Title : Harnessing computational tools to identify novel inhibitors of SARS-CoV-2 programmed -1 ribosomal frameshifting

Abstract:

Background: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been identified as the causal agent of Coronavirus Disease-19 (COVID-19), a typical pneumonia-like syndrome that emerged in December 2019. Numerous drug discovery programs launched to combat the COVID-19 outbreak focus on proteins as a biological target. However, resistance to their inhibitors and long-term toxicity has forced the drug discovery of antivirals to look for new therapeutic targets. The drug discovery targeting the viral genome can destroy the viral life cycle and are less prone to mutations. The RNA genome of the SARS-CoV-2 virus contains programmed -1 ribosomal frameshifting (-1 PRF) elements needed to express many essential proteins, such as RNA-dependent RNA polymerase (RdRp), necessary for replicating its genome and the transcription of viral genes.

Methodology: Frameshifting is regulated by an RNA folding topology downstream in the viral genome called “Pseudoknot.” It is hypothesized that compound binding to RNA pseudoknot could interfere with the frameshifting process, abolishing the viral replication. Molecular dynamic simulation was carried out for a time scale of 1000ns (1microsecond). The SARS pseudoknot's active site, defined as encompassing all residues within 10Å of U21 nucleotide in all directions is serving as a focal point in our study. This site is utilized for the purpose of docking known active compounds with reported IC₅₀ values. Our investigation yields docking scores and highlights critical interactions with specific residues. Notably, Valnemulin stands out with highest docking score of -2.427, indicating strong interactions with the residues surrounding U21.

Results: In the course of our research, we subjected a commercially available compound database containing 2,500 compounds from RNA focused for docking into the active site of SARS pseudoknot structure. The docking process yielded 30 hits, each with docking scores ranging from -4.11 to -5.16. The interactions of these hits with key residues have led to the identification of ten novel ligands. These specific hits identified as F1918-0003, F8889-8684, F2199-0263, F1916-0019, F2189-0986, F2191-0002, F1244-0004, F6782-7064, F1983-0081, and F1131-005 are slated for in-vitro evaluation using the dual luciferase frameshift assay to pinpoint potential novel lead compounds.

Conclusion:

• MD simulation of the RNA pseudoknot resulted in calculation of RMSD, RMSF, SASA, Rg and free energy landscape. Analysis showed that the RNA was quite stable throughout the simulation period.
• Virtual screening of the RNA-focused library resulted in 30 active compounds out of which 10 compounds binds with the active site and 8 of them were interacting with the target U21.
• All the hit molecules had better dock score than the standard molecule, Valnemulin.
• This suggests that all the hit molecules had better binding affinity towards the RNA- pseudoknot.

Key words: MD Simulation, Antiframeshifting agent, -1PRF, pseudoknot, SARS-CoV-2

Audience Take Away Notes:

1.The audience will understand the shift in antiviral drug discovery towards targeting the viral RNA genome, particularly focusing on RNA pseudoknot in SARS-CoV-2, which regulates -1 programmed ribosomal frameshifting essential for viral replication.

2. They will understand the methodology used in the study such as Molecular dynamics simulation, docking etc.

Biography:

Neha Jeena is a PhD research scholar in the Department of Microbiology at the Central University of Rajasthan, Ajmer, specialising in Molecular Biology. She earned her Bachelor’s degree in Biotechnology from Surajmal Agrawal Pvt. Kanya Mahavidyalaya and MSc. Degree in Microbiology from Department of Biotechnology, Kumaun University, Bhimtal.  As a part of her MSc. degree she undertook a six month dissertation work at Bhabha Atomic Research centre(BARC), Mumbai. At Central University of Rajasthan, Neha’s research focuses on developing RNA-targeted therapies by identifying ligands that bind to SARS-CoV-2 pseudoknot structures, disrupting frameshifting and inhibiting viral propagation within the host cell. The ligands will be identify through virtual docking of small molecule libraries followed by validation of hits through dual frameshifting and in-vitro antiviral assays. Identified compounds will then be profiled for safety in HepG2 cell lines and evaluated for their ADME properties. Novel anti-frameshifting agents with high specificity and efficacy will be identified, followed by optimization of lead compounds using medicinal chemistry approaches. Ultimately, targeting the viral genome -1 PRF elements aims to minimize resistance and mutations, providing a sustainable and effective antiviral strategy.