Molecular Mechanism of the Non-Covalent Orally Targeted SARS-CoV-2 Mpro Inhibitor S-217622 and Computational Assessment of Its Effectiveness against Mainstream Variants.

Convenient and efficient therapeutic agents are urgently needed to block the continued spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, the mechanism for the novel orally targeted SARS-CoV-2 main protease (Mpro) inhibitor S-217622 is revealed through a molecular dynamics simulation. The difference in the movement modes of the S-217622-Mpro complex and apo-Mpro suggested S-217622 could inhibit the motility intensity of Mpro, thus maintaining their stable binding. Subsequent energy calculations showed that the P2 pharmacophore possessed the highest energy contribution among the three pharmacophores of S-217622. Additionally, hot-spot residues H41, M165, C145, E166, and H163 have strong interactions with S-217622. To further investigate the resistance of S-217622 to six mainstream variants, the binding modes of S-217622 with these variants were elucidated. The subtle differences in energy compared to that of the wild type implied that the binding patterns of these systems were similar, and S-217622 still inhibited these variants. We hope this work will provide theoretical insights for optimizing novel targeted Mpro drugs.

Anti-HIV-drug and phyto-flavonoid combination against SARS-CoV-2: a molecular docking-simulation base assessment.

At the health emergence, no such potent prophylactic therapy is available to control the deadly emerged Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). However, existing antiviral, anti-inflammatory, antimalarial drugs is the only option against SARS-CoV-2, but it may be harmful to patients without more clinical evidence. As an alternative solution, we proposed a newer hypothesis using the selective 10 potent anti-HIV drugs and flavonoid class of phytochemicals from previous reports to use in combination against SARS-CoV-2. Primarily, 10 anti-HIV protease inhibitor drugs and 10 phyto-flavonoids as ligands in molecular docking study against the putative target, the SARS-CoV-2-main protease (Mpro) ID: 6Y2E), as an essential enzyme in viral genome replication. According to molecular docking and drug-ability scores of each ligand, the anti-HIV drug, the darunavir (with a docking score, -10.25 kcal/mol and drug-likeness rating, 0.60) and the quercetin-3-rhamnoside (with a docking score, -10.90 kcal/mol and drug-likeness rating, 0.82) were selected for further analysis in combined effect. Perceptibly, the combined 'anti-HIV drug and phyto-flavonoid' docking complex has actively interacted with eight strong H-bonds with stability, briefly elucidated through RMRD-, RMSF- Rg-plots and MM/PBSA-binding energy calculation during 100 ns than the individual against SARS-CoV-2-Mpro. Thus, the 'anti-HIV-drug-phyto-flavonoid' combination therapy could be used against SARS-CoV-2 after some experimental validation.Communicated by Ramaswamy H. Sarma.

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.

A COVID moonshot: assessment of ligand binding to the SARS-CoV-2 main protease by saturation transfer difference NMR spectroscopy.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiological cause of the coronavirus disease 2019, for which no effective antiviral therapeutics are available. The SARS-CoV-2 main protease (Mpro) is essential for viral replication and constitutes a promising therapeutic target. Many efforts aimed at deriving effective Mpro inhibitors are currently underway, including an international open-science discovery project, codenamed COVID Moonshot. As part of COVID Moonshot, we used saturation transfer difference nuclear magnetic resonance (STD-NMR) spectroscopy to assess the binding of putative Mpro ligands to the viral protease, including molecules identified by crystallographic fragment screening and novel compounds designed as Mpro inhibitors. In this manner, we aimed to complement enzymatic activity assays of Mpro performed by other groups with information on ligand affinity. We have made the Mpro STD-NMR data publicly available. Here, we provide detailed information on the NMR protocols used and challenges faced, thereby placing these data into context. Our goal is to assist the interpretation of Mpro STD-NMR data, thereby accelerating ongoing drug design efforts.

SARS-CoV-2 Papain-Like Protease Potential Inhibitors-In Silico Quantitative Assessment.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encodes the papain-like protease (PLpro). The protein not only plays an essential role in viral replication but also cleaves ubiquitin and ubiquitin-like interferon-stimulated gene 15 protein (ISG15) from host proteins, making it an important target for developing new antiviral drugs. In this study, we searched for novel, noncovalent potential PLpro inhibitors by employing a multistep in silico screening of a 15 million compound library. The selectivity of the best-scored compounds was evaluated by checking their binding affinity to the human ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), which, as a deubiquitylating enzyme, exhibits structural and functional similarities to the PLpro. As a result, we identified 387 potential, selective PLpro inhibitors, from which we retrieved the 20 best compounds according to their IC50 values toward PLpro estimated by a multiple linear regression model. The selected candidates display potential activity against the protein with IC50 values in the nanomolar range from approximately 159 to 505 nM and mostly adopt a similar binding mode to the known, noncovalent SARS-CoV-2 PLpro inhibitors. We further propose the six most promising compounds for future in vitro evaluation. The results for the top potential PLpro inhibitors are deposited in the database prepared to facilitate research on anti-SARS-CoV-2 drugs.

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.

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.

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.

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.

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.

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.

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.

Validation of an electrospray ionisation LC-MS/MS method for quantitative analysis of telaprevir and its R-diastereomer.

A sensitive high-performance reverse phase liquid chromatography-positive ion electrospray tandem mass spectrometry method was developed and validated for the quantification of telaprevir and its inactive R-diastereomer (VRT-127394) in human plasma. The analytes and the internal standard (telaprevir-d11) were extracted from plasma by liquid-liquid extraction using tert-Butyl methyl ether (TBME). Chromatographic separation was achieved on a reversed-phase Accucore C18 column with a gradient programme consisting of water:ammonia (25%), 100:0.01 (v/v) (mobile phase A) and ACN:MeOH:ammonia (25%), 15:85:0.01 (v/v/v) (mobile phase B). The MS acquisition was performed with selective reaction monitoring mode using the respective [M+H](+) ions, m/z 680.59→322.42 for telaprevir and VRT-127394, and 691.15→110.13 for telaprevir-d11. The assay exhibited a linear dynamic range of 5-5000ng/mL for telaprevir and VRT-127394. Acceptable precision (%RSD<6.5%) and accuracy (94-108%) were obtained for concentrations over the range of the standard curve. A procedure was established to stabilise the plasma to prevent ex vivo interconversion of the isomers.

Development of [Ile4°]HTLV-I protease inhibition assay using novel fluorogenic and chromogenic substrate.

HTLV-I is a debilitating and/or lethal retrovirus that causes HTLV-I-associated myelopathy/tropical spastic paraparesis, adult T-cell leukemia and several inflammatory diseases. HTLV-I protease is an aspartic retropepsin involved in HTLV-I replication and its inhibition could treatHTLV-I infection. A recombinant L40I mutant HTLV-I protease was designed and obtained from Escherichia coli, self-processingand purification by ion-exchange chromatography. The protease was refolded by a one-step dialysis and recovered activity. The cleavage efficiency of the [Ile4°]HTLV-I protease was at least 300 times higher for a fluorescent substratethan that of our previously reported recombinant His-tagged non-mutated HTLV-I protease. In addition, we designed and synthesized a substrate containing a highly fluorescent Mca moiety in the fragment before the scissile bond, and a chromogenic p-nitrophenylalanine moiety after the scissile bond that greatly amplified spectrometry detection and improved the HTLV-I protease inhibition potency assay. The HTLV-I protease inhibition assay with the [Ile4°]HTLV-I protease and fluorogenic substrate requires distinctively less protease, substrate, inhibitor and assay time than our previous methods. This means our new assay is more cost-effective and more time-efficient while being reproducible and less labor-intensive.

Boom in the development of non-peptidic beta-secretase (BACE1) inhibitors for the treatment of Alzheimer's disease.

Beta-amyloid cleaving enzyme-1 (BACE1) has become a significant target for the therapy of Alzheimer's disease. After the discovery of the first non-peptidomimetic beta-secretase inhibitors by Takeda Chemicals in 2001, several research teams focused on SAR development of these agents. The non-peptidic BACE1 inhibitors may potentially overcome the classical problems associated with the peptide structure of first generation, such as blood-brain barrier crossing, poor oral bioavailability and susceptibility to P-glycoprotein transport. In the past 6 years a boom in research of non-peptidic BACE1 inhibitors has disseminated findings over hundreds of publications and patents. The rapidly growing literature has been reviewed with particular emphasis on literature of pharmaceutical companies.

Automated, fast, and sensitive quantification of drugs in human plasma by LC/LC-MS: quantification of 6 protease inhibitors and 3 nonnucleoside transcriptase inhibitors.

An analytic assay based on automated sample preparation and liquid chromatography (LC) coupled with electrospray mass spectrometry (ESI-MS) was developed for the quantification of 6 protease inhibitors (PIs) and 3 nonnucleoside reverse transcriptase inhibitors (NNRTIs). The 6 PIs, amprenavir, indinavir, ritonavir, lopinavir, nelfinavir, and saquinavir, as well as the three NNRTIs, nevirapine, efavirenz, and delavirdine, require a succinct analysis technique for therapeutic drug monitoring in HIV/AIDS patients. After protein precipitation, samples were loaded on a C8, 10 x 4-mm extraction column, washed, and, after activation of the column-switching valve, backflushed onto the 30 x 2.1 mm C8 analytic column. [M+H] ions were detected in the selected ion mode. A nonlinear fit (y(-1) = a + b/x, all r2 > 0.999) for amprenavir, indinavir, ritonavir, lopinavir, nelfinavir, and saquinavir and a linear fit (y = ax + b, all r2 > 0.999) for nevirapine, efavirenz, and delavirdine led to best regression. Absolute recoveries were as follows: PIs > 81%; NNRTIs > 76%. Interday and intraday precision were <12.5% for the PIs and <11.7% for the NNRTIs. Interday and intraday accuracy were <12.2% for the PIs and <14.9% for the NNRTIs. Limits of quantification were 20, 40, 50, 40, 40, 20, and 100 microg/L for amprenavir, indinavir, ritonavir, lopinavir, nelfinavir, saquinavir, and the NNRTIs, respectively. The assay allows fast analysis of patient samples for therapeutic drug monitoring (TDM) and has successfully been used for TDM and pharmacokinetic drug-drug interactions studies.

A heterogeneous enzymatic assay for quantification of Plasmepsin II activity and the evaluation of its inhibitors.

The emergence and worldwide spreading of Plasmodium falciparum strains that shown to be resistant to traditional drugs is considered a very serious health problem, given the high mortality and morbidity rate of Malaria. In the search for new drugs against this parasite, Hb hydrolyzing enzymes, such as Plasmepsin II (Plm II), have been classified as very promising targets for therapeutic attacks. In this work, it is developed a cheap and high-throughput heterogeneous enzymatic assay for measuring Plasmepsin II activity in order to use it as a tool in the discovery of new inhibitors of this enzyme. In this assay, Plasmepsin II acts upon a solid-phase bound synthetic peptide (DU2) whose sequence comprises the cleavage site F(33)-L(34) present in Hb alpha-chain. The peptide surface density is quantified by means of a classical ELISA-based procedure. In order to estimate the kinetic constants of the system and to quantify both, enzymatic and inhibitory activity, it was used a model for the kinetics of enzyme quasi-saturable systems previously developed by our group, that fitted very well to the experimental data. It was used Pepstatin as a model inhibitor of Plasmepsin II and the resulting dose-response relation agreed with the expected behavior for the Pepstatin-Plasmepsin II pair under the employed experimental conditions.

Analyses of activity for factor Xa inhibitors based on Monte Carlo simulations.

Monte Carlo/Extended Linear Response (MC/ELR) simulations have been conducted on 60 inhibitors of human factor Xa to determine the important interactions associated with their activity. A variety of physicochemical descriptors were configurationally averaged during the course of the simulations of each inhibitor bound to factor Xa and free in water. A regression equation was then derived; it reproduces the experimental inhibition data with a correlation coefficient, r(2), of 0.74, an rms error of 0.67 kcal/mol, and an average unsigned error of 0.60 kcal/mol using only two physically reasonable descriptors. The two factors that emerged as important in determining inhibitory potential are (1) favorable van der Waals interactions between protein and ligand and (2) direct hydrogen bonding between the inhibitor and protein. The conclusions were supported with structural analyses and results of MC/free energy perturbation (FEP) calculations.