In Silico Study by Quantum MicroRNA Language for the Development of Anti-COVID-19 Agents: COVID-19 Is Prevented by Rice MIR2097-5p through Suppression of SARS-Cov-2 Viral MicroRNAs plus HIPK2 Target Proteins
Abstract
Objective: The pandemic of coronavirus disease 2019 (COVID-19) is caused by severe respiratory syndrome human coronavirus 2 (SARS-CoV-2). We have previously found that mutations in haplotype C79F upon MAVS/VISA in CaucasianAmerican and African-American were fatal to COVID-19 compared to Asian-American in the USA model (approximate 100 times to Asian), which showed that there is a risk factor of people in Europa/America. This result was simulated by the integrated network algorithm as the MicroRNA (miRNA) entangling sorter (METS) analysis with quantum miRNA language. Since SARS-CoV-2 replication has been blocked in vitro and in patients by Honeysuckle, traditional Chinese herbal medicine, MIR2911, it was further investigated in silico that Japanese people might have some advantages into their culture against COVID-19 for prevention of SARS-CoV-2. Materials and Methods: The METS computer analysis was performed as previously described. Information about coronavirus and miRNAs was extracted from the Viral Genomes and miRBase databases, respectively. The binding affinity between SARSCoV-2 miRNAs and their targets was computed by mfold analysis. Sequence homology analysis among honeysuckle MIR2911 and other miRNAs was performed by BLASTN database. Results and Discussion: The sequences of rice osa-MIR2097-5p was 52% homologous to those of MIR2911 and both plant miRNAs had similar properties in the quantum miRNA language. MIR2097-5p showed binding activity to SARS-CoV-2 viral miRNAs…
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