful Increased risk of severe outcomes and mortality.
Remdesivir Harmful Increased mortality with longer followup. Increased kidney and liver injury, cardiac disorders.

Citicoline may be beneficial for COVID-19 according to the studies below. COVID-19 involves the interplay of 400+ viral and host proteins and factors providing many therapeutic targets. Scientists have proposed 11,000+ potential treatments. c19early.org analyzes 210+ treatments. We have not reviewed citicoline in detail.

Studies suggesting benefit with citicoline

Zhao et al., Identification of RdRp-NiRAN/JAK1 Dual-Target Drugs for COVID-19 Treatment, The Journal of Physical Chemistry B, doi:10.1021/acs.jpcb.4c06123

Kouznetsova et al., Potential SARS-CoV-2 protease M^pro inhibitors: repurposing FDA-approved drugs, Physical Biology, doi:10.1088/1478-3975/abcb66

Abstract Using as a template the crystal structure of the SARS-CoV-2 main protease, we developed a pharmacophore model of functional centers of the protease inhibitor-binding pocket. With this model, we conducted data mining of the conformational database of FDA-approved drugs. This search brought 64 compounds that can be potential inhibitors of the SARS-CoV-2 protease. The conformations of these compounds undergone 3D fingerprint similarity clusterization. Then we conducted docking of possible conformers of these drugs to the binding pocket of the protease. We also conducted the same docking of random compounds. Free energies of the docking interaction for the selected compounds were clearly lower than random compounds. Three of the selected compounds were carfilzomib, cyclosporine A, and azithromycin—the drugs that already are tested for COVID-19 treatment. Among the selected compounds are two HIV protease inhibitors and two hepatitis C protease inhibitors. We recommend testing of the selected compounds for treatment of COVID-19.

Puhl et al., Discovery of PL^pro and M^pro Inhibitors for SARS-CoV-2, ACS Omega, doi:10.1021/acsomega.3c01110

Schake et al., An interaction-based drug discovery screen explains known SARS-CoV-2 inhibitors and predicts new compound scaffolds, Scientific Reports, doi:10.1038/s41598-023-35671-x

AbstractThe recent outbreak of the COVID-19 pandemic caused by severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) has shown the necessity for fast and broad drug discovery methods to enable us to react quickly to novel and highly infectious diseases. A well-known SARS-CoV-2 target is the viral main 3-chymotrypsin-like cysteine protease (Mpro), known to control coronavirus replication, which is essential for the viral life cycle. Here, we applied an interaction-based drug repositioning algorithm on all protein-compound complexes available in the protein database (PDB) to identify Mpro inhibitors and potential novel compound scaffolds against SARS-CoV-2. The screen revealed a heterogeneous set of 692 potential Mpro inhibitors containing known ones such as Dasatinib, Amodiaquine, and Flavin mononucleotide, as well as so far untested chemical scaffolds. In a follow-up evaluation, we used publicly available data published almost two years after the screen to validate our results. In total, we are able to validate 17% of the top 100 predictions with publicly available data and can furthermore show that predicted compounds do cover scaffolds that are yet not associated with Mpro. Finally, we detected a potentially important binding pattern consisting of 3 hydrogen bonds with hydrogen donors of an oxyanion hole within the active side of Mpro. Overall, these results give hope that we will be better prepared for future pandemics and that drug development will become more efficient in the upcoming years.