ABSTRACT
Research related to SARS-CoV-2 drugs is still ongoing. In this initial research, we perform a computational approach on SARS-CoV-2 inhibitors. RNA-dependent RNA polymerase (RdRp) is one of the functional proteins in SARS-CoV-2 that can be a target for drug development, which has an essential function in the viral replication process synthesizing the RNA genome of the virus. This study used the RdRp-Remdesivir complex structure from RCSB with ID PDB 7BV2, with a resolution of 2.5 Å. Currently, Remdesivir is under the clinical trial phase as a Covid-19 drug. In this study, we tested a thousand natural Indonesian compounds used as SARS-CoV-2 RdRp inhibitors obtained from the Indonesian natural compounds database (HerbalDB). The first stage of this computational analysis was pharmacophore modeling structure-based drug design. The natural compounds were analyzed based on their steric and electronic similarities to Remdesivir. A molecular docking simulation was then performed to obtain binding energy and bond stability to produce natural compounds that can inhibit RdRp SARS-CoV-2. The final stage was the molecular dynamics simulation that explored the conformational space of natural compounds and proteins. The ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) test was carried out on the five best compounds to obtain these natural compounds' computational pharmacology and pharmacokinetics. The simulation identified Sotetsuflavone (CID: 5494868) from Cycas revoluta, Grossamide (CID: 5322012) from Cannabis sativa, and 6-Hydroxyluteolin-6,7-disulfate (CID: 13845917) from Lippia nodiflora are the best compounds that can inhibit RdRp SARS-CoV-2. These potential compounds can then be tested in-vitro and in-vivo in the future. © 2022, Universitas Jenderal Soedirman. All rights reserved.