In Silico Drug Repositioning to Target the SARS-CoV-2 Main Protease as Covalent Inhibitors Employing a Combined Structure-Based Virtual Screening Strategy of Pharmacophore Models and Covalent Docking

An automated positive selection screen in yeast provides support for boron-containing compounds as inhibitors of SARS-CoV-2 main protease

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus continues to cause severe disease and deaths in many parts of the world, despite massive vaccination efforts. Antiviral drugs to curb an ongoing infection remain a priority. The virus-encoded 3C-like main protease (MPro; nsp5) is seen as a promising target. Here, with a positive selection genetic system engineered in Saccharomyces cerevisiae using cleavage and release of MazF toxin as an indicator, we screened in a robotized setup small molecule libraries comprising ~2,500 compounds for MPro inhibitors. We detected eight compounds as effective against MPro expressed in yeast, five of which are characterized proteasome inhibitors. Molecular docking indicates that most of these bind covalently to the MPro catalytically active cysteine. Compounds were confirmed as MPro inhibitors in an in vitro enzymatic assay. Among those were three previously only predicted in silico; the boron-containing proteasome inhibitors bortezomib, delanzomib, and ixazomib. Importantly, we establish reaction conditions in vitro preserving the MPro-inhibitory activity of the boron-containing drugs. These differ from the standard conditions, which may explain why boron compounds have gone undetected in screens based on enzymatic in vitro assays. Our screening system is robust and can find inhibitors of a specific protease that are biostable, able to penetrate a cell membrane, and are not generally toxic. As a cellular assay, it can detect inhibitors that fail in a screen based on an in vitro enzymatic assay using standardized conditions, and now give support for boron compounds as MPro inhibitors. This method can also be adapted for other viral proteases.IMPORTANCEThe coronavirus disease 2019 (COVID-19) pandemic triggered the realization that we need flexible approaches to find treatments for emerging viral threats. We implemented a genetically engineered platform in yeast to detect inhibitors of the virus's main protease (MPro), a promising target to curb severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Screening molecule libraries, we identified candidate inhibitors and verified them in a biochemical assay. Moreover, the system detected boron-containing molecules as MPro inhibitors. Those were previously predicted computationally but never shown effective in a biochemical assay. Here, we demonstrate that they require a non-standard reaction buffer to function as MPro inhibitors. Hence, our cell-based method detects protease inhibitors missed by other approaches and provides support for the boron-containing molecules. We have thus demonstrated that our platform can screen large numbers of chemicals to find potential inhibitors of a viral protease. Importantly, the platform can be modified to detect protease targets from other emerging viruses.

A review on in silico virtual screening methods in COVID-19 using anticancer drugs and other natural/chemical inhibitors

The present coronavirus disease 2019 (COVID-19) pandemic scenario has posed a difficulty for cancer treatment. Even under ideal conditions, malignancies like small cell lung cancer (SCLC) are challenging to treat because of their fast development and early metastases. The treatment of these patients must not be jeopardized, and they must be protected as much as possible from the continuous spread of the COVID-19 infection. Initially identified in December 2019 in Wuhan, China, the contagious coronavirus illness 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Finding inhibitors against the druggable targets of SARS-CoV-2 has been a significant focus of research efforts across the globe. The primary motivation for using molecular modeling tools against SARS-CoV-2 was to identify candidates for use as therapeutic targets from a pharmacological database. In the published study, scientists used a combination of medication repurposing and virtual drug screening methodologies to target many structures of SARS-CoV-2. This virus plays an essential part in the maturation and replication of other viruses. In addition, the total binding free energy and molecular dynamics (MD) modeling findings showed that the dynamics of various medications and substances were stable; some of them have been tested experimentally against SARS-CoV-2. Different virtual screening (VS) methods have been discussed as potential means by which the evaluated medications that show strong binding to the active site might be repurposed for use against SARS-CoV-2.

Exploration of SARS-CoV-2 Mpro Noncovalent Natural Inhibitors Using Structure-Based Approaches

With the emergence of antibody-evasive omicron subvariants (BA.2.12.1, BA.4, and BA.5), which can compromise the efficacy of vaccination, it is of utmost importance to widen the finite therapeutic options for COVID-19. Although more than 600 co-crystal complexes of Mpro with inhibitors have been revealed, utilizing them to search for novel Mpro inhibitors remains limited. Although there were two major groups of Mpro inhibitors, covalent and noncovalent inhibitors, noncovalent inhibitors were our main focus due to the safety concerns with their covalent counterparts. Hence, this study aimed to explore Mpro noncovalent inhibition ability of phytochemicals extracted from Vietnamese herbals by combining multiple structure-based approaches. By closely inspecting 223 complexes of Mpro with noncovalent inhibitors, a 3D-pharmacophore model representing typical chemical features of Mpro noncovalent inhibitors was generated with good validation scores (sensitivity = 92.11%, specificity = 90.42%, accuracy = 90.65%, and goodness-of-hit score = 0.61). Afterward, the pharmacophore model was applied to explore the potential Mpro inhibitors from our in-house Vietnamese phytochemical database, revealing 18 substances, 5 of which were in vitro assayed. The remaining 13 substances were then examined by induced-fit molecular docking, revealing 12 suitable compounds. A machine-learning activity prediction model was developed to rank the hit, suggesting nigracin and calycosin-7-O-β-glucopyranoside as promising Mpro natural noncovalent inhibitors.

Pharmacophore-Based Virtual Screening of Potential SARS-CoV-2 Main Protease Inhibitors from Library of Natural Products

Background: The SARS-CoV-2 main protease (Mpro) is an attractive target for drug discovery. Methods: A pharmacophore model was built using the three-dimensional (3D) pharmacophore generation algorithm HypoGen in Discovery Studio 2019. The best pharmacophore model was selected for validation using a test set of 24 compounds and was used as a 3D query for further screening of an in-house database of natural compounds. Lipinski's rule of five was used to assess the drug-like properties of the hit compounds. The filtered compounds were then subjected to bioactivity evaluations. The active compounds were docked into the active site of the SARS-CoV-2 Mpro crystal structure (PDB ID: 7D1M). Results: A suitable 3D pharmacophore model, Hypo1, was found to be the best model, consisting of four features (one hydrophobic feature, one hydrogen bond donor, and two hydrogen bond acceptors). Pharmacophore-based virtual screening with Hypo1 as the query to search an in-house database of 34 439 natural compounds resulted in 1502 hits. Among these, 255 compounds satisfied Lipinski's rule of five. The highest ranking 10 compounds were selected for further experimental testing, and one hit (W-7) illustrated inhibitory activity against SARS-CoV-2 Mpro with an IC50 value of 75 μM. Docking studies revealed that this hit compound retained the necessary interactions within the active site of SARS-CoV-2 Mpro. Conclusion The identified lead natural compound could provide a scaffold for the further development of SARS-CoV-2 Mpro inhibitors.

Drug repurposing against main protease and RNA-dependent RNA polymerase of SARS-CoV-2 using molecular docking, MM-GBSA calculations and molecular dynamics

A virus called severe acute respiratory distress syndrome coronavirus type 2 (SARS‐CoV‐2) is the causing organism of coronavirus disease 2019 (COVID-19), which has severely affected human life and threatened public health. The pandemic took millions of lives worldwide and caused serious negative effects on human society and the economy. SARS-CoV-2 main protease (Mpro) and RNA-dependent RNA polymerase (RdRp) are interesting targets due to their crucial role in viral replication and growth. Since there is only one approved therapy for COVID-19, drug repurposing is a promising approach to finding molecules with potential activity against COVID-19 in a short time and at minimal cost. In this study, virtual screening was performed on the ChEMBL library containing 9923 FDA-approved drugs, using various docking filters with different accuracy. The best drugs with the highest docking scores were further examined for molecular dynamics (MD) studies and MM-GBSA calculations. The results of this study suggest that nadide, cangrelor and denufosol are promising potential candidates against COVID-19. Further in vitro, preclinical and clinical studies of these candidates would help to discover safe and effective anti-COVID-19 drugs.