Computational drug repurposing strategy predicted peptide-based drugs that can potentially inhibit the interaction of SARS-CoV-2 spike protein with its target (humanACE2)

Structural, functional, molecular docking analysis of a hypothetical protein from Talaromyces marneffei and its molecular dynamic simulation: an in-silico approach

Telaromyces marneffei (formerly Penicillium marneffei) is an endemic pathogenic fungus in Southern China and Southeast Asia. It can cause disease in patients with travel-related exposure to this organism and high morbidity and mortality in acquired immune deficiency syndrome (AIDS). In this study, we analyzed the structure and function of a hypothetical protein from T. marneffei using several bioinformatics tools and servers to unveil novel pharmacological targets and design a peptide vaccine against specific epitopes. A total of seven functional epitopes were screened on the protein, and 'STGVDMWSV' was the most antigenic, non-allergenic and non-toxic. Molecular docking showed stronger affinity between the CTL epitope 'STGVDMWSV' and the MHC I allele HLA-A*02:01, a higher docking score -234.98 kcal/mol, revealed stable interactions during a 100 ns molecular dynamic simulation. Overall, the results of this study revealed that this hypothetical protein is crucial for comprehending biochemical, physiological pathways and identifying novel therapeutic targets for human health. Communicated by Ramaswamy H. Sarma.

Exploring 3-O-glycosylations of 20(R)-dammarane ginsenosides and the catalytic mechanism underlying the stereoselectivity with the combined assistance of AlphaFold 2 and molecular docking

Glycosylation at C3-OH is the favorable modification for pharmaceutical activities and diversity expansion of 20(R)-dammarane ginsenosides. The 3-O-glycosylation, exclusively occurring in 20(R)-PPD ginsenosides, has never been achieved in 20(R)-PPT ginsenosides. Herein, 3-O-glycosylation of 20(R)-PPT enabled by a glycosyltransferase (GT) OsSGT2 was achieved with the combined assistance of AlphaFold 2 and molecular docking. Firstly, we combined AlphaFold2 algorithm and molecular docking to predict interactions between 20(R)-PPT and candidate GTs. A catalytically favorable binding geometry was thus identified in the OsSGT2-20(R)-PPT complex, suggesting OsSGT2 might act on 20(R)-PPT. The enzymatic assays demonstrated that OsSGT2 reacted with varied sugar donors to form 20(R)-PPT 3-O-glycosides, exhibiting donor promiscuity. Additionally, OsSGT2 displayed acceptor promiscuity, catalyzing 3-O-glucosylation of 20(R/S)-PPT, 20(R/S)-PPD and 20(R/S)-Rh1, respectively. Protein engineering on OsSGT2 was thus performed to probe its catalytic mechanism underlying its stereoselectivity. The W207A mutant preferred 20(S)-dammarane aglycons, while F395Q/A396G(QG) displayed a conversion enhancement towards both 20(R/S)-dammarane aglycons. The QG mutant was then used to synthesize 20(R)-PPT 3-O-glucoside, which displayed a moderate angiotensin-converting enzyme inhibitory effect with an IC50 of 27.5 ± 4.7 μM, superior to that of its 20(S)-epimer, with the combined assistance of target fishing and reverse docking. The water solubility of 20(R)-PPT 3-O-glucoside increased as well.

A review of SARS-CoV-2 drug repurposing: databases and machine learning models

The emergence of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) posed a serious worldwide threat and emphasized the urgency to find efficient solutions to combat the spread of the virus. Drug repurposing has attracted more attention than traditional approaches due to its potential for a time- and cost-effective discovery of new applications for the existing FDA-approved drugs. Given the reported success of machine learning (ML) in virtual drug screening, it is warranted as a promising approach to identify potential SARS-CoV-2 inhibitors. The implementation of ML in drug repurposing requires the presence of reliable digital databases for the extraction of the data of interest. Numerous databases archive research data from studies so that it can be used for different purposes. This article reviews two aspects: the frequently used databases in ML-based drug repurposing studies for SARS-CoV-2, and the recent ML models that have been developed for the prospective prediction of potential inhibitors against the new virus. Both types of ML models, Deep Learning models and conventional ML models, are reviewed in terms of introduction, methodology, and its recent applications in the prospective predictions of SARS-CoV-2 inhibitors. Furthermore, the features and limitations of the databases are provided to guide researchers in choosing suitable databases according to their research interests.

Structure based Drug Designing Approaches in SARS-CoV-2 Spike Inhibitor Design

The COVID-19 outbreak and the pandemic situation have hastened the research community to design a novel drug and vaccine against its causative organism, the SARS-CoV-2. The spike glycoprotein present on the surface of this pathogenic organism plays an immense role in viral entry and antigenicity. Hence, it is considered an important drug target in COVID-19 drug design. Several three-dimensional crystal structures of this SARS-CoV-2 spike protein have been identified and deposited in the Protein DataBank during the pandemic period. This accelerated the research in computer- aided drug designing, especially in the field of structure-based drug designing. This review summarizes various structure-based drug design approaches applied to this SARS-CoV-2 spike protein and its findings. Specifically, it is focused on different structure-based approaches such as molecular docking, high-throughput virtual screening, molecular dynamics simulation, drug repurposing, and target-based pharmacophore modelling and screening. These structural approaches have been applied to different ligands and datasets such as FDA-approved drugs, small molecular chemical compounds, chemical libraries, chemical databases, structural analogs, and natural compounds, which resulted in the prediction of spike inhibitors, spike-ACE-2 interface inhibitors, and allosteric inhibitors.

The role of Substance P in the defense line of the respiratory tract and neurological manifestations post COVID-19 infection

Substance P (SP) has been a great interest for scientists due to its unique properties and involvement in various physiological and pathological phenomenon. It took almost a century for the current understanding of this peptide so far. Its role in brain and gut were initially discussed and later on it was widely studied and observed in cardiovascular system, asthma, traumatic brain injury, immune response, vasodilation, behavior, inflammation, arthritis, cancer, airway hyper responsiveness and respiratory disorders. Involvement of SP in sudden perinatal death and COVID-19 has also been discussed which shed light on its vital role in respiratory rhythm regulation and initiation of cytokine storming in COVID-19. This article will provide a comprehensive overview of the researches done to understand the basic functions and involvement of SP in different processes of cell and its association with various diseases. This article describes the historical and scientific journey of SP from its discovery until today, including its future perspectives.

Antiviral potential of diminazene aceturate against SARS-CoV-2 proteases using computational and in vitro approaches

Diminazene aceturate (DIZE), an antiparasitic, is an ACE2 activator, and studies show that activators of this enzyme may be beneficial for COVID-19, disease caused by SARS-CoV-2. Thus, the objective was to evaluate the in silico and in vitro affinity of diminazene aceturate against molecular targets of SARS-CoV-2. 3D structures from DIZE and the proteases from SARS-CoV-2, obtained through the Protein Data Bank and Drug Database (Drubank), and processed in computer programs like AutodockTools, LigPlot, Pymol for molecular docking and visualization and GROMACS was used to perform molecular dynamics. The results demonstrate that DIZE could interact with all tested targets, and the best binding energies were obtained from the interaction of Protein S (closed conformation −7.87 kcal/mol) and M_pro (−6.23 kcal/mol), indicating that it can act both by preventing entry and viral replication. The results of molecular dynamics demonstrate that DIZE was able to promote a change in stability at the cleavage sites between S1 and S2, which could prevent binding to ACE2 and fusion with the membrane. In addition, in vitro tests confirm the in silico results showing that DIZE could inhibit the binding between the spike receptor-binding domain protein and ACE2, which could promote a reduction in the virus infection. However, tests in other experimental models with in vivo approaches are needed.

Comprehensive role of SARS-CoV-2 spike glycoprotein in regulating host signaling pathway

Since the outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, global public health and the economy have suffered unprecedented damage. Based on the increasing related literature, the characteristics and pathogenic mechanisms of the virus, and epidemiological and clinical features of the disease are being rapidly discovered. The spike glycoprotein (S protein), as a key antigen of SARS-CoV-2 for developing vaccines, antibodies, and drug targets, has been shown to play an important role in viral entry, tissue tropism, and pathogenesis. In this review, we summarize the molecular mechanisms of interaction between S protein and host factors, especially receptor-mediated viral modulation of host signaling pathways, and highlight the progression of potential therapeutic targets, prophylactic and therapeutic agents for prevention and treatment of SARS-CoV-2 infection.

DNA aptamers inhibit SARS-CoV-2 spike-protein binding to hACE2 by an RBD- independent or dependent approach

Objective: Nobody knows when the COVID-19 pandemic will end or when and where the next coronavirus will outbreak. Therefore, it is still necessary to develop SARS-CoV-2 inhibitors for different variants or even the new coronavirus. Since SARS-CoV-2 uses its surface spike-protein to recognize hACE2, mediating its entry into cells, ligands that can specifically recognize the spike-protein have the potential to prevent infection. Methods: We have recently discovered DNA aptamers against the S2-domain of the WT spike-protein by exploiting the selection process called SELEX. After optimization, among all candidates, the aptamer S2A2C1 has the shortest sequence and the best binding affinity toward the S2-protein. More importantly, the S2A2C1 aptamer does not bind to the RBD of the spike-protein, but it efficiently blocks the spike-protein/hACE2 interaction, suggesting an RBD-independent inhibition approach. To further improve its performance, we conjugated the S2A2C1 aptamer with a reported anti-RBD aptamer, S1B6C3, using various linkers and constructed hetero-bivalent fusion aptamers. Binding affinities of mono and fusion aptamers against the spike-proteins were measured. The inhibition efficacies of mono and fusion aptamers to prevent the hACE2/spike-protein interaction were determined using ELISA. Results: Anti-spike-protein aptamers, including S2A2C1 and S1B6C3-A5-S2A2C1, maintained high binding affinity toward the WT, Delta, and Omicron spike-proteins and high inhibition efficacies to prevent them from binding to hACE2, rendering them well-suited as diagnostic and therapeutic molecular tools to target SARS-CoV-2 and its variants. Conclusions: Overall, we discovered the anti-S2 aptamer, S2A2C1, which inhibits the hACE2/spike-protein interaction via an RBD-independent approach. The anti-S2 and anti-RBD aptamers were conjugated to obtain the fusion aptamer, S1B6C3-A5-S2A2C1, which recognizes the spike-protein by an RBD-dependent approach. Our strategies, which discovered aptamer inhibitors targeting the highly conserved S2-protein, as well as the design of fusion aptamers, can be used to target new coronaviruses as they emerge.

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.

Identification of Hypericin as a Candidate Repurposed Therapeutic Agent for COVID-19 and Its Potential Anti-SARS-CoV-2 Activity

The COVID-19 pandemic has had an unprecedented impact on the global economy and public health. Its etiologic agent, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly transmissible, pathogenic and has a rapid global spread. Currently, the increase in the number of new confirmed cases has been slowed down due to the increase of vaccination in some regions of the world. Still, the rise of new variants has influenced the detection of additional waves of rising cases that some countries have experienced. Since the virus replication cycle is composed of many distinct stages, some viral proteins related to them, as the main-protease (Mpro) and RNA dependent RNA polymerase (RdRp), constitute individual potential antiviral targets. In this study, we challenged the mentioned enzymes against compounds pre-approved by health regulatory agencies in a virtual screening and later in Molecular Mechanics/Poisson–Bolzmann Surface Area (MM/PBSA) analysis. Our results showed that, among the identified potential drugs with anti-SARS-CoV-2 properties, Hypericin, an important component of the Hypericum perforatum that presents antiviral and antitumoral properties, binds with high affinity to viral Mpro and RdRp. Furthermore, we evaluated the activity of Hypericin anti-SARS-CoV-2 replication in an in vitro model of Vero-E6 infected cells. Therefore, we show that Hypericin inhibited viral replication in a dose dependent manner. Moreover, the cytotoxicity of the compound, in cultured cells, was evaluated, but no significant activity was found. Thus, the results observed in this study indicate that Hypericin is an excellent candidate for repurposing for the treatment of COVID-19, with possible inhibition of two important phases of virus maturation.

Gorobets N, Desenko SM, Poonam, Rathi B. Drug repurposing against SARS-CoV-2 using computational approaches

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has generated a critical need for treatments to reduce morbidity and mortality associated with this disease. However, traditional drug development takes many years, which is not practical solution given the current pandemic. Therefore, a viable option is to repurpose existing drugs. The structural data of several proteins vital for the virus became available shortly after the start of the pandemic. In this review, we discuss the importance of these targets and their available potential inhibitors predicted by the computational approaches. Among the hits identified by computational approaches, 35 candidates were suggested for further evaluation, among which ten drugs are in clinical trials (Phase III and IV) for treating Coronavirus 2019 (COVID-19).

A Perspective on Nanotechnology and COVID-19 Vaccine Research and Production in South Africa

Advances in nanotechnology have enabled the development of a new generation of vaccines, which are playing a critical role in the global control of the COVID-19 pandemic and the return to normalcy. Vaccine development has been conducted, by and large, by countries in the global north. South Africa, as a major emerging economy, has made extensive investments in nanotechnology and bioinformatics and has the expertise and resources in vaccine development and manufacturing. This has been built at a national level through decades of investment. In this perspective article, we provide a synopsis of the investments made in nanotechnology and highlight how these could support innovation, research, and development for vaccines for this disease. We also discuss the application of bioinformatics tools to support rapid and cost-effective vaccine development and make recommendations for future research and development in this area to support future health challenges.

Tackling Immune Pathogenesis of COVID-19 through Molecular Pharmaceutics

An increasing number of clinical studies worldwide are investigating the repurposing of antiviral, immune-modulatory, and anti-inflammatory agents to face the coronavirus disease-19 (COVID-19) pandemic. Nevertheless, few effective therapies exist to prevent or treat COVID-19, which demands increased drug discovery and repurposing efforts. In fact, many currently tested drugs show unknown efficacy and unpredictable drug interactions, such that interventions are needed to guarantee access to effective and safe medicines. Anti-inflammatory therapy has proven to be effective in preventing further injury in COVID-19 patients, but the benefit comes at a cost, as targeting inflammatory pathways can imply an increased risk of infection. Thus, optimization of the risk/benefit ratio is required in the anti-inflammatory strategy against COVID-19, which accounts for drug formulations and delivery towards regionalization and personalization of treatment approaches. In this perspective, we discuss how better knowledge of endogenous immunomodulatory pathways may optimize the clinical use of novel and repurposed drugs against COVID-19 in inpatient, outpatient, and home settings through innovative drug discovery, appropriate drug delivery systems and dedicated molecular pharmaceutics.

Repurposing FDA-approved drugs to fight COVID-19 using in silico methods: Targeting SARS-CoV-2 RdRp enzyme and host cell receptors (ACE2, CD147) through virtual screening and molecular dynamic simulations

Background

Different approaches have been proved effective for combating the COVID-19 pandemic. Accordingly, in silico drug repurposing strategy, has been highly regarded as an accurate computational tool to achieve fast and reliable results. Considering SARS-CoV-2's structural proteins and their interaction the host's cell-specific receptors, this study investigated a drug repurposing strategy aiming to screen compatible inhibitors of FDA-approved drugs against viral entry receptors (ACE2 and CD147) and integral enzyme of the viral polymerase (RdRp).

Methods

The study screened the FDA-approved drugs against ACE2, CD147, and RDRP by virtual screening and molecular dynamics (MD) simulation.

Results

The results of this study indicated that five drugs with ACE2, four drugs with RDRP, and seven drugs with CD147 achieved the most favorable free binding energy (ΔG < −10). This study selected these drugs for MD simulation investigation whose results demonstrated that ledipasvir with ACE2, estradiol benzoate with CD147, and vancomycin with RDRP represented the most favorable ΔG. Also, paritaprevir and vancomycin have good binding energy with both targets (ACE2 and RdRp).

Conclusions

Ledipasvir, estradiol benzoate, and vancomycin and paritaprevir are potentially suitable candidates for further investigation as possible treatments of COVID-19 and novel drug development.