Pharmacoinformatics and molecular dynamics simulation studies reveal potential covalent and FDA-approved inhibitors of SARS-CoV-2 main protease 3CLpro

Network pharmacology, molecular docking, and dynamics analyses to predict the antiviral activity of ginger constituents against coronavirus infection

COVID-19 is a global pandemic that caused a dramatic loss of human life worldwide, leading to accelerated research for antiviral drug discovery. Herbal medicine is one of the most commonly used alternative medicine for the prevention and treatment of many conditions including respiratory system diseases. In this study, a computational pipeline was employed, including network pharmacology, molecular docking simulations, and molecular dynamics simulations, to analyze the common phytochemicals of ginger rhizomes and identify candidate constituents as viral inhibitors. Furthermore, experimental assays were performed to analyze the volatile and non-volatile compounds of ginger and to assess the antiviral activity of ginger oil and hydroalcoholic extract. Network pharmacology analysis showed that ginger compounds target human genes that are involved in related cellular processes to the viral infection. Docking analysis highlighted five pungent compounds and zingiberenol as potential inhibitors for the main protease (Mpro), spike receptor-binding domain (RBD), and human angiotensin-converting enzyme 2 (ACE2). Then, (6)-gingerdiacetate was selected for molecular dynamics (MD) simulations as it exhibited the best binding interactions and free energies over the three target proteins. Trajectories analysis of the three complexes showed that RBD and ACE2 complexes with the ligand preserved similar patterns of root mean square deviation (RMSD) and radius of gyration (Rg) values to their respective native structures. Finally, experimental validation of the ginger hydroalcoholic extract confirmed the existence of (6)-gingerdiacetate and revealed the strong antiviral activity of the hydroalcoholic extract with IC50 of 2.727 μ g / ml . Our study provides insights into the potential antiviral activity of (6)-gingerdiacetate that may enhance the host immune response and block RBD binding to ACE2, thereby, inhibiting SARS-CoV-2 infection.

Critical assessment of popular biomolecular force fields for molecular dynamics simulations of folding and enzymatic activity of main protease of coronavirus SARS-CoV-2

The main cysteine protease (Mpro) of coronavirus SARS-CoV-2 has become a promising target for computational development in anti-COVID-19 treatments. Here, we benchmarked the performance of six biomolecular molecular dynamics (MD) force fields (OPLS-AA, CHARMM27, CHARMM36, AMBER03, AMBER14SB and GROMOS G54A7) and three water models (TIP3P, TIP4P and SPC) for reproducing the native fold and the enzymatic activity of Mpro as monomeric and dimeric units. The MD sampling up to 1 μs suggested that the proper choice of the force fields and water models plays an essential role in reproducing the tertiary structure and the inter-residue distance between the catalytic dyad His41-Cys145. We found that while most benchmarked all-atom force fields reproduce well the native fold of Mpro, the CHARMM27/TIP3P and OPLS-AA/TIP4P setups revealed a good performance in reproducing the structure of the catalytic domain. In addition, these FF setups were also well-adopted for MD sampling of Mpro at the physiologic conditions by mimicking the presence of 100 mM NaCl and the elevated temperature of 310 K. Finally, both FFs were also performed well in reproducing the native fold of Mpro in a dimeric form. Therefore, comparing the preservation of the native fold of Mpro and the stability of its catalytic site architecture, our MD benchmarking suggests that the OPLS-AA/TIP4P and CHARMM27/TIP3P MD setups at the physiologic conditions may be well-suited for rapid in silico screening and developing broad-spectrum anti-coronaviral therapeutic agents.

Almaary K, Allah Nafidi H, Bourhia M, Kilani-Jaziri S, A. Bin Jardan Y. Integrating virtual screening, pharmacoinformatics profiling, and molecular dynamics: identification of promising inhibitors targeting 3CLpro of SARS-CoV-2

Introduction: The pursuit of effective therapeutic solutions for SARS-CoV-2 infections and COVID-19 necessitates the repurposing of existing compounds. This study focuses on the detailed examination of the central protease, 3-chymotrypsin-like protease (3CLpro), a pivotal player in virus replication. The combined approach of molecular dynamics simulations and virtual screening is employed to identify potential inhibitors targeting 3CLpro. Methods: A comprehensive virtual screening of 7120 compounds sourced from diverse databases was conducted. Four promising inhibitors, namely EN1036, F6548-4084, F6548-1613, and PUBT44123754, were identified. These compounds exhibited notable attributes, including high binding affinity (ranging from -5.003 to -5.772 Kcal/mol) and superior Induced Fit Docking scores (ranging from -671.66 to -675.26 Kcal/mol) compared to co-crystallized ligands. Results: In-depth analysis revealed that F6548-1613 stood out, demonstrating stable hydrogen bonds with amino acids His41 and Thr62. Notably, F6548-1613 recorded a binding energy of -65.72 kcal/mol in Molecular Mechanics Generalized Born Surface Area (MMGBSA) simulations. These findings were supported by Molecular Dynamics simulations, highlighting the compound's efficacy in inhibiting 3CLpro. Discussion: The identified compounds, in compliance with Lipinski's rule of five and exhibiting functional molecular interactions with 3CLpro, present promising therapeutic prospects. The integration of in silico methodologies significantly expedites drug discovery, laying the foundation for subsequent experimental validation and optimization. This approach holds the potential to develop effective therapeutics for SARS-CoV-2.

Fourteen immunomodulatory alkaloids and two prenylated phenylpropanoids with dual therapeutic approach for COVID-19: molecular docking and dynamics studies

The pandemic outbreak of COVID-19 caused by the new severe acute respiratory syndrome coronavirus (SARS-CoV-2) is a global health burden. To date, there is no highly effective antiviral therapy to eradicate the virus; as a result, researchers are racing to introduce new potential therapeutic agents. Alternatively, traditional immunity boosters and symptomatic treatment based on natural bioactive compounds are also an option. The 3-chymotrypsin-like protease (3CLpro) crystal structure, the main proteolytic enzyme of SARS-CoV-2, has been unraveled, allowing the development of effective protease inhibitors via in silico and biological studies. In COVID-19 infected patients, the loss of lung function, and mortality are reported to be linked to several inflammatory mediators and cytokines. In this context, the approach of introducing immunomodulatory agents may be considered a dual lifesaving strategy in combination with antiviral drugs. This study aims to provide immunomodulatory natural products exhibiting potential protease inhibitory activities. Selected groups of alkaloids of different classes and two prenylated phenylpropanoids from the Brazilian green propolis were in silico screened for their ability to inhibit COVID-19 3CLpro protease. Results showed that compounds exhibited binding energy scores with values ranging from -6.96 to -3.70 compared to the reference synthetic protease inhibitor O6K with a binding energy score of -7.57. O6K binding energy was found comparable with lead phytochemicals in our study, while their toxicity and drug-likeness criteria are better than that of O6K. The activities of these molecules are mainly ascribed to their ability to form hydrogen bonding with 3CLpro crucial amino acid residues of the catalytic site. In addition, the molecular dynamics simulations further showed that some of these compounds formed stable complexes as evidenced by the occupancy fraction measurements. The study suggested that the major immunomodulators 3β, 20α-diacetamido-5α-pregnane, (20S)-(benzamido)-3β-(N,N-dimethyamino)-pregnane, and baccharin are 3CLpro inhibitors. Biological screenings of these phytochemicals will be valuable to experimentally validate and consolidate the results of this study before a rigid conclusion is reached, which may pave the way for the development of efficient modulatory bioactive compounds with dual bioactions in COVID-19 intervention. Communicated by Ramaswamy H. Sarma.

Identification of terpenoids as dihydropteroate synthase and dihydrofolate reductase inhibitors through structure-based virtual screening and molecular dynamic simulations

Bacterial infections are rising, and antimicrobial resistance (AMR) in bacteria has worsened the scenario, requiring extensive research to find alternative therapeutic agents. Terpenoids play an essential role in protecting plants from herbivores and pathogens. The present study was designed to focus on in silico evaluation of terpenoids for their affinity towards two necessary enzymes, i.e. DHFR and DHPS, which are involved in forming 5, 6, 7, 8-tetrahydrofolate, a key component in bacterial DNA synthesis proteins. Additionally, to account for activity against resistant bacteria, their affinity towards the L28R mutant of DHFR was also assessed in the study. The structure-based drug design approach was used to screen the compound library of terpenes for their interaction with active sites of DHFR and DHPS. Further, compounds were screened based on their dock score, pharmacokinetic properties, and binding affinities. A total of five compounds for each target protein were screened, having dock scores better than their respective standard drug molecules. CNP0169378 (-8.4 kcal/mol) and CNP0309455 (-6.5 kcal/mol) have been identified as molecules with a higher affinity toward the targets of DHFR and DHPS, respectively. At the same time, one molecule CNP0298407 (-5.8 kcal/mol for DHPS, -7.6 kcal/mol for DHFR, -6.1 kcal/mol for the L28R variant), has affinity for both proteins (6XG5 and 6XG4). All the molecules have good pharmacokinetic properties. We further validated the docking study by binding free energy calculations using the MM/GBSA approach and molecular dynamics simulations.Communicated by Ramaswamy H. Sarma.

Integrated virtual screening and molecular dynamics simulation approaches revealed potential natural inhibitors for DNMT1 as therapeutic solution for triple negative breast cancer

Triple negative breast cancers (TNBC) are clinically heterogeneous but mostly aggressive malignancies devoid of expression of the estrogen, progesterone, and HER2 (ERBB2 or NEU) receptors. It accounts for 15-20% of all cases. Altered epigenetic regulation including DNA hypermethylation by DNA methyltransferase 1 (DNMT1) has been implicated as one of the causes of TNBC tumorigenesis. The antitumor effect of DNMT1 has also been explored in TNBC that currently lacks targeted therapies. However, the actual treatment for TNBC is yet to be discovered. This study is attributed to the identification of novel drug targets against TNBC. A comprehensive docking and simulation analysis was performed to optimize promising new compounds by estimating their binding affinity to the target protein. Molecular dynamics simulation of 500 ns well complemented the binding affinity of the compound and revealed strong stability of predicted compounds at the docked site. Calculation of binding free energies using MMPBSA and MMGBSA validated the strong binding affinity between compound and binding pockets of DNMT1. In a nutshell, our study uncovered that Beta-Mangostin, Gancaonin Z, 5-hydroxysophoranone, Sophoraflavanone L, and Dorsmanin H showed maximum binding affinity with the active sites of DNMT1. Furthermore, all of these compounds depict maximum drug-like properties. Therefore, the proposed compounds can be a potential candidate for patients with TNBC, but, experimental validation is needed to ensure their safety.Communicated by Ramaswamy H. Sarma.

Identification of novel inhibitors against VP40 protein of Marburg virus by integrating molecular modeling and dynamics approaches

Marburg virus (MV) is a highly etiological agent of haemorrhagic fever in humans and has spread across the world. Its outbreaks caused a 23-90% human death rate. However, there are currently no authorized preventive or curative measures yet. VP40 is the MV matrix protein, which builds protein shell underneath the viral envelope and confers hallmark filamentous. VP40 alone is able to induce assembly and budding of filamentous virus-like particles (VLPs), which resemble authentic virions. As a result, this research is credited with clarifying the function of VP40 and leading to the discovery of new therapeutic targets effective in combating MV disease (MVD). Virtual screening, molecular docking and molecular dynamics (MD) simulation were used to find the putative active chemicals based on a 3D pharmacophore model of the protein's active site cavity. Initially, andrographidine-C, a potent inhibitor was selected for the development of the pharmacophore model. Later, a library of 30,000 compounds along with the andrographidine-C was docked against VP40 protein. Three best hits including avanafil, diuvaretin and macrourone were subjected to further MD simulation analysis, as these compounds had better binding affinities as compared to andrographidine-C. Furthermore, throughout the 100 ns simulations, the back bone of VP40 protein in presence of avanafil, diuvaretin and macrourone remained stable which was further validated by MM-PBSA analysis. Additionally, all of these compounds depict maximum drug-like properties. The predicted drugs based on the ligand, avanafil, diuvaretin and macrourone could be exploited and developed as an alternative or complementary therapy for the treatment of MVD.Communicated by Ramaswamy H. Sarma.

Identifying potent inhibitory phytocompounds from Lagerstroemia speciosa against SARS-Coronavirus-2: structure-based virtual screening

The ongoing spillover of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) calls for expedited countermeasure through developing therapeutics from natural reservoirs and/or the use of less time-consuming drug discovery methodologies. This study aims to apply these approaches to identify potential blockers of the virus from the longstanding medicinal herb, Lagerstroemia speciosa, through comprehensive computational-based screening. Nineteen out of 22 L. speciosa phytochemicals were selected on the basis of their pharmacokinetic properties. SARS-CoV-2 Main protease (Mpro), RNA-directed RNA polymerase (RdRp), Envelope viroporin protein (Evp) and receptor-binding domain of Spike glycoprotein (S-RBD), as well as the human receptor Angiotensin-converting enzyme-2 (hACE2) were chosen as targets. The screening was performed by molecular docking, followed by 100-ns molecular dynamic simulations and free energy calculations. 24-Methylene cycloartanol acetate (24MCA) was found as the best inhibitor for both Evp and RdRp, and sitosterol acetate (SA) as the best hit for Mpro, S-RBD and hACE2. Dynamic simulations, binding mode analyses, free energy terms and share of key amino acids in protein-drug interactions confirmed the stable binding of these phytocompounds to the hotspot sites on the target proteins. With their possible multi-targeting capability, the introduced phytoligands might offer promising lead compounds for persistent fight with the rapidly evolving coronavirus. Therefore, experimental verification of their safety and efficacy is recommended.

A comprehensive review on recent nanosystems for enhancing antifungal activity of fenticonazole nitrate from different routes of administration

This review aims to comprehensively highlight the recent nanosystems enclosing Fenticonazole nitrate (FTN) and to compare between them regarding preparation techniques, studied factors and responses. Moreover, the optimum formulae were compared in terms of in vitro, ex vivo and in vivo studies in order to detect the best formula. FTN is a potent antifungal imidazole compound that had been used for treatment of many dangerous fungal infections affecting eye, skin or vagina. FTN had been incorporated in various innovative nanosystems in the recent years in order to achieve significant recovery such as olaminosomes, novasomes, cerosomes, terpesomes and trans-novasomes. These nanosystems were formulated by various techniques (ethanol injection or thin film hydration) utilizing different statistical designs (Box-Behnken, central composite, full factorial and D-optimal). Different factors were studied in each nanosystem regarding its composition as surfactant concentrations, surfactant type, amount of oleic acid, cholesterol, oleylamine, ceramide, sodium deoxycholate, terpene concentration and ethanol concentration. Numerous responses were studied such as percent entrapment efficiency (EE%), particle size (PS), poly-dispersity index (PDI), zeta potential (ZP), and in vitro drug release. Selection of the optimum formula was based on numerical optimization accomplished by Design-Expert® software taking in consideration the largest EE %, ZP (as absolute value) and in vitro drug release and lowest PS and PDI. In vitro comparisons were done employing different techniques such as Transmission electron microscopy, pH determination, effect of gamma sterilization, elasticity evaluation and docking study. In addition to, ex vivo permeation, in vivo irritancy test, histopathological, antifungal activity and Kinetic study.

A Multifaceted Computational Approach to Understanding the MERS-CoV Main Protease and Brown Algae Compounds' Interaction

Middle East Respiratory Syndrome (MERS) is a viral respiratory disease caused b a special type of coronavirus called MERS-CoV. In the search for effective substances against the MERS-CoV main protease, we looked into compounds from brown algae, known for their medicinal benefits. From a set of 1212 such compounds, our computer-based screening highlighted four-CMNPD27819, CMNPD1843, CMNPD4184, and CMNPD3156. These showed good potential in how they might attach to the MERS-CoV protease, comparable to a known inhibitor. We confirmed these results with multiple computer tests. Studies on the dynamics and steadiness of these compounds with the MERS-CoV protease were performed using molecular dynamics (MD) simulations. Metrics like RMSD and RMSF showed their stability. We also studied how these compounds and the protease interact in detail. An analysis technique, PCA, showed changes in atomic positions over time. Overall, our computer studies suggest brown algae compounds could be valuable in fighting MERS. However, experimental validation is needed to prove their real-world effectiveness.

Structure-based virtual screening, ADMET analysis, and molecular dynamics simulation of Moroccan natural compounds as candidates for the SARS-CoV-2 inhibitors

The lack of treatments and vaccines effective against SARS-CoV-2 has forced us to explore natural compounds that could potentially inhibit this virus. Additionally, Morocco is renowned for its rich plant diversity and traditional medicinal uses, which inspires us to leverage our cultural heritage and the abundance of natural resources in our country for therapeutic purposes. In this study, an extensive investigation was conducted to gather a collection of phytoconstituents extracted from Moroccan plants, aiming to evaluate their ability to inhibit the proliferation of the SARS-CoV-2 virus. Molecular docking of the studied compounds was performed at the active sites of the main protease (6lu7) and spike (6m0j) proteins to assess their binding affinity to these target proteins. Compounds exhibiting high affinity to the proteins underwent further evaluation based on Lipinski's rule and ADME-Tox analysis to gain insights into their oral bioavailability and safety. The results revealed that the two compounds demonstrated strong binding affinity to the target proteins, making them potential candidates for oral antiviral drugs against SARS-CoV-2. The molecular dynamics results from this computational analysis supported the overall stability of the resulting complex.

Computational screening of natural products to identify potential inhibitors for human neuropilin-1 (NRP1) receptor to abrogate the binding of SARS-CoV-2 and host cell

Recently, a new variant B.1.1.529 or Omicron variant and its sub-variants (BA2.75, BA.5) of SARS-CoV-2 (Severe acute respiratory virus 2) have been reported with a larger number of mutations in the spike protein and particularly in the RBD (receptor-binding domain). The omicron (B.1.1.529) variant has aggravated the pandemic situation further and needs more analysis for therapeutic development. Keeping in view the urgency of the required data, the current study used molecular modeling and simulation-based methods to target the NRP1 (Neuropilin 1) protein to halt the entry into the host cell. Employing a molecular screening approach to screen the North-East African natural compounds database (NEANCDB) revealed Subereamine B with a docking score of -8.44 kcal/mol, Zinolol with the docking score of -8.05 while Subereamine A with a docking score of -7.88 kcal/mol as the best hits against NRP1. Molecular simulation-based further validation revealed stable dynamics, good structural packing, and dynamic residues flexibility index. Moreover, hydrogen bonding fraction analysis demonstrated the interactions remained sustained during the simulation. Furthermore, the total binding free energy for Subereamine B was -44.24 ±0.91 kcal/mol, for Zinolol -34.32 ±0.40 kcal/mol while for Subereamine A the TBE was calculated to be -41.78 ± 0.36 kcal/mol respectively. This shows that the two arginine-based alkaloids, i.e. Subereamine B and Subereamine A could inhibit the NRP1 more strongly than Zinolol. In conclusion, this study provides a basis for the development of novel drugs against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Structure-based virtual screening of natural compounds as inhibitors of HCV using molecular docking and molecular dynamics simulation studies

The hepatitis C virus (HCV), which causes hepatitis C, is a viral infection that damages the liver and causes inflammation in the liver. New potentially effective antiviral drugs are required for its treatment owing to various issues associated with the existing medications, including moderate to severe adverse effects, higher costs, and the emergence of drug-resistant strains. The objective of the current study was to utilize computational techniques to assess the anti-HCV efficacy of certain phytochemicals against tetraspanin (CD81) and claudin 1 (CLDN1) entry proteins. A 200-nanosecond molecular dynamics (MD) simulation was employed to examine the stability of the lead-protein complexes. Free binding energy and molecular docking calculations were conducted utilizing MM/GBSA method, and the selectivity of hit compounds for CD81 and CLDN1 was determined. Five significant CD81 and CLDN1 inhibitors were identified: Petasiphenone, Silibinin, Tanshinone IIA, Taxifolin, and Topaquinone. The MM/GBSA analysis of the compounds revealed high free binding energies. All the identified compounds were stable within the CD81 and CLDN1 binding pockets. This study indicated the promising inhibitory potential of the identified compounds against CD81 and CLDN1 receptors and might develop into potential viral entry inhibitors. However, to validate the chemotherapeutic capabilities of the discovered leads extensive preclinical research is required.Communicated by Ramaswamy H. Sarma.

Computational prediction and analysis of targeting 17-beta-hydroxysteroid dehydrogenase (17-beta-HSD1) with natural products for colorectal cancer treatment

Colorectal cancer (CRC) is a type of cancer that occurs in the colon or rectum and kills millions of people each year. Steroid hormones are interconverted between their potent, high-affinity forms by using 17-beta hydroxysteroid dehydrogenase for their respective receptors in these tissues, with a high probability of random genetic errors. Currently, 17-beta-HSD1 studies have revealed the role of steroid metabolism in the development and proliferation of colorectal cancer. However, there is little information on how to target this enzyme with either modern medicine or natural products. In this study, we looked at 17-beta-HSD1 as a target for treating CRC development and proliferation using selected plant metabolites from previous studies. Plants are used to produce medicinal and novel bioactive compounds that are used to treat different infection. They primarily demonstrated anti-cancer effects through the regulation of cancer-related proteins, epigenetic factors and reactive oxygenase species. The study utilized Avogadro, ADMET lab 2.0, SWISS-MODEL, AutoDock, and Gromacs. Five lead molecules were chosen from a pool of plant metabolites based on their affinity for the 17-beta-HSD1 enzyme. Furthermore, two bind with high affinity are resveratrol (DG 11.29 kcal/mol) and folate (DG 12.23 kcal/mol) with low Ki values, while the rest binds with moderate affinity. Molecular dynamic simulation results also revealed that the folate-17-beta-HSD complex and reserverol- 17-beta-HSD1 complex maintained a stable conformation until the end of 100 ns. As a result, reserverol and folate could be used as lead molecules to target 17-beta-HSD1 and provide a promising starting point for further in vivo research.Communicated by Ramaswamy H. Sarma.

Theoretical insights into the binding interaction of Nirmatrelvir with SARS-CoV-2 Mpro mutants (C145A and C145S): MD simulations and binding free-energy calculation to understand drug resistance

Mpro, the main protease and a crucial enzyme in SARS-CoV-2 is the most fascinating molecular target for pharmacological treatment and is also liable for viral protein maturation. For antiviral therapy, no drugs have been approved clinically to date. Targeting the Mpro with a compound having inhibitory properties against it can hinder viral replication. The therapeutic potential of the antiviral compound Nirmatrelvir (NMV) against SARS-CoV-2 Mpro was investigated using a systematic approach of molecular docking, MD simulations, and binding free energy calculation based on the MM-GBSA method. NMV, a covalent inhibitor with a recently revealed chemical structure, is a promising oral antiviral clinical candidate with significant in vitro anti-SARS-CoV-2 action in third-phase clinical trials. To explore the therapeutic ability and possible drug resistance, the Mpro system was studied for WT and two of its primary mutants (C145A & C145S). The protein-ligand (Mpro/NMV) complexes were further examined through long MD simulations to check the possible drug resistance in the mutants. To understand the binding affinity, the MM-GBSA method was applied to the Mpro/NMV complexes. Moreover, PCA analysis confirms the detachment of the linker region from the major domains in C145S and C145A mutants allowing for conformational alterations in the active-site region. Based on the predicted biological activities and binding affinities of NMV to WT and mutant (C145A & C145S) Mpro, it can be stipulated that NMV may have conventional potency to act as an anti-viral agent against WT Mpro, while the catalytic-dyad mutations may show substantial mutation-induced drug resistance.Communicated by Ramaswamy H. Sarma.

Antimicrobial activities of metabolites isolated from endophytic Aspergillus flavus of Sarcophyton ehrenbergi supported by in-silico study and NMR spectroscopy

BACKGROUND

Endophytic Aspergillus species produce countless valuable bioactive secondary metabolites. In the current study, Aspergillus flavus an endophyte from the soft coral Sarcophyton ehrenbergi was chemically explored and the extracted phytoconstituents were subsequently evaluated for antimicrobial activity. This is accomplished by employing nuclear magnetic resonance (NMR) spectroscopy and computational techniques. Additionally, An in vitro anticancer analysis of A. flavus total extract against breast cancer cells (MCF-7) was investigated.

RESULT

Six compounds were separated from the crude alcohol extract of the endophytic Aspergillus flavus out of which anhydro-mevalonolactone was reported for the first time. The anti-fungal and anti-Helicobacter pylori properties of two distinct compounds (Scopularides A and B) were assessed. Additionally, computational research was done to identify the binding mechanisms for all compounds. Both the compounds were found to be active against H. pylori with minimum inhibitory concentration (MIC) values ranging from 7.81 to 15.63 µg/ mL as compared with clarithromycin 1.95 µg/ mL. Scopularides A was potent against both Candida albicans and Aspergillus niger with MIC values ranging from 3.9 to 31.25 µg/ mL, while scopularides B only inhibits Candida albicans with MIC value of 15.63 µg/ mL and weak inhibitory activity against A. niger (MIC = 125 µg/ mL). Furthermore, cytotoxic activity showed a significant effect (IC50: 30.46 mg/mL) against MCF-7 cells.

CONCLUSION

Our findings report that cytotoxic activity and molecular docking support the antimicrobial activity of Aspergillus flavus, which could be a promising alternative source as a potential antimicrobial agent.

Computational studies indicated the effectiveness of human metabolites against SARS-Cov-2 main protease

To fight against the devastating coronavirus disease 2019 (COVID-19), identifying robust anti-SARS-CoV-2 therapeutics from all possible directions is necessary. To contribute to this effort, we selected a human metabolites database containing waters and lipid-soluble metabolites to screen against the 3-chymotrypsin-like proteases (3CLpro) protein of SARS-CoV-2. The top 8 hits from virtual screening displayed a docking score varying between ~ - 11 and ~ - 14 kcal/mol. Molecular dynamics simulations complement the virtual screening study in conjunction with the molecular mechanics generalized Born surface area (MM/GBSA) scheme. Our analyses revealed that (HMDB0132640) has the best glide docking score, - 14.06 kcal/mol, and MM-GBSA binding free energy, - 18.08 kcal/mol. The other three lead molecules are also selected along with the top molecule through a critical inspection of their pharmacokinetic properties. HMDB0132640 displayed a better binding affinity than the other three compounds (HMDB0127868, HMDB0134119, and HMDB0125821) due to increased favorable contributions from the intermolecular electrostatic and van der Waals interactions. Further, we have investigated the ligand-induced structural dynamics of the main protease. Overall, we have identified new compounds that can serve as potential leads for developing novel antiviral drugs against SARS-CoV-2 and elucidated molecular mechanisms of their binding to the main protease. Identification of probable hits from human metabolites against SARS-CoV-2 using integrated computational approaches-Missed against MS.

Integrated molecular modeling and dynamics approaches revealed potential natural inhibitors of NF-κB transcription factor as breast cancer therapeutics

Breast cancer is a silent killer malady among women and a serious economic burden in health care management. A case of breast cancer is diagnosed among women every 19 s, and every 74 s, a woman dies of breast cancer somewhere in the world. Despite the pop-up of progressive research, advanced treatment approaches, and preventive measures, breast cancer remains amplifying ailment. The nuclear factor kappa B (NF-κB) is a key transcription factor that links inflammation with cancer and is demonstrated as being involved in the tumorigenesis of breast cancer. The NF-κB transcription factor family in mammals consists of five proteins; c-Rel, RelA(p65), RelB, NF-κB1(p50), and NF-κB2(p52). The antitumor effect of NF-κB has also been explored in breast cancer, however, the actual treatment for breast cancer is yet to be discovered. This study is attributed to the identification of novel drug targets against breast cancer by targeting c-Rel, RelA(p65), RelB, NF-κB1(p50), and NF-κB2(p52) proteins. To identify the putative active compounds, a structure-based 3D pharmacophore model to the protein active site cavity was generated followed by virtual screening, molecular docking, and molecular dynamics (MD) simulation. Initially, a library of 45000 compounds were docked against the target protein and five compounds namely Z56811101, Z653426226, Z1097341967, Z92743432, and Z464101066 were selected for further analysis. The relative binding affinity of Z56811101, Z653426226, Z1097341967, Z92743432, and Z464101066 with NF-κB1 (p50), NF-κB2 (p52), RelA (p65), RelB, and c-Rel proteins were -6.8, -8, -7.0, -6.9, and -7.2 kcal/mol, respectively which remained stable throughout the simulations of 200 ns. Furthermore, all of these compounds depict maximum drug-like properties. Therefore, the proposed compounds can be a potential candidate for patients with breast cancer, but, experimental validation is needed to ensure their safety.Communicated by Ramaswamy H. Sarma.

An In Silico Molecular Modelling-Based Prediction of Potential Keap1 Inhibitors from Hemidesmus indicus (L.) R.Br. against Oxidative-Stress-Induced Diseases

The present study investigated the antioxidant potential of aqueous methanolic extracts of Hemidesmus indicus (L.) R.Br., followed by a pharmacoinformatics-based screening of novel Keap1 protein inhibitors. Initially, the antioxidant potential of this plant extract was assessed via antioxidant assays (DPPH, ABTS radical scavenging, and FRAP). Furthermore, 69 phytocompounds in total were derived from this plant using the IMPPAT database, and their three-dimensional structures were obtained from the PubChem database. The chosen 69 phytocompounds were docked against the Kelch-Neh2 complex protein (PDB entry ID: 2flu, resolution 1.50 Å) along with the standard drug (CPUY192018). H. indicus (L.) R.Br. extract (100 µg × mL-1) showed 85 ± 2.917%, 78.783 ± 0.24% of DPPH, ABTS radicals scavenging activity, and 161 ± 4 μg × mol (Fe (II)) g-1 ferric ion reducing power. The three top-scored hits, namely Hemidescine (-11.30 Kcal × mol-1), Beta-Amyrin (-10.00 Kcal × mol-1), and Quercetin (-9.80 Kcal × mol-1), were selected based on their binding affinities. MD simulation studies showed that all the protein-ligand complexes (Keap1-HEM, Keap1-BET, and Keap1-QUE) were highly stable during the entire simulation period, compared with the standard CPUY192018-Keap1 complex. Based on these findings, the three top-scored phytocompounds may be used as significant and safe Keap1 inhibitors, and could potentially be used for the treatment of oxidative-stress-induced health complications.

Interactome-Based Machine Learning Predicts Potential Therapeutics for COVID-19

COVID-19, the disease caused by SARS-CoV-2, has been disrupting our lives for more than two years now. SARS-CoV-2 interacts with human proteins to pave its way into the human body, thereby wreaking havoc. Moreover, the mutating variants of the virus that take place in the SARS-CoV-2 genome are also a cause of concern among the masses. Thus, it is very important to understand human-spike protein-protein interactions (PPIs) in order to predict new PPIs and consequently propose drugs for the human proteins in order to fight the virus and its different mutated variants, with the mutations occurring in the spike protein. This fact motivated us to develop a complete pipeline where PPIs and drug-protein interactions can be predicted for human-SARS-CoV-2 interactions. In this regard, initially interacting data sets are collected from the literature, and noninteracting data sets are subsequently created for human-SARS-CoV-2 by considering only spike glycoprotein. On the other hand, for drug-protein interactions both interacting and noninteracting data sets are considered from DrugBank and ChEMBL databases. Thereafter, a model based on a sequence-based feature is used to code the protein sequences of human and spike proteins using the well-known Moran autocorrelation technique, while the drugs are coded using another well-known technique, viz., PaDEL descriptors, to predict new human-spike PPIs and eventually new drug-protein interactions for the top 20 predicted human proteins interacting with the original spike protein and its different mutated variants like Alpha, Beta, Delta, Gamma, and Omicron. Such predictions are carried out by random forest as it is found to perform better than other predictors, providing an accuracy of 90.53% for human-spike PPI and 96.15% for drug-protein interactions. Finally, 40 unique drugs like eicosapentaenoic acid, doxercalciferol, ciclesonide, dexamethasone, methylprednisolone, etc. are identified that target 32 human proteins like ACACA, DST, DYNC1H1, etc.

Multidimensional virtual screening approaches combined with drug repurposing to identify potential covalent inhibitors of SARS-CoV-2 3CL protease

The outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused an unprecedented global pandemic, and new cases are still on the rise due to the absence of effective medicines. However, developing new drugs within a short time is extremely difficult. Repurposing the existing drugs provides a fast and effective strategy to identify promising inhibitors. Here we focus on the screening of drugs database for discovering potential covalent inhibitors that target 3-chymotrypsin-like protease (3CLpro), an essential enzyme mediating viral replication and transcription. Firstly, we constructed a receptor-ligand pharmacophore model and verified it through decoy set. The importance of pharmacophore features was evaluated by combining molecular dynamics simulation with interaction analyses. Then, covalent docking was used to perform further screening. According to docking score and Prime/Molecular Mechanics Generalized Born Surface Area (MM-GBSA) score, total ten compounds obtained good scores and successfully established covalent bonds with the catalytic Cys145 residue. They also formed favorable interactions with key residues in active sites and closely integrated with 3CLpro with binding modes similar to known 3CLpro inhibitor. Finally, the top four hits DB08732, DB04653, DB01871 and DB07299 were further subjected to 100 ns molecular dynamics (MD) simulation and MM-GBSA binding free energy calculations. The results suggest that the four candidates show good binding affinities for 3CLpro, which warrants further evaluation for their in-vitro/in-vivo activities. Overall, our research methods provide a valuable reference for discovering promising inhibitors against SARS-CoV-2 and help to fight against the epidemic.Communicated by Ramaswamy H. Sarma.

Disruption of 3CLpro protease self-association by short peptides as a potential route to broad spectrum coronavirus inhibitors

Coronaviruses have posed a persistent threat to human health over the last two decades. Despite the accumulated knowledge about coronavirus-related pathogens, development of an effective treatment for its new variant COVID-19 is highly challenging. For the highly-conserved and main coronavirus protease 3CLpro, dimerization is known to be essential for its catalytic activity and thereby for virus proliferation. Here, we assess the potential of short peptide segments to disrupt dimerization of the 3CLpro protease as a route to block COVID-19 proliferation. Based on the X-ray structure of the 3CLpro dimer, we identified the SPSGVY₁₂₆QCAMRP dodecapeptide segment as overlapping the hotspot regions on the 3CLpro dimer interface. Using computational blind docking of the peptide to the 3CLpro monomer, we found that the SPSGVY₁₂₆QCAMRP peptide has favourable thermodynamic binding (ΔG= -5.93 kcal/mol) to the hotspot regions at the 3CLpro dimer interface. Importantly, the peptide was also found to preferentially bind to the hotspot regions compared to other potential binding sites lying away from the dimer interface (ΔΔG=-1.31 kcal/mol). Docking of peptides corresponding to systematic mutation of the V125 and Y126 residues led to the identification of seven peptides, SPSGHAQCAMRP, SPSGVTQCAMRP, SPSGKPQCAMRP, SPSGATQCAMRP, SPSGWLQCAMRP, SPSGAPQCAMRP and SPSGHPQCAMRP, that outperform the wild-type SPSGVY₁₂₆QCAMRP peptide in terms of preferential binding to the 3CLpro dimer interface. These peptides have the potential to disrupt 3CLpro dimerization and therefore could provide lead structures for the development of broad spectrum COVID-19 inhibitors.Communicated by Ramaswamy H. Sarma.

Discovery of potential SARS-CoV 3CL protease inhibitors from approved antiviral drugs using: virtual screening, molecular docking, pharmacophore mapping evaluation and dynamics simulation

The spread of corona-virus disease 2019 (COVID-19) has been faster than any other corona-viruses that have succeeded in crossing the animal-human barrier. This disease, caused by the severe acute respiratory syndrome corona-virus 2 (SARS-CoV-2/2019-nCoV) posing a serious threat to global public health and local economies. There are three responsible for this disease; SARS-CoV-2, SARS-CoV and MERS-CoV. Whereas our goal is to test the affinity for a new class of compounds obtained from a hybridization of Chloroquine, Amodiaquine and Mefloquine with three targets SARS-CoV-2, SARS-CoV and MERS-CoV, in order to find new compounds as new inhibitors against Covid-19. In this work, we first used: the molecular docking/dynamics methods and ADME properties to study interaction and affinity between eight new compounds against three targets involved in the Covid-19. The results of the docking simulations and dynamics revealed that inhibitor of the malaria (Ligand 87) has an affinity to interact with SARS-CoV-2, SARS-CoV and MERS-CoV targets and they can be good inhibitors for treatment of Covid-19. Moreover, they give best affinity compared to the Remdesivir and Chloroquine and other clinical tests. The Pharmacokinetics was justified by means of lipophilicity and high coefficient of skin permeability. The in silico evaluation of ADME and drug-likeness revealed that L87 has higher absorption in the intestines with good bioavailability. However, an additional in vitro and/or in vivo experimental study should make it possible to verify the theoretical results obtained in silico.Communicated by Ramaswamy H. Sarma.

Anti-HIV and anti-HCV small molecule protease inhibitors in-silico repurposing against SARS-CoV-2 Mpro for the treatment of COVID-19

The COVID-19 pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is a global health emergency warranting development and implementation of targeted treatment. The enzyme main protease (M^pro; also known as 3C-like protease) is emerging as an attractive drug target. This enzyme plays an indispensable role in processing the translated polyproteins of viral RNA. Inhibiting the activity of M^pro would wedge viral replication. To facilitate the discovery of targeted therapy for COVID-19, we carried out the structure-assisted repurposing of existing protease inhibiting small molecules to target SARS-CoV-2 M^pro. Based on the structure of SARS-CoV-2 M^pro, here we report the small drug molecule namely saquinavir as its potent inhibitor. Findings support the premise that this promising antiviral protease inhibiting small drug molecule can be validated and implemented for the treatment and clinical management of COVID-19 pandemic disease.Communicated by Ramaswamy H. Sarma.

Molecular and Structural Analysis of Specific Mutations from Saudi Isolates of SARS-CoV-2 RNA-Dependent RNA Polymerase and their Implications on Protein Structure and Drug-Protein Binding

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has stressed the global health system to a significant level, which has not only resulted in high morbidity and mortality but also poses a threat for future pandemics. This situation warrants efforts to develop novel therapeutics to manage SARS-CoV-2 in specific and other emerging viruses in general. This study focuses on SARS-CoV2 RNA-dependent RNA polymerase (RdRp) mutations collected from Saudi Arabia and their impact on protein structure and function. The Saudi SARS-CoV-2 RdRp sequences were compared with the reference Wuhan, China RdRp using a variety of computational and biophysics-based approaches. The results revealed that three mutations-A97V, P323I and Y606C-may affect protein stability, and hence the relationship of protein structure to function. The apo wild RdRp is more dynamically stable with compact secondary structure elements compared to the mutants. Further, the wild type showed stable conformational dynamics and interaction network to remdesivir. The net binding energy of wild-type RdRp with remdesivir is -50.76 kcal/mol, which is more stable than the mutants. The findings of the current study might deliver useful information regarding therapeutic development against the mutant RdRp, which may further furnish our understanding of SARS-CoV-2 biology.

Virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is considered the etiological agent of the disease that caused the COVID-19 pandemic, and for which there is currently no effective treatment. This pandemic has shown that the rapid identification of therapeutic compounds is critical (when a new virus with high transmissibility occurs) to prevent or reduce as much as possible the loss of human lives. To meet the urgent need for drugs, many strategies were applied for the discovery, respectively the identification of potential therapies / drugs for SARS-CoV-2. Molecular docking and virtual screening are two of the in silico tools/techniques that provided the identification of few SARS-CoV-2 inhibitors, removing ineffective or less effective drugs and thus preventing the loss of resources such as time and additional costs. The main target of this review is to provide a comprehensive overview of how in-silico tools have been used in the crisis management of anti-SARS-CoV-2 drugs, especially in virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses; also, completions were added to the way in which these methods came to meet the requirements of biomedical research in the field. Moreover, the importance and impact of the topic approached for researchers was highlighted by conducting an extensive bibliometric analysis.

Search for Novel Potent Inhibitors of the SARS-CoV-2 Papain-like Enzyme: A Computational Biochemistry Approach

The rapid emergence and spread of new variants of coronavirus type 2, as well as the emergence of zoonotic viruses, highlights the need for methodologies that contribute to the search for new pharmacological treatments. In the present work, we searched for new SARS-CoV-2 papain-like protease inhibitors in the PubChem database, which has more than 100 million compounds. Based on the ligand efficacy index obtained by molecular docking, 500 compounds with higher affinity than another experimentally tested inhibitor were selected. Finally, the seven compounds with ADME parameters within the acceptable range for such a drug were selected. Next, molecular dynamics simulation studies at 200 ns, ΔG calculations using molecular mechanics with generalized Born and surface solvation, and quantum mechanical calculations were performed with the selected compounds. Using this in silico protocol, seven papain-like protease inhibitors are proposed: three compounds with similar free energy (D28, D04, and D59) and three compounds with higher binding free energy (D60, D99, and D06) than the experimentally tested inhibitor, plus one compound (D24) that could bind to the ubiquitin-binding region and reduce the effect on the host immune system. The proposed compounds could be used in in vitro assays, and the described protocol could be used for smart drug design.

Computational Investigations of Traditional Chinese Medicinal Compounds against the Omicron Variant of SARS-CoV-2 to Rescue the Host Immune System

Macrodomain-I of the NSP3 (non-structural protein 3) is responsible for immune response hijacking in the SARS-CoV-2 infection known as COVID-19. In the omicron variant (B.1.1.529), this domain harbors a new mutation, V1069I, which may increase the binding of ADPr and consequently the infection severity. This macrodomain-I, due to its significant role in infection, is deemed to be an important drug target. Hence, using structural bioinformatics and molecular simulation approaches, we performed a virtual screening of the traditional Chinese medicines (TCM) database for potential anti-viral drugs. The screening of 57,000 compounds yielded the 10 best compounds with docking scores better than the control ADPr. Among the top ten, the best three hits—TCM42798, with a docking score of −13.70 kcal/mol, TCM47007 of −13.25 kcal/mol, and TCM30675 of −12.49 kcal/mol—were chosen as the best hits. Structural dynamic features were explored including stability, compactness, flexibility, and hydrogen bonding, further demonstrating the anti-viral potential of these hits. Using the MM/GBSA approach, the total binding free energy for each complex was reported to be −69.78 kcal/mol, −50.11 kcal/mol, and −47.64 kcal/mol, respectively, which consequently reflect the stronger binding and inhibitory potential of these compounds. These agents might suppress NSP3 directly, allowing the host immune system to recuperate. The current study lays the groundwork for the development of new drugs to combat SARS-CoV-2 and its variants.

Structural Elucidation of Rift Valley Fever Virus L Protein towards the Discovery of Its Potential Inhibitors

Rift valley fever virus (RVFV) is the causative agent of a viral zoonosis that causes a significant clinical burden in domestic and wild ruminants. Major outbreaks of the virus occur in livestock, and contaminated animal products or arthropod vectors can transmit the virus to humans. The viral RNA-dependent RNA polymerase (RdRp; L protein) of the RVFV is responsible for viral replication and is thus an appealing drug target because no effective and specific vaccine against this virus is available. The current study reported the structural elucidation of the RVFV-L protein by in-depth homology modeling since no crystal structure is available yet. The inhibitory binding modes of known potent L protein inhibitors were analyzed. Based on the results, further molecular docking-based virtual screening of Selleckchem Nucleoside Analogue Library (156 compounds) was performed to find potential new inhibitors against the RVFV L protein. ADME (Absorption, Distribution, Metabolism, and Excretion) and toxicity analysis of these compounds was also performed. Besides, the binding mechanism and stability of identified compounds were confirmed by a 50 ns molecular dynamic (MD) simulation followed by MM/PBSA binding free energy calculations. Homology modeling determined a stable multi-domain structure of L protein. An analysis of known L protein inhibitors, including Monensin, Mycophenolic acid, and Ribavirin, provide insights into the binding mechanism and reveals key residues of the L protein binding pocket. The screening results revealed that the top three compounds, A-317491, Khasianine, and VER155008, exhibited a high affinity at the L protein binding pocket. ADME analysis revealed good pharmacodynamics and pharmacokinetic profiles of these compounds. Furthermore, MD simulation and binding free energy analysis endorsed the binding stability of potential compounds with L protein. In a nutshell, the present study determined potential compounds that may aid in the rational design of novel inhibitors of the RVFV L protein as anti-RVFV drugs.

Molecular dynamics simulation approach for discovering potential inhibitors against SARS-CoV-2: A structural review

Since the commencement of the novel Coronavirus, the disease has quickly turned into a worldwide crisis so that there has been growing attention in discovering possible hit compounds for tackling this pandemic. Discovering standard treatment strategies is a serious challenge because little information is available about this emerged infectious virus. Regarding the high impact of time, applying computational procedures to choose promising drugs from a catalog of licensed medications provides a precious chance for combat against the life-threatening disorder of COVID-19. Molecular dynamics (MD) simulation is a promising approach for assessing the binding affinity of ligand-receptor as well as observing the conformational trajectory of docked complexes over time. Given that many computational studies are performed using MD along with the molecular docking on various candidates as antiviral inhibitors of COVID-19 protease, there is a demand to conduct a comprehensive review of the most important studies to reveal and compare the potential introduced agents that this study covers this defect. In this context, the present review intends to prepare an overview of these studies by considering RMSD, RMSF, radius of gyration, binding free energy, and Solvent-Accessible Surface Area (SASA) as effective parameters for evaluation. The outcomes will offer a road map for adjusting antiviral inhibitors, which can facilitate the selection and development of drug candidates for use in the medical therapy. Finally, the molecular modeling approaches rendered by this study may be valuable for future computational studies.

The effect of various compounds on the COVID mechanisms, from chemical to molecular aspects

The novel coronavirus that caused COVID-19 pandemic is SARS-CoV-2. Although various vaccines are currently being used to prevent the disease's severe consequences, there is still a need for medications for those who become infected. The SARS-CoV-2 has a variety of proteins that have been studied extensively since the virus's advent. In this review article, we looked at chemical to molecular aspects of the various structures studied that have pharmaceutical activity and attempted to find a link between drug activity and compound structure. For example, designing of the compounds which bind to the allosteric site and modify hydrogen bonds or the salt bridges can disrupt SARS-CoV2 RBD–ACE2 complex. It seems that quaternary ammonium moiety and quinolin-1-ium structure could act as a negative allosteric modulator to reduce the tendency between spike-ACE2. Pharmaceutical structures with amino heads and hydrophobic tails can block envelope protein to prevent making mature SARS-CoV-2. Also, structures based on naphthalene pharmacophores or isosteres can form a strong bond with the PLpro and form a π-π and the Mpro's active site can be occupied by octapeptide compounds or linear compounds with a similar fitting ability to octapeptide compounds. And for protein RdRp, it is critical to consider pH and pKa so that pKa regulation of compounds to comply with patients is very effective, thus, the presence of tetrazole, phenylpyrazole groups, and analogs of pyrophosphate in the designed drugs increase the likelihood of the RdRp active site inhibition. Finally, it can be deduced that designing hybrid drug molecules along with considering the aforementioned characteristics would be a suitable approach for developing medicines in order to accurate targeting and complete inhibition this virus.

Molecular Docking as a Potential Approach in Repurposing Drugs Against COVID-19: a Systematic Review and Novel Pharmacophore Models

Purpose of Review

This article provides a review of the recent literature related to the FDA-approved drugs that had been repurposed as potential drug candidates against COVID-19. Moreover, we performed a quality pharmacophore study for frequently studied targets, namely, the main protease, RNA-dependent RNA polymerase, and spike protein.

Recent Findings

Ever since the COVID-19 pandemic, the whole spectrum of scientific community is still unable to invent an absolute therapeutic agent for COVID-19. Considering such a fact, drug repurposing strategies seem a truly viable approach to develop novel therapeutic interventions.

Summery

Drug repurposing explores previously approved drugs of known safety and pharmacokinetics profile for possible new effects, reducing the cost, time, and predicting prospective side effects and drug interactions. COVID-19 virulent machinery appeared similar to other viruses, making antiviral agents widely repurposed in pursuit for curative candidates. Our main protease pharmacophoric study revealed multiple features and could be a probable starting point for upcoming research.

Fenticonazole nitrate loaded trans-novasomes for effective management of tinea corporis: design characterization, in silico study, and exploratory clinical appraisal

The current investigation aimed for loading fenticonazole nitrate (FTN), an antifungal agent with low aqueous solubility, into trans-novasomes (TNs) for management of tinea corporis topically. TNs contain Brij^® as an edge activator besides the components of novasomes (cholesterol, Span 60, and oleic acid) owing to augment the topical delivery of FTN. TNs were fabricated applying ethanol injection method based on D-optimal experiment. TNs were evaluated with regard to entrapment efficiency percent (EE%), particle size (PS), polydispersity index (PDI), and zeta potential (ZP). Further explorations were conducted on the optimum formulation (F7). F7 showed spherical appearance with EE%, PS, PDI, and ZP of 100.00 ± 1.10%, 358.60 ± 10.76 nm, 0.51 ± 0.004, and −30.00 ± 0.80 mV, respectively. The in silico study revealed the ability of the FTN–cholesterol complex to maintain favorable interactions throughout the molecular dynamics simulation (MDS) study. Moreover, Trichophyton mentagrophytes growth was inhibited effectively by F7 than by FTN suspension applying 2,3-bis(2-methyloxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide (XTT) reduction assay. Furthermore, a clinical appraisal on patients with tinea corporis fungal lesions confirmed the superiority of F7 compared to Miconaz^® cream in the magnitude of clinical cure of tinea corporis. Thereby, TNs could be considered as promising vesicles for enhancing the antifungal potential of FTN for the topical management of tinea corporis.

Computer aided identification of potential SARS CoV-2 main protease inhibitors from diterpenoids and biflavonoids of Torreya nucifera leaves

SARS CoV-2 is the causative agent of the pandemic disease COVID-19. There is an urgent need for effective drugs or vaccines which can effectively combat this outbreak. The main protease (Mpro), a key component for the SARS CoV-2 replication, is considered to be one of the important drug targets for developing anti-COVID-19 drugs. This SARS CoV-2 Mpro/cysteine protease has high sequence similarity with the same protease from SARS CoV-1. Previously, it has been shown experimentally that eight diterpenoids and four biflavonoids derived from the leaf of Torreya nucifera show inhibitory effect on the cleavage/catalytic activity of the SARS CoV-1 Mpro. But whether these phytochemicals exhibit any inhibitory effect on SARS CoV-2 Mpro is unclear. To understand this fact, here, we have adopted various in-silico approaches. Diterpenoids and biflavonoids those qualified pharmacological test (hinokiol, amentoflavone, bilobetin and ginkgetin) and two well-known Mpro inhibitors (N3 and lopinavir) were subjected for molecular docking studies. Only three biflavonoids (amentoflavone, bilobetin and ginkgetin) were selected by comparing their binding affinities with N3 and lopinavir. They interacted with two most important catalytic residues of Mpro (His41 and Cys145). Molecular dynamics studies further revealed that these three Mpro-biflavonoid complexes are highly stable and share a similar degree of compactness. Besides, these complexes experience less conformational fluctuations and more expansion than Mpro-N3 and/or Mpro-lopinavir complex. MM-GBSA and H-bond analysis further corroborated these findings. Altogether, our study suggested that these three biflavonoids could possibly inhibit the proteolytic/catalytic activity of SARS CoV-2 Mpro and might be useful for COVID-19 treatment.Communicated by Ramaswamy H. Sarma.

Inhibitory effects of selected isoquinoline alkaloids against main protease (Mpro) of SARS-CoV-2, in silico study

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global threat. Despite the production of various vaccines and different treatments, finding natural compounds to control COVID-19 is still a challenging task. Isoquinoline alkaloids are naturally occurring compounds known to have some potential antiviral activity. In this study, ten abundant isoquinoline alkaloids with antiviral activity were selected to analyze the preventive effect on COVID-19. A scrutinized evaluation based on Lipinski’s rule showed that one out of ten compounds was toxic. Based on molecular docking analysis using Autodock software one of the best molecules with maximum negative binding energy was selected for further analysis. The Gromacs simulation analysis revealed that Coptisine has more action against active site M^pro of COVID-19. Overall, to make a rational design of various preventive analogues that inhibit the COVID-19, associated in vitro and in vivo analyses are needed to confirm this claim.

Targeting the RBD of Omicron Variant (B.1.1.529) with Medicinal Phytocompounds to Abrogate the Binding of Spike Glycoprotein with the hACE2 Using Computational Molecular Search and Simulation Approach

Simple Summary

The current study based on virtual drugs screening and simulations identified novel drugs to target the RBD of the spike protein from Omicron variant of SARS-CoV-2. Using molecular modeling tools to search for a good binding drugs we identified SANC00944, SANC01032, SANC00992, and SANC00317 from South African natural compounds database as potential inhibitor of the Spike-ACE2 complex. In sum, this study will help in the design and discovery of novel drug therapeutics, which may be used against the emerging Omicron variant of SARS-CoV-2.

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus continues to inflict chaos globally. The emergence of a novel Omicron variant (B.1.1.529) in South Africa harbors 30 mutations in the spike protein. The variant is distinguished from other variants of concern (VOCs) with an increased (15) number of mutations in the receptor-binding domain (RBD) and suggests higher chances of causing reinfections. Initial reports also claimed that this variant escapes all the neutralizing antibodies, thus demanding a novel strategy against it. Thus, in this study, we performed a computational molecular screening against the RBD of the Omicron (B.1.1.529) variant and assessed the binding affinity of potent drugs against the RBD. The multi-steps screening of the South African Natural Compounds Database (SANCDB) revealed four medicinal compounds as excellent (potential) anti-viral agents against the Omicron variant, namely SANC00944, SANC01032, SANC00992, and SANC00317. The simulation analysis of these compounds in complex with the RBD demonstrated stable dynamics and structural compactness. Moreover, the residual flexibility analysis revealed that the flexibility of three loops required for interaction with hACE2 has been reduced by the binding of these drugs. The post-simulation validation of these compounds such as binding free energy, in silico bioactivity, and dissociation constant prediction validated the anti-viral potency of these compounds. The total binding free energy (TBFE) for the SANC01032–RBD complex was reported to be −46.54 kcal/mol; for the SANC01032–RBD complex, the TBFE was −41.88 kcal/mol; for the SANC00992–RBD complex the TBFE was −29.05 kcal/mol, while for the SANC00317–RBD complex the TBFE was −31.03 kcal/mol. The results showed the inhibition potential of these compounds by targeting the RBD. In conclusion, this study will help in the design and discovery of novel drug therapeutics, which may be used against the emerging Omicron variant of SARS-CoV-2.

Identification of Potential Antiviral Inhibitors from Hydroxychloroquine and 1,2,4,5-Tetraoxanes Analogues and Investigation of the Mechanism of Action in SARS-CoV-2

This study aimed to identify potential inhibitors and investigate the mechanism of action on SARS-CoV-2 ACE2 receptors using a molecular modeling study and theoretical determination of biological activity. Hydroxychloroquine was used as a pivot structure and antimalarial analogues of 1,2,4,5 tetraoxanes were used for the construction and evaluation of pharmacophoric models. The pharmacophore-based virtual screening was performed on the Molport^® database (~7.9 million compounds) and obtained 313 structures. Additionally, a pharmacokinetic study was developed, obtaining 174 structures with 99% confidence for human intestinal absorption and penetration into the blood-brain barrier (BBB); posteriorly, a study of toxicological properties was realized. Toxicological predictions showed that the selected molecules do not present a risk of hepatotoxicity, carcinogenicity, mutagenicity, and skin irritation. Only 54 structures were selected for molecular docking studies, and five structures showed binding affinity (ΔG) values satisfactory for ACE2 receptors (PDB 6M0J), in which the molecule MolPort-007-913-111 had the best ΔG value of -8.540 Kcal/mol, followed by MolPort-002-693-933 with ΔG = -8.440 Kcal/mol. Theoretical determination of biological activity was realized for 54 structures, and five molecules showed potential protease inhibitors. Additionally, we investigated the Mpro receptor (6M0K) for the five structures via molecular docking, and we confirmed the possible interaction with the target. In parallel, we selected the TopsHits 9 with antiviral potential that evaluated synthetic accessibility for future synthesis studies and in vivo and in vitro tests.

A new glimpse on the active site of SARS-CoV-2 3CLpro, coupled with drug repurposing study

Coronavirus disease 2019 (COVID-19) is caused by novel severe acute respiratory syndrome coronavirus (SARS-CoV-2). Its main protease, 3C-like protease (3CLpro), is an attractive target for drug design, due to its importance in virus replication. The analysis of the radial distribution function of 159 3CLpro structures reveals a high similarity index. A study of the catalytic pocket of 3CLpro with bound inhibitors reveals that the influence of the inhibitors is local, perturbing dominantly only residues in the active pocket. A machine learning based model with high predictive ability against SARS-CoV-2 3CLpro is designed and validated. The model is used to perform a drug-repurposing study, with the main aim to identify existing drugs with the highest 3CLpro inhibition power. Among antiviral agents, lopinavir, idoxuridine, paritaprevir, and favipiravir showed the highest inhibition potential. Enzyme - ligand interactions as a key ingredient for successful drug design.

Identifying the Hot Spot Residues of the SARS-CoV-2 Main Protease Using MM-PBSA and Multiple Force Fields

In this study, we investigated the binding affinities between the main protease of SARS-CoV-2 virus (Mpro) and its various ligands to identify the hot spot residues of the protease. To benchmark the influence of various force fields on hot spot residue identification and binding free energy calculation, we performed MD simulations followed by MM-PBSA analysis with three different force fields: CHARMM36, AMBER99SB, and GROMOS54a7. We performed MD simulations with 100 ns for 11 protein-ligand complexes. From the series of MD simulations and MM-PBSA calculations, it is identified that the MM-PBSA estimations using different force fields are weakly correlated to each other. From a comparison between the force fields, AMBER99SB and GROMOS54a7 results are fairly correlated while CHARMM36 results show weak or almost no correlations with the others. Our results suggest that MM-PBSA analysis results strongly depend on force fields and should be interpreted carefully. Additionally, we identified the hot spot residues of Mpro, which play critical roles in ligand binding through energy decomposition analysis. It is identified that the residues of the S4 subsite of the binding site, N142, M165, and R188, contribute strongly to ligand binding. In addition, the terminal residues, D295, R298, and Q299 are identified to have attractive interactions with ligands via electrostatic and solvation energy. We believe that our findings will help facilitate developing the novel inhibitors of SARS-CoV-2.

Structure-Based Pharmacophore Modeling, Virtual Screening, Molecular Docking, ADMET, and Molecular Dynamics (MD) Simulation of Potential Inhibitors of PD-L1 from the Library of Marine Natural Products

Background: In the past decade, several antibodies directed against the PD-1/PD-L1 interaction have been approved. However, therapeutic antibodies also exhibit some shortcomings. Using small molecules to regulate the PD-1/PD-L1 pathway may be another way to mobilize the immune system to fight cancer. Method: 52,765 marine natural products were screened against PD-L1(PDBID: 6R3K). To identify natural compounds, a structure-based pharmacophore model was generated, following by virtual screening and molecular docking. Then, the absorption, distribution, metabolism, and excretion (ADME) test was carried out to select the most suitable compounds. Finally, molecular dynamics simulation was also performed to validate the binding property of the top compound. Results: Initially, 12 small marine molecules were screened based on the pharmacophore model. Then, two compounds were selected for further evaluation based on the molecular docking scores. After ADME and toxicity studies, molecule 51320 was selected for further verification. By molecular dynamics analysis, molecule 51320 maintains a stable conformation with the target protein, so it has the chance to become an inhibitor of PD-L1. Conclusions: Through structure-based pharmacophore modeling, virtual screening, molecular docking, ADMET approaches, and molecular dynamics (MD) simulation, the marine natural compound 51320 can be used as a small molecule inhibitor of PD-L1.

Rescuing the Host Immune System by Targeting the Immune Evasion Complex ORF8-IRF3 in SARS-CoV-2 Infection with Natural Products Using Molecular Modeling Approaches

The perennial emergence of SARS-CoV-2 and its new variants causing upper respiratory complexities since December 2019 has aggravated the pandemic situation around the world. SARS-CoV-2 encodes several proteins among which ORF8 is a novel factor that is unique to SARS-CoV-2 only and is reported to help the virus in disease severity and immune evasion. ORF8-IRF3 complex induces endoplasmic reticulum stress, thus helps in the evasion of immune response. Consequently, targeting the ORF8-IRF3 complex is considered as a prime target for the discovery of novel drugs against SARS-CoV-2. In this regard, computational methods are of great interest to fast track the identification and development of novel drugs. Virtual screening of South African Natural Compounds Database (SANCDB), followed by docking and molecular dynamics (MD) simulation analysis, were performed to determine novel natural compounds. Computational molecular search and rescoring of the SANCDB database followed by induced-fit docking (IFD) protocol identified Quercetin 3-O-(6″-galloyl)-beta-D-galactopyranoside (SANC00850), Tribuloside (SANC01050), and Rutin (SANC00867) are the best scoring compounds. Structural-dynamic properties assessment revealed that these three compounds have stable dynamics, compactness, and a higher number of hydrogen bonds. For validation, we used MM/GBSA, in silico bioactivity estimation and dissociation constant (KD) approaches, which revealed that these compounds are the more potent inhibitors of the ORF8-IRF3 complex and would rescue the host immune system potentially. These compounds need further in vitro and in vivo validations to be used as therapeutics against SARS-CoV-2 to rescue the host immune system during COVID-19 infection.

Ligand-based quantitative structural assessments of SARS-CoV-2 3CLpro inhibitors: An analysis in light of structure-based multi-molecular modeling evidences

Due to COVID-19, the whole world is undergoing a devastating situation, but treatment with no such drug candidates still has been established exclusively. In that context, 69 diverse chemicals with potential SARS-CoV-2 3CL^pro inhibitory property were taken into consideration for building different internally and externally validated linear (SW-MLR and GA-MLR), non-linear (ANN and SVM) QSAR, and HQSAR models to identify important structural and physicochemical characters required for SARS-CoV-2 3CL^pro inhibition. Importantly, 2-oxopyrrolidinyl methyl and benzylester functions, and methylene (hydroxy) sulphonic acid warhead group, were crucial for retaining higher SARS-CoV-2 3CL^pro inhibition. These GA-MLR and HQSAR models were also applied to predict some already repurposed drugs. As per the GA-MLR model, curcumin, ribavirin, saquinavir, sepimostat, and remdesivir were found to be the potent ones, whereas according to the HQSAR model, lurasidone, saquinavir, lopinavir, elbasvir, and paritaprevir were the highly effective SARS-CoV-2 3CL^pro inhibitors. The binding modes of those repurposed drugs were also justified by the molecular docking, molecular dynamics (MD) simulation, and binding energy calculations conducted by several groups of researchers. This current work, therefore, may be able to find out important structural parameters to accelerate the COVID-19 drug discovery processes in the future.

Discovery of Novel Inhibitors From Medicinal Plants for V-Domain Ig Suppressor of T-Cell Activation

V-domain Ig suppressor of T cell activation (VISTA) is an immune checkpoint and is a type I transmembrane protein. VISTA is linked to immunotherapy resistance, and it is a potential immune therapeutic target, especially for triple-negative breast cancer. It expresses at a high concentration in regulatory T cells and myeloid-derived suppressor cells, and its functional blockade is found to delay tumor growth. A useful medicinal plant database for drug designing (MPD3), which is a collection of phytochemicals from diverse plant families, was employed in virtual screening against VISTA to prioritize natural inhibitors against VISTA. Three compounds, Paratocarpin K (PubChem ID: 14187087), 3-(1H-Indol-3-yl)-2-(trimethylazaniumyl)propanoate (PubChem ID: 3861164), and 2-[(5-Benzyl-4-ethyl-1,2,4-triazol-3-yl)sulfanylmethyl]-5-methyl-1,3,4-oxadiazole (PubChem ID: 6494266), having binding energies stronger than -6 kcal/mol were found to have two common hydrogen bond interactions with VISTA active site residues: Arg54 and Arg127. The dynamics of the compound-VISTA complexes were further explored to infer binding stability of the systems. Results revealed that the compound 14187087 and 6494266 systems are highly stable with an average RMSD of 1.31 Å. Further affirmation on the results was achieved by running MM-GBSA on the MD simulation trajectories, which re-ranked 14187087 as the top-binder with a net binding energy value of -33.33 kcal/mol. In conclusion, the present study successfully predicted natural compounds that have the potential to block the function of VISTA and therefore can be utilized further in experimental studies to validate their real anti-VISTA activity.

De novo design of novel protease inhibitor candidates in the treatment of SARS-CoV-2 using deep learning, docking, and molecular dynamic simulations

The main protease of SARS-CoV-2 is a critical target for the design and development of antiviral drugs. 2.5 M compounds were used in this study to train an LSTM generative network via transfer learning in order to identify the four best candidates capable of inhibiting the main proteases in SARS-CoV-2. The network was fine-tuned over ten generations, with each generation resulting in higher binding affinity scores. The binding affinities and interactions between the selected candidates and the SARS-CoV-2 main protease are predicted using a molecular docking simulation using AutoDock Vina. The compounds selected have a strong interaction with the key MET 165 and Cys145 residues. Molecular dynamics (MD) simulations were run for 150ns to validate the docking results on the top four ligands. Additionally, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and hydrogen bond analysis strongly support these findings. Furthermore, the MM-PBSA free energy calculations revealed that these chemical molecules have stable and favorable energies, resulting in a strong binding with Mpro's binding site. This study's extensive computational and statistical analyses indicate that the selected candidates may be used as potential inhibitors against the SARS-CoV-2 in-silico environment. However, additional in-vitro, in-vivo, and clinical trials are required to demonstrate their true efficacy.

Natural Products-Based Drug Design against SARS-CoV-2 Mpro 3CLpro

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has received global attention due to the serious threat it poses to public health. Since the outbreak in December 2019, millions of people have been affected and its rapid global spread has led to an upsurge in the search for treatment. To discover hit compounds that can be used alone or in combination with repositioned drugs, we first analyzed the pharmacokinetic and toxicological properties of natural products from Brazil's semiarid region. After, we analyzed the site prediction and druggability of the SARS-CoV-2 main protease (Mpro), followed by docking and molecular dynamics simulation. The best SARS-CoV-2 Mpro complexes revealed that other sites were accessed, confirming that our approach could be employed as a suitable starting protocol for ligand prioritization, reinforcing the importance of catalytic cysteine-histidine residues and providing new structural data that could increase the antiviral development mainly against SARS-CoV-2. Here, we selected 10 molecules that could be in vitro assayed in response to COVID-19. Two compounds (b01 and b02) suggest a better potential for interaction with SARS-CoV-2 Mpro and could be further studied.

Identification of nut protein-derived peptides against SARS-CoV-2 spike protein and main protease

Recently, an outbreak of a novel coronavirus disease (COVID-19) has reached pandemic proportions, and there is an urgent need to develop nutritional supplements to assist with prevention, treatment, and recovery. In this study, SARS-CoV-2 inhibitory peptides were screened from nut proteins in silico, and binding affinities of the peptides to the SARS-CoV-2 main protease (M^pro) and the spike protein receptor-binding domain (RBD) were evaluated. Peptide NDQF from peanuts and peptide ASGCGDC from almonds were found to have a strong binding affinity for both targets of the coronavirus. The binding sites of the NDQF and ASGCGDC peptides are highly consistent with the M^pro inhibitor N3. In addition, NDQF and ASGCGDC exhibited an effective binding affinity for amino acid residues Tyr453 and Gln493 of the spike RBD. Molecular dynamics simulation further confirmed that the NDQF and ASGCGDC peptides could bind stably to the SARS-COV-2 M^pro and spike RBD. In summary, nut protein may be helpful as nutritional supplements for COVID-19 patients, and the screened peptides could be considered a potential lead compound for designing entry inhibitors against SARS-CoV-2.

A survey on computational methods in discovering protein inhibitors of SARS-CoV-2

The outbreak of acute respiratory disease in 2019, namely Coronavirus Disease-2019 (COVID-19), has become an unprecedented healthcare crisis. To mitigate the pandemic, there are a lot of collective and multidisciplinary efforts in facilitating the rapid discovery of protein inhibitors or drugs against COVID-19. Although many computational methods to predict protein inhibitors have been developed [ 1– 5], few systematic reviews on these methods have been published. Here, we provide a comprehensive overview of the existing methods to discover potential inhibitors of COVID-19 virus, so-called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). First, we briefly categorize and describe computational approaches by the basic algorithms involved in. Then we review the related biological datasets used in such predictions. Furthermore, we emphatically discuss current knowledge on SARS-CoV-2 inhibitors with the latest findings and development of computational methods in uncovering protein inhibitors against COVID-19.

Fragment-based in silico design of SARS-CoV-2 main protease inhibitors

3CLpro is essential for SARS-CoV-2 replication and infection; its inhibition using small molecules is a potential therapeutic strategy. In this study, a comprehensive crystallography-guided fragment-based drug discovery approach was employed to design new inhibitors for SARS-CoV-2 3CLpro. All small molecules co-crystallized with SARS-CoV-2 3CLpro with structures deposited in the Protein Data Bank were used as inputs. Fragments sitting in the binding pocket (87) were grouped into eight geographical types. They were interactively coupled using various synthetically reasonable linkers to generate larger molecules with divalent binding modes taking advantage of two different fragments' interactions. In total, 1,251 compounds were proposed, and 7,158 stereoisomers were screened using Glide (standard precision and extra precision), AutoDock Vina, and Prime MMGBSA. The top 22 hits having conformations approaching the linear combination of their constituent fragments were selected for MD simulation on Desmond. MD simulation suggested 15 of these did adopt conformations very close to their constituent pieces with far higher binding affinity than either constituent domain alone. These structures could provide a starting point for the further design of SARS-CoV-2 3CLpro inhibitors with improved binding, and structures are provided.

SARS-CoV-2 spike protein and RNA dependent RNA polymerase as targets for drug and vaccine development: A review

The present pandemic has posed a crisis to the economy of the world and the health sector. Therefore, the race to expand research to understand some good molecular targets for vaccine and therapeutic development for SARS-CoV-2 is inevitable. The newly discovered coronavirus 2019 (COVID-19) is a positive sense, single-stranded RNA, and enveloped virus, assigned to the beta CoV genus. The virus (SARS-CoV-2) is more infectious than the previously detected coronaviruses (MERS and SARS). Findings from many studies have revealed that S protein and RdRp are good targets for drug repositioning, novel therapeutic development (antibodies and small molecule drugs), and vaccine discovery. Therapeutics such as chloroquine, convalescent plasma, monoclonal antibodies, spike binding peptides, and small molecules could alter the ability of S protein to bind to the ACE-2 receptor, and drugs such as remdesivir (targeting SARS-CoV-2 RdRp), favipir, and emetine could prevent SASR-CoV-2 RNA synthesis. The novel vaccines such as mRNA1273 (Moderna), 3LNP-mRNAs (Pfizer/BioNTech), and ChAdOx1-S (University of Oxford/Astra Zeneca) targeting S protein have proven to be effective in combating the present pandemic. Further exploration of the potential of S protein and RdRp is crucial in fighting the present pandemic.

Hepatitis C Virus Protease Inhibitors Show Differential Efficacy and Interactions with Remdesivir for Treatment of SARS-CoV-2 In Vitro

Antivirals targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could improve treatment of COVID-19. We evaluated the efficacy of clinically relevant hepatitis C virus (HCV) NS3 protease inhibitors (PIs) against SARS-CoV-2 and their interactions with remdesivir, the only direct-acting antiviral approved for COVID-19 treatment. HCV PIs showed differential potency in short-term treatment assays based on the detection of SARS-CoV-2 spike protein in Vero E6 cells. Linear PIs boceprevir, telaprevir, and narlaprevir had 50% effective concentrations (EC₅₀) of ∼40 μM. Among the macrocyclic PIs, simeprevir had the highest (EC₅₀, 15 μM) and glecaprevir the lowest (EC₅₀, >178 μM) potency, with paritaprevir, grazoprevir, voxilaprevir, vaniprevir, danoprevir, and deldeprevir in between. Acyclic PIs asunaprevir and faldaprevir had EC₅₀s of 72 and 23 μM, respectively. ACH-806, inhibiting the HCV NS4A protease cofactor, had an EC₅₀ of 46 μM. Similar and slightly increased PI potencies were found in human hepatoma Huh7.5 cells and human lung carcinoma A549-hACE2 cells, respectively. Selectivity indexes based on antiviral and cell viability assays were highest for linear PIs. In short-term treatments, combination of macrocyclic but not linear PIs with remdesivir showed synergism in Vero E6 and A549-hACE2 cells. Longer-term treatment of infected Vero E6 and A549-hACE2 cells with 1-fold EC₅₀ PI revealed minor differences in the barrier to SARS-CoV-2 escape. Viral suppression was achieved with 3- to 8-fold EC₅₀ boceprevir or 1-fold EC₅₀ simeprevir or grazoprevir, but not boceprevir, in combination with 0.4- to 0.8-fold EC₅₀ remdesivir; these concentrations did not lead to viral suppression in single treatments. This study could inform the development and application of protease inhibitors for optimized antiviral treatments of COVID-19.