Hepatitis C virus NS3/4A inhibitors and other drug-like compounds as covalent binders of SARS-CoV-2 main protease

In Silico Comparative Analysis of Ivermectin and Nirmatrelvir Inhibitors Interacting with the SARS-CoV-2 Main Protease

Exploring therapeutic options is crucial in the ongoing COVID-19 pandemic caused by SARS-CoV-2. Nirmatrelvir, which is a potent inhibitor that targets the SARS-CoV-2 Mpro, shows promise as an antiviral treatment. Additionally, Ivermectin, which is a broad-spectrum antiparasitic drug, has demonstrated effectiveness against the virus in laboratory settings. However, its clinical implications are still debated. Using computational methods, such as molecular docking and 100 ns molecular dynamics simulations, we investigated how Nirmatrelvir and Ivermectin interacted with SARS-CoV-2 Mpro(A). Calculations using density functional theory were instrumental in elucidating the behavior of isolated molecules, primarily by analyzing the frontier molecular orbitals. Our analysis revealed distinct binding patterns: Nirmatrelvir formed strong interactions with amino acids, like MET49, MET165, HIS41, HIS163, HIS164, PHE140, CYS145, GLU166, and ASN142, showing stable binding, with a root-mean-square deviation (RMSD) of around 2.0 Å. On the other hand, Ivermectin interacted with THR237, THR239, LEU271, LEU272, and LEU287, displaying an RMSD of 1.87 Å, indicating enduring interactions. Both ligands stabilized Mpro(A), with Ivermectin showing stability and persistent interactions despite forming fewer hydrogen bonds. These findings offer detailed insights into how Nirmatrelvir and Ivermectin bind to the SARS-CoV-2 main protease, providing valuable information for potential therapeutic strategies against COVID-19.

Electrochemical synthesis of peptide aldehydes via C‒N bond cleavage of cyclic amines

Peptide aldehydes are crucial biomolecules essential to various biological systems, driving a continuous demand for efficient synthesis methods. Herein, we develop a metal-free, facile, and biocompatible strategy for direct electrochemical synthesis of unnatural peptide aldehydes. This electro-oxidative approach enabled a step- and atom-economical ring-opening via C‒N bond cleavage, allowing for homoproline-specific peptide diversification and expansion of substrate scope to include amides, esters, and cyclic amines of various sizes. The remarkable efficacy of the electro-synthetic protocol set the stage for the efficient modification and assembly of linear and macrocyclic peptides using a concise synthetic sequence with racemization-free conditions. Moreover, the combination of experiments and density functional theory (DFT) calculations indicates that different N-acyl groups play a decisive role in the reaction activity.

Eliminating the missing cone challenge through innovative approaches

Microcrystal electron diffraction (MicroED) has emerged as a powerful technique for unraveling molecular structures from microcrystals too small for X-ray diffraction. However, a significant hurdle arises with plate-like crystals that consistently orient themselves flat on the electron microscopy grid. If the normal of the plate correlates with the axes of the crystal lattice, the crystal orientations accessible for measurement are restricted because the crystal cannot be arbitrarily rotated. This limits the information that can be acquired, resulting in a missing cone of information. We recently introduced a novel crystallization strategy called suspended drop crystallization and proposed that crystals in a suspended drop could effectively address the challenge of preferred crystal orientation. Here we demonstrate the success of the suspended drop approach in eliminating the missing cone in two samples that crystallize as thin plates: bovine liver catalase and the SARS‑CoV‑2 main protease (Mpro). This innovative solution proves indispensable for crystals exhibiting systematic preferred orientations, unlocking new possibilities for structure determination by MicroED.

Targeting cellular cathepsins inhibits hepatitis E virus entry

BACKGROUND AND AIMS

HEV is estimated to be responsible for 70,000 deaths annually, yet therapy options remain limited. In the pursuit of effective antiviral therapies, targeting viral entry holds promise and has proven effective for other viruses. However, the precise mechanisms and host factors required during HEV entry remain unclear. Cellular proteases have emerged as host factors required for viral surface protein activation and productive cell entry by many viruses. Hence, we investigated the functional requirement and therapeutic potential of cellular protease during HEV infection.

APPROACH AND RESULTS

Using our established HEV cell culture model and subgenomic HEV replicons, we found that blocking lysosomal cathepsins (CTS) with small molecule inhibitors impedes HEV infection without affecting replication. Most importantly, the pan-cathepsin inhibitor K11777 suppressed HEV infections with an EC 50 of ~0.02 nM. Inhibition by K11777, devoid of notable toxicity in hepatoma cells, was also observed in HepaRG and primary human hepatocytes. Furthermore, through time-of-addition and RNAscope experiments, we confirmed that HEV entry is blocked by inhibition of cathepsins. Cathepsin L (CTSL) knockout cells were less permissive to HEV, suggesting that CTSL is critical for HEV infection. Finally, we observed cleavage of the glycosylated ORF2 protein and virus particles by recombinant CTSL.

CONCLUSIONS

In summary, our study highlights the pivotal role of lysosomal cathepsins, especially CTSL, in the HEV entry process. The profound anti-HEV efficacy of the pan-cathepsin inhibitor K11777, especially with its notable safety profile in primary cells, further underscores its potential as a therapeutic candidate.

Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds

To date, the COVID-19 pandemic has still been infectious around the world, continuously causing social and economic damage on a global scale. One of the most important therapeutic targets for the treatment of COVID-19 is the main protease (Mpro) of SARS-CoV-2. In this study, we combined machine-learning (ML) model with atomistic simulations to computationally search for highly promising SARS-CoV-2 Mpro inhibitors from the representative natural compounds of the National Cancer Institute (NCI) Database. First, the trained ML model was used to scan the library quickly and reliably for possible Mpro inhibitors. The ML output was then confirmed using atomistic simulations integrating molecular docking and molecular dynamic simulations with the linear interaction energy scheme. The results turned out to show that there was evidently good agreement between ML and atomistic simulations. Ten substances were proposed to be able to inhibit SARS-CoV-2 Mpro. Seven of them have high-nanomolar affinity and are very potential inhibitors. The strategy has been proven to be reliable and appropriate for fast prediction of SARS-CoV-2 Mpro inhibitors, benefiting for new emerging SARS-CoV-2 variants in the future accordingly.

Exploiting high-energy hydration sites for the discovery of potent peptide aldehyde inhibitors of the SARS-CoV-2 main protease with cellular antiviral activity

Small-molecule antivirals that prevent the replication of the SARS-CoV-2 virus by blocking the enzymatic activity of its main protease (Mpro) are and will be a tenet of pandemic preparedness. However, the peptidic nature of such compounds often precludes the design of compounds within favorable physical property ranges, limiting cellular activity. Here we describe the discovery of peptide aldehyde Mpro inhibitors with potent enzymatic and cellular antiviral activity. This structure-activity relationship (SAR) exploration was guided by the use of calculated hydration site thermodynamic maps (WaterMap) to drive potency via displacement of waters from high-energy sites. Thousands of diverse compounds were designed to target these high-energy hydration sites and then prioritized for synthesis by physics- and structure-based Free-Energy Perturbation (FEP+) simulations, which accurately predicted biochemical potencies. This approach ultimately led to the rapid discovery of lead compounds with unique SAR that exhibited potent enzymatic and cellular activity with excellent pan-coronavirus coverage.

An orally bioavailable SARS-CoV-2 main protease inhibitor exhibits improved affinity and reduced sensitivity to mutations

Inhibitors of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro) such as nirmatrelvir (NTV) and ensitrelvir (ETV) have proven effective in reducing the severity of COVID-19, but the presence of resistance-conferring mutations in sequenced viral genomes raises concerns about future drug resistance. Second-generation oral drugs that retain function against these mutants are thus urgently needed. We hypothesized that the covalent hepatitis C virus protease inhibitor boceprevir (BPV) could serve as the basis for orally bioavailable drugs that inhibit SARS-CoV-2 Mpro more efficiently than existing drugs. Performing structure-guided modifications of BPV, we developed a picomolar-affinity inhibitor, ML2006a4, with antiviral activity, oral pharmacokinetics, and therapeutic efficacy similar or superior to those of NTV. A crucial feature of ML2006a4 is a derivatization of the ketoamide reactive group that improves cell permeability and oral bioavailability. Last, ML2006a4 was found to be less sensitive to several mutations that cause resistance to NTV or ETV and occur in the natural SARS-CoV-2 population. Thus, anticipatory design can preemptively address potential resistance mechanisms to expand future treatment options against coronavirus variants.

Discovery of pyrimidoindol and benzylpyrrolyl inhibitors targeting SARS-CoV-2 main protease (Mpro) through pharmacophore modelling, covalent docking, and biological evaluation

The main protease (Mpro) enzyme has an imperative function in disease progression and the life cycle of the SARS-CoV-2 virus. Although the orally active drug nirmatrelvir (co-administered with ritonavir as paxlovid) has been approved for emergency use as the frontline antiviral agent, there are a number of limitations that necessitate the discovery of new drug scaffolds, such as poor pharmacokinetics and susceptibility to proteolytic degradation due to its peptidomimetic nature. This study utilized a novel virtual screening workflow that combines pharmacophore modelling, multiple-receptor covalent docking, and biological evaluation in order to find new Mpro inhibitors. After filtering and analysing ∼66,000 ligands from three different electrophilic libraries, 29 compounds were shortlisted for experimental testing, and two of them exhibited ≥20% inhibition at 100 μM. Our top candidate, GF04, is a benzylpyrrolyl compound that exhibited the highest inhibition activity of 38.3%, with a relatively small size (<350 Da) and leadlike character. Interestingly, our approach also identified another hit, DR07, a pyrimidoindol with a non-peptide character, and a molecular weight of 438.9 Da, reporting an inhibition of 26.3%. The established approach detailed in this study, in conjunction with the discovered inhibitors, has the capacity to yield novel perspectives for devising covalent inhibitors targeting the COVID-19 Mpro enzyme and other comparable targets.

Eliminating the Missing Cone Challenge through Innovative Approaches

Microcrystal electron diffraction (MicroED) has emerged as a powerful technique for unraveling molecular structures from microcrystals too small for X-ray diffraction. However, a significant hurdle arises with plate-like crystals that consistently orient themselves flat on the electron microscopy grid. If, as is typically the case, the normal of the plate correlates with the axes of the crystal lattice, the crystal orientations accessible for measurement are restricted because the grid cannot be arbitrarily rotated. This limits the information that can be acquired, resulting in a missing cone of information. We recently introduced a novel crystallization strategy called suspended drop crystallization and proposed that this method could effectively address the challenge of preferred crystal orientation. Here we demonstrate the success of the suspended drop crystallization approach in eliminating the missing cone in two samples that crystallize as thin plates: bovine liver catalase and the COVID-19 main protease (Mpro). This innovative solution proves indispensable for crystals exhibiting preferred orientations, unlocking new possibilities for structure determination by MicroED.

Antiviral Activity of Natural Herbs and their Isolated BioactiveCompounds: A Review

Viruses are the cause of many human pathogenesis-related conditions. A serious hazard to public health has been created because of the increase in worldwide travel, fast urbanization, and infectious epidemics. At the same time, no preventative vaccines or antiviral treatments are currently available. Resources for developing new antiviral medications can be found in enhanced natural products and herbal medicines. These natural substances have aided the research on developing preventive vaccines and antiviral treatments. Based primarily on in vitro and in vivo searches, this review aims to explore the antiviral properties of plant extracts and some isolated plant natural products. Only a few antiviral medications have been given clinical approval, while numerous viruses continue to elude adequate immunization. Therefore, developing novel antiviral medicines is crucial, and natural substances make excellent sources for these new drugs. This review highlights various natural herbal drugs possessing antiviral properties.

Unsupervised deep learning for molecular dynamics simulations: a novel analysis of protein-ligand interactions in SARS-CoV-2 Mpro

Molecular dynamics (MD) simulations, which are central to drug discovery, offer detailed insights into protein-ligand interactions. However, analyzing large MD datasets remains a challenge. Current machine-learning solutions are predominantly supervised and have data labelling and standardisation issues. In this study, we adopted an unsupervised deep-learning framework, previously benchmarked for rigid proteins, to study the more flexible SARS-CoV-2 main protease (Mpro). We ran MD simulations of Mpro with various ligands and refined the data by focusing on binding-site residues and time frames in stable protein conformations. The optimal descriptor chosen was the distance between the residues and the center of the binding pocket. Using this approach, a local dynamic ensemble was generated and fed into our neural network to compute Wasserstein distances across system pairs, revealing ligand-induced conformational differences in Mpro. Dimensionality reduction yielded an embedding map that correlated ligand-induced dynamics and binding affinity. Notably, the high-affinity compounds showed pronounced effects on the protein's conformations. We also identified the key residues that contributed to these differences. Our findings emphasize the potential of combining unsupervised deep learning with MD simulations to extract valuable information and accelerate drug discovery.

Analyzing 3D structures of the SARS-CoV-2 main protease reveals structural features of ligand binding for COVID-19 drug discovery

The severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) main protease has an essential role in viral replication and has become a major target for coronavirus 2019 (COVID-19) drug development. Various inhibitors have been discovered or designed to bind to the main protease. The availability of more than 550 3D structures of the main protease provides a wealth of structural details on the main protease in both ligand-free and ligand-bound states. Therefore, we examined these structures to ascertain the structural features for the role of the main protease in the cleavage of polyproteins, the alternative conformations during main protease maturation, and ligand interactions in the main protease. The structural features unearthed could promote the development of COVID-19 drugs targeting the SARS-CoV-2 main protease.

Substitutions in SARS-CoV-2 Mpro Selected by Protease Inhibitor Boceprevir Confer Resistance to Nirmatrelvir

Nirmatrelvir, which targets the SARS-CoV-2 main protease (Mpro), is the first-in-line drug for prevention and treatment of severe COVID-19, and additional Mpro inhibitors are in development. However, the risk of resistance development threatens the future efficacy of such direct-acting antivirals. To gain knowledge on viral correlates of resistance to Mpro inhibitors, we selected resistant SARS-CoV-2 under treatment with the nirmatrelvir-related protease inhibitor boceprevir. SARS-CoV-2 selected during five escape experiments in VeroE6 cells showed cross-resistance to nirmatrelvir with up to 7.3-fold increased half-maximal effective concentration compared to original SARS-CoV-2, determined in concentration-response experiments. Sequence analysis revealed that escape viruses harbored Mpro substitutions L50F and A173V. For reverse genetic studies, these substitutions were introduced into a cell-culture-infectious SARS-CoV-2 clone. Infectivity titration and analysis of genetic stability of cell-culture-derived engineered SARS-CoV-2 mutants showed that L50F rescued the fitness cost conferred by A173V. In the concentration-response experiments, A173V was the main driver of resistance to boceprevir and nirmatrelvir. Structural analysis of Mpro suggested that A173V can cause resistance by making boceprevir and nirmatrelvir binding less favorable. This study contributes to a comprehensive overview of the resistance profile of the first-in-line COVID-19 treatment nirmatrelvir and can thus inform population monitoring and contribute to pandemic preparedness.

Phytoconstituents as potential therapeutic agents against COVID-19: a computational study on inhibition of SARS-CoV-2 main protease

The Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) has become a global health crisis, and the urgent need for effective treatments is evident. One potential target for COVID-19 therapeutics is the main protease (Mpro) of SARS‑CoV‑2, an essential enzyme for viral replication. Natural compounds have been explored as a source of potential inhibitors for Mpro due to their safety and availability. In this study, we employed a computational approach to screen a library of phytoconstituents and identified potential Mpro inhibitors based on their binding affinities and molecular interactions. The top-ranking compounds were further validated through molecular dynamics simulations (MDS) and free energy calculations. As a result of the above procedures, we identified two phytoconstituents, Khelmarin B and Neogitogenin, with appreciable binding affinity and specificity towards the Mpro binding pocket. Our results suggest that Khelmarin B and Neogitogenin could potentially serve as Mpro inhibitors and have the potential to be developed as COVID-19 therapeutics. Further experimental studies are required to confirm the efficacy and safety of these compounds.Communicated by Ramaswamy H. Sarma.

Validation of X-ray Crystal Structure Ensemble Representations of SARS-CoV-2 Main Protease by Solution NMR Residual Dipolar Couplings

Considerable debate has focused on whether sampling of molecular dynamics trajectories restrained by crystallographic data can be used to develop realistic ensemble models for proteins in their natural, solution state. For the SARS-CoV-2 main protease, Mpro, we evaluated agreement between solution residual dipolar couplings (RDCs) and various recently reported multi-conformer and dynamic-ensemble crystallographic models. Although Phenix-derived ensemble models showed only small improvements in crystallographic Rfree, substantially improved RDC agreement over fits to a conventionally refined 1.2-Å X-ray structure was observed, in particular for residues with above average disorder in the ensemble. For a set of six lower resolution (1.55-2.19 Å) Mpro X-ray ensembles, obtained at temperatures ranging from 100 to 310 K, no significant improvement over conventional two-conformer representations was found. At the residue level, large differences in motions were observed among these ensembles, suggesting high uncertainties in the X-ray derived dynamics. Indeed, combining the six ensembles from the temperature series with the two 1.2-Å X-ray ensembles into a single 381-member "super ensemble" averaged these uncertainties and substantially improved agreement with RDCs. However, all ensembles showed excursions that were too large for the most dynamic fraction of residues. Our results suggest that further improvements to X-ray ensemble refinement are feasible, and that RDCs provide a sensitive benchmark in such endeavors. Remarkably, a weighted ensemble of 350 PDB Mpro X-ray structures provided slightly better cross-validated agreement with RDCs than any individual ensemble refinement, implying that differences in lattice confinement also limit the fit of RDCs to X-ray coordinates.

Structure-based discovery of thiosemicarbazones as SARS-CoV-2 main protease inhibitors

Aim: Discovery of novel SARS-CoV-2 main protease (Mpro) inhibitors using a structure-based drug discovery strategy. Materials & methods: Virtual screening employing covalent and noncovalent docking was performed to discover Mpro inhibitors, which were subsequently evaluated in biochemical and cellular assays. Results: 91 virtual hits were selected for biochemical assays, and four were confirmed as reversible inhibitors of SARS CoV-2 Mpro with IC50 values of 0.4-3 μM. They were also shown to inhibit SARS-CoV-1 Mpro and human cathepsin L. Molecular dynamics simulations indicated the stability of the Mpro inhibitor complexes and the interaction of ligands at the subsites. Conclusion: This approach led to the discovery of novel thiosemicarbazones as potent SARS-CoV-2 Mpro inhibitors.

In-silico study: docking simulation and molecular dynamics of peptidomimetic fullerene-based derivatives against SARS-CoV-2 Mpro

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, has become a global pandemic resulting in significant morbidity and mortality. This study presents 12 new peptidomimetic fullerene-based derivatives in three groups that are investigated theoretically as SARS-CoV-2 M^pro inhibitors to increase the chance of treating COVID-19. Studied compounds are designed and optimized at B88-LYP/DZVP method. Molecular descriptors results show the stability and reactivity of the compounds with M^pro, especially in the 3rd group (Ser compounds). However, Lipinski's Rule of Five values indicates that the compounds are not suitable as oral drugs. Furthermore, molecular docking simulations are carried out to investigate the binding affinity and interaction modes of the top five compounds (compounds 1, 9, 11, 2, and 10) with the M^pro protein, which have the lowest binding energy. Molecular dynamics simulations are also performed to evaluate the stability of the protein-ligand complexes with compounds 1 and 9 and compare them with natural substrate interaction. The analysis of RMSD, H-bonds, Rg, and SASA indicates that both compounds 1 (Gly-α acid) and 9 (Ser-α acid) have good stability and strong binding affinity with the M^pro protein. However, compound 9 shows slightly better stability and binding affinity compared to compound 1.

Exploring potential SARS-CoV-2 Mpro non-covalent inhibitors through docking, pharmacophore profile matching, molecular dynamic simulation, and MM-GBSA

CONTEXT

In the replication of SARS-CoV-2, the main protease (Mpro/3CLpro) is significant. It is conserved in a number of novel coronavirus variations, and no known human proteases share its cleavage sites. Therefore, 3CLpro is an ideal target. In the report, we screened five potential inhibitors (1543, 2308, 3717, 5606, and 9000) of SARS-CoV-2 Mpro through a workflow. The calculation of MM-GBSA binding free energy showed that three of the five potential inhibitors (1543, 2308, 5606) had similar inhibitor effects to X77 against Mpro of SARS-CoV-2. In conclusion, the manuscript lays the groundwork for the design of Mpro inhibitors.

METHODS

In the virtual screening phase, we used structure-based virtual screening (Qvina2.1) and ligand-based virtual screening (AncPhore). In the molecular dynamic simulation part, we used the Amber14SB + GAFF force field to perform molecular dynamic simulation of the complex for 100 ns (Gromacs2021.5) and performed MM-GBSA binding free energy calculation according to the simulation trajectory.

Structural and functional characterization of NEMO cleavage by SARS-CoV-2 3CLpro

In addition to its essential role in viral polyprotein processing, the SARS-CoV-2 3C-like protease (3CLpro) can cleave human immune signaling proteins, like NF-κB Essential Modulator (NEMO) and deregulate the host immune response. Here, in vitro assays show that SARS-CoV-2 3CLpro cleaves NEMO with fine-tuned efficiency. Analysis of the 2.50 Å resolution crystal structure of 3CLpro C145S bound to NEMO226-234 reveals subsites that tolerate a range of viral and host substrates through main chain hydrogen bonds while also enforcing specificity using side chain hydrogen bonds and hydrophobic contacts. Machine learning- and physics-based computational methods predict that variation in key binding residues of 3CLpro-NEMO helps explain the high fitness of SARS-CoV-2 in humans. We posit that cleavage of NEMO is an important piece of information to be accounted for, in the pathology of COVID-19.

The temperature-dependent conformational ensemble of SARS-CoV-2 main protease (Mpro)

The COVID-19 pandemic, instigated by the SARS-CoV-2 coronavirus, continues to plague the globe. The SARS-CoV-2 main protease, or Mpro, is a promising target for the development of novel antiviral therapeutics. Previous X-ray crystal structures of Mpro were obtained at cryogenic tem-per-ature or room tem-per-ature only. Here we report a series of high-resolution crystal structures of unliganded Mpro across multiple tem-per-atures from cryogenic to physiological, and another at high humidity. We inter-rogate these data sets with parsimonious multiconformer models, multi-copy ensemble models, and isomorphous difference density maps. Our analysis reveals a perturbation-dependent conformational landscape for Mpro, including a mobile zinc ion inter-leaved between the catalytic dyad, mercurial conformational heterogeneity at various sites including a key substrate-binding loop, and a far-reaching intra-molecular network bridging the active site and dimer inter-face. Our results may inspire new strategies for antiviral drug development to aid preparation for future coronavirus pandemics.