A Bioluminescent 3CLPro Activity Assay to Monitor SARS-CoV-2 Replication and Identify Inhibitors.
Ontology highlight
ABSTRACT:
SUBMITTER: Mathieu C
PROVIDER: S-EPMC8473059 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The 3C-like protease (3CLpro) of SARS-CoV-2 is considered an excellent target for COVID-19 antiviral drug development because it is essential for viral replication and has a cleavage specificity distinct from human proteases. However, drug development for 3CLpro has been hindered by a lack of cell-based reporter assays that can be performed in a BSL-2 setting. Current efforts to identify 3CLpro inhibitors largely rely upon in vitro screening, which fails to account for cell permeability and cytotoxicity of compounds, or assays involving replication-competent virus, which must be performed in a BSL-3 facility. To address these limitations, we have developed a novel cell-based luciferase complementation reporter assay to identify inhibitors of SARS-CoV-2 3CLpro in a BSL-2 setting. The assay is based on a lentiviral vector that co-expresses 3CLpro and two luciferase fragments linked together by a 3CLpro cleavage site. 3CLpro-mediated cleavage results in a loss of complementation and low luciferase activity, whereas inhibition of 3CLpro results in 10-fold higher levels of luciferase activity. The luciferase reporter assay can easily distinguish true 3CLpro inhibition from cytotoxicity, a powerful feature that should reduce false positives during screening. Using the assay, we screened 32 small molecules for activity against SARS-CoV-2 3CLpro, including HIV protease inhibitors, HCV protease inhibitors, and various other compounds that have been reported to inhibit SARS-CoV-2 3CLpro. Of these, only five exhibited significant inhibition of 3CLpro in cells: GC376, boceprevir, Z-FA-FMK, calpain inhibitor XII, and GRL-0496. This assay should greatly facilitate efforts to identify more potent inhibitors of SARS-CoV-2 3CLpro.
| S-EPMC7911889 | biostudies-literature
Project description:COVID-19 caused by a novel coronavirus (SARS-CoV-2) has been spreading all over the world since the end of 2019, and no specific drug has been developed yet. 3C-like protease (3CLpro) acts as an important part of the replication of novel coronavirus and is a promising target for the development of anticoronavirus drugs. In this paper, eight machine learning models were constructed using naïve Bayesian (NB) and recursive partitioning (RP) algorithms for 3CLpro on the basis of optimized two-dimensional (2D) molecular descriptors (MDs) combined with ECFP_4, ECFP_6, and MACCS molecular fingerprints. The optimal models were selected according to the results of 5-fold cross verification, test set verification, and external test set verification. A total of 5766 natural compounds from the internal natural product database were predicted, among which 369 chemical components were predicted to be active compounds by the optimal models and the EstPGood values were more than 0.6, as predicted by the NB (MD + ECFP_6) model. Through ADMET analysis, 31 compounds were selected for further biological activity determination by the fluorescence resonance energy transfer (FRET) method and cytopathic effect (CPE) detection. The results indicated that (+)-shikonin, shikonin, scutellarein, and 5,3',4'-trihydroxyflavone showed certain activity in inhibiting SARS-CoV-2 3CLpro with the half-maximal inhibitory concentration (IC50) values ranging from 4.38 to 87.76 μM. In the CPE assay, 5,3',4'-trihydroxyflavone showed a certain antiviral effect with an IC50 value of 8.22 μM. The binding mechanism of 5,3',4'-trihydroxyflavone with SARS-CoV-2 3CLpro was further revealed through CDOCKER analysis. In this study, 3CLpro prediction models were constructed based on machine learning algorithms for the prediction of active compounds, and the activity of potential inhibitors was determined by the FRET method and CPE assay, which provide important information for further discovery and development of antinovel coronavirus drugs.
| S-EPMC8631171 | biostudies-literature
Project description:The main protease Mpro , 3CLpro is an important target from coronaviruses. In spite of having 96% sequence identity among Mpros from SARS-CoV-1 and SARS-CoV-2; the inhibitors used to block the activity of SARS-CoV-1 Mpro so far, were found to have differential inhibitory effect on Mpro of SARS-CoV-2. The possible reason could be due to the difference of few amino acids among the peptidases. Since, overall 3-D crystallographic structure of Mpro from SARS-CoV-1 and SARS-CoV-2 is quite similar and mapping a subtle structural variation is seemingly impossible. Hence, we have attempted to study a structural comparison of SARS-CoV-1 and SARS-CoV-2 Mpro in apo and inhibitor bound states using protein structure network (PSN) based approach at contacts level. The comparative PSNs analysis of apo Mpros from SARS-CoV-1 and SARS-CoV-2 uncovers small but significant local changes occurring near the active site region and distributed throughout the structure. Additionally, we have shown how inhibitor binding perturbs the PSG and the communication pathways in Mpros . Moreover, we have also investigated the network connectivity on the quaternary structure of Mpro and identified critical residue pairs for complex formation using three centrality measurement parameters along with the modularity analysis. Taken together, these results on the comparative PSN provide an insight into conformational changes that may be used as an additional guidance towards specific drug development.
| S-EPMC8242809 | biostudies-literature
Project description:The pandemic, COVID-19, has spread worldwide and affected millions of people. There is an urgent need, therefore, to find a proper treatment for the novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent. This paper focuses on identifying inhibitors that target SARS-CoV-2 proteases, PLPRO and 3CLPRO, which control the duplication and manages the life cycle of SARS-CoV-2. We have carried out detailed in silico Virtual high-throughput screening using Food and Drug Administration (FDA) approved drugs from the Zinc database, COVID-19 clinical trial compounds from Pubchem database, Natural compounds from Natural Product Activity and Species Source (NPASS) database and Maybridge database against PLPRO and 3CLPRO proteases. After thoroughly analyzing the screening results, we found five compounds, Bemcentinib, Pacritinib, Ergotamine, MFCD00832476, and MFCD02180753 inhibit PLPRO and six compounds, Bemcentinib, Clofazimine, Abivertinib, Dasabuvir, MFCD00832476, Leuconicine F inhibit the 3CLPRO. These compounds are stable within the protease proteins' active sites at 20ns MD simulation. The stability is revealed by hydrogen bond formations, hydrophobic interactions, and salt bridge interactions. Our study results also reveal that the selected five compounds against PLPRO and the six compounds against 3CLPRO bind to their active sites with good binding free energy. These compounds that inhibit the activity of PLPRO and 3CLPRO may, therefore, be used for treating COVID-19 infection.
| S-EPMC8018918 | biostudies-literature
Project description: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".
| S-EPMC8158358 | biostudies-literature
Project description: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.
| S-EPMC8592230 | biostudies-literature
Project description:The main protease, Mpro, of SARS-CoV-2 is required to cleave the viral polyprotein into precise functional units for virus replication and pathogenesis. Here, we report quantitative reporters for Mpro function in living cells in which protease inhibition by genetic or chemical methods results in robust signal readouts by fluorescence (enhanced green fluorescent protein [eGFP]) or bioluminescence (firefly luciferase). These gain-of-signal systems are scalable to high-throughput platforms for quantitative discrimination between Mpro mutants and/or inhibitor potencies as evidenced by validation of several reported inhibitors. Additional utility is shown by single Mpro amino acid variants and structural information combining to demonstrate that both inhibitor conformational dynamics and amino acid differences are able to influence inhibitor potency. We further show that a recent variant of concern (Omicron) has an unchanged response to a clinically approved drug, nirmatrelvir, whereas proteases from divergent coronavirus species show differential susceptibility. Together, we demonstrate that these gain-of-signal systems serve as robust, facile, and scalable assays for live cell quantification of Mpro inhibition, which will help expedite the development of next-generation antivirals and enable the rapid testing of emerging variants. IMPORTANCE The main protease, Mpro, of SARS-CoV-2 is an essential viral protein required for the earliest steps of infection. It is therefore an attractive target for antiviral drug development. Here, we report the development and implementation of two complementary cell-based systems for quantification of Mpro inhibition by genetic or chemical approaches. The first is fluorescence based (eGFP), and the second is luminescence based (firefly luciferase). Importantly, both systems rely upon gain-of-signal readouts such that stronger inhibitors yield higher fluorescent or luminescent signal. The high versatility and utility of these systems are demonstrated by characterizing Mpro mutants and natural variants, including Omicron, as well as a panel of existing inhibitors. These systems rapidly, safely, and sensitively identify Mpro variants with altered susceptibilities to inhibition, triage-nonspecific, or off-target molecules and validate bona fide inhibitors, with the most potent thus far being the first-in-class drug nirmatrelvir.
| S-EPMC9239272 | biostudies-literature
Project description:Since the first report of a new pneumonia disease in December 2019 (Wuhan, China) the WHO reported more than 148 million confirmed cases and 3.1 million losses globally up to now. The causative agent of COVID-19 (SARS-CoV-2) has spread worldwide, resulting in a pandemic of unprecedented magnitude. To date, several clinically safe and efficient vaccines (e.g., Pfizer-BioNTech, Moderna, Johnson & Johnson, and AstraZeneca COVID-19 vaccines) as well as drugs for emergency use have been approved. However, increasing numbers of SARS-Cov-2 variants make it imminent to identify an alternative way to treat SARS-CoV-2 infections. A well-known strategy to identify molecules with inhibitory potential against SARS-CoV-2 proteins is repurposing clinically developed drugs, e.g., antiparasitic drugs. The results described in this study demonstrated the inhibitory potential of quinacrine and suramin against SARS-CoV-2 main protease (3CLpro). Quinacrine and suramin molecules presented a competitive and noncompetitive inhibition mode, respectively, with IC50 values in the low micromolar range. Surface plasmon resonance (SPR) experiments demonstrated that quinacrine and suramin alone possessed a moderate or weak affinity with SARS-CoV-2 3CLpro but suramin binding increased quinacrine interaction by around a factor of eight. Using docking and molecular dynamics simulations, we identified a possible binding mode and the amino acids involved in these interactions. Our results suggested that suramin, in combination with quinacrine, showed promising synergistic efficacy to inhibit SARS-CoV-2 3CLpro. We suppose that the identification of effective, synergistic drug combinations could lead to the design of better treatments for the COVID-19 disease and repurposable drug candidates offer fast therapeutic breakthroughs, mainly in a pandemic moment.
| S-EPMC8170883 | biostudies-literature
Project description:Severe diseases such as the ongoing COVID-19 pandemic, as well as the previous SARS and MERS outbreaks, are the result of coronavirus infections and have demonstrated the urgent need for antiviral drugs to combat these deadly viruses. Due to its essential role in viral replication and function, 3CLpro (main coronaviruses cysteine-protease) has been identified as a promising target for the development of antiviral drugs. Previously reported SARS-CoV 3CLpro non-covalent inhibitors were used as a starting point for the development of covalent inhibitors of SARS-CoV-2 3CLpro. We report herein our efforts in the design and synthesis of submicromolar covalent inhibitors when the enzymatic activity of the viral protease was used as a screening platform.
| S-EPMC8665847 | biostudies-literature
Project description:The appearance at the end of 2019 of the new SARS-CoV-2 coronavirus led to an unprecedented response by the structural biology community, resulting in the rapid determination of many hundreds of structures of proteins encoded by the virus. As part of an effort to analyze and, if necessary, remediate these structures as deposited in the Protein Data Bank (PDB), this work presents a detailed analysis of 81 crystal structures of the main protease 3CLpro, an important target for the design of drugs against COVID-19. The structures of the unliganded enzyme and its complexes with a number of inhibitors were determined by multiple research groups using different experimental approaches and conditions; the resulting structures span 13 different polymorphs representing seven space groups. The structures of the enzyme itself, all determined by molecular replacement, are highly similar, with the exception of one polymorph with a different inter-domain orientation. However, a number of complexes with bound inhibitors were found to pose significant problems. Some of these could be traced to faulty definitions of geometrical restraints for ligands and to the general problem of a lack of such information in the PDB depositions. Several problems with ligand definition in the PDB itself were also noted. In several cases extensive corrections to the models were necessary to adhere to the evidence of the electron-density maps. Taken together, this analysis of a large number of structures of a single, medically important protein, all determined within less than a year using modern experimental tools, should be useful in future studies of other systems of high interest to the biomedical community.
| S-EPMC7924243 | biostudies-literature