Screening of Natural Products Targeting SARS-CoV-2-ACE2 Receptor Interface - A MixMD Based HTVS Pipeline

Virtual Screening Strategy to Identify Retinoic Acid-Related Orphan Receptor γt Modulators

Molecular docking is a key method used in virtual screening (VS) campaigns to identify small-molecule ligands for drug discovery targets. While docking provides a tangible way to understand and predict the protein-ligand complex formation, the docking algorithms are often unable to separate active ligands from inactive molecules in practical VS usage. Here, a novel docking and shape-focused pharmacophore VS protocol is demonstrated for facilitating effective hit discovery using retinoic acid receptor-related orphan receptor gamma t (RORγt) as a case study. RORγt is a prospective target for treating inflammatory diseases such as psoriasis and multiple sclerosis. First, a commercial molecular database was flexibly docked. Second, the alternative docking poses were rescored against the shape/electrostatic potential of negative image-based (NIB) models that mirror the target's binding cavity. The compositions of the NIB models were optimized via iterative trimming and benchmarking using a greedy search-driven algorithm or brute force NIB optimization. Third, a pharmacophore point-based filtering was performed to focus the hit identification on the known RORγt activity hotspots. Fourth, free energy binding affinity evaluation was performed on the remaining molecules. Finally, twenty-eight compounds were selected for in vitro testing and eight compounds were determined to be low μM range RORγt inhibitors, thereby showing that the introduced VS protocol generated an effective hit rate of ~29%.

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.

High-Throughput Screening for the Potential Inhibitors of SARS-CoV-2 with Essential Dynamic Behavior

Global health security has been challenged by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Due to the lengthy process of generating vaccinations, it is vital to reposition currently available drugs in order to relieve anti-epidemic tensions and accelerate the development of therapies for Coronavirus Disease 2019 (COVID-19), the public threat caused by SARS-CoV-2. High throughput screening techniques have established their roles in the evaluation of already available medications and the search for novel potential agents with desirable chemical space and more cost-effectiveness. Here, we present the architectural aspects of highthroughput screening for SARS-CoV-2 inhibitors, especially three generations of virtual screening methodologies with structural dynamics: ligand-based screening, receptor-based screening, and machine learning (ML)-based scoring functions (SFs). By outlining the benefits and drawbacks, we hope that researchers will be motivated to adopt these methods in the development of novel anti- SARS-CoV-2 agents.

Insights from computational studies on the potential of natural compounds as inhibitors against SARS-CoV-2 spike omicron variant

Coronavirus disease 2019 (COVID-19) is a major global health emergency, with more than six million deaths worldwide. It is becoming increasingly challenging to treat COVID-19 due to the emergence of novel variants. The omicron variant is capable to evade defences and spread quickly. Among many validated COVID-19 targets, the spike (S) protein plays an important role in receptor recognition (via the S1 subunit) and membrane fusion (via the S2 subunit). The S protein is one of the vital targets for the development of drugs to combat this illness. In this research, we applied various computational methods such as molecular docking, molecular dynamics, MM-GBSA calculations, and ADMET prediction to identify potential natural products from Saudi medicinal plants against the spike omicron variant. As a result, three compounds (LTS0002490, LTS0117007, and LTS0217912) were identified with better binding affinity to the spike omicron variant compared to the reference compound (VE607). In addition, these compounds showed stable interactions with the target during molecular dynamics simulations for 140 ns. Last, these compounds have optimal ADMET properties. We suggest that these compounds may be considered promising hits to treat COVID-19 if experimentally validated.

Analysis and Identification of Bioactive Compounds of Cannabinoids in Silico for Inhibition of SARS-CoV-2 and SARS-CoV

Despite the approval of multiple vaccinations in different countries, the majority of the world's population remains unvaccinated due to discrepancies in vaccine distribution and limited production capacity. The SARS-CoV-2 RBD-ACE2 complex (receptor binding domain that binds to ACE2) could be a suitable target for the development of a vaccine or an inhibitor. Various natural products have been used against SARS-CoV-2. Here, we docked 42 active cannabinoids to the active site of the SARS-CoV-2 and SARS-CoV complex of RBD-ACE2. To ensure the flexibility and stability of the complex produced after docking, the top three ligand molecules with the best overall binding energies were further analyzed through molecular dynamic simulation (MDS). Then, we used the webserver Swissadme program and binding free energy to calculate and estimate the MMPBSA and ADME characteristics. Our results showed that luteolin, CBGVA, and CBNA were the top three molecules that interact with the SARS-CoV-2 RBD-ACE2 complex, while luteolin, stigmasterol, and CBNA had the strongest contact with that SARS-CoV. Our findings show that luteolin may be a potential inhibitor of infections caused by coronavirus-like pathogens such as COVID-19, although further in vivo and in vitro research is required.

A review on computational approaches that support the researches on traditional Chinese medicines (TCM) against COVID-19

BACKGROUND

COVID-19 highly caused contagious infections and massive deaths worldwide as well as unprecedentedly disrupting global economies and societies, and the urgent development of new antiviral medications are required. Medicinal herbs are promising resources for the discovery of prophylactic candidate against COVID-19. Considerable amounts of experimental efforts have been made on vaccines and direct-acting antiviral agents (DAAs), but neither of them was fast and fully developed.

PURPOSE

This study examined the computational approaches that have played a significant role in drug discovery and development against COVID-19, and these computational methods and tools will be helpful for the discovery of lead compounds from phytochemicals and understanding the molecular mechanism of action of TCM in the prevention and control of the other diseases.

METHODS

A search conducting in scientific databases (PubMed, Science Direct, ResearchGate, Google Scholar, and Web of Science) found a total of 2172 articles, which were retrieved via web interface of the following websites. After applying some inclusion and exclusion criteria and full-text screening, only 292 articles were collected as eligible articles.

RESULTS

In this review, we highlight three main categories of computational approaches including structure-based, knowledge-mining (artificial intelligence) and network-based approaches. The most commonly used database, molecular docking tool, and MD simulation software include TCMSP, AutoDock Vina, and GROMACS, respectively. Network-based approaches were mainly provided to help readers understanding the complex mechanisms of multiple TCM ingredients, targets, diseases, and networks.

CONCLUSION

Computational approaches have been broadly applied to the research of phytochemicals and TCM against COVID-19, and played a significant role in drug discovery and development in terms of the financial and time saving.

The battle between host and SARS-CoV-2: Innate immunity and viral evasion strategies

The SARS-CoV-2 virus, the pathogen causing COVID-19, has caused more than 200 million confirmed cases, resulting in more than 4.5 million deaths worldwide by the end of August, 2021. Upon detection of SARS-CoV-2 infection by pattern recognition receptors (PRRs), multiple signaling cascades are activated, which ultimately leads to innate immune response such as induction of type I and III interferons, as well as other antiviral genes that together restrict viral spread by suppressing different steps of the viral life cycle. Our understanding of the contribution of the innate immune system in recognizing and subsequently initiating a host response to an invasion of SARS-CoV-2 has been rapidly expanding from 2020. Simultaneously, SARS-CoV-2 has evolved multiple immune evasion strategies to escape from host immune surveillance for successful replication. In this review, we will address the current knowledge of innate immunity in the context of SARS-CoV-2 infection and highlight recent advances in the understanding of the mechanisms by which SARS-CoV-2 evades a host's innate defense system.

Plastic Antibodies Mimicking the ACE2 Receptor for Selective Binding of SARS-CoV-2 Spike

Molecular imprinting has proven to be a versatile and simple strategy to obtain selective materials also termed "plastic antibodies" for a wide variety of species, i.e., from ions to macromolecules and viruses. However, to the best of the authors' knowledge, the development of epitope-imprinted polymers for selective binding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is not reported to date. An epitope from the SARS-CoV-2 spike protein comprising 17 amino acids is used as a template during the imprinting process. The interactions between the epitope template and organosilane monomers used for the polymer synthesis are predicted via molecular docking simulations. The molecularly imprinted polymer presents a 1.8-fold higher selectivity against the target epitope compared to non-imprinted control polymers. Rebinding studies with pseudoviruses containing SARS-CoV-2 spike protein demonstrate the superior selectivity of the molecularly imprinted matrices, which mimic the interactions of angiotensin-converting enzyme 2 receptors from human cells. The obtained results highlight the potential of SARS-CoV-2 molecularly imprinted polymers for a variety of applications including chem/biosensing and antiviral delivery.

Inhibitory effects of specific combination of natural compounds against SARS-CoV-2 and its Alpha, Beta, Gamma, Delta, Kappa, and Mu variants

Despite vaccine availability, the global spread of COVID-19 continues, largely facilitated by emerging SARS-CoV-2 mutations. Our earlier research documented that a specific combination of plant-derived compounds can inhibit SARS-CoV-2 binding to its ACE2 receptor and controlling key cellular mechanisms of viral infectivity. In this study, we evaluated the efficacy of a defined mixture of plant extracts and micronutrients against original SARS-CoV-2 and its Alpha, Beta, Gamma, Delta, Kappa, and Mu variants. The composition containing vitamin C, N-acetylcysteine, resveratrol, theaflavin, curcumin, quercetin, naringenin, baicalin, and broccoli extract demonstrated a highest efficacy by inhibiting the receptor-binding domain (RBD) binding of SARS-CoV-2 to its cellular ACE2 receptor by 90%. In vitro exposure of test pseudo-typed variants to this formula for 1 h before or simultaneously administrated to human pulmonary cells resulted in up to 60% inhibition in their cellular entry. Additionally, this composition significantly inhibited other cellular mechanisms of viral infectivity, including the activity of viral RdRp, furin, and cathepsin L. These findings demonstrate the efficacy of natural compounds against SARS-CoV-2 including its mutated forms through pleiotropic mechanisms. Our results imply that simultaneous inhibition of multiple mechanisms of viral infection of host cells could be an effective strategy to prevent SARS-CoV-2 infection.

Virtual screening and in vitro validation of natural compound inhibitors against SARS-CoV-2 spike protein

The COVID-19 pandemic caused by the SARS-CoV-2 virus has led to a major public health burden and has resulted in millions of deaths worldwide. As effective treatments are limited, there is a significant requirement for high-throughput, low resource methods for the discovery of novel antivirals. The SARS-CoV-2 spike protein plays a key role in viral entry and has been identified as a therapeutic target. Using the available spike crystal structure, we performed a virtual screen with a library of 527 209 natural compounds against the receptor binding domain of this protein. Top hits from this screen were subjected to a second, more comprehensive molecular docking experiment and filtered for favourable ADMET properties. The in vitro activity of 10 highly ranked compounds was assessed using a virus neutralisation assay designed to facilitate viral entry in a physiologically relevant manner via the plasma membrane route. Subsequently, four compounds ZINC02111387, ZINC02122196, SN00074072 and ZINC04090608 were identified to possess antiviral activity in the µM range. These findings validate the virtual screening method as a tool for identifying novel antivirals and provide a basis for future drug development against SARS-CoV-2.

Screening S protein - ACE2 blockers from natural products: Strategies and advances in the discovery of potential inhibitors of COVID-19

The Coronavirus disease, 2019 (COVID-19) is caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), which poses a major threat to human life and health. Given its continued development, limiting the spread of COVID-19 in the population remains a challenging task. Currently, multiple therapies are being tried around the world to deal with SARS-CoV-2 infection, and a variety of studies have shown that natural products have a significant effect on COVID-19 patients. The combination of SARS-CoV-2 S protein with Angiotensin converting enzyme II(ACE2) of host cell to promote membrane fusion is an initial critical step for SARS-CoV-2 infection. Therefore, screening natural products that inhibit the binding of SARS-CoV-2 S protein and ACE2 also provides a feasible strategy for the treatment of COVID-19. Establishment of high throughput screening model is an important basis and key technology for screening S protein-ACE2 blockers. Based on this, the molecular structures of SARS-CoV-2 and ACE2 and their processes in the life cycle of SARS-CoV-2 and host cell infection were firstly reviewed in this paper, with emphasis on the methods and techniques of screening S protein-ACE2 blockers, including Virtual Screening (VS), Surface Plasmon Resonance (SPR), Biochromatography, Biotin-avidin with Enzyme-linked Immunosorbent assay and Gene Chip Technology. Furthermore, the technical principle, advantages and disadvantages and application scope were further elaborated. Combined with the application of the above screening technologies in S protein-ACE2 blockers, a variety of natural products, such as flavonoids, terpenoids, phenols, alkaloids, were summarized, which could be used as S protein-ACE2 blockers, in order to provide ideas for the efficient discovery of S protein-ACE2 blockers from natural sources and contribute to the development of broad-spectrum anti coronavirus drugs.

Antcins from Antrodia cinnamomea and Antrodia salmonea Inhibit Angiotensin-Converting Enzyme 2 (ACE2) in Epithelial Cells: Can Be Potential Candidates for the Development of SARS-CoV-2 Prophylactic Agents

Antcins are newly identified steroid-like compounds from Taiwan's endemic medicinal mushrooms Antrodia cinnamomea and Antrodia salmonea. Scientific studies of the past two decades confirmed that antcins have various pharmacological activities, including potent anti-oxidant and anti-inflammatory effects. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the coronavirus disease-2019 (COVID-19) pandemic and is characterized as a significant threat to global public health. It was recently identified that SARS-CoV-2 required angiotensin converting enzyme 2 (ACE2), a receptor which supports host cell entry and disease onset. Here, we report a novel function of antcins, in which antcins exhibit inhibitory effects on ACE2. Compared to the untreated control group, treatment with various antcins (antcin-A, antcin-B, antcin-C, antcin-H, antcin-I, and antcin-M) significantly inhibited ACE2 activity in cultured human epithelial cells. Indeed, among the investigated antcins, antcin-A, antcin-B, antcin-C, and antcin-I showed a pronounceable inhibition against ACE2. These findings suggest that antcins could be novel anti-ACE2 agents to prevent SARS-CoV-2 host cell entry and the following disease onset.

Detection of Binding Sites on SARS-CoV-2 Spike Protein Receptor-Binding Domain by Molecular Dynamics Simulations in Mixed Solvents

The novel SARS-CoV-2 uses ACE2 (Angiotensin-Converting Enzyme 2) receptor as an entry point. Insights on S protein receptor-binding domain (RBD) interaction with ACE2 receptor and drug repurposing has accelerated drug discovery for the novel SARS-CoV-2 infection. Finding small molecule binding sites in S protein and ACE2 interface is crucial in search of effective drugs to prevent viral entry. In this study, we employed molecular dynamics simulations in mixed solvents together with virtual screening to identify small molecules that could be potential inhibitors of S protein -ACE2 interaction. Observation of organic probe molecule localization during the simulations revealed multiple sites at the S protein surface related to small molecule, antibody, and ACE2 binding. In addition, a novel conformation of the S protein was discovered that could be stabilized by small molecules to inhibit attachment to ACE2. The most promising binding site on RBD-ACE2 interface was targeted with virtual screening and top-ranked compounds (DB08248, DB02651, DB03714, and DB14826) are suggested for experimental testing. The protocol described here offers an extremely fast method for characterizing key proteins of a novel pathogen and for the identification of compounds that could inhibit or accelerate spreading of the disease.

Recent efforts for drug identification from phytochemicals against SARS-CoV-2: Exploration of the chemical space to identify druggable leads

Nature, which remains a central drug discovery pool, is always looked upon to find a putative druggable lead. The natural products and phytochemical derived from plants are essential during a global health crisis. This class represents one of the most practical and promising approaches to decrease pandemic's intensity owing to their therapeutic potential. The present manuscript is therefore kept forth to give the researchers updated information on undergoing research in allied areas of natural product-based drug discovery, particularly for Covid-19 disease. The study briefly shreds evidence from in vitro and in silico researches done so far to find a lead molecule against Covid-19. Following this, we exhaustively explored the concept of chemical space and molecular similarity parameters for the drug discovery about the lead(s) generated from in silico-based studies. The comparison was drawn using FDA-approved anti-infective agents during 2015–2020 using key descriptors to evaluate druglike properties. The outcomes of results were further corroborated using Molecular Dynamics studies which suggested the outcomes in alignment with chemical space ranking. In a nutshell, current research work aims to provide a holistic strategic approach to drug design, keeping in view the identified phytochemicals against Covid-19.