PENGEMBANGAN SISTEM SELEKSI KANDIDAT OBAT YANG MENGHAMBAT DIMERISASI DARI C-TERMINAL DOMAIN PROTEIN NUKLEOKAPSID SARS-COV-2

• Main Author: Angelina Putri.T, Audrey
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/57110
• Institution: Institut Teknologi Bandung

The COVID-19 pandemic has caused negative impacts in terms of health, economy, even social. Although vaccines have been developed to minimize the viral transmission, there are not many antivirals that able to cure COVID-19. On the other hand, it has been known that nucleocapsid (N) protein of SARS-CoV-2 plays an important role to bind viral RNA, which turns the protein as one of the potential target for antiviral. Dimerization of N-protein mediated by C-terminal domain (CTD) plays a role in the assembly of helical structure to protect viral RNA. Thus, antiviral that inhibits CTD N-protein dimerization, should be able to interfere the process of structural assembly, which hopefully able to disturb the viral replication. Natural compounds have the potential to be developed as antiviral, and the initial step to do so is evaluating the interaction between protein and antiviral candidates (ligands). Therefore, this study aims to determine antiviral candidates that able to inhibit the dimerization of SARS-CoV-2 N-protein, while designing a drug screening system based on cross-linking and dimer-based screening system (DBSS) approaches. This study begins with alignment of 1081 nucleotide sequences encoding CTD N-protein of SARS-CoV-2 to evaluate mutations that able to alter the structure of protein. Furthermore, molecular docking analysis was performed using SARS-CoV-2 CTD protein model from PDB (ID:6ZCO). In this molecular docking analysis, 166 previously selected natural compounds were used. Construction of CTD N-protein expression system for drug screening based on cross-linking approach, was carried out in silico using pET-28a(+) plasmid as plasmid backbone. Whilst construction of screening system based on DBSS approach, was carried out in silico using pRSET_AraC plasmid as plasmid backbone. Modelling of protein fusion of AraC and CTD N-protein was performed using TrRosetta. All protein structures were validated based on ?G, Ramachandran, Prosa-Web Analysis, and Molprobity. This study shows that alignment of sequences did not find any mutations that could alter the structure of protein. Furthermore, docking results shows that compound with the highest total interaction, namely ocoteine (20%) with affinity binding energy of -8.8 kcal/mol. Whereas, construction of expression system based on cross-linking approach was successfully done by producing pET_CTD plasmid with the size of 5713 bp. Lastly, construction of DBSS screening system was successfully done by producing pRSET_AraC_CTD plasmid with the size of 4585 bp. Both systems can be expressed properly using E.coli K12 based on in silico study and codon optimization. Overall, it can be concluded that SARS-CoV-2 N-protein may be able to be a candidate for antiviral target. Whilst construction of expression system based on cross-linking approach, and construction of DBSS screening system was successfully carried out.