Discovery of potential small molecular SARS-CoV-2 entry blockers targeting the spike protein

Computational analysis of spike protein of SARS-CoV-2 (Omicron variant) for development of peptide-based therapeutics and diagnostics

In the last few years, the worldwide population has suffered from the SARS-CoV-2 pandemic. The WHO dashboard indicated that around 504,079,039 people were infected and 6,204,155 died from COVID-19 caused by different variants of SARS-CoV-2. Recently, a new variant of SARS-CoV-2 (B.1.1.529) was reported by South Africa known as Omicron. The high transmissibility rate and resistance towards available anti-SARS-CoV-2 drugs/vaccines/monoclonal antibodies, make Omicron a variant of concern. Because of various mutations in spike protein, available diagnostic and therapeutic treatments are not reliable. Therefore, the present study explored the development of some therapeutic peptides that can inhibit the SARS-CoV-2 virus interaction with host ACE2 receptors and can also be used for diagnostic purposes. The screened linear B cell epitopes derived from receptor-binding domain of spike protein of Omicron variant were evaluated as peptide inhibitor/vaccine candidates through different bioinformatics tools including molecular docking and simulation to analyze the interaction between Omicron peptide and human ACE2 receptor. Overall, in-silico studies revealed that Omicron peptides OP1-P12, OP14, OP20, OP23, OP24, OP25, OP26, OP27, OP28, OP29, and OP30 have the potential to inhibit Omicron interaction with ACE2 receptor. Moreover, Omicron peptides OP20, OP22, OP23, OP24, OP25, OP26, OP27, and OP30 have shown potential antigenic and immunogenic properties that can be used in design and development vaccines against Omicron. Although the in-silico validation was performed by comparative analysis with the control peptide inhibitor, further validation through wet lab experimentation is required before its use as therapeutic peptides.Communicated by Ramaswamy H. Sarma.

Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking

Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and machine-learning-based binding pocket detection with the ensemble-based ligand docking and binding free energy analysis to characterize the potential allosteric binding sites and determine structural and energetic determinants of allosteric inhibition for a series of experimentally validated allosteric molecules. The results demonstrate a good agreement between computational and experimental binding affinities, providing support to the predicted binding modes and suggesting key interactions formed by the allosteric ligands to elicit the experimentally observed inhibition. We establish structural and energetic determinants of allosteric binding for the experimentally known allosteric molecules, indicating a potential mechanism of allosteric modulation by targeting the hinges of the inter-protomer movements and blocking conformational changes between the closed and open spike trimer forms. The results of this study demonstrate that combining ensemble-based ligand docking with conformational states of spike protein and rigorous binding energy analysis enables robust characterization of the ligand binding modes, the identification of allosteric binding hotspots, and the prediction of binding affinities for validated allosteric modulators, which is consistent with the experimental data. This study suggested that the conformational adaptability of the protein allosteric sites and the diversity of ligand bound conformations are both in play to enable efficient targeting of allosteric binding sites and interfere with the conformational changes.

The Discovery of inhibitors of the SARS-CoV-2 S protein through computational drug repurposing

SARS-CoV-2 must bind its principal receptor, ACE2, on the target cell to initiate infection. This interaction is largely driven by the receptor binding domain (RBD) of the viral Spike (S) protein. Accordingly, antiviral compounds that can block RBD/ACE2 interactions can constitute promising antiviral agents. To identify such molecules, we performed a virtual screening of the Selleck FDA approved drugs and the Selleck database of Natural Products using a multistep computational procedure. An initial set of candidates was identified from an ensemble docking process using representative structures determined from the analysis of four 3 μ s molecular dynamics trajectories of the RBD/ACE2 complex. Two procedures were used to construct an initial set of candidates including a standard and a pharmacophore guided docking procedure. The initial set was subsequently subjected to a multistep sieving process to reduce the number of candidates to be tested experimentally, using increasingly demanding computational procedures, including the calculation of the binding free energy computed using the MMPBSA and MMGBSA methods. After the sieving process, a final list of 10 candidates was proposed, compounds which were subsequently purchased and tested ex-vivo. The results identified estradiol cypionate and telmisartan as inhibitors of SARS-CoV-2 entry into cells. Our findings demonstrate that the methodology presented here enables the discovery of inhibitors targeting viruses for which high-resolution structures are available.

Discovery of High Affinity Cyclic Peptide Ligands for Human ACE2 with SARS-CoV-2 Entry Inhibitory Activity

The development of effective antiviral compounds is essential for mitigating the effects of the COVID-19 pandemic. Entry of SARS-CoV-2 virions into host cells is mediated by the interaction between the viral spike (S) protein and membrane-bound angiotensin-converting enzyme 2 (ACE2) on the surface of epithelial cells. Inhibition of this viral protein-host protein interaction is an attractive avenue for the development of antiviral molecules with numerous spike-binding molecules generated to date. Herein, we describe an alternative approach to inhibit the spike-ACE2 interaction by targeting the spike-binding interface of human ACE2 via mRNA display. Two consecutive display selections were performed to direct cyclic peptide ligand binding toward the spike binding interface of ACE2. Through this process, potent cyclic peptide binders of human ACE2 (with affinities in the picomolar to nanomolar range) were identified, two of which neutralized SARS-CoV-2 entry. This work demonstrates the potential of targeting ACE2 for the generation of anti-SARS-CoV-2 therapeutics as well as broad spectrum antivirals for the treatment of SARS-like betacoronavirus infection.

CellSTAR: a comprehensive resource for single-cell transcriptomic annotation

Large-scale studies of single-cell sequencing and biological experiments have successfully revealed expression patterns that distinguish different cell types in tissues, emphasizing the importance of studying cellular heterogeneity and accurately annotating cell types. Analysis of gene expression profiles in these experiments provides two essential types of data for cell type annotation: annotated references and canonical markers. In this study, the first comprehensive database of single-cell transcriptomic annotation resource (CellSTAR) was thus developed. It is unique in (a) offering the comprehensive expertly annotated reference data for annotating hundreds of cell types for the first time and (b) enabling the collective consideration of reference data and marker genes by incorporating tens of thousands of markers. Given its unique features, CellSTAR is expected to attract broad research interests from the technological innovations in single-cell transcriptomics, the studies of cellular heterogeneity & dynamics, and so on. It is now publicly accessible without any login requirement at: https://idrblab.org/cellstar.

Structure-based drug discovery to identify SARS-CoV2 spike protein-ACE2 interaction inhibitors

After the emergence of the COVID-19 pandemic in late 2019, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has undergone a dynamic evolution driven by the acquisition of genetic modifications, resulting in several variants that are further classified as variants of interest (VOIs), variants under monitoring (VUM) and variants of concern (VOC) by World Health Organization (WHO). Currently, there are five SARS-CoV-2 VOCs (Alpha, Beta, Delta, Gamma and Omicron), two VOIs (Lambda and Mu) and several other VOIs that have been reported globally. In this study, we report a natural compound, Curcumin, as the potential inhibitor to the interactions between receptor binding domain (RBD(S1)) and human angiotensin-converting enzyme 2 (hACE2) domains and showcased its inhibitory potential for the Delta and Omicron variants through a computational approach by implementing state of the art methods. The study for the first time revealed a higher efficiency of Curcumin, especially for hindering the interaction between RBD(S1) and hACE-2 domains of Delta and Omicron variants as compared to other lead compounds. We investigated that the mutations in the RBD(S1) of VOC especially Delta and Omicron variants affect its structure compared to that of the wild type and other variants and therefore altered its binding to the hACE2 receptor. Molecular docking and molecular dynamics (MD) simulation analyses substantially supported the findings in terms of the stability of the docked complexes. This study offers compelling evidence, warranting a more in-depth exploration into the impact of these alterations on the binding of identified drug molecules with the Spike protein. Further investigation into their potential therapeutic effects in vivo is highly recommended.Communicated by Ramaswamy H. Sarma.

DeepSA: a deep-learning driven predictor of compound synthesis accessibility

With the continuous development of artificial intelligence technology, more and more computational models for generating new molecules are being developed. However, we are often confronted with the question of whether these compounds are easy or difficult to synthesize, which refers to synthetic accessibility of compounds. In this study, a deep learning based computational model called DeepSA, was proposed to predict the synthesis accessibility of compounds, which provides a useful tool to choose molecules. DeepSA is a chemical language model that was developed by training on a dataset of 3,593,053 molecules using various natural language processing (NLP) algorithms, offering advantages over state-of-the-art methods and having a much higher area under the receiver operating characteristic curve (AUROC), i.e., 89.6%, in discriminating those molecules that are difficult to synthesize. This helps users select less expensive molecules for synthesis, reducing the time and cost required for drug discovery and development. Interestingly, a comparison of DeepSA with a Graph Attention-based method shows that using SMILES alone can also efficiently visualize and extract compound's informative features. DeepSA is available online on the below web server ( https://bailab.siais.shanghaitech.edu.cn/services/deepsa/ ) of our group, and the code is available at https://github.com/Shihang-Wang-58/DeepSA .

Structural understanding of SARS-CoV-2 virus entry to host cells

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major global health concern associated with millions of fatalities worldwide. Mutant variants of the virus have further exacerbated COVID-19 mortality and infection rates, emphasizing the urgent need for effective preventive strategies. Understanding the viral infection mechanism is crucial for developing therapeutics and vaccines. The entry of SARS-CoV-2 into host cells is a key step in the infection pathway and has been targeted for drug development. Despite numerous reviews of COVID-19 and the virus, there is a lack of comprehensive reviews focusing on the structural aspects of viral entry. In this review, we analyze structural changes in Spike proteins during the entry process, dividing the entry process into prebinding, receptor binding, proteolytic cleavage, and membrane fusion steps. By understanding the atomic-scale details of viral entry, we can better target the entry step for intervention strategies. We also examine the impacts of mutations in Spike proteins, including the Omicron variant, on viral entry. Structural information provides insights into the effects of mutations and can guide the development of therapeutics and vaccines. Finally, we discuss available structure-based approaches for the development of therapeutics and vaccines. Overall, this review provides a detailed analysis of the structural aspects of SARS-CoV-2 viral entry, highlighting its significance in the development of therapeutics and vaccines against COVID-19. Therefore, our review emphasizes the importance of structural information in combating SARS-CoV-2 infection.

Exploring the disruption of SARS-CoV-2 RBD binding to hACE2

The COVID-19 pandemic was declared due to the spread of the novel coronavirus, SARS-CoV-2. Viral infection is caused by the interaction between the SARS-CoV-2 receptor binding domain (RBD) and the human ACE2 receptor (hACE2). Previous computational studies have identified repurposed small molecules that target the RBD, but very few have screened drugs in the RBD-hACE2 interface. When studies focus solely on the binding affinity between the drug and the RBD, they ignore the effect of hACE2, resulting in an incomplete analysis. We screened ACE inhibitors and previously identified SARS-CoV-2 inhibitors for binding to the RBD-hACE2 interface, and then conducted 500 ns of unrestrained molecular dynamics (MD) simulations of fosinopril, fosinoprilat, lisinopril, emodin, diquafosol, and physcion bound to the interface to assess the binding characteristics of these ligands. Based on MM-GBSA analysis, all six ligands bind favorably in the interface and inhibit the RBD-hACE2 interaction. However, when we repeat our simulation by first binding the drug to the RBD before interacting with hACE2, we find that fosinopril, fosinoprilat, and lisinopril result in a strongly interacting trimeric complex (RBD-drug-hACE2). Hydrogen bonding and pairwise decomposition analyses further suggest that fosinopril is the best RBD inhibitor. However, when lisinopril is bound, it stabilizes the trimeric complex and, therefore, is not an ideal potential drug candidate. Overall, these results reveal important atomistic interactions critical to the binding of the RBD to hACE2 and highlight the significance of including all protein partners in the evaluation of a potential drug candidate.

Review and perspective on bioinformatics tools using machine learning and deep learning for predicting antiviral peptides

Viruses constitute a constant threat to global health and have caused millions of human and animal deaths throughout human history. Despite advances in the discovery of antiviral compounds that help fight these pathogens, finding a solution to this problem continues to be a task that consumes time and financial resources. Currently, artificial intelligence (AI) has revolutionized many areas of the biological sciences, making it possible to decipher patterns in amino acid sequences that encode different functions and activities. Within the field of AI, machine learning, and deep learning algorithms have been used to discover antimicrobial peptides. Due to their effectiveness and specificity, antimicrobial peptides (AMPs) hold excellent promise for treating various infections caused by pathogens. Antiviral peptides (AVPs) are a specific type of AMPs that have activity against certain viruses. Unlike the research focused on the development of tools and methods for the prediction of antimicrobial peptides, those related to the prediction of AVPs are still scarce. Given the significance of AVPs as potential pharmaceutical options for human and animal health and the ongoing AI revolution, we have reviewed and summarized the current machine learning and deep learning-based tools and methods available for predicting these types of peptides.

Aptamer-, heparin- or cocktail-based inhibition of S1-ACE2 protein complexes

The Spike protein (S1) from the Severe acute respiratory syndrome 2 virus binds to angiotensin converting enzyme 2 (ACE2) receptor to initiate infection. Hence, antiviral therapeutic targeting the S1-ACE2 interface is of interest. Herein, we compare the inhibition efficacy of an aptamer to heparin or their cocktail, against wild-type (WT), Omicron, Delta, and Lambda S1-ACE2 complexes. The aptamer-protein complexes had the dissociation constant K_D values in the 2-13 nM range. The aptamer half-maximal inhibitory concentration against WT S1-ACE was 17 nM, with the % inhibition in the 12-35% range. Several aptamer-S1 protein complexes were also stable at low pH with 60% inhibition. Despite the similarity in S1 sequences, the extent of inhibition (2-27%) with heparin was highly dependent on the type of S1 protein. More importantly, heparin did not inhibit the WT S1-ACE2 complex but was effective with mutants. The aptamer-heparin cocktail was less effective compared to aptamer or heparin, individually. Modelling data show that either a direct or proximal binding to RBD sites by aptamer or heparin prevents the ACE2 binding. Overall, heparin was as an effective inhibitor as aptamer against certain variants, and represents the more cost-effective neutralizing agent against emerging coronaviruses.

The Sea Cucumber Thyonella gemmata Contains a Low Anticoagulant Sulfated Fucan with High Anti-SARS-CoV-2 Actions against Wild-Type and Delta Variants

In this work, we isolated two new sulfated glycans from the body wall of the sea cucumber Thyonella gemmata: one fucosylated chondroitin sulfate (TgFucCS) (17.5 ± 3.5% kDa) and one sulfated fucan (TgSF) (383.3 ± 2.1% kDa). NMR results showed the TgFucCS backbone composed of [→3)-β-N-acetylgalactosamine-(1→4)-β-glucuronic acid-(1→] with 70% 4-sulfated and 30% 4,6-disulfated GalNAc units and one-third of the GlcA units decorated at the C3 position with branching α-fucose (Fuc) units either 4-sulfated (65%) or 2,4-disulfated (35%) and the TgSF structure composed of a tetrasaccharide repeating unit of [→3)-α-Fuc2,4S-(1→2)-α-Fuc4S-(1→3)-α-Fuc2S-(1→3)-α-Fuc2S-(1→]n. Inhibitory properties of TgFucCS and TgSF were investigated using SARS-CoV-2 pseudovirus coated with S-proteins of the wild-type (Wuhan-Hu-1) or the delta (B.1.617.2) strains and in four different anticoagulant assays, comparatively with unfractionated heparin. Molecular binding to coagulation (co)-factors and S-proteins was investigated by competitive surface plasmon resonance spectroscopy. Among the two sulfated glycans tested, TgSF showed significant anti-SARS-CoV-2 activity against both strains together with low anticoagulant properties, indicating a good candidate for future studies in drug development.

Different In Silico Approaches Using Heterocyclic Derivatives against the Binding between Different Lineages of SARS-CoV-2 and ACE2

Over the last few years, the study of the SARS-CoV-2 spike protein and its mutations has become essential in understanding how it interacts with human host receptors. Since the crystallized structure of the spike protein bound to the angiotensin-converting enzyme 2 (ACE2) receptor was released (PDB code 6M0J), in silico studies have been performed to understand the interactions between these two proteins. Specifically, in this study, heterocyclic compounds with different chemical characteristics were examined to highlight the possibility of interaction with the spike protein and the disruption of the interaction between ACE2 and the spike protein. Our results showed that these compounds interacted with the spike protein and interposed in the interaction zone with ACE2. Although further studies are needed, this work points to these heterocyclic push-pull compounds as possible agents capable of interacting with the spike protein, with the potential for the inhibition of spike protein-ACE2 binding.

Computational Protein Design for COVID-19 Research and Emerging Therapeutics

As the world struggles with the ongoing COVID-19 pandemic, unprecedented obstacles have continuously been traversed as new SARS-CoV-2 variants continually emerge. Infectious disease outbreaks are unavoidable, but the knowledge gained from the successes and failures will help create a robust health management system to deal with such pandemics. Previously, scientists required years to develop diagnostics, therapeutics, or vaccines; however, we have seen that, with the rapid deployment of high-throughput technologies and unprecedented scientific collaboration worldwide, breakthrough discoveries can be accelerated and insights broadened. Computational protein design (CPD) is a game-changing new technology that has provided alternative therapeutic strategies for pandemic management. In addition to the development of peptide-based inhibitors, miniprotein binders, decoys, biosensors, nanobodies, and monoclonal antibodies, CPD has also been used to redesign native SARS-CoV-2 proteins and human ACE2 receptors. We discuss how novel CPD strategies have been exploited to develop rationally designed and robust COVID-19 treatment strategies.

Vitamin C promotes ACE2 degradation and protects against SARS-CoV-2 infection

ACE2 is a major receptor for cellular entry of SARS-CoV-2. Despite advances in targeting ACE2 to inhibit SARS-CoV-2 binding, strategies to flexibly and sufficiently reduce ACE2 levels for the prevention of SARS-CoV-2 infection have not been explored. Here, we reveal vitamin C (VitC) administration as a potent strategy to prevent SARS-CoV-2 infection. VitC reduces ACE2 protein levels in a dose-dependent manner, while even a partial reduction in ACE2 levels can greatly inhibit SARS-CoV-2 infection. Further studies reveal that USP50 is a crucial regulator of ACE2 levels. VitC blocks the USP50-ACE2 interaction, thus promoting K48-linked polyubiquitination of ACE2 at Lys788 and subsequent degradation of ACE2 without affecting its transcriptional expression. Importantly, VitC administration reduces host ACE2 levels and greatly blocks SARS-CoV-2 infection in mice. This study reveals that ACE2 protein levels are down-regulated by an essential nutrient, VitC, thereby enhancing protection against infection of SARS-CoV-2 and its variants.

Anti-SARS-CoV-2 Activity of Ampelozizyphus amazonicus (Saracura-Mirá): Focus on the Modulation of the Spike-ACE2 Interaction by Chemically Characterized Bark Extracts by LC-DAD-APCI-MS/MS

Traditional medicine shows several treatment protocols for COVID-19 based on natural products, revealing its potential as a possible source of anti-SARS-CoV-2 agents. Ampelozizyphus amazonicus is popularly used in the Brazilian Amazon as a fortifier and tonic, and recently, it has been reported to relieve COVID-19 symptoms. This work aimed to investigate the antiviral potential of A. amazonicus, focusing on the inhibition of spike and ACE2 receptor interaction, a key step in successful infection. Although saponins are the major compounds of this plant and often reported as its active principles, a polyphenol-rich extract was the best inhibitor of the spike and ACE2 interaction. Chemical characterization of A. amazonicus bark extracts by LC-DAD-APCI-MS/MS before and after clean-up steps for polyphenol removal showed that the latter play an essential role in maintaining this activity. The effects of the extracts on viral replication were also assessed, and all samples (aqueous and ethanol extracts) demonstrated in vitro activity, inhibiting viral titers in the supernatant of Calu-3 cells after 24 hpi. By acting both in the SARS-CoV-2 cell entry process and its replication, A. amazonicus bark extracts stand out as a multitarget agent, highlighting the species as a promising candidate in the development of anti-SARS-CoV-2 drugs.

Molecular Modeling of Viral Type I Fusion Proteins: Inhibitors of Influenza Virus Hemagglutinin and the Spike Protein of Coronavirus

The fusion of viral and cell membranes is one of the basic processes in the life cycles of viruses. A number of enveloped viruses confer fusion of the viral envelope and the cell membrane using surface viral fusion proteins. Their conformational rearrangements lead to the unification of lipid bilayers of cell membranes and viral envelopes and the formation of fusion pores through which the viral genome enters the cytoplasm of the cell. A deep understanding of all the stages of conformational transitions preceding the fusion of viral and cell membranes is necessary for the development of specific inhibitors of viral reproduction. This review systematizes knowledge about the results of molecular modeling aimed at finding and explaining the mechanisms of antiviral activity of entry inhibitors. The first section of this review describes types of viral fusion proteins and is followed by a comparison of the structural features of class I fusion proteins, namely influenza virus hemagglutinin and the S-protein of the human coronavirus.

Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches

Allosteric mechanisms are commonly employed regulatory tools used by proteins to orchestrate complex biochemical processes and control communications in cells. The quantitative understanding and characterization of allosteric molecular events are among major challenges in modern biology and require integration of innovative computational experimental approaches to obtain atomistic-level knowledge of the allosteric states, interactions, and dynamic conformational landscapes. The growing body of computational and experimental studies empowered by emerging artificial intelligence (AI) technologies has opened up new paradigms for exploring and learning the universe of protein allostery from first principles. In this review we analyze recent developments in high-throughput deep mutational scanning of allosteric protein functions; applications and latest adaptations of Alpha-fold structural prediction methods for studies of protein dynamics and allostery; new frontiers in integrating machine learning and enhanced sampling techniques for characterization of allostery; and recent advances in structural biology approaches for studies of allosteric systems. We also highlight recent computational and experimental studies of the SARS-CoV-2 spike (S) proteins revealing an important and often hidden role of allosteric regulation driving functional conformational changes, binding interactions with the host receptor, and mutational escape mechanisms of S proteins which are critical for viral infection. We conclude with a summary and outlook of future directions suggesting that AI-augmented biophysical and computer simulation approaches are beginning to transform studies of protein allostery toward systematic characterization of allosteric landscapes, hidden allosteric states, and mechanisms which may bring about a new revolution in molecular biology and drug discovery.

Screening of honey bee pollen constituents against COVID-19: an emerging hot spot in targeting SARS-CoV-2-ACE-2 interaction

The attachment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike to angiotensin-converting enzyme 2 (ACE-2) leads the cell fusion process, so spike blockade may be a promising therapy combating COVID-19. Bee pollen bioflavonoids with intrinsic bioactivities are of outmost importance to block SARS-CoV-2-ACE-2 interaction. Herein, we conducted a molecular docking assessment through natural phenolics/non-phenolics of pollen to investigate their affinity against SARS-CoV-2 spike. Finally, kaempferol 3-neohesperidoside 7-O-rhamnoside (compound a), quercetin 7-rhamnoside (compound b), delphinidin-3-O-(6-p-coumaroyl) glucoside (compound c), and luteolin-7-O-6″-malonylglucoside (compound d) showed the lowest binding affinity of -8.1, -7.7, -7.3 and -6.7 kcal/mol. The docking procedure was validated using protein-protein interactions between ACE-2 and SARS-CoV-2 RBD via HADDOCK webserver. MD simulations were fulfilled to investigate different ligands' effects on protein movements. Collectively, compound a may possess the potency to disturb the binding of SARS-CoV-2 spike-ACE-2, which can be on the call for further in vitro and in vivo study to investigate its antiviral potential against SARS-CoV-2.

In Silico Discovery of Small Molecule Modulators Targeting the Achilles' Heel of SARS-CoV-2 Spike Protein

The spike protein of SARS-CoV-2 has been a promising target for developing vaccines and therapeutics due to its crucial role in the viral entry process. Previously reported cryogenic electron microscopy (cryo-EM) structures have revealed that free fatty acids (FFA) bind with SARS-CoV-2 spike protein, stabilizing its closed conformation and reducing its interaction with the host cell target in vitro. Inspired by these, we utilized a structure-based virtual screening approach against the conserved FFA-binding pocket to identify small molecule modulators of SARS-CoV-2 spike protein, which helped us identify six hits with micromolar binding affinities. Further evaluation of their commercially available and synthesized analogs enabled us to discover a series of compounds with better binding affinities and solubilities. Notably, our identified compounds exhibited similar binding affinities against the spike proteins of the prototypic SARS-CoV-2 and a currently circulating Omicron BA.4 variant. Furthermore, the cryo-EM structure of the compound SPC-14 bound spike revealed that SPC-14 could shift the conformational equilibrium of the spike protein toward the closed conformation, which is human ACE2 (hACE2) inaccessible. Our identified small molecule modulators targeting the conserved FFA-binding pocket could serve as the starting point for the future development of broad-spectrum COVID-19 intervention treatments.

Robust anti-inflammatory activity of genistein against neutrophil elastase: a microsecond molecular dynamics simulation study

Human Neutrophil Elastase (HNE) is one of the major causes of tissue destruction in numerous chronic and inflammatory disorders and has been reported as a therapeutic target for inflammatory diseases. Overexpression of this enzyme plays a critical role in the pathogenesis of rheumatoid arthritis (RA). The focus of this study is to identify potent natural inhibitors that could target the active site of the HNE through the use of computational methods. The molecular structure of small molecules was retrieved from several natural compound databases. This was followed by structure-based virtual screening, molecular docking, ADMET property predictions and molecular dynamic simulation studies to screen potential HNE inhibitors. In total, 1881 natural compounds were extracted and subjected to molecular docking studies, and 10 compounds were found to have good interactions, exhibiting the best docking scores. Genistein showed higher binding efficacy (-10.28 Kcal/mol) to HNE in comparison to other natural compounds. The conformational stability of the docked complex of the ELANE gene (HNE) with genistein was assessed using 1-microsecond molecular dynamic simulation (MDs), which reliably revealed the unique stereochemical alteration of the complex, indicating its conformational stability and flexibility. Alterations in the enzyme structure upon complex formation were further characterized through clustering analysis and linear interaction energy (LIE) calculation. The outcomes of this research propose novel potential candidates against target HNE.Communicated by Ramaswamy H. Sarma.

Anti-Entry Activity of Natural Flavonoids against SARS-CoV-2 by Targeting Spike RBD

COVID-19 is still a global public health concern, and the SARS-CoV-2 mutations require more effective antiviral agents. In this study, the antiviral entry activity of thirty-one flavonoids was systematically evaluated by a SARS-CoV-2 pseudovirus model. Twenty-four flavonoids exhibited antiviral entry activity with IC50 values ranging from 10.27 to 172.63 µM and SI values ranging from 2.33 to 48.69. The structure-activity relationship of these flavonoids as SARS-CoV-2 entry inhibitors was comprehensively summarized. A subsequent biolayer interferometry assay indicated that flavonoids bind to viral spike RBD to block viral interaction with ACE2 receptor, and a molecular docking study also revealed that flavonols could bind to Pocket 3, the non-mutant regions of SARS-CoV-2 variants, suggesting that flavonols might be also active against virus variants. These natural flavonoids showed very low cytotoxic effects on human normal cell lines. Our findings suggested that natural flavonoids might be potential antiviral entry agents against SARS-CoV-2 via inactivating the viral spike. It is hoped that our study will provide some encouraging evidence for the use of natural flavonoids as disinfectants to prevent viral infections.

Small molecules in the treatment of COVID-19

The outbreak of COVID-19 has become a global crisis, and brought severe disruptions to societies and economies. Until now, effective therapeutics against COVID-19 are in high demand. Along with our improved understanding of the structure, function, and pathogenic process of SARS-CoV-2, many small molecules with potential anti-COVID-19 effects have been developed. So far, several antiviral strategies were explored. Besides directly inhibition of viral proteins such as RdRp and Mpro, interference of host enzymes including ACE2 and proteases, and blocking relevant immunoregulatory pathways represented by JAK/STAT, BTK, NF-κB, and NLRP3 pathways, are regarded feasible in drug development. The development of small molecules to treat COVID-19 has been achieved by several strategies, including computer-aided lead compound design and screening, natural product discovery, drug repurposing, and combination therapy. Several small molecules representative by remdesivir and paxlovid have been proved or authorized emergency use in many countries. And many candidates have entered clinical-trial stage. Nevertheless, due to the epidemiological features and variability issues of SARS-CoV-2, it is necessary to continue exploring novel strategies against COVID-19. This review discusses the current findings in the development of small molecules for COVID-19 treatment. Moreover, their detailed mechanism of action, chemical structures, and preclinical and clinical efficacies are discussed.

Potential antiviral peptides targeting the SARS-CoV-2 spike protein

BACKGROUND

The coronavirus disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection became an international pandemic and created a public health crisis. The binding of the viral Spike glycoprotein to the human cell receptor angiotensin-converting enzyme 2 (ACE2) initiates viral infection. The development of efficient treatments to combat coronavirus disease is considered essential.

METHODS

An in silico approach was employed to design amino acid peptide inhibitor against the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. The designed inhibitor (SARS-CoV-2 PEP 49) consists of amino acids with the α1 helix and the β4 - β5 sheets of ACE2. The PEP-FOLD3 web tool was used to create the 3D structures of the peptide amino acids. Analyzing the interaction between ACE2 and the RBD of the Spike protein for three protein data bank entries (6M0J, 7C8D, and 7A95) indicated that the interacting amino acids were contained inside two regions of ACE2: the α1 helical protease domain (PD) and the β4 - β5 sheets.

RESULTS

Molecular docking analysis of the designed inhibitor demonstrated that SARS-CoV-2 PEP 49 attaches directly to the ACE2 binding site of the Spike protein with a binding affinity greater than the ACE2, implying that the SARS-CoV-2 PEP 49 model may be useful as a potential RBD binding blocker.

Neurological disorders of COVID-19: insights to applications of natural products from plants and microorganisms

In addition to the typical respiratory manifestations, various disorders including involvement of the nerve system have been detected in COVID-19 ranging from 22 to 36%. Although growing records are focusing on neurological aspects of COVID-19, the pathophysiological mechanisms and related therapeutic methods remain obscure. Considering the increased concerns of SARS-CoV-2 potential for more serious neuroinvasion conditions, the present review attempts to focus on the neuroprotective effects of natural compounds as the principle source of therapeutics inhibiting multiple steps of the SARS-CoV-2 infection cycle. The great majority of the natural products with anti-SARS-CoV-2 activity mainly inhibit the attachment, entry and gene expression rather than the replication, assembly, or release. Although microbial-derived natural products comprise 38.5% of the known natural products with neuroprotective effects following viral infection, the neuroprotective potential of the majority of microorganisms is still undiscovered. Among natural products, chrysin, huperzine A, ginsenoside Rg1, pterostilbene, and terrein have shown potent in vitro neuroprotective activity and can be promising for new or repurpose drugs for neurological complications of SARS-CoV-2.

Mulberrofuran G, a Mulberry Component, Prevents SARS-CoV-2 Infection by Blocking the Interaction between SARS-CoV-2 Spike Protein S1 Receptor-Binding Domain and Human Angiotensin-Converting Enzyme 2 Receptor

Despite the recent development of RNA replication-targeted COVID-19 drugs by global pharmaceutical companies, their prescription in clinical practice is limited by certain factors, including drug interaction, reproductive toxicity, and drug resistance. COVID-19 drugs with multiple targets for the SARS-CoV-2 life cycle may lead to a successful reduction in drug resistance as well as enhanced therapeutic efficacy, and natural products are a potential source of molecules with therapeutic effects against COVID-19. In this study, we investigated the inhibitory efficacy of mulberrofuran G (MG), a component of Morus alba L., also known as mulberry, which has been used as food and traditional medicine, on the binding of the spike S1 receptor-binding domain (RBD) protein to the angiotensin-converting enzyme 2 (ACE2) receptor, which is the initial stage of the SARS-CoV-2 infection. In competitive enzyme-linked immunosorbent assays, MG effectively blocked the spike S1 RBD: ACE2 receptor molecular binding, and investigations using the BLItz system and in silico modeling revealed that MG has high affinity for both proteins. Finally, we confirmed that MG inhibits the entry of SARS-CoV-2 spike pseudotyped virus and a clinical isolate of SARS-CoV-2 into cells, suggesting that MG might be a promising therapeutic candidate for preventing SARS-CoV-2 binding to the cell surface during early infection.

Mutation informatics: SARS-CoV-2 receptor-binding domain of the spike protein

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) undergoes mutations at a high rate and with frequent genetic reassortment (antigenic drift/shift), leading to variability in targets. The receptor-binding domain (RBD) of the spike (S) protein has a major role in the binding of SARS-CoV-2 with human angiotensin-converting enzyme 2 (ACE2). Mutations at the RBD influence the binding interaction at the SARS-CoV-2 S-ACE2 interface and impact viral pathogenicity. Here, we discuss different reported mutations of concern in RBD, physicochemical characteristic changes resulting from mutated amino acids and their effect on binding between the RBD and ACE2. Along with mutation informatics, we highlight recently developed small-molecule inhibitors of RBD and the ACE2 interface. This information provides a rational basis for the design of inhibitors against the multivariant strains of SARS-CoV-2.

Small Molecules Targeting SARS-CoV-2 Spike Glycoprotein Receptor-Binding Domain

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the coronavirus disease 2019 (COVID-19) pandemic. Several variants of SARS-CoV-2 have emerged worldwide. These variants show different transmissibility infectivity due to mutations in the viral spike (S) glycoprotein that interacts with the human angiotensin-converting enzyme 2 (hACE2) receptor and facilitates viral entry into target cells. Despite the effective SARS-CoV-2 vaccines, we still need to identify selective antivirals, and the S glycoprotein is a key target to neutralize the virus. We hypothesize that small molecules could disrupt the interaction of S glycoprotein with hACE2 and inhibit viral entry. We analyzed the S glycoprotein-hACE2 complex structure (PDB: 7DF4) and created models for different viral variants using visual molecular dynamics (VMD) and molecular operating environment (MOE) programs. Moreover, we started the hits search by performing structure-based molecular docking virtual screening of commercially available small molecules against S glycoprotein models using OEDocking FRED-4.0.0.0 software. The FRED-4.0.0.0 Chemguass4 scoring function was used to rank the small molecules based on their affinities. The best candidate compounds were purchased and tested using a standard SARS-CoV-2 pseudotyped cell-based bioassay to investigate their antiviral activity. Three of these compounds, alone or in combination, showed antiviral selectivity. These small molecules may lead to an effective antiviral treatment or serve as probes to better understand the biology of SARS-CoV-2.

Smaller, Stronger, More Stable: Peptide Variants of a SARS-CoV-2 Neutralizing Miniprotein

Based on the structure of a de novo designed miniprotein (LCB1) in complex with the receptor binding domain (RBD) of the SARS-CoV-2 spike protein, we have generated and characterized truncated peptide variants of LCB1, which present only two of the three LCB1 helices, and which fully retained the virus neutralizing potency against different SARS-CoV-2 variants of concern (VOC). This antiviral activity was even 10-fold stronger for a cyclic variant of the two-helix peptides, as compared to the full-length peptide. Furthermore, the proteolytic stability of the cyclic peptide was substantially improved, rendering it a better potential candidate for SARS-CoV-2 therapy. In a more mechanistic approach, the peptides also served as tools to dissect the role of individual mutations in the RBD for the susceptibility of the resulting virus variants to neutralization by the peptides. As the peptides reported here were generated through chemical synthesis, rather than recombinant protein expression, they are amenable to further chemical modification, including the incorporation of a wide range of non-proteinogenic amino acids, with the aim to further stabilize the peptides against proteolytic degradation, as well as to improve the strength, as well the breadth, of their virus neutralizing capacity.

Newly Emerged Antiviral Strategies for SARS-CoV-2: From Deciphering Viral Protein Structural Function to the Development of Vaccines, Antibodies, and Small Molecules

Coronavirus disease 2019 (COVID-19) caused by the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become the most severe health crisis, causing extraordinary economic disruption worldwide. SARS-CoV-2 is a single-stranded RNA-enveloped virus. The process of viral replication and particle packaging is finished in host cells. Viral proteins, including both structural and nonstructural proteins, play important roles in the viral life cycle, which also provides the targets of treatment. Therefore, a better understanding of the structural function of virus proteins is crucial to speed up the development of vaccines and therapeutic strategies. Currently, the structure and function of proteins encoded by the SARS-CoV-2 genome are reviewed by several studies. However, most of them are based on the analysis of SARS-CoV-1 particles, lacking a systematic review update for SARS-CoV-2. Here, we specifically focus on the structure and function of proteins encoded by SARS-CoV-2. Viral proteins that contribute to COVID-19 infection and disease pathogenesis are reviewed according to the most recent research findings. The structure-function correlation of viral proteins provides a fundamental rationale for vaccine development and targeted therapy. Then, current antiviral vaccines are updated, such as inactive viral vaccines and protein-based vaccines and DNA, mRNA, and circular RNA vaccines. A summary of other therapeutic options is also reviewed, including monoclonal antibodies such as a cross-neutralizer antibody, a constructed cobinding antibody, a dual functional monoclonal antibody, an antibody cocktail, and an engineered bispecific antibody, as well as peptide-based inhibitors, chemical compounds, and clustered regularly interspaced short palindromic repeats (CRISPR) exploration. Overall, viral proteins and their functions provide the basis for targeted therapy and vaccine development.

Anti-SARS-CoV-2 potential of Cissampelos pareira L. identified by connectivity map-based analysis and in vitro studies

Background

Viral infections have a history of abrupt and severe eruptions through the years in the form of pandemics. And yet, definitive therapies or preventive measures are not present. Herbal medicines have been a source of various antiviral compounds such as Oseltamivir, extracted using shikimic acid from star anise (Illicium verum) and Acyclovir from Carissa edulis are FDA (Food and Drug Administration) approved antiviral drugs. In this study, we dissect the anti-coronavirus infection activity of Cissampelos pareira L (Cipa) extract using an integrative approach.

Methods

We analysed the signature similarities between predicted antiviral agents and Cipa using the connectivity map (https://clue.io/). Next, we tested the anti-SARS-COV-2 activity of Cipa in vitro. Molecular docking analyses of constituents of with key targets of SARS-CoV2 protein viz. spike protein, RNA‑dependent RNA‑polymerase (RdRp) and 3C‑like proteinase. was also performed. A three-way comparative analysis of Cipa transcriptome, COVID-19 BALF transcriptome and CMAP signatures of small compounds was also performed.

Results

Several predicted antivirals showed a high positive connectivity score with Cipa such as apcidin, emetine, homoharringtonine etc. We also observed 98% inhibition of SARS-COV-2 replication in infected Vero cell cultures with the whole extract. Some of its prominent pure constituents e.g. pareirarine, cissamine, magnoflorine exhibited 40–80% inhibition. Comparison of genes between BALF and Cipa showed an enrichment of biological processes like transcription regulation and response to lipids, to be downregulated in Cipa while being upregulated in COVID-19. CMAP also showed that Triciribine, torin-1 and VU-0365114–2 had positive connectivity with BALF 1 and 2, and negative connectivity with Cipa. Amongst all the tested compounds, Magnoflorine and Salutaridine exhibited the most potent and consistent strong in silico binding profiles with SARS-CoV2 therapeutic targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03584-3.

Anti-Fungal Drug Anidulafungin Inhibits SARS-CoV-2 Spike-Induced Syncytia Formation by Targeting ACE2-Spike Protein Interaction

Drug repositioning continues to be the most effective, practicable possibility to treat COVID-19 patients. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus enters target cells by binding to the ACE2 receptor via its spike (S) glycoprotein. We used molecular docking-based virtual screening approaches to categorize potential antagonists, halting ACE2-spike interactions by utilizing 450 FDA-approved chemical compounds. Three drug candidates (i.e., anidulafungin, lopinavir, and indinavir) were selected, which show high binding affinity toward the ACE2 receptor. The conformational stability of selected docked complexes was analyzed through molecular dynamics (MD) simulations. The MD simulation trajectories were assessed and monitored for ACE2 deviation, residue fluctuation, the radius of gyration, solvent accessible surface area, and free energy landscapes. The inhibitory activities of the selected compounds were eventually tested in-vitro using Vero and HEK-ACE2 cells. Interestingly, besides inhibiting SARS-CoV-2 S glycoprotein induced syncytia formation, anidulafungin and lopinavir also blocked S-pseudotyped particle entry into target cells. Altogether, anidulafungin and lopinavir are ranked the most effective among all the tested drugs against ACE2 receptor-S glycoprotein interaction. Based on these findings, we propose that anidulafungin is a novel potential drug targeting ACE2, which warrants further investigation for COVID-19 treatment.

A Drug Repurposing Approach for Antimalarials Interfering with SARS-CoV-2 Spike Protein Receptor Binding Domain (RBD) and Human Angiotensin-Converting Enzyme 2 (ACE2)

Host cell invasion by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is mediated by the interaction of the viral spike protein (S) with human angiotensin-converting enzyme 2 (ACE2) through the receptor-binding domain (RBD). In this work, computational and experimental techniques were combined to screen antimalarial compounds from different chemical classes, with the aim of identifying small molecules interfering with the RBD-ACE2 interaction and, consequently, with cell invasion. Docking studies showed that the compounds interfere with the same region of the RBD, but different interaction patterns were noted for ACE2. Virtual screening indicated pyronaridine as the most promising RBD and ACE2 ligand, and molecular dynamics simulations confirmed the stability of the predicted complex with the RBD. Bio-layer interferometry showed that artemisone and methylene blue have a strong binding affinity for RBD (KD = 0.363 and 0.226 μM). Pyronaridine also binds RBD and ACE2 in vitro (KD = 56.8 and 51.3 μM). Overall, these three compounds inhibit the binding of RBD to ACE2 in the μM range, supporting the in silico data.