3CLpro Research Articles

Determination of Novel SARS-CoV-2 Inhibitors by Combination of Machine Learning and Molecular Modeling Methods.

Within the scope of the project, this study aimed to find novel inhibitors by combining computational methods. In order to design inhibitors, it was aimed to produce molecules similar to the RdRp inhibitor drug Favipiravir by using the deep learning method. For this purpose, a Trained Neural Network (TNN) was used to produce 75 molecules similar to Favipiravir by using Simplified Molecular Input Line Entry System (SMILES) representations. The binding properties of molecules to Viral RNA-dependent RNA polymerase (RdRp) were studied by using molecular docking studies. To confirm the accuracy of this method, compounds were also tested against 3CL protease (3CLpro), which is another important enzyme for the progression of SARS-CoV-2. Compounds having better binding energies and RMSD values than favipiravir were searched with similarity analysis on the ChEMBL drug database in order to find similar structures with RdRp and 3CLpro inhibitory activities. A similarity search found new 200 potential RdRp and 3CLpro inhibitors structurally similar to produced molecules, and these compounds were again evaluated for their receptor interactions with molecular docking studies. Compounds showed better interaction with RdRp protease than 3CLpro. This result presented that artificial intelligence correctly produced structures similar to favipiravir that act more specifically as RdRp inhibitors. In addition, Lipinski's rules were applied to the molecules that showed the best interaction with RdRp, and 7 compounds were determined to be potential drug candidates. Among these compounds, a Molecular Dynamic simulation study was applied for ChEMBL ID:1193133 to better understand the existence and duration of the compound in the receptor site. The results confirmed that the ChEMBL ID:1193133 compound showed good Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), hydrogen bonding, and remaining time in the active site; therefore, it was considered that it could be active against the virus. This compound was also tested for antiviral activity, and it was determined that it did not delay viral infection, although it was cytotoxic between 5mg/mL-1.25mg/mL concentrations. However, if other compounds could be tested, it might provide a chance to obtain activity, and compounds should also be tested against the enzymes as well as the other types of viruses.

Recent Discovery of Triazine Derivatives as Protease Inhibitors for the Treatment of Coronavirus-19 (COVID-19)

Abstract: The present application describes a class of compounds exhibiting a coronavirus 3CL protease inhibitory effect and pharmaceutically acceptable salts thereof, and a pharmaceutical composition containing the same. The application also provides the synthesis of compounds and efficacy from in vitro and cell- based assays.

Cleavage of HDAC6 to dampen its antiviral activity by nsp5 is a common strategy of swine enteric coronaviruses.

HDAC6, a structurally and functionally unique member of the histone deacetylase (HDAC) family, is an important host factor that restricts viral infection. The broad-spectrum antiviral activity of HDAC6 makes it a potent antiviral agent. Previously, we found that HDAC6 functions to antagonize porcine deltacoronavirus (PDCoV), an emerging enteropathogenic coronavirus with zoonotic potential. However, the final outcome is typically a productive infection that materializes as cells succumb to viral infection, indicating that the virus has evolved sophisticated mechanisms to combat the antiviral effect of HDAC6. Here, we demonstrate that PDCoV nonstructural protein 5 (nsp5) can cleave HDAC6 at glutamine 519 (Q519), and cleavage of HDAC6 was also detected in the context of PDCoV infection. More importantly, the anti-PDCoV activity of HDAC6 was damaged by nsp5 cleavage. Mechanistically, the cleaved HDAC6 fragments (amino acids 1-519 and 520-1159) lost the ability to degrade PDCoV nsp8 due to their impaired deacetylase activity. Furthermore, nsp5-mediated cleavage impaired the ability of HDAC6 to activate RIG-I-mediated interferon responses. We also tested three other swine enteric coronaviruses (transmissible gastroenteritis virus, porcine epidemic diarrhea virus, and swine acute diarrhea syndrome-coronavirus) and found that all these coronaviruses have adopted similar mechanisms to cleave HDAC6 in both an overexpression system and virus-infected cells, suggesting that cleavage of HDAC6 is a common strategy utilized by swine enteric coronaviruses to antagonize the host's antiviral capacity. Together, these data illustrate how swine enteric coronaviruses antagonize the antiviral function of HDAC6 to maintain their infection, providing new insights to the interaction between virus and host.IMPORTANCEViral infections and host defenses are in constant opposition. Once viruses combat or evade host restriction, productive infection is achieved. HDAC6 is a broad-spectrum antiviral protein that has been demonstrated to inhibit many viruses, including porcine deltacoronavirus (PDCoV). However, whether HDAC6 is reciprocally targeted and disabled by viruses remains unclear. In this study, we used PDCoV as a model and found that HDAC6 is targeted and cleaved by nsp5, a viral 3C-like protease. The cleaved HDAC6 loses its deacetylase activity as well as its ability to degrade viral proteins and activate interferon responses. Furthermore, this cleavage mechanism is shared among other swine enteric coronaviruses. These findings shed light on the intricate interplay between viruses and HDAC6, highlighting the strategies employed by viruses to evade host antiviral defenses.

Molecular Docking, Dynamics Simulations, ADMET, and DFT Calculations: Combined In Silico Approach to Screen Natural Inhibitors of 3CL and PL Proteases of SARS-CoV-2

Considering natural compounds for the antiviral effect is another opportunity for exploring novel drug candidates for severe acute respiratory syndrome coronavirus 2. The selected natural compounds were interacted using a molecular docking approach. The 3D structures of the main protease and papain-like protease were used for the virtual screening to detect the potent inhibitor against SARS-CoV-2. The top-scored compounds were further analyzed for absorption, digestion, metabolism, excretion, and toxicity properties and density functional theory analysis. Our results indicated that glycyrrhizin exhibited better docking scores of -9.5 kcal/mol with main protease and -9.7 kcal/mol with papain-like protease. Next to glycyrrhizin, rutin showed a better docking score of -9.1 kcal/mol and -9.2 kcal/mol with 3-chymotrypsin-like and papain-like proteases. Violaxanthin and naringin occupied the subsequent position in the docking score table with 3CL and PL proteases, respectively. In addition, the crucial properties like drug likeliness and pharmacokinetics of the compounds were determined. There is no significant toxicity identified.

Capillary electrokinetic chromatography for chiral separation of potential SARS-CoV-2 3CL protease inhibitors.

In this work, a capillary electrophoresis method was developed as a quality control tool to determine the enantiomeric purity of a series of five chiral compounds evaluated as potential severe acute respiratory syndrome coronavirus 2 3CL protease inhibitors. The first cyclodextrin tested, that is, highly sulfated-β-cyclodextrin, at 6% (m/v) in a 25mM phosphate buffer, using a capillary dynamically coated with polyethylene oxide, at an applied voltage of 15kV and a temperature of 25°C, was found to successfully separate the five derivatives. The limits of detection and quantification were calculated together with the greenness score of the method in order to evaluate the method in terms of analytical and environmental performance. In addition, it is noteworthy that simultaneously high-performance liquid chromatography separation of the enantiomers of the same compounds with two different columns, the amylose tris(3,5-dimethylphenylcarbamate)-coated and the cellulose tris(3,5-dichlorophenylcarbamate)-immobilized on silica stationary phases, was studied. Neither the former stationary phase nor the latter was able to separate all derivatives in a mobile phase consisting of n-heptane/propan-2-ol 80/20 (v/v).

All-trans retinoic acid acts as a dual-purpose inhibitor of SARS-CoV-2 infection and inflammation

Coronavirus disease 2019 (COVID-19) was an epidemic that effected human health caused by SARS-CoV-2 infection. All-trans retinoic acid (ATRA) has anti-inflammatory capability. In this article, we evaluated the effectiveness and revealed the molecular mechanism of ATRA for treating SARS-CoV-2 using deep learning, in vitro studies, multi-scale molecular modeling, and network pharmacology. The DeepDTA model suggested that ATRA would be effective against COVID-19. In vitro studies confirmed the antiviral activity of ATRA. Subsequently, multi-scale molecular modeling indicated that ATRA could binding to angiotensin converting enzyme 2 (ACE2), 3C-like protease (3CLpro), RNA dependent RNA polymerase (RdRp), helicase, and 3′-to-5′ exonuclease by non-covalent interactions. Additionally, network pharmacology suggested that ATRA alleviated inflammatory response by regulating the IL-17 signaling pathway and binding with TNF, PTGS2, and MAPK1 directly. In summary, our findings provide the first evidence that ATRA suppresses the entry and replication of SARS-CoV-2, and regulates inflammatory response of host cells.

Identification of musk compounds as inhibitors of the main SARS-CoV-2 protease by molecular docking and molecular dynamics studies

As new drug development is a long process, reuse of bioactives may be the answer to new epidemics; thus, screening existing bioactive compounds against a new SARS-CoV-2 infection is an important task. With this in mind, we have systematically screened potential odorant molecules in the treatment of this infection based on the affinity of the selected odorant compounds on the studied enzyme and the sequence identity of their target proteins (olfactory receptors) to the same enzyme (the main protease of SARS-CoV-2). A total of 12 musk odorant compounds were subjected to a molecular docking and molecular dynamics study to predict their impact against the main protease of SARS-CoV- 2. In this study, we have identified two musk-scented compounds (androstenol and vulcanolide) that have good binding energy at the major protease binding site of SARS-CoV-2. However, the RMSD values recorded during dynamic simulation show that vulcanolide exhibits high stability of the protein-ligand complex compared to androstenol. The perspectives of this work are as follows: in vitro, in vivo, and clinical trials to verify the computational findings.

Natural 7,8-secolignans from Schisandra sphenanthera fruit potently inhibit SARS-CoV-2 3CLpro and inflammation

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), turned into a global pandemic, and there remains an urgent demand for specific/targeted drugs for the disease. The 3C-like protease (3CLpro) is a promising target for developing anti-coronavirus drugs. Schisandra sphenanthera fruit is a well-known traditional Chinese medicine (TCM) with good antiviral activity. This study found that the ethanolic extract displayed a significant inhibitory effect against SARS-CoV-2 3CLpro. Forty-four compounds were identified in this extract using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS). Combining molecular docking and in vitro experiments, we found that two epimeric 7,8-secolignans, rel-(1S,2R)-1-(3,4-dimethoxyphenyl)-2-methyl-3-oxobutyl-3,4-dimethoxybenzoate (2) and rel-(1S,2S)-1-(3,4-dimethoxyphenyl)-2-methyl-3-oxobutyl-3,4-dimethoxybenzoate (4), potently inhibited 3CLpro with IC50 values of 4.88 ± 0.60 μM and 4.75 ± 0.34 μM, respectively. Moreover, in vivo and in vitro experiments indicated that compounds 2 and 4 were potent in regulating the inflammatory response and preventing lung injury. Our findings indicate that compounds 2 and 4 may emerge as promising SARS-CoV-2 inhibitors via 3CLpro inhibition and anti-inflammatory mechanisms.

High-throughput modular click chemistry synthesis of catechol derivatives as covalent inhibitors of SARS-CoV-2 3CLpro

The 3C-like protease (3CLpro) is a crucial target in anti-Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) drug design. Herein, we performed high-throughput synthesis of catechol derivatives from the bioactive catechol-terminal alkyne scaffold A4, by using modular click chemistry. Subsequently, we conducted two rounds of SARS-CoV-2 3CLpro inhibition screening and selected seven compounds for synthesis and further efficacy validation. Compound P1-E11 had potent inhibitory effects toward SARS-CoV-2 3CLpro (IC50 = 2.54 ± 0.46 μM); exhibited good selectivity toward the human cysteine proteases cathepsins B and L; and demonstrated superior anti-SARS-CoV-2 potency (EC50 = 4.66 ± 0.58 μM) with low cytotoxicity (CC50 > 100 μM) in A549-hACE2-TMPRSS2 cells. The irreversible covalent mechanism of P1-E11 was confirmed through time-dependent experiments, enzyme kinetic studies, and dilution and dialysis assays. The binding affinity between P1-E11 and SARS-CoV-2 3CLpro with a KD value of 0.57 μM was validated through surface plasmon resonance (SPR) experiments. Molecular docking provided insights into the binding mode of P1-E11 to the target protein. This study demonstrated the feasibility and efficacy of modular click reactions in natural-product-based structural modifications and presents a novel approach for leveraging this strategy in antiviral drug discovery.

Exploring 7β-amino-6-nitrocholestens as COVID-19 antivirals: in silico, synthesis, evaluation, and integration of artificial intelligence (AI) in drug design: assessing the cytotoxicity and antioxidant activity of 3β-acetoxynitrocholestane.

In light of the ongoing pandemic caused by SARS-CoV-2, effective and clinically translatable treatments are desperately needed for COVID-19 and its emerging variants. In this study, some derivatives, including 7β-aminocholestene compounds, and 3β-acetoxy-6-nitrocholesta-4,6-diene were synthesized, in quantitative yields from 7β-bromo-6-nitrocholest-5-enes (1-3) with a small library of amines. The synthesized steroidal products were then thoroughly characterized using a range of physicochemical techniques, including IR, NMR, UV, MS, and elemental analysis. Next, a virtual screening based on structures using docking studies was conducted to investigate the potential of these synthesized compounds as therapeutic candidates against SARS-CoV-2. Specifically, we evaluated the compounds' binding energy of the reactants and their products with three SARS-CoV-2 functional proteins: the papain-like protease, 3C-like protease or main protease, and RNA-dependent RNA polymerase. Our results indicate that the 7β-aminocholestene derivatives (4-8) display intermediate to excellent binding energy, suggesting that they interact strongly with the receptor's active amino acids and may be promising drug candidates for inhibiting SARS-CoV-2. Although the starting steroid derivatives; 7β-bromo-6-nitrocholest-5-enes (1-3) and one steroid product; 3β-acetoxy-6-nitrocholesta-4,6-diene (9) exhibited strong binding energies with various SARS-CoV-2 receptors, they did not meet the Lipinski Rule and ADMET properties required for drug development. These compounds showed either mutagenic or reproductive/developmental toxicity when assessed using toxicity prediction software. The findings based on structure-based virtual screening, suggest that 7β-aminocholestaines (4-8) may be useful for reducing the susceptibility to SARS-CoV-2 infection. The docking pose of compound 4, which has a high score of -7.4 kcal mol-1, was subjected to AI-assisted deep learning to generate 60 AI-designed molecules for drug design. Molecular docking of these AI molecules was performed to select optimal candidates for further analysis and visualization. The cytotoxicity and antioxidant effects of 3β-acetoxy-6-nitrocholesta-4,6-diene were tested in vitro, showing marked cytotoxicity and antioxidant activity. To elucidate the molecular basis for these effects, steroidal compound 9 was subjected to molecular docking analysis to identify potential binding interactions. The stability of the top-ranked docking pose was subsequently assessed using molecular dynamics simulations.

QSAR of SARS-CoV-2 Main Protease Inhibitors Utilizing Theoretical Molecular Descriptors

Background: COVID-19 is caused by a novel strain of severe acute respiratory syndrome coronaviruses (SARS-CoV-2). It has claimed casualties around the world since the end of 2019 due to its high virulence and quick multiplicity in the human body. Hence, there has been a requirement to develop effective remedial measures to mitigate the mortality. Scientists have been able to develop corona vaccines to provide immunity, but there are no specific small-molecule chemotherapeutics to combat the novel coronavirus which has spread to the whole world due to its contagiousness. In the viral genome exploration, it has been found that the main protease, also known as chymotrypsin-like cysteine protease ([Mpro] or 3C-like protease [3CLpro]) is responsible for the novel coronavirus replication, transcription, and host immunity destruction. Objectives: Therefore, the main protease has been selected as one of the major targets for the design of new inhibitors. The protein crystallographic and molecular docking studies on SARS-CoV-2 Mpro inhibitors and some quantitative structure-activity relationship (QSAR) studies have been carried out on SARSCoV main protease inhibitors to get some lead molecules for SARS-CoV-2 inhibition. However, there is hardly any QSAR done on the diverse data of SARS-CoV-2 main protease inhibitors. In view of it, QSAR studies have been attempted on SARS-CoV-2 Mpro inhibitors utilizing theoretical molecular descriptors solely computed from the structures of novel corona viral main protease inhibitors. Methods: Methods: As the number of structural descriptors is more than the observations, a genetic algorithm coupled with multiple linear methods has been applied for the development of QSAR models taking diverse SARS-CoV-2 Mpro inhibitors. Results: The developed best QSAR model showing R2 , Q2 Loo, and R2 pred values of 0.7389, 0.6666, and 0.6453 respectively has been further validated on an external data set where a good correlation (r = 0.787) has been found. Conclusion: Therefore, this model may be useful for the design of new SARS-CoV-2 main protease inhibitors.

DNA encoded peptide library for SARS-CoV-2 3CL protease covalent inhibitor discovery and profiling.

Covalent protease inhibitors serve as valuable tools for modulating protease activity and are essential for investigating the functions of protease targets. These inhibitors typically consist of a recognition motif and a covalently reactive electrophile. Substrate peptides, featuring residues capable of fitting into the substrate pockets of proteases, undergo chemical modification at the carbonyl carbon of the P1 residue with an electrophile and have been widely applied in the development of covalent inhibitors. In this study, we utilized a DNA-encoded peptide library to replicate peptide binder sequences and introduced a vinyl sulfone warhead at the C-termini to construct the DNA-encoded peptide covalent inhibitor library (DEPCIL) for targeting cysteine proteases. Screening results toward 3CL protease demonstrated the efficacy of this library, not only in identifying protease inhibitors, but also in discovering amino acids that can conform to aligned protease pockets. The identified peptide sequences provide valuable insight into the amino acid preferences within substrate binding pockets, and our novel technology is indicative of the potential for similar strategies to discover covalent inhibitors and profile binding preferences of other proteases.

Computational Approaches for Lead Discovery against SARS-CoV-2 3C-Like Protease: Virtual Screening and Molecular Dynamics Studies

Background: The COVID-19 pandemic has caused significant difficulties in multiple emotional, social, and financial areas. Despite the positive effects of vaccination in reducing infection and fatality rates, the need for efficient antiviral medications, particularly those that can be taken orally, remains a critical concern. Methods: A virtual screening method based on structure, referred to as SBVS, was used to identify potential inhibitory small molecules that specifically target the 3C-like protease (3CLPRO) found in SARS-CoV-2. Results: The filtering process for potential ligands involved strict criteria based on their molecular properties, including a molecular weight limit of 500 g/mol, maximum of five hydrogen bond donors, maximum of 10 hydrogen bond acceptors, and logP limit of 5. This was done to identify five candidates with lower ∆G values than the reference drugs lopinavir (-8.19 kcal/mol) and ritonavir (-8.04 kcal/mol). Three hits were identified through further evaluation using the hydrogen bond criteria and the BOILED-Egg model. The pharmacokinetic attributes of these two hits were compared with those of the reference drugs lopinavir and ritonavir. Conclusion: The molecular dynamics simulation (20 ns) outcomes unequivocally demonstrated the stability and promising nature of MCULE-2367618737 as a possible lead compound against the targeted 3CLPRO.

A deep learning framework for predicting molecular property based on multi-type features fusion

Extracting expressive molecular features is essential for molecular property prediction. Sequence-based representation is a common representation of molecules, which ignores the structure information of molecules. While molecular graph representation has a weak ability in expressing the 3D structure. In this article, we try to make use of the advantages of different type representations simultaneously for molecular property prediction. Thus, we propose a fusion model named DLF-MFF, which integrates the multi-type molecular features. Specifically, we first extract four different types of features from molecular fingerprints, 2D molecular graph, 3D molecular graph and molecular image. Then, in order to learn molecular features individually, we use four essential deep learning frameworks, which correspond to four distinct molecular representations. The final molecular representation is created by integrating the four feature vectors and feeding them into prediction layer to predict molecular property. We compare DLF-MFF with 7 state-of-the-art methods on 6 benchmark datasets consisting of multiple molecular properties, the experimental results show that DLF-MFF achieves state-of-the-art performance on 6 benchmark datasets. Moreover, DLF-MFF is applied to identify potential anti-SARS-CoV-2 inhibitor from 2500 drugs. We predict probability of each drug being inferred as a 3CL protease inhibitor and also calculate the binding affinity scores between each drug and 3CL protease. The results show that DLF-MFF product better performance in the identification of anti-SARS-CoV-2 inhibitor. This work is expected to offer novel research perspectives for accurate prediction of molecular properties and provide valuable insights into drug repurposing for COVID-19.

Design of new dipeptide inhibitors against SARS-CoV 3CLpro: 3D-QSAR, molecular docking, MD simulation, ADMET studies and retrosynthesis strategy

The 3CL protease plays a crucial role in the life cycle of SARS-CoV. This protease is considered an important antiviral target. In the present work, the 3D-QSAR study was performed on a set composed of twenty-six dipeptide SARS-CoV 3CLpro inhibitors in order to propose the new potent anti-SARS agents with a high predicted activity value. The model of CoMSIA/SH is the optimal, with good statistical results presenting a high value of the cross-validation coefficient Q2 = 0.796 and a good value of the determination coefficient R2 = 0.887, the external validation of this model is justified by the high value of the prediction coefficient R2pred = 0.884 and the validation of Globraikh, Roy and Tropsha criteria. The exploitation of the different results provided key information about the structures favored to improve the inhibitory activity against 3CLpro, and has enabled us to propose seven new potent inhibitors with significant predictive activity values, notably compound M−1 with pKipred = 7.080. Then, a molecular docking study was performed to determine the binding energy and to identify the key interactions between the receptor (PDB ID: 1WOF) and the ligands. All the newly designed compounds showed low binding energy values as compared to the Remdesivir −8.144 kcal. mol−1 especially for compounds M−5 and M−4 with the binding affinity values −10.022 kcal. mol−1 and −9.727 kcal.mol−1 respectively. In addition, these inhibitors were verified for in silico pharmacokinetic proprieties and toxicity profile using ADMET. Two compounds M−4 and M−5 with potential results in the molecular docking were selected for the molecular dynamic simulation of 100 ns. The MM-GBSA results show that the predicted compound M−5 has the lowest free energy with −38.200 KJ/mol. We exploited the computer-aided synthesis technology using the ASKCOS website to perform a retrosynthetic analysis of compound M−5.

Syringa reticulata potently inhibits the activity of SARS-CoV-2 3CL protease

The ongoing coronavirus infectious disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still urgently requires effective treatments. The 3C-like (3CL) protease of SARS-CoV-2 is a highly conserved cysteine protease that plays an important role in the viral life cycle and host inflammation, providing an ideal target for developing broad-spectrum antiviral drugs. Herein, we describe the discovery of a large number of herbs mainly produced in Heilongjiang Province, China, that exhibited different inhibitory activities against SARS-CoV-2 3CL protease. We confirmed that Syringa reticulata, which is used for clinical treatment of chronic bronchitis and asthma, is a specific and potent inhibitor of 3CL protease. A 70 % ethanol extract of S. reticulata dose-dependently inhibited the cleavage activity of 3CL protease in a fluorescence resonance energy transfer assay with an IC50 value of 0.0018 mg/mL, but had minimal effect in pseudovirus-based cell entry and luciferase-based RNA-dependent RNA polymerase assays. These results suggest that S. reticulata will be a potential leading candidate for COVID-19 treatment.

Potent 3CLpro inhibitors effective against SARS-CoV-2 and MERS-CoV in animal models by therapeutic treatment.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome coronavirus (MERS-CoV) are zoonotic betacoronaviruses that continue to have a significant impact on public health. Timely development and introduction of vaccines and antivirals against SARS-CoV-2 into the clinic have substantially mitigated the burden of COVID-19. However, a limited or lacking therapeutic arsenal for SARS-CoV-2 and MERS-CoV infections, respectively, calls for an expanded and diversified portfolio of antivirals against these coronavirus infections. In this report, we examined the efficacy of two potent 3CLpro inhibitors, 5d and 11d, in fatal animal models of SARS-CoV-2 and MERS-CoV to demonstrate their broad-spectrum activity against both viral infections. These compounds significantly increased the survival of mice in both models when treatment started 1 day post infection compared to no treatment which led to 100% fatality. Especially, the treatment with compound 11d resulted in 80% and 90% survival in SARS-CoV-2 and MERS-CoV-infected mice, respectively. Amelioration of lung viral load and histopathological changes in treated mice correlated well with improved survival in both infection models. Furthermore, compound 11d exhibited significant antiviral activities in K18-hACE2 mice infected with SARS-CoV-2 Omicron subvariant XBB.1.16. The results suggest that these are promising candidates for further development as broad-spectrum direct-acting antivirals against highly virulent human coronaviruses.IMPORTANCEHuman coronaviruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome coronavirus (MERS-CoV) continue to have a significant impact on public health. A limited or lacking therapeutic arsenal for SARS-CoV-2 and MERS-CoV infections calls for an expanded and diversified portfolio of antivirals against these coronavirus infections. We have previously reported a series of small-molecule 3C-like protease (3CLpro) inhibitors against human coronaviruses. In this report, we demonstrated the in vivo efficacy of 3CLpro inhibitors for their broad-spectrum activity against both SARS-CoV-2 and MERS-CoV infections using the fatal animal models. The results suggest that these are promising candidates for further development as broad-spectrum direct-acting antivirals against highly virulent human coronaviruses.

A naturally occurring G11S mutation in the 3C-like protease from the SARS-CoV-2 virus dramatically weakens the dimer interface.

The 3C-like protease (3CLpro ) is crucial to the replication of SARS-CoV-2, the causative agent of COVID-19, and is the target of several successful drugs including Paxlovid and Xocova. Nevertheless, the emergence of viral resistance underlines the need for alternative drug strategies. 3CLpro only functions as a homodimer, making the protein-protein interface an attractive drug target. Dimerization is partly mediated by a conserved glycine at position 11. However, some naturally occurring SARS-CoV-2 sequences contain a serine at this position, potentially disrupting the dimer. We have used concentration-dependent activity assays and mass spectrometry to show that indeed the G11S mutation reduces the stability of the dimer by 600-fold. This helps to set a quantitative benchmark for the minimum potency required of any future protein-protein interaction inhibitors targeting 3CLpro and raises interesting questions regarding how coronaviruses bearing such weakly dimerizing 3CLpro enzymes are capable of replication.

Inhibitory effects against SARSCoV-2 main protease (Mpro) of biflavonoids and benzophenones from the fruit of Platonia insignis

The SARS-CoV-2 mutation and the limitation of the approved drug against COVID-19 are still a challenge in many country healthcare systems and need to be affronted despite the set of vaccines to prevent this viral infection. To contribute to the identification of new antiviral agents, the present study focused on natural products from an edible fruit with potential inhibitory effects against the SARS-CoV-2 main protease (Mpro). First, LC-ESIMS analysis of Platonia insignis fruits was performed and showed the presence of biflavonoids and benzophenones in the seed and pulp, respectively. Then, maceration and chromatographic purification led to the identification of two triglycerides (1 and 2) alongside chamaejasmine (3) and volkensiflavone (4) from the seed and isogarcinol (5) and cycloxanthochymol (6), from the pulp. Compounds 1–6 after evaluating their inhibitory against Mpro, displayed from no to significant activity. Compound 5 was the most potent with an IC50 value of 0.72 μM and was more active than the positive control, Ebselen (IC50 of 3.4 μM). It displayed weak and no cytotoxicity against THP-1 (CC50 of 116.2 μM) and Vero cell lines, respectively. Other active compounds showed no cytotoxicity against THP-1. and Vero cell lines. Molecular docking studies revealed interactions in the catalytic pocket between compound 5 and amino acid residues that composed the catalytic dyads (His 41 and Cyst 145).

Anemoside B4 inhibits SARS-CoV-2 replication in vitro and in vivo

ObjectiveAnemoside B4 (AB4), the most abundant triterpenoidal saponin isolated from Pulsatilla chinensis, inhibited influenza virus FM1 or Klebsiella pneumoniae-induced pneumonia. However, the anti-SARS-CoV-2 effect of AB4 has not been unraveled. Therefore, this study aimed to determine the antiviral activity and potential mechanism of AB4 in inhibiting human coronavirus SARS-CoV-2 in vivo and in vitro. MethodsThe cytotoxicity of AB4 was evaluated using the Cell Counting Kit-8 (CCK8) assay. SARS-CoV-2 infected HEK293T, HPAEpiC, and Vero E6 cells were used for in vitro assays. The antiviral effect of AB4 in vivo was evaluated by SARS-CoV-2-infected hACE2-IRES-luc transgenic mouse model. Furthermore, label-free quantitative proteomics and bioinformatic analysis were performed to explore the potential antiviral mechanism of action of AB4. Type I IFN signaling-associated proteins were assessed using Western blotting or immumohistochemical staining. ResultsThe data showed that AB4 reduced the propagation of SARS-CoV-2 along with the decreased Nucleocapsid protein (N), Spike protein (S), and 3C-like protease (3CLpro) in HEK293T cells. In vivo antiviral activity data revealed that AB4 inhibited viral replication and relieved pneumonia in a SARS-CoV-2 infected mouse model. We further disclosed that the antiviral activity of AB4 was associated with the enhanced interferon (IFN)-β response via the activation of retinoic acid-inducible gene I (RIG-1) like receptor (RLP) pathways. Additionally, label-free quantitative proteomic analyses discovered that 17 proteins were significantly altered by AB4 in the SARS-CoV-2 coronavirus infections cells. These proteins mainly clustered in RNA metabolism. ConclusionOur results indicated that AB4 inhibited SARS-CoV-2 replication through the RLR pathways and moderated the RNA metabolism, suggesting that it would be a potential lead compound for the development of anti-SARS-CoV-2 drugs.