Repurposing potential of posaconazole and grazoprevir as inhibitors of SARS-CoV-2 helicase

Targeting neuroblastoma by small-molecule inhibitors of human ALYREF protein: mechanistic insights using molecular dynamics simulations

Neuroblastoma is a tumour of the sympathetic nervous system mainly prevalent in children. Many strategies have been employed to target several drug-targetable proteins for the clinical management of neuroblastoma. However, the heterogeneous nature of neuroblastoma presents serious challenges in drug development for its treatment. Albeit numerous medications have been developed to target various signalling pathways in neuroblastoma, the redundant nature of the tumour pathways makes its suppression unsuccessful. Recently, the quest for neuroblastoma therapy resulted in the identification of human ALYREF, a nuclear protein that plays an essential role in tumour growth and progression. Therefore, this study used the structure-based drug discovery method to identify the putative inhibitors targeting ALYREF for the Neuroblastoma treatment. Herein, a library of 119 blood-brain barrier crossing small molecules from the ChEMBL database was downloaded and docked against the predicted binding pocket of the human ALYREF protein. Based on docking scores, the top four compounds were considered for intermolecular interactions and molecular dynamics simulation analysis, which revealed CHEMBL3752986 and CHEMBL3753744 with substantial affinity and stability with the ALYREF. These results were further supported by binding free energies and essential dynamics analysis of the respective complexes. Hence, this study advocates the sorted compounds targeting ALYREF for further in vitro and in vivo assessment to develop a drug against neuroblastoma.Communicated by Ramaswamy H. Sarma.

Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics

With more than 5 million fatalities and close to 300 million reported cases, COVID-19 is the first documented pandemic due to a coronavirus that continues to be a major health challenge. Despite being rapid, uncontrollable, and highly infectious in its spread, it also created incentives for technology development and redefined public health needs and research agendas to fast-track innovations to be translated. Breakthroughs in computational biology peaked during the pandemic with renewed attention to making all cutting-edge technology deliver agents to combat the disease. The demand to develop effective treatments yielded surprising collaborations from previously segregated fields of science and technology. The long-standing pharmaceutical industry's aversion to repurposing existing drugs due to a lack of exponential financial gain was overrun by the health crisis and pressures created by front-line researchers and providers. Effective vaccine development even at an unprecedented pace took more than a year to develop and commence trials. Now the emergence of variants and waning protections during the booster shots is resulting in breakthrough infections that continue to strain health care systems. As of now, every protein of SARS-CoV-2 has been structurally characterized and related host pathways have been extensively mapped out. The research community has addressed the druggability of a multitude of possible targets. This has been made possible due to existing technology for virtual computer-assisted drug development as well as new tools and technologies such as artificial intelligence to deliver new leads. Here in this article, we are discussing advances in the drug discovery field related to target-based drug discovery and exploring the implications of known target-specific agents on COVID-19 therapeutic management. The current scenario calls for more personalized medicine efforts and stratifying patient populations early on for their need for different combinations of prognosis-specific therapeutics. We intend to highlight target hotspots and their potential agents, with the ultimate goal of using rational design of new therapeutics to not only end this pandemic but also uncover a generalizable platform for use in future pandemics.

Coronaviruses SARS-CoV, MERS-CoV, and SARS-CoV-2 helicase inhibitors: A systematic review of in vitro studies

Introduction

The recent outbreak of SARS-CoV-2 significantly increased the need to find inhibitors that target the essential enzymes for virus replication in the host cells. This systematic review was conducted to identify potential inhibitors of SARS-CoV, MERS-CoV, and SARS-CoV-2 helicases that have been tested by in vitro methods. The inhibition mechanisms of these compounds were discussed in this review, in addition to their cytotoxic and viral infection protection properties.

Methods

The databases PUBMED/MEDLINE, EMBASE, SCOPUS, and Web of Science were searched using different combinations of the keywords "helicase", "nsp13", "inhibitors", "coronaviridae", "coronaviruses", "virus replication", "replication", and "antagonists and inhibitors".

Results

By the end of this search, a total of 6854 articles had been identified. Thirty-one articles were included in this review. These studies reported the inhibitory effects of 309 compounds on SARS-CoV, MERS-CoV, and SARS-CoV-2 helicase activities measured by in vitro methods. Helicase inhibitors were categorized according to the type of coronavirus and the type of tested enzymatic activity, nature, approval, inhibition level, cytotoxicity, and viral infection protection effects. These inhibitors are classified according to the site of their interaction with the coronavirus helicases into four types: zinc-binding site inhibitors, nucleic acid binding site inhibitors, nucleotide-binding site inhibitors, and inhibitors with no clear interaction site.

Conclusion

Evidence from in vitro studies suggests that helicase inhibitors have a high potential as antiviral agents. Several helicase inhibitors tested in vitro showed good antiviral activities while maintaining moderate cytotoxicity. These inhibitors should be clinically investigated to determine their efficiency in treating different coronavirus infections, particularly COVID-19.

Speed vs Accuracy: Effect on Ligand Pose Accuracy of Varying Box Size and Exhaustiveness in AutoDock Vina

Structure-based virtual high-throughput screening involves docking chemical libraries to targets of interest. A parameter pertinent to the accuracy of the resulting pose is the root mean square deviation (RMSD) from a known crystallographic structure, i. e., the 'docking power'. Here, using a popular algorithm, Autodock Vina, as a model program, we evaluate the effects of varying two common docking parameters: the box size (the size of docking search space) and the exhaustiveness of the global search (the number of independent runs starting from random ligand conformations) on the RMSD from the PDBbind v2017 refined dataset of experimental protein-ligand complexes. Although it is clear that exhaustiveness is an important parameter, there is wide variation in the values used, with variation between 1 and >100. We, therefore, evaluated a combination of cubic boxes of different sizes and five exhaustiveness values (1, 8, 25, 50, 75, 100) within the range of those commonly adopted. The results show that the default exhaustiveness value of 8 performs well overall for most box sizes. In contrast, for all box sizes, but particularly for large boxes, an exhaustiveness value of 1 led to significantly higher median RMSD (mRMSD) values. The docking power was slightly improved with an exhaustiveness of 25, but the mRMSD changes little with values higher than 25. Therefore, although low exhaustiveness is computationally faster, the results are more likely to be far from reality, and, conversely, values >25 led to little improvement at the expense of computational resources. Overall, we recommend users to use at least the default exhaustiveness value of 8 for virtual screening calculations.

DNA binding studies of antifungal drug posaconazole using spectroscopic and molecular docking methods

The binding studies of DNA with small molecules have been an emerging field of research all the time since DNA as the genetic material is a major biological target for various drugs. Interpretation of small molecule-DNA binding helps in understanding their interactions with designing new drugs of greater medicinal activity. Posaconazole is an antifungal drug in the class of triazoles which are known to possess numerous pharmacological properties. In this work, the nature of the binding of posaconazole with calf-thymus DNA has been studied using spectroscopic techniques and molecular docking studies. A binding constant of the order of 10³ M^-1 was observed from UV-visible and fluorescence studies for the interaction between posaconazole and calf-thymus DNA. The fluorescence property of posaconazole was found to be quenched by calf-thymus DNA with a quenching constant of the order of 10³ M^-1. Competitive displacement of ethidium bromide and Hoechst 33258 by posaconazole using fluorescence technique suggested minor groove binding of posaconazole in calf-thymus DNA. Confirmation of the binding mode was further complemented by the viscosity measurement and DNA melting studies followed by KI quenching experiments. The studies on the effect of ionic strength on the binding suggested a possible role of electrostatic force in the interaction. Molecular docking studies reflected a crescent shape of the posaconazole within the minor groove of calf-thymus DNA validating the experimental findings showing the residues involved in the interaction.

Antiviral Disaccharide Lead Compounds against SARS-CoV-2 through Computer-Aided High-Throughput Screen

SARS-CoV-2 infects human epithelial cells through specific interaction with angiotensin-converting enzyme 2 (ACE2). In addition, heparan sulfate proteoglycans act as the attachment factor to promote the binding of viral spike protein receptor binding domain (RBD) to ACE2 on host cells. Though the rapid development of vaccines has contributed significantly to preventing severe disease, mutated SARS-CoV-2 strains, especially the SARS-CoV-2 Omicron variant, show increased affinity of RBD binding to ACE2, leading to immune escape. Thus, there is still an unmet need for new antiviral drugs. In this study, we constructed pharmacophore models based on the spike RBD of SARS-CoV-2 and SARS-CoV-2 Omicron variant and performed virtual screen for best-hit compounds from our disaccharide library. Screening of 96 disaccharide structures identified two disaccharides that displayed higher binding affinity to RBD in comparison to reported small molecule antiviral drugs. Further, screening PharmMapper demonstrated interactions of the disaccharides with a number of inflammatory cytokines, suggesting a potential for disaccharides with multiple-protein targets.

Therapeutic potential of compounds targeting SARS-CoV-2 helicase

The economical and societal impact of COVID-19 has made the development of vaccines and drugs to combat SARS-CoV-2 infection a priority. While the SARS-CoV-2 spike protein has been widely explored as a drug target, the SARS-CoV-2 helicase (nsp13) does not have any approved medication. The helicase shares 99.8% similarity with its SARS-CoV-1 homolog and was shown to be essential for viral replication. This review summarizes and builds on existing research on inhibitors of SARS-CoV-1 and SARS-CoV-2 helicases. Our analysis on the toxicity and specificity of these compounds, set the road going forward for the repurposing of existing drugs and the development of new SARS-CoV-2 helicase inhibitors.

Targeting SARS-CoV-2 nsp13 Helicase and Assessment of Druggability Pockets: Identification of Two Potent Inhibitors by a Multi-Site In Silico Drug Repurposing Approach

The SARS-CoV-2 non-structural protein 13 (nsp13) helicase is an essential enzyme for viral replication and has been identified as an attractive target for the development of new antiviral drugs. In detail, the helicase catalyzes the unwinding of double-stranded DNA or RNA in a 5' to 3' direction and acts in concert with the replication-transcription complex (nsp7/nsp8/nsp12). In this work, bioinformatics and computational tools allowed us to perform a detailed conservation analysis of the SARS-CoV-2 helicase genome and to further predict the druggable enzyme's binding pockets. Thus, a structure-based virtual screening was used to identify valuable compounds that are capable of recognizing multiple nsp13 pockets. Starting from a database of around 4000 drugs already approved by the Food and Drug Administration (FDA), we chose 14 shared compounds capable of recognizing three out of four sites. Finally, by means of visual inspection analysis and based on their commercial availability, five promising compounds were submitted to in vitro assays. Among them, PF-03715455 was able to block both the unwinding and NTPase activities of nsp13 in a micromolar range.

Targeting an evolutionarily conserved "E-L-L" motif in spike protein to identify a small molecule fusion inhibitor against SARS-CoV-2

As newer variants of SARS-CoV-2 continue to pose major threats to global human health and economy, identifying novel druggable antiviral targets is the key toward sustenance. Here, we identify an evolutionarily conserved "Ex3Lx6L" ("E-L-L") motif present within the HR2 domain of all human and nonhuman coronavirus spike (S) proteins that play a crucial role in stabilizing its postfusion six-helix bundle (6-HB) structure and thus, fusion-mediated viral entry. Mutations within this motif reduce the fusogenicity of the S protein without affecting its stability or membrane localization. We found that posaconazole, an FDA-approved drug, binds to this "E-L-L" motif and impedes the formation of 6-HB, thus effectively inhibiting SARS-CoV-2 infection in cells. While posaconazole exhibits high efficacy in blocking S protein-mediated viral entry, mutations within the "E-L-L" motif rendered the protein completely resistant to the drug, establishing its specificity toward this motif. Our data demonstrate that posaconazole restricts early stages of infection through specific inhibition of membrane fusion and viral genome release into the host cell and is equally effective toward all major variants of concerns of SARS-CoV-2, including Beta, Kappa, Delta, and Omicron. Together, we show that this conserved essential "E-L-L" motif is an ideal target for the development of prophylactic and therapeutic interventions against SARS-CoV-2.

(+)-Usnic acid and its salts, inhibitors of SARS-CoV-2, identified by using in silico methods and in vitro assay

The pandemic caused by severe acute respiratory Coronavirus-2 (SARS-CoV-2) has been ongoing for over two years, and treatment for COVID-19, other than monoclonal antibodies, is urgently required. Accordingly, we have investigated the inhibitors of SARS-CoV-2 protein targets by high-throughput virtual screening using a marine natural products database. Considering the calculated molecular properties and availability of the compounds, (+)-usnic acid was selected as a suitable hit. In the in vitro antiviral assay of (+)-usnic acid by the immunofluorescence method, IC₅₀ was 7.99 μM, which is similar to that of remdesivir used as a positive control. The generalized Born and surface area continuum solvation (MM/GBSA) method was performed to find the potent target of (+)-usnic acid, and the Mpro protein showed the most prominent value, -52.05 kcal/mol, among other SARS-CoV-2 protein targets. Thereafter, RMSD and protein-ligand interactions were profiled using molecular dynamics (MD) simulations. Sodium usnate (NaU) improved in vitro assay results with an IC₅₀ of 5.33 μM and a selectivity index (SI) of 9.38. Additionally, when (+)-usnic acid was assayed against SARS-CoV-2 variants, it showed enhanced efficacy toward beta variants with an IC₅₀ of 2.92 μM and SI of 11.1. We report the in vitro anti-SARS-CoV-2 efficacy of (+)-usnic acid in this study and propose that it has the potential to be developed as a COVID-19 treatment if its in vivo efficacy has been confirmed.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Development of a database of RNA helicase inhibitors (VHIMDB) of pathogenic viruses and in silico screening for the potential drug molecules

The pathogenic RNA virus that infects human beings contains the RNA helicase enzyme, responsible for the replication of the viral genome. The enzyme is used as a suitable target against which the drug molecule acts. Therefore, the identification and proposal the novel compounds that can be targeted toward the helicase enzymes to stop the functioning of the enzyme is desirable. Although many viral helicase inhibitor molecules have been identified, still yet no unique database is available for these compounds. This research work envisages developing a curated database of RNA helicase inhibitors. The database contains in total of 353 entries that are computationally predicted and experimentally verified RNA helicase inhibitors. The database contains information like compound name, chemical properties, chemical format, and name of the target virus to which it acts against it with a user-friendly menu-driven search engine. Presently, the database is freely available at: https://vhimdb.rsatpathy.in/. Further, in silico screening of the whole database by drug-likeness and toxicity resulted in 14 potential drug molecules. The selected molecules were analyzed for their effectiveness in binding by using molecular docking score and interaction with the helicase enzymes of three categories of pathogenic viruses (SARS-CoV-2, SARS-CoV, and MERS-CoV).

Drugs repurposing for SARS-CoV-2: new insight of COVID-19 druggability

INTRODUCTION

The ongoing epidemic of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) creates a massive panic worldwide due to the absence of effective medicines. Developing a new drug or vaccine is time-consuming to pass safety and efficacy testing. Therefore, repurposing drugs have been introduced to treat COVID-19 until effective drugs are developed.

AREA COVERED

A detailed search of repurposing drugs against SARS-CoV-2 was carried out using the PubMed database, focusing on articles published 2020 years onward. A different class of drugs has been described in this article to target hosts and viruses. Based on the previous pandemic experience of SARS-CoV and MERS, several antiviral and antimalarial drugs are discussed here. This review covers the failure of some repurposed drugs that showed promising activity in the earlier CoV-pandemic but were found ineffective against SARS-CoV-2. All these discussions demand a successful drug development strategy for screening and identifying an effective drug for better management of COVID-19. The drug development strategies described here will serve a new scope of research for academicians and researchers.

EXPERT OPINION

Repurposed drugs have been used since COVID-19 to eradicate disease propagation. Drugs found effective for MERS and SARS may not be effective against SARS-CoV-2. Drug libraries and artificial intelligence are helpful tools to screen and identify different molecules targeting viruses or hosts.