Identification of 3-chymotrypsin like protease (3CLPro) inhibitors as potential anti-SARS-CoV-2 agen
Abstract Emerging outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is a major threat to public health. The morbidity is increasing due to lack of SARS-CoV-2 specific drugs. Herein, we have identified potential drugs that target the 3-chymotrypsin like protease (3CLpro), the main protease that is pivotal for the replication of SARS-CoV-2. Computational molecular modeling was used to screen 3987 FDA approved drugs, and 47 drugs were selected to study their inhibitory effects on SARS-CoV-2 specific 3CLpro enzyme in vitro. Our results indicate that boceprevir, ombitasvir, paritaprevir, tipranavir, ivermectin, and micafungin exhibited inhibitory effect towards 3CLpro enzymatic activity. The 100 ns molecular dynamics simulation studies showed that ivermectin may require homodimeric form of 3CLpro enzyme for its inhibitory activity. In summary, these molecules could be useful to develop highly specific therapeutically viable drugs to inhibit the SARS-CoV-2 replication either alone or in combination with drugs specific for other SARS-CoV-2 viral targets.
Introduction The major pandemic outbreak of the 21st century due to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a global threat to public health because of its high rate of infection leading to mortality. As of 24 December 2020, there are a total of 13,881,620 COVID-19 positive cases and 272,820 deaths in the United States alone and 64,326,880 confirmed cases and 1,488,992 deaths globally (https://coronavirus.jhu.edu/). The death toll is increasing at an alarming rate because of the lack of COVID-19 specific drugs or vaccines. Development, validation, and approval of COVID-19 specific drugs takes years1. Therefore, the idea of drug repositioning, also known as repurposing, is an important strategy to control the sudden outbreak of life-threatening infectious agents that spread rapidly. FDA approved anti-viral drugs are known to be safe for use in humans2, but their effectiveness against SARS-CoV-2 needs to be experimentally validated. Several FDA approved anti-viral drugs such as favipiravir, danoprevir, darunavir, lopinavir, oseltamivir, ritonavir, remdesivir, and umifenovir are in clinical trials to study anti-COVID-19 activity3. However, the effectiveness of these drugs for preventing or reducing the severity of symptoms of COVID-19 has not yet been completely established. Therefore, there is an urgent need to identify additional drug candidates to target different SARS-CoV-2 proteins for enhanced efficacy in the treatment of COVID-19.
The genomic and protein sequences for SARS-CoV-2 are publicly available from the NIH gene data bank4,6,14. Herein, we have selected 3CLpro of SARS-CoV-2 as a target to identify potential inhibitors since this protease is indispensable for viral replication and hence an excellent drug target9. The structure of 3CLpro protein of SARS-CoV-2 in complex with an inhibitor N3 is available in the PDB database (ID: 6LU7). To identify the FDA approved drugs as inhibitors for 3CLpro, in silico drug screening studies were carried out. In all, 3987 FDA approved drugs (SuperDrugs2 database) were sorted as viral protease inhibitors (PIs), viral non-protease inhibitors (VNIs) and off-target drugs (OTDs), and screened for the anti-3CLpro activity using the Molecular Operating Environment (MOE) software. The protein structure-based drug design using computational methods is an alternative for screening of currently approved drugs to rapidly identify potential drug candidates for the treatment of emerging infectious diseases such as COVID-1915,16,17. However, the potential for false positives with computational modeling is one of the most common limitation of docking studies18. Therefore, we have established SARS-CoV-2 3CLpro enzymatic assays for selected drugs using commercially available 3CLpro protease inhibitor screening assay kits to evaluate the in vitro inhibitory activity of the drugs and investigated whether any correlation exist between the computational binding score and the in vitro inhibitory activity. In this report, we have selected 47 from the list of 3987 FDA approved drugs based on binding score, side effects, half-life, active form, immunosuppressant properties, autofluorescence, and availability for an in vitro 3CLpro enzymatic inhibitor-screening assay. We observed that, boceprevir, ombitasvir, paritaprevir, tipranavir, and micafungin exhibited partial inhibitory effect whereas, ivermectin blocked more than 85% of 3CLpro activity of SARS-CoV-2. Although the anti-viral activity of ivermectin mediated through the blocking of α/β1 importin19,20,21,22,23 is established, herein we report the inhibitory effects of ivermectin on 3CLpro enzyme of SARS-CoV-2, suggesting additional anti-viral mechanism of ivermectin towards SARS-CoV-2.
In silico screening of FDA approved drugs for potential binding to SARS-CoV-2 3CLpro enzyme All the 3987 FDA approved drugs (downloaded from SuperDrugs2) were sorted as PIs, VNIs, and OTDs and docked with monomeric form of 3CLpro protein using the Molecular Operating Environment (MOE) software. Drugs were ranked according to the highest binding energy (S score). S score was calculated using the London dG score for placement and GBVI/WSA dG score for refinement of poses. A binding energy with ≤−6.5 kcal/mol (S score) was selected as a cutoff to rank the drugs with highest binding affinity16. The list was further narrowed down based on the criteria listed in the Methods section. We found that 56 drugs have a binding affinity of <−6.50 kcal/mol for the 3CLpro enzyme (Table 1). The computational study suggested that the list of drugs identified might inhibit the SARS-CoV-2 viral replication by targeting the viral 3CL protease. However, the potential for false positives with the predicted binding score is one of the most common limitation of docking studies24,25. Hence, to rule out any ambiguity in false prediction, we carried out the in vitro enzymatic assay to identify potential therapeutics and investigate correlation between the binding score and the in vitro activity. In the current study, we did not find any correlation between the in vitro results of selected drugs and their computational inhibition constants. Even though, computational studies are being widely used to predict the initial protein-drug interactions, in vitro screening of the drugs is necessary to confirm the inhibitory activities of the drugs.
Credited to communication biology