Abstract
The SARS-CoV-2 or COVID-19 pandemic has reached a new height with an unprecedented infection rate and mortality post-world war II history. However, there is no particular designed drug for COVID-19 up to this point. Thus, there exist three strategies for COVID-19 drug design; drug repurposing option, herbal medicine development, and transcriptomics-based drug lead. As the most underutilized option, transcriptomics-based drug lead could be leveraged to deal with SARS-CoV-2 infection. One of the main methods to block the SARS-CoV-2 infection is to inhibit the RNA polymerase enzyme that is responsible to the viral replication. In this regard, the objective of the strategy is to design the anti-sense siRNA drug and lead to inhibit the mRNA of the RNA Polymerase Enzyme (RdRp) gene that encodes the viral RNA Polymerase of the SARS-CoV-2. The Computer-Aided Drug Design (CADD)-based method was leveraged with sequence retrieval of 24 RdRp gene sequences, multiple sequence alignment, phylogenetic tree reconstruction, 2D/3D RNA structure predictions, and RNA-RNA docking. Both the RNAalifold conserved structure from the RdRp genes and the RNAfold structure of the siRNA for blocking the conserved structure are negative or less than 0 kcal/mol. The predicted RNA docking occurred with the best RMSD score of 22.53 Å, which is beyond the accepted threshold of 10-20 Å. Based on the findings, the 2D/3D structures of both the siRNA and mRNA could be elucidated, and the docking between them is feasible. However, this finding should be elucidated in the wet laboratory setting for the final lead validation.
Publisher
Indonesian Institute of Sciences
Cited by
8 articles.
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