In silico discovery of novel inhibitors from Northern African natural products database against main protease (Mpro) of SARS-CoV-2.

The recent outbreak of COVID-19 (Coronavirus Disease 2019), caused by a novel SARS-CoV-2 virus, has led to public health emergencies worldwide where time is as important as equipment to save lives. Antimalarial drugs such as hydroxychloroquine and chloroquine derivatives are used in emergencies but they are not suitable for patients with high blood pressure, diabetes and heart problems. Since there are no approved drugs for this disease, science is challenged to find vaccines and new drugs. Therefore, as part of our Silico drug design strategy, we identified drug-like compounds that inhibit replication of the main protease (Mpro) of SARS-CoV-2 based on receptor-based virtual database screening, molecular docking, molecular dynamics, and drug-similarity profiling from the NANPDB natural products database available at North African. The two resulting hit compounds named 5- Chloro-Omega-hydroxy-1-O-methylemodin and cystodion E showed the highest binding energy with Mpro of SARS-CoV-2 and strong inhibitory activity compared with the previously published N3 inhibitor. The complexes of these two compounds were validated by molecular dynamics analysis (RMSD, RMSF, Rg, total number of hydrogen bonds and secondary structure fractions of the protein in the complex) as the best method to evaluate the biological stability of the system. Therefore, these molecules deserve more attention in drug development compared to COVID-19. HighlightsA large database of natural compounds was screened against nCoV-2's Mpro.Molecular docking and Molecular dynamics were used as powerful methods.Two compounds were found are very attractive to inhibit Mpro of nCoV-2.ADME-Tox profiling is evaluated the active compounds are not cancerogenic.Communicated by Ramaswamy H. Sarma.

Inhibition of the SARS-CoV-2 3CLpro main protease by plant polyphenols.

The abundance of polyphenols in edible plants makes them an important component of human nutrition. Considering the ongoing COVID-19 pandemic, a number of studies have investigated polyphenols as bioactive constituents. We applied in-silico molecular docking as well as molecular dynamics supported by in-vitro assays to determine the inhibitory potential of various plant polyphenols against an important SARS-CoV-2 therapeutic target, the protease 3CLpro. Of the polyphenols in initial in-vitro screening, quercetin, ellagic acid, curcumin, epigallocatechin gallate and resveratrol showed IC50 values of 11.8 µM to 23.4 µM. In-silico molecular dynamics simulations indicated stable interactions with the 3CLpro active site over 100 ns production runs. Moreover, surface plasmon resonance spectroscopy was used to measure the binding of polyphenols to 3CLpro in real time. Therefore, we provide evidence for inhibition of SARS-CoV-2 3CLpro by natural plant polyphenols, and suggest further research into the development of these novel 3CLpro inhibitors or biochemical probes.

Prioritisation of Compounds for 3CLpro Inhibitor Development on SARS-CoV-2 Variants.

COVID-19 represents a new potentially life-threatening illness caused by severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 pathogen. In 2021, new variants of the virus with multiple key mutations have emerged, such as B.1.1.7, B.1.351, P.1 and B.1.617, and are threatening to render available vaccines or potential drugs ineffective. In this regard, we highlight 3CLpro, the main viral protease, as a valuable therapeutic target that possesses no mutations in the described pandemically relevant variants. 3CLpro could therefore provide trans-variant effectiveness that is supported by structural studies and possesses readily available biological evaluation experiments. With this in mind, we performed a high throughput virtual screening experiment using CmDock and the "In-Stock" chemical library to prepare prioritisation lists of compounds for further studies. We coupled the virtual screening experiment to a machine learning-supported classification and activity regression study to bring maximal enrichment and available structural data on known 3CLpro inhibitors to the prepared focused libraries. All virtual screening hits are classified according to 3CLpro inhibitor, viral cysteine protease or remaining chemical space based on the calculated set of 208 chemical descriptors. Last but not least, we analysed if the current set of 3CLpro inhibitors could be used in activity prediction and observed that the field of 3CLpro inhibitors is drastically under-represented compared to the chemical space of viral cysteine protease inhibitors. We postulate that this methodology of 3CLpro inhibitor library preparation and compound prioritisation far surpass the selection of compounds from available commercial "corona focused libraries".