Assessment of the frequency of SARS-CoV-2 Omicron variant escape from RNA-dependent RNA polymerase inhibitors and 3C-like protease inhibitors.

The emergence and spread of antiviral-resistant SARS-CoV-2 is of great concern. In this study, we evaluated the propensity of Omicron variants to escape from RNA-dependent RNA polymerase (RdRP) inhibitors and 3C-like protease (3CLpro) inhibitors. SARS-CoV-2 Delta and Omicron variants were serially passaged in vitro in the presence of RdRP inhibitors (remdesivir and molnupiravir) and 3CLpro inhibitors (nirmatrelvir and lufotrelvir) to detect SARS-CoV-2 escape mutants. After five passages with 3CLpro inhibitors, mutant viruses that escaped from 3CLpro inhibitors emerged; however, in the presence of RdRP inhibitors all variants disappeared within 2-4 passages. Our findings suggest that the frequency of SARS-CoV-2 mutant escape from RdRP inhibitors is lower than that from 3CLpro inhibitors. We also found that Delta variants were more likely to acquire amino acid substitutions associated with resistance to 3CLpro inhibitors under the selective pressure of this drug compared with Omicron variants.

Computational assessment of herbal medicine-derived compounds as potential inhibitors of SARS-CoV-2 main protease.

Since the main protease (Mpro) is crucial for the COVID-19 virus replication and transcription, searching for Mpro inhibitors is one possible treatment option. In our study, 258 small molecules were collected from lung-related herbal medicines, and their structures were optimized with the B3LYP-D3/6-31G* method. After the molecular docking with Mpro, we selected the top 20 compounds for the further geometry optimization with the larger basis sets. After the further molecular docking, the top eight compounds were screened out. Then we performed molecular dynamics simulations and binding free energy calculations to determine stability of the complexes. Our results show that mulberrofuran G, Xambioona, and kuwanon D can bind Mpro well. In quantum chemistry studies, such as ESP and CDFT analyses, the compounds properties are predicted. Additionally, the drug-likeness analyses and ADME studies on these three candidate compounds verified that all of them conform to Libinski's rule and may be drug-like compounds.

Small molecule interactions with the SARS-CoV-2 main protease: In silico all-atom microsecond MD simulations, PELE Monte Carlo simulations, and determination of in vitro activity inhibition.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the ongoing COVID-19 pandemic. With some notable exceptions, safe and effective vaccines, which are now being widely distributed globally, have largely begun to stabilise the situation. However, emerging variants of concern and vaccine hesitancy are apparent obstacles to eradication. Therefore, the need for the development of potent antivirals is still of importance. In this context, the SARS-CoV-2 main protease (Mpro) is a critical target and numerous clinical trials, predominantly in the private domain, are currently in progress. Here, our aim was to extend our previous studies, with hypericin and cyanidin-3-O-glucoside, as potential inhibitors of the SARS-CoV-2 Mpro. Firstly, we performed all-atom microsecond molecular dynamics simulations, which highlight the stability of the ligands in the Mpro active site over the duration of the trajectories. We also invoked PELE Monte Carlo simulations which indicate that both hypericin and cyanidin-3-O-glucoside preferentially interact with the Mpro active site and known allosteric sites. For further validation, we performed an in vitro enzymatic activity assay that demonstrated that hypericin and cyanidin-3-O-glucoside inhibit Mpro activity in a dose-dependent manner at biologically relevant (µM) concentrations. However, both ligands are much less potent than the well-known covalent antiviral GC376, which was used as a positive control in our experiments. Nevertheless, the biologically relevant activity of hypericin and cyanidin-3-O-glucoside is encouraging. In particular, a synthetic version of hypericin has FDA orphan drug designation, which could simplify potential clinical evaluation in the context of COVID-19.

The index of ideality of correlation: QSAR studies of hepatitis C virus NS3/4A protease inhibitors using SMILES descriptors.

Robust and reliable QSAR models were developed to predict half-maximal inhibitory concentration (IC50) values of hepatitis C virus NS3/4A protease inhibitors from the Monte Carlo technique. 524 HCV NS3/4A protease inhibitors were extracted from the scientific literature to create a reasonably large set. The models were developed using CORAL software by using two target functions namely target function 1 (TF1) without applying the index of ideality of correlation (IIC) and target function 2 (TF2) that uses IIC. The constructed models based on TF2 were statistically more significant and robust than the models based on TF1. The determination coefficients (r2) of training and test sets were 0.86 and 0.88 for the best split based on TF2. The promoters of the increase/decrease of activity were also extracted and interpreted in detail. The model interpretation results explain the role of different structural attributes in predicting the pIC50 values of hepatitis C virus NS3/4A protease inhibitors. Based on the mechanistic model interpretation results, eight new compounds were designed and their pIC50 values were predicted based on the average prediction of ten models.

Computational Selectivity Assessment of Protease Inhibitors against SARS-CoV-2.

The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious global health threat. Since no specific therapeutics are available, researchers around the world screened compounds to inhibit various molecular targets of SARS-CoV-2 including its main protease (Mpro) essential for viral replication. Due to the high urgency of these discovery efforts, off-target binding, which is one of the major reasons for drug-induced toxicity and safety-related drug attrition, was neglected. Here, we used molecular docking, toxicity profiling, and multiple molecular dynamics (MD) protocols to assess the selectivity of 33 reported non-covalent inhibitors of SARS-CoV-2 Mpro against eight proteases and 16 anti-targets. The panel of proteases included SARS-CoV Mpro, cathepsin G, caspase-3, ubiquitin carboxy-terminal hydrolase L1 (UCHL1), thrombin, factor Xa, chymase, and prostasin. Several of the assessed compounds presented considerable off-target binding towards the panel of proteases, as well as the selected anti-targets. Our results further suggest a high risk of off-target binding to chymase and cathepsin G. Thus, in future discovery projects, experimental selectivity assessment should be directed toward these proteases. A systematic selectivity assessment of SARS-CoV-2 Mpro inhibitors, as we report it, was not previously conducted.

Phytocompounds from Anvillea radiata as promising anti-Covid-19 drugs: in silico studies and in vivo safety assessment.

As an alternative strategy in combating the COVID-19 pandemic, phytoconstituents from medicinal plants are getting attention worldwide. The current investigation focused on the efficacy of the essential phytocompounds identified in Anvillea radiata to target the main protease (Mpro) of SARS-COV-2 through molecular docking and dynamic analyses; in addition to the safety assessment of this herb in vivo. In silico, the 6LU7 structure of Mpro was prepared as a target by Discovery Studio 2020. The virtual screening of phytocompounds from Anvillea radiata was performed through iGEMDOCK program, followed by an evaluation of the potential inhibitors based on the docking scores calculated using AutoDock Vina and MGL Tools programs, as well as complexes stability assessment through MD simulation. In vivo toxicity studies of Anvillea radiata aqueous extract were also conducted in Wistar rats. Among the phytocompounds evaluated in this study, 3,5-Dicaffeoylquinic acid, Spinacetin, 9α-Epoxyparthenolide, Hispidulin, Quercetin, jaceosidin, Nepetin, and isorhamnetin were predicted to have the highest binding affinity for the Main protease (Mpro) target of SARS-CoV-2. The aqueous extract of Anvillea radiata did not induce any signs of toxicity. 3,5-Dicaffeoylquinic acid, Spinacetin, 9α-Epoxyparthenolide, jaceosidin, and isorhamnetin from Anvillea radiata were selected as potential inhibitors of SARS-Cov-2 to develop new drugs anti-COVID-19.

Chemical-informatics approach to COVID-19 drug discovery: Monte Carlo based QSAR, virtual screening and molecular docking study of some in-house molecules as papain-like protease (PLpro) inhibitors.

World Health Organization characterized novel coronavirus disease (COVID-19), caused by severe acute respiratory syndrome (SARS) coronavirus-2 (SARS-CoV-2) as world pandemic. This infection has been spreading alarmingly by causing huge social and economic disruption. In order to response quickly, the inhibitors already designed against different targets of previous human coronavirus infections will be a great starting point for anti-SARS-CoV-2 inhibitors. In this study, our approach integrates different ligand based drug design strategies of some in-house chemicals. The study design was composed of some major aspects: (a) classification QSAR based data mining of diverse SARS-CoV papain-like protease (PLpro) inhibitors, (b) QSAR based virtual screening (VS) to identify in-house molecules that could be effective against putative target SARS-CoV PLpro and (c) finally validation of hits through receptor-ligand interaction analysis. This approach could be used to aid in the process of COVID-19 drug discovery. It will introduce key concepts, set the stage for QSAR based screening of active molecules against putative SARS-CoV-2 PLpro enzyme. Moreover, the QSAR models reported here would be of further use to screen large database. This study will assume that the reader is approaching the field of QSAR and molecular docking based drug discovery against SARS-CoV-2 PLpro with little prior knowledge.Communicated by Ramaswamy H. Sarma.

Assessment of antiviral potencies of cannabinoids against SARS-CoV-2 using computational and in vitro approaches.

Effective treatment choices to the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are limited because of the absence of effective target-based therapeutics. The main object of the current research was to estimate the antiviral activity of cannabinoids (CBDs) against the human coronavirus SARS-CoV-2. In the presented research work, we performed in silico and in vitro experiments to aid the sighting of lead CBDs for treating the viral infections of SARS-CoV-2. Virtual screening was carried out for interactions between 32 CBDs and the SARS-CoV-2 Mpro enzyme. Afterward, in vitro antiviral activity was carried out of five CBDs molecules against SARS-CoV-2. Interestingly, among them, two CBDs molecules namely Δ9 -tetrahydrocannabinol (IC50 = 10.25 µM) and cannabidiol (IC50 = 7.91 µM) were observed to be more potent antiviral molecules against SARS-CoV-2 compared to the reference drugs lopinavir, chloroquine, and remdesivir (IC50 ranges of 8.16-13.15 µM). These molecules were found to have stable conformations with the active binding pocket of the SARS-CoV-2 Mpro by molecular dynamic simulation and density functional theory. Our findings suggest cannabidiol and Δ9 -tetrahydrocannabinol are possible drugs against human coronavirus that might be used in combination or with other drug molecules to treat COVID-19 patients.

Assessment of effective imidazole derivatives against SARS-CoV-2 main protease through computational approach.

Because of the fast increase in deaths due to Corona Viral Infection in majority region in the world, the detection of drugs potent of this infection is a major need. With this idea, docking study was executed on eighteen imidazole derivatives based on 7-chloro-4-aminoquinoline against novel Coronavirus (SARS-CoV-2). In this study, we carried out a docking study of these molecules in the active site of SARS-CoV-2 main protease. The result indicate that Molecules N° 3, 7 and 14 have more binding energy with SARS-CoV-2 main protease recently crystallized (pdb code 6LU7) in comparison with the other imidazole derivatives and the two drug; Chloroquine and hydroxychloroquine. Because of the best energy of interaction, these three molecules could have the most potential antiviral treatment of COVID-19 than the other studied compounds. The structures with best affinity in the binding site of the protease have more than 3 cycles and electronegative atoms in the structure. This may increase the binding affinity of these molecules because of formation of π-bonds, halogen interactions and/or Hydrogen bond interactions between compounds and the enzyme. So, compounds with more cycles and electronegative atoms could have a potent inhibition of SARS-CoV-2 main protease.

Ligand-centered assessment of SARS-CoV-2 drug target models in the Protein Data Bank.

A bright spot in the SARS-CoV-2 (CoV-2) coronavirus pandemic has been the immediate mobilization of the biomedical community, working to develop treatments and vaccines for COVID-19. Rational drug design against emerging threats depends on well-established methodology, mainly utilizing X-ray crystallography, to provide accurate structure models of the macromolecular drug targets and of their complexes with candidates for drug development. In the current crisis, the structural biological community has responded by presenting structure models of CoV-2 proteins and depositing them in the Protein Data Bank (PDB), usually without time embargo and before publication. Since the structures from the first-line research are produced in an accelerated mode, there is an elevated chance of mistakes and errors, with the ultimate risk of hindering, rather than speeding up, drug development. In the present work, we have used model-validation metrics and examined the electron density maps for the deposited models of CoV-2 proteins and a sample of related proteins available in the PDB as of April 1, 2020. We present these results with the aim of helping the biomedical community establish a better-validated pool of data. The proteins are divided into groups according to their structure and function. In most cases, no major corrections were necessary. However, in several cases significant revisions in the functionally sensitive area of protein-inhibitor complexes or for bound ions justified correction, re-refinement, and eventually reversioning in the PDB. The re-refined coordinate files and a tool for facilitating model comparisons are available at https://covid-19.bioreproducibility.org. DATABASE: Validated models of CoV-2 proteins are available in a dedicated, publicly accessible web service https://covid-19.bioreproducibility.org.

Changes in nationwide Medicare and Medicaid expenditures on lipid-lowering therapies after proprotein convertase/subtilisin type 9 inhibitor availability.

BACKGROUND: Several advances in lipid-lowering pharmacotherapy and changes in generic formulation availability occurred between 2013 and 2017. OBJECTIVE: We sought to examine nationwide trends in Medicare Part D and Medicaid expenditures on lipid-lowering therapies from 2013 to 2017. METHODS: We aggregated 662.2 million Medicare Part D and Medicaid prescription claims with associated expense data for 2013 to 2017 from the Medicare and Medicaid Drug Spending Dashboards for nine therapeutic classes of lipid-lowering therapies. RESULTS: Total Medicare Part D expenditures on lipid-lowering therapies was $7.01 billion in 2013 and $5.07 billion in 2017. Total Medicaid lipid-lowering therapy expenditures decreased from $440.9 million in 2013 to $398.7 million in 2017. Annual Medicare expenditures on Crestor were $2.2 billion in 2013 and $0.31 billion in 2017. Annual Medicaid Crestor expenditures decreased from $92.4 million in 2013 to $30.1 million in 2017. From 2013 to 2016, Medicare expenditures on Zetia decreased from $0.89 billion to $0.70 billion, whereas Medicaid Zetia expenditures decreased from $38.6 million in 2013 to $25.4 million in 2017. In 2017, PCSK9 inhibitors accounted for $317.3 million and $14.2 million in Medicare and Medicaid expenditures, respectively. CONCLUSIONS: Overall Medicare and Medicaid expenditures on lipid-lowering therapies decreased by $2.5 billion from 2013 to 2017.

Fast Identification of Possible Drug Treatment of Coronavirus Disease-19 (COVID-19) through Computational Drug Repurposing Study.

The recent outbreak of novel coronavirus disease-19 (COVID-19) calls for and welcomes possible treatment strategies using drugs on the market. It is very efficient to apply computer-aided drug design techniques to quickly identify promising drug repurposing candidates, especially after the detailed 3D structures of key viral proteins are resolved. The virus causing COVID-19 is SARS-CoV-2. Taking advantage of a recently released crystal structure of SARS-CoV-2 main protease in complex with a covalently bonded inhibitor, N3 (Liu et al., 10.2210/pdb6LU7/pdb), I conducted virtual docking screening of approved drugs and drug candidates in clinical trials. For the top docking hits, I then performed molecular dynamics simulations followed by binding free energy calculations using an end point method called MM-PBSA-WSAS (molecular mechanics/Poisson-Boltzmann surface area/weighted solvent-accessible surface area; Wang, Chem. Rev. 2019, 119, 9478; Wang, Curr. Comput.-Aided Drug Des. 2006, 2, 287; Wang; ; Hou J. Chem. Inf. Model., 2012, 52, 1199). Several promising known drugs stand out as potential inhibitors of SARS-CoV-2 main protease, including carfilzomib, eravacycline, valrubicin, lopinavir, and elbasvir. Carfilzomib, an approved anticancer drug acting as a proteasome inhibitor, has the best MM-PBSA-WSAS binding free energy, -13.8 kcal/mol. The second-best repurposing drug candidate, eravacycline, is synthetic halogenated tetracycline class antibiotic. Streptomycin, another antibiotic and a charged molecule, also demonstrates some inhibitory effect, even though the predicted binding free energy of the charged form (-3.8 kcal/mol) is not nearly as low as that of the neutral form (-7.9 kcal/mol). One bioactive, PubChem 23727975, has a binding free energy of -12.9 kcal/mol. Detailed receptor-ligand interactions were analyzed and hot spots for the receptor-ligand binding were identified. I found that one hot spot residue, His41, is a conserved residue across many viruses including SARS-CoV, SARS-CoV-2, MERS-CoV, and hepatitis C virus (HCV). The findings of this study can facilitate rational drug design targeting the SARS-CoV-2 main protease.

α-Ketoamides as Broad-Spectrum Inhibitors of Coronavirus and Enterovirus Replication: Structure-Based Design, Synthesis, and Activity Assessment.

The main protease of coronaviruses and the 3C protease of enteroviruses share a similar active-site architecture and a unique requirement for glutamine in the P1 position of the substrate. Because of their unique specificity and essential role in viral polyprotein processing, these proteases are suitable targets for the development of antiviral drugs. In order to obtain near-equipotent, broad-spectrum antivirals against alphacoronaviruses, betacoronaviruses, and enteroviruses, we pursued a structure-based design of peptidomimetic α-ketoamides as inhibitors of main and 3C proteases. Six crystal structures of protease-inhibitor complexes were determined as part of this study. Compounds synthesized were tested against the recombinant proteases as well as in viral replicons and virus-infected cell cultures; most of them were not cell-toxic. Optimization of the P2 substituent of the α-ketoamides proved crucial for achieving near-equipotency against the three virus genera. The best near-equipotent inhibitors, 11u (P2 = cyclopentylmethyl) and 11r (P2 = cyclohexylmethyl), display low-micromolar EC50 values against enteroviruses, alphacoronaviruses, and betacoronaviruses in cell cultures. In Huh7 cells, 11r exhibits three-digit picomolar activity against the Middle East Respiratory Syndrome coronavirus.

Good and bad molecular fingerprints for human rhinovirus 3C protease inhibition: identification, validation, and application in designing of new inhibitors through Monte Carlo-based QSAR study.

HRV 3 C protease (HRV 3Cpro) is an important target for common cold and upper respiratory tract infection. Keeping in view of the non-availability of drug for the treatment, newer computer-based modelling strategies should be applied to rationalize the process of antiviral drug discovery in order to decrease the valuable time and huge expenditure of the process. The present work demonstrates a structure wise optimization using Monte Carlo-based QSAR method that decomposes ligand compounds (in SMILES format) into several molecular fingerprints/descriptors. The current state-of-the-art in QSAR study involves the balance of correlation approach using four different sets: training, invisible training, calibration, and validation. The final models were also validated through mean absolute error, index of ideality of correlation, Y-randomization and applicability domain analysis. R2 and Q2 values for the best model were 0.8602, 0.8507 (training); 0.8435, 0.8331 (invisible training); 0.7424, 0.7020 (calibration); 0.5993, 0.5216 (validation), respectively. The process identified some molecular substructures as good and bad fingerprints depending on their effect to increase or decrease the HRV 3Cpro inhibition. Finally, new inhibitors were designed based on the fundamental concept to replace the bad fragments with the good fragments as well as including more good fragments into the structure. The study points out the importance of the fingerprint based drug design strategy through Monte Carlo optimization method in the modelling of HRV 3Cpro inhibitors.

Barriers to PCSK9 inhibitor prescriptions for patients with high cardiovascular risk: Results of a healthcare provider survey conducted by the National Lipid Association.

BACKGROUND: Statin therapy is recommended for reducing atherosclerotic cardiovascular disease (ASCVD) risk. Significant risk can remain because of insufficient clinical response or statin intolerance. Proprotein convertase subtilisin/kexin type-9 (PCSK9) therapy lowers low-density lipoprotein cholesterol and has recently been shown to lower ASCVD events. OBJECTIVE: The aim of the study was to assess the barriers and challenges experienced with the access and approval reimbursement process for PCSK9 inhibitor prescriptions. METHODS: In 2016, the National Lipid Association conducted an online survey on PCSK9 inhibitor use and barriers to prescription among experienced healthcare workers who provide care to high-risk patients with ASCVD or familial hypercholesterolemia (FH). RESULTS: There were 434 respondent healthcare workers with extensive experience in treating lipid disorders. PCSK9 inhibitors are considered by 71.3% of respondent providers with statin-intolerant patients. There were high rates (>85%) of initial denial. The major barriers to approvals were insurer processes, provider documentation (inadequate documentation of maximally tolerated statin dose, diagnostic criteria for FH, number of statins failed if statin intolerant and most recent low-density lipoprotein cholesterol), and administrative burden (time, staff, paperwork, and appeals). Provider approval rates for getting ≥75% patients approved were higher for FH (43%) than for ASCVD patients (36%). Among providers with good approval rates, documentation was the most critical factor. Barriers more difficult to overcome include perceived higher threshold requirements by payers, drugs not on formulary, and drug costs. CONCLUSIONS: Healthcare providers encounter significant barriers to PCSK9 inhibitor prescriptions; many of these are related to documentation issues and can be overcome with checklists, staff support, and experience.

Microdialysis Sampling from Wound Fluids Enables Quantitative Assessment of Cytokines, Proteins, and Metabolites Reveals Bone Defect-Specific Molecular Profiles.

Bone healing involves a variety of different cell types and biological processes. Although certain key molecules have been identified, the molecular interactions of the healing progress are not completely understood. Moreover, a clinical routine for predicting the quality of bone healing after a fracture in an early phase is missing. This is mainly due to a lack of techniques to comprehensively screen for cytokines, growth factors and metabolites at their local site of action. Since all soluble molecules of interest are present in the fracture hematoma, its in-depth assessment could reveal potential markers for the monitoring of bone healing. Here, we describe an approach for sampling and quantification of cytokines and metabolites by using microdialysis, combined with solid phase extractions of proteins from wound fluids. By using a control group with an isolated soft tissue wound, we could reveal several bone defect-specific molecular features. In bone defect dialysates the neutrophil chemoattractants CXCL1, CXCL2 and CXCL3 were quantified with either a higher or earlier response compared to dialysate from soft tissue wound. Moreover, by analyzing downstream adaptions of the cells on protein level and focusing on early immune response, several proteins involved in the immune cell migration and activity could be identified to be specific for the bone defect group, e.g. immune modulators, proteases and their corresponding inhibitors. Additionally, the metabolite screening revealed different profiles between the bone defect group and the control group. In summary, we identified potential biomarkers to indicate imbalanced healing progress on all levels of analysis.

Assessment of a Protease Inhibitor Peptide for Anti-Ageing.

Ageing and skin exposure to UV radiation induces production and activation of matrix metalloproteinases (MMPs) and human neutrophil elastase (HNE). These enzymes are known to break down the extracellular matrix (ECM) which leads to wrinkle formation. Here, we demonstrated the potential of a solid-in-oil nanodispersion containing a competitive inhibitor peptide of HNE mixed with hyaluronic acid (HA), displaying 158 nm of mean diameter, to protect the skin against the ageing effects. Western blot analysis demonstrated that activation of MMP-1 in fibroblasts by HNE treatment is inhibited by the solid-in-oil nanodispersion containing the peptide and HA. The results clearly demonstrate that solid-in-oil nanodispersion containing the HNE inhibitor peptide is a promising strategy for anti-ageing effects. This effect can be seen particularly by ECM regulation by affecting fibroblasts. The formulation also enhances the formation of thicker bundles of actin filaments.

Enabling Low Cost Biopharmaceuticals: A Systematic Approach to Delete Proteases from a Well-Known Protein Production Host Trichoderma reesei.

The filamentous fungus Trichoderma reesei has tremendous capability to secrete proteins. Therefore, it would be an excellent host for producing high levels of therapeutic proteins at low cost. Developing a filamentous fungus to produce sensitive therapeutic proteins requires that protease secretion is drastically reduced. We have identified 13 major secreted proteases that are related to degradation of therapeutic antibodies, interferon alpha 2b, and insulin like growth factor. The major proteases observed were aspartic, glutamic, subtilisin-like, and trypsin-like proteases. The seven most problematic proteases were sequentially removed from a strain to develop it for producing therapeutic proteins. After this the protease activity in the supernatant was dramatically reduced down to 4% of the original level based upon a casein substrate. When antibody was incubated in the six protease deletion strain supernatant, the heavy chain remained fully intact and no degradation products were observed. Interferon alpha 2b and insulin like growth factor were less stable in the same supernatant, but full length proteins remained when incubated overnight, in contrast to the original strain. As additional benefits, the multiple protease deletions have led to faster strain growth and higher levels of total protein in the culture supernatant.