Amantadine disrupts lysosomal gene expression; potential therapy for COVID19
Smieszek, S.; Przychodzen, B.; Polymeropoulos, M. H.
Show abstract
SARS-coronavirus 2 is the causal agent of the COVID-19 outbreak. SARS-Cov-2 entry into a cell is dependent upon binding of the viral spike (S) protein to cellular receptor and on cleavage of the spike protein by the host cell proteases such as Cathepsin L and Cathepsin B. CTSL/B are crucial elements of lysosomal pathway and both enzymes are almost exclusively located in the lysosomes.CTSL disruption offers potential for CoVID-19 therapies. The mechanisms of disruption include: decreasing expression of CTSL, direct inhibition of CTSL activity and affecting the conditions of CTSL environment (increase pH in lysosomes). We have conducted a high throughput drug screen gene expression analysis to identify compounds that would downregulate the expression of CTSL/CTSB. One of the top significant results shown to downregulate the expression of the CTSL gene is Amantadine. Amantadine was approved by the US Food and Drug Administration in 1968 as a prophylactic agent for influenza and later for Parkinsons disease. It is available as a generic drug.. Amantadine in addition to downregulating CTSL appears to further disrupt lysosomal pathway, hence interfering with the capacity of the virus to replicate. It acts as a lysosomotropic agent altering the CTSL functional environment. We hypothesize that Amantadine could decrease the viral load in SARS-CoV-2 positive patients and as such it may serve as a potent therapeutic decreasing the replication and infectivity of the virus likely leading to better clinical outcomes. Clinical studies will be needed to examine the therapeutic utility of amantadine in COVID-19 infection.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Innovative, rapid, high throughput method for drug repurposing in a pandemic - a case study of SARS-CoV-2 and COVID-19 96%
- Several FDA-approved drugs effectively inhibit SARS-CoV-2 infection in vitro 95%
- Antidepressant and antipsychotic drugs reduce viral infection by SARS-CoV-2 and fluoxetine show antiviral activity against the novel variants in vitro 93%
Similar papers in this journal
- Meta-analysis of transcriptomes of SARS-Cov2 infected human lung epithelial cells identifies transmembrane serine proteases co-expressed with ACE2 and biological processes related to viral entry, immunity, inflammation and cellular stress. 95%
- Probenecid Inhibits SARS-CoV-2 Replication In Vivo and In Vitro 94%
- The Effect Of Famotidine On SARS-CoV-2 Proteases And Virus Replication 94%
Similar papers in this journal
- Brilacidin, a COVID-19 Drug Candidate, demonstrates broad-spectrum antiviral activity against human coronaviruses OC43, 229E and NL63 through targeting both the virus and the host cell 94%
- Omicron and Delta Variant of SARS-CoV-2: A Comparative Computational Study of Spike protein 94%
- Omicron (BA.1) and Sub-Variants (BA.1, BA.2 and BA.3) of SARS-CoV-2 Spike Infectivity and Pathogenicity: A Comparative Sequence and Structural-based Computational Assessment 94%
Similar papers in this journal
- Active components of commonly prescribed medicines affect influenza A virus-host cell interaction: a pilot study 96%
- ZRC3308 monoclonal antibody cocktail shows protective efficacy in Syrian hamsters against SARS-CoV-2 infection 94%
- The Petasites hybridus CO2-extract (Ze 339) blocks SARS-CoV-2 replication in vitro 93%
Similar papers in this journal
- Efficacy and safety of nitazoxanide combined with ritonavir-boosted atazanavir for the treatment of mild to moderate COVID-19 93%
- Jinhua Qinggan Granules for Nonhospitalized COVID-19 Patients: a Double-Blind, Placebo-Controlled, Randomized Controlled Trial 92%
- SARS-CoV-2 viremia precedes an IL6 response in severe COVID-19 patients: results of a longitudinal prospective cohort 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.