In Silico Drug Repurposing for SARS-CoV-2 Main Proteinase and Spike Proteins

Antibiotics daptomycin interacts with S protein of SARS-CoV-2 to promote cell invasion of Omicron (B1.1.529) pseudovirus

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has posed enormous challenges to global public health. The use of antibiotics has greatly increased during the SARS-CoV-2 epidemic owing to the presence of bacterial co-infection and secondary bacterial infections. The antibiotics daptomycin (DAP) is widely used in the treatment of infectious diseases caused by gram-positive bacteria owing to its highly efficient antibacterial activity. It is pivotal to study the antibiotics usage options for patients of coronavirus infectious disease (COVID-19) with pneumonia those need admission to receive antibiotics treatment for bacterial co-infection in managing COVID-19 disease. Herein, we have revealed the interactions of DAP with the S protein of SARS-CoV-2 and the variant Omicron (B1.1.529) using the molecular docking approach and Omicron (B1.1.529) pseudovirus (PsV) mimic invasion. Molecular docking analysis shows that DAP has a certain degree of binding ability to the S protein of SARS-CoV-2 and several derived virus variants, and co-incubation of 1-100 μM DAP with cells promotes the entry of the PsV into human angiotensin-converting enzyme 2 (hACE2)-expressing HEK-293T cells (HEK-293T-hACE2), and this effect is related to the concentration of extracellular calcium ions (Ca2+). The PsV invasion rate in the HEK-293T-hACE2 cells concurrently with DAP incubation was 1.7 times of PsV infection alone. In general, our findings demonstrate that DAP promotes the infection of PsV into cells, which provides certain reference of antibiotics selection and usage optimization for clinicians to treat bacterial coinfection or secondary infection during SARS-CoV-2 infection.

Chemical Proteomics Approaches for Screening Small Molecule Inhibitors Covalently Binding to SARS-Cov-2

Although various strategies have been used to prevent and treat SARS-CoV-2, the spread and evolution of SARS-CoV-2 is still progressing rapidly. The emerging variants Omicron and its sublineage have a greater ability to spread and escape nearly all current monoclonal antibodies treatments, highlighting an urgent need to develop therapeutics targeting current and emerging Omicron variants or recombinants with breadth and potency. Here, some small molecule drugs are rapidly identified that could covalently binding to receptor binding domain (RBD) protein of Omicron through the combined application of artificial intelligence (AI) and activity-based protein profiling (ABPP) technology. The surface plasmon resonance (SPR) and pseudo-virus neutralization experiments further reveal that an FDA-approved drug gallic acid has robust neutralization potency against Omicron pseudo-virus with the IC50 values of 23.56 × 10-6 m. Taken together, a platform combining AI intelligence, biochemical, SPR, molecular docking, and pseudo-virus-based screening for rapid identification and evaluation of potential anti-SARS-CoV-2 small molecule drugs is established and the effectiveness of the platform is validated.

Effective drug design screening in bacterial glycolytic enzymes via targeting alternative allosteric sites

Three glycolytic enzymes phosphofructokinase (PFK), glyceraldehyde-3-phosphate dehydrogenase (GADPH) and pyruvate kinase (PK) that belong to Staphylococcus aureus were used as targets for screening a dataset composed of 7229 compounds of which 1416 were FDA-approved. Instead of catalytic sites, evolutionarily less conserved allosteric sites were targeted to identify compounds that would selectively bind the bacteria's glycolytic enzymes instead of the human host. Seven different allosteric sites provided by three enzymes were used in independent screening experiments via docking. For each of the seven sites, a total of 723 compounds were selected as the top 10 % which displayed the highest binding affinities. All compounds were then united to yield the top 54 drug candidates shared by all seven sites. Next, 17 out of 54 were selected and subjected to in vitro experiments for testing their inhibition capability for antibacterial growth and enzymatic activity. Accordingly, four compounds displaying antibacterial growth inhibition above 40 % were determined as Candesartan cilexetil, Montelukast (sodium), Dronedarone (hydrochloride) and Thonzonium (bromide). In a second round of experiment, Candesartan cilexetil and Thonzonium displayed exceptionally high killing efficiencies on two bacterial strains of S.aureus (methicillin-sensitive and methicillin-resistant) with concentrations as low as 4 μg/mL and 0.5 μg/mL. Yet, their enzymatic assays were not in accordance with their killing effectiveness. Different inhibitory effects was observed for each compound in each enzymatic assay. A more effective target strategy would be to screen for drug compounds that woud inhibit a combination of glycolytic enzymes observed in the glycolytic pathway.

Boosting immunity: synergistic antiviral effects of luteolin, vitamin C, magnesium and zinc against SARS-CoV-2 3CLpro

SARS-CoV-2 was first discovered in 2019 and has disseminated throughout the globe to pandemic levels, imposing significant health and economic burdens. Although vaccines against SARS-CoV-2 have been developed, their long-term efficacy and specificity have not been determined, and antiviral drugs remain necessary. Flavonoids, which are commonly found in plants, fruits, and vegetables and are part of the human diet, have attracted considerable attention as potential therapeutic agents due to their antiviral and antimicrobial activities and effects on other biological activities, such as inflammation. The present study uses a combination of biochemical, cellular, molecular dynamics, and molecular docking experiments to provide compelling evidence that the flavonoid luteolin (2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-4H-chromen-4-one) has antiviral activity against SARS-CoV-2 3-chymotrypsin-like protease (3CLpro) that is synergistically enhanced by magnesium, zinc, and vitamin C. The IC50 of luteolin against 2 µM 3CLpro is 78 µM and decreases 10-fold to 7.6 µM in the presence of zinc, magnesium, and vitamin C. Thermodynamic stability analyses revealed that luteolin has minimal effects on the structure of 3CLpro, whereas metal ions and vitamin C significantly alter the thermodynamic stability of the protease. Interactome analysis uncovered potential host-virus interactions and functional clusters associated with luteolin activity, supporting the relevance of this flavone for combating SARS-CoV-2 infection. This comprehensive investigation sheds light on luteolin's therapeutic potential and provides insights into its mechanisms of action against SARS-CoV-2. The novel formulation of luteolin, magnesium, zinc, and vitamin C may be an effective avenue for treating COVID-19 patients.

The Malaria Box molecules: a source for targeting the RBD and NTD cryptic pocket of the spike glycoprotein in SARS-CoV-2

CONTEXT

SARS-CoV-2, responsible for COVID-19, has led to over 500 million infections and more than 6 million deaths globally. There have been limited effective treatments available. The study aims to find a drug that can prevent the virus from entering host cells by targeting specific sites on the virus's spike protein.

METHOD

We examined 13,397 compounds from the Malaria Box library against two specific sites on the spike protein: the receptor-binding domain (RBD) and a predicted cryptic pocket. Using virtual screening, molecular docking, molecular dynamics, and MMPBSA techniques, they evaluated the stability of two compounds. TCMDC-124223 showed high stability and binding energy in the RBD, while TCMDC-133766 had better binding energy in the cryptic pocket. The study also identified that the interacting residues are conserved, which is crucial for addressing various virus variants. The findings provide insights into the potential of small molecules as drugs against the spike protein.

Compromise in Docking Power of Liganded Crystal Structures of Mpro SARS-CoV-2 Surpasses 90% Success Rate

Herein, we present the capacity of three different molecular docking programs (AutoDock, AutoDock Vina, and PLANTS) to identify and reproduce the binding modes of ligands present in 247 covalent and 169 noncovalent complex crystal structures of the severe acute respiratory syndrome coronavirus 2 main protease (Mpro). The compromise in docking power is evaluated with respect to their ability to generate poses similar to the crystal structure binding mode (heavy atoms' root-mean-square deviation < 2 Å) and their ability to recognize the native binding mode with an included compensation for the scoring function error. Noncovalently bound inhibitors are best modeled by AutoDock Vina (90.6% success rate in the active site), while the most relevant results for covalently bound inhibitors are produced by PLANTS (93.0%). AutoDock shows acceptable performance for both types of ligands, 81.1 and 76.4% for noncovalent and covalent complexes, respectively. All three programs manifest worse performance when reproducing surface-bound ligands. Comparison with other works illustrates the importance of crystal structure processing (12% of noncovalent and 26% of covalent ligands had to be manually corrected), proper sampling protocol settings, and inclusion of root-mean-square deviation (RMSD)/scoring function error compensations in crystal structure pose identification. Results are analyzed with respect to a clustering scheme of the noncovalently bound ligands and the chemical reaction type of the covalent ligand bound to the Cys145 residue. A comparison of screening power based on the docking scores of noncovalent ligands from the crystal structures with a "Directory of Useful Decoys, Enhanced" set of known decoys (6562 compounds) and ZINC15 in vivo subset (60,394 compounds) is provided. Ligand and protein input files are provided for future benchmarking purposes.

The Coming of Age of AI/ML in Drug Discovery, Development, Clinical Testing, and Manufacturing: The FDA Perspectives

Artificial intelligence (AI) and machine learning (ML) represent significant advancements in computing, building on technologies that humanity has developed over millions of years-from the abacus to quantum computers. These tools have reached a pivotal moment in their development. In 2021 alone, the U.S. Food and Drug Administration (FDA) received over 100 product registration submissions that heavily relied on AI/ML for applications such as monitoring and improving human performance in compiling dossiers. To ensure the safe and effective use of AI/ML in drug discovery and manufacturing, the FDA and numerous other U.S. federal agencies have issued continuously updated, stringent guidelines. Intriguingly, these guidelines are often generated or updated with the aid of AI/ML tools themselves. The overarching goal is to expedite drug discovery, enhance the safety profiles of existing drugs, introduce novel treatment modalities, and improve manufacturing compliance and robustness. Recent FDA publications offer an encouraging outlook on the potential of these tools, emphasizing the need for their careful deployment. This has expanded market opportunities for retraining personnel handling these technologies and enabled innovative applications in emerging therapies such as gene editing, CRISPR-Cas9, CAR-T cells, mRNA-based treatments, and personalized medicine. In summary, the maturation of AI/ML technologies is a testament to human ingenuity. Far from being autonomous entities, these are tools created by and for humans designed to solve complex problems now and in the future. This paper aims to present the status of these technologies, along with examples of their present and future applications.

Reviving the interest in the versatile drug nystatin: A multitude of strategies to increase its potential as an effective and safe antifungal agent

Nystatin is an antifungal molecule with a remarkable yet squandered versatility. In this review, its mechanism of action is explored, along with its extensive action spectrum and toxicity. A multitude of methodologies to tackle the drug's physical and chemical hurdles are outlined along with some proven-effective strategies to increase its activity and/or decrease its toxicity. A separate detailed section focused on micro and nanotechnology solutions addresses new drug delivery systems made of polymeric, metallic or lipid materials. Although the topical route depicts greater representativeness amongst these formulations, the intravenous, dental, oral, vaginal and inhalation routes are also mentioned. The unsuccessful previous attempts at developing parenteral formulations of nystatin or even the withdrawal of a nystatin-loaded multilamellar liposome should not divert research away from this drug. In fact, the interest in nystatin ought to be reawakened with the ongoing clinical trials on the promising nystatin-like genetically engineered derivate BSG005.

Genome-Wide Mining of Selaginella moellendorffii for Hevein-like Lectins and Their Potential Molecular Mimicry with SARS-CoV-2 Spike Glycoprotein

Multidisciplinary research efforts on potential COVID-19 vaccine and therapeutic candidates have increased since the pandemic outbreak of SARS-CoV-2 in 2019. This search has become imperative due to the increasing emergences and limited widely available medicines. The presence of bioactive anti-SARS-CoV-2 molecules was examined from various plant sources. Among them is a group of proteins called lectins that can bind carbohydrate moieties. In this article, we present ten novel, chitin-specific Hevein-like lectins that were derived from Selaginella moellendorffii v1.0's genome. The capacity of these lectin homologs to bind with the spike protein of SARS-CoV-2 was examined. Using the HDOCK server, 3D-modeled Hevein-domains were docked to the spike protein's receptor binding domain (RBD). The Smo446851, Smo125663, and Smo99732 interacted with Asn343-located complex N-glycan and RBD residues, respectively, with binding free energies of -17.5, -13.0, and -26.5 Kcal/mol. The molecular dynamics simulation using Desmond and the normal-state analyses via torsional coordinate association for the Smo99732-RBD complex using iMODS is characterized by overall higher stability and minimum deformity than the other lectin complexes. The three lectins interacting with carbohydrates were docked against five individual mutations that frequently occur in major SARS-CoV-2 variants. These were in the spike protein's receptor-binding motif (RBM), while Smo125663 and Smo99732 only interacted with the spike glycoprotein in a protein-protein manner. The precursors for the Hevein-like homologs underwent additional characterization, and their expressional profile in different tissues was studied. These in silico findings offered potential lectin candidates targeting key N-glycan sites crucial to the virus's virulence and infection.

Antiviral Activity Against SARS-CoV-2 Variants Using in Silico and in Vitro Approaches

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emergence in 2019 led to global health crises and the persistent risk of viral mutations. To combat SARS-CoV-2 variants, researchers have explored new approaches to identifying potential targets for coronaviruses. This study aimed to identify SARS-CoV-2 inhibitors using drug repurposing. In silico studies and network pharmacology were conducted to validate targets and coronavirus-associated diseases to select potential candidates, and in vitro assays were performed to evaluate the antiviral effects of the candidate drugs to elucidate the mechanisms of the viruses at the molecular level and determine the effective antiviral drugs for them. Plaque and cytopathic effect reduction were evaluated, and real-time quantitative reverse transcription was used to evaluate the antiviral activity of the candidate drugs against SARS-CoV-2 variants in vitro. Finally, a comparison was made between the molecular docking binding affinities of fenofibrate and remdesivir (positive control) to conventional and identified targets validated from protein-protein interaction (PPI). Seven candidate drugs were obtained based on the biological targets of the coronavirus, and potential targets were identified by constructing complex disease targets and PPI networks. Among the candidates, fenofibrate exhibited the strongest inhibition effect 1 h after Vero E6 cell infection with SARS-CoV-2 variants. This study identified potential targets for coronavirus disease (COVID-19) and SARS-CoV-2 and suggested fenofibrate as a potential therapy for COVID-19.

Novel Polymyxin-Inspired Peptidomimetics Targeting the SARS-CoV-2 Spike:hACE2 Interface

Though the bulk of the COVID-19 pandemic is behind, the search for effective and safe anti-SARS-CoV-2 drugs continues to be relevant. A highly pursued approach for antiviral drug development involves targeting the viral spike (S) protein of SARS-CoV-2 to prevent its attachment to the cellular receptor ACE2. Here, we exploited the core structure of polymyxin B, a naturally occurring antibiotic, to design and synthesize unprecedented peptidomimetics (PMs), intended to target contemporarily two defined, non-overlapping regions of the S receptor-binding domain (RBD). Monomers 1, 2, and 8, and heterodimers 7 and 10 bound to the S-RBD with micromolar affinity in cell-free surface plasmon resonance assays (KD ranging from 2.31 μM to 2.78 μM for dimers and 8.56 μM to 10.12 μM for monomers). Although the PMs were not able to fully protect cell cultures from infection with authentic live SARS-CoV-2, dimer 10 exerted a minimal but detectable inhibition of SARS-CoV-2 entry in U87.ACE2+ and A549.ACE2.TMPRSS2+ cells. These results validated a previous modeling study and provided the first proof-of-feasibility of using medium-sized heterodimeric PMs for targeting the S-RBD. Thus, heterodimers 7 and 10 may serve as a lead for the development of optimized compounds, which are structurally related to polymyxin, with improved S-RBD affinity and anti-SARS-CoV-2 potential.

Triterpene Derivatives as Potential Inhibitors of the RBD Spike Protein from SARS-CoV-2: An In Silico Approach

The appearance of a new coronavirus, SARS-CoV-2, in 2019 kicked off an international public health emergency. Although rapid progress in vaccination has reduced the number of deaths, the development of alternative treatments to overcome the disease is still necessary. It is known that the infection begins with the interaction of the spike glycoprotein (at the virus surface) and the angiotensin-converting enzyme 2 cell receptor (ACE2). Therefore, a straightforward solution for promoting virus inhibition seems to be the search for molecules capable of abolishing such attachment. In this work, we tested 18 triterpene derivatives as potential inhibitors of SARS-CoV-2 against the receptor-binding domain (RBD) of the spike protein by means of molecular docking and molecular dynamics simulations, modeling the RBD S1 subunit from the X-ray structure of the RBD-ACE2 complex (PDB ID: 6M0J). Molecular docking revealed that at least three triterpene derivatives of each type (i.e., oleanolic, moronic and ursolic) present similar interaction energies as the reference molecule, i.e., glycyrrhizic acid. Molecular dynamics suggest that two compounds from oleanolic and ursolic acid, OA5 and UA2, can induce conformational changes capable of disrupting the RBD-ACE2 interaction. Finally, physicochemical and pharmacokinetic properties simulations revealed favorable biological activity as antivirals.

Surface-Functionalized Metal-Organic Frameworks for Binding Coronavirus Proteins

Since the outbreak of SARS-CoV-2, a multitude of strategies have been explored for the means of protection and shielding against virus particles: filtration equipment (PPE) has been widely used in daily life. In this work, we explore another approach in the form of deactivating coronavirus particles through selective binding onto the surface of metal-organic frameworks (MOFs) to further the fight against the transmission of respiratory viruses. MOFs are attractive materials in this regard, as their rich pore and surface chemistry can easily be modified on demand. The surfaces of three MOFs, UiO-66(Zr), UiO-66-NH2(Zr), and UiO-66-NO2(Zr), have been functionalized with repurposed antiviral agents, namely, folic acid, nystatin, and tenofovir, to enable specific interactions with the external spike protein of the SARS virus. Protein binding studies revealed that this surface modification significantly improved the binding affinity toward glycosylated and non-glycosylated proteins for all three MOFs. Additionally, the pores for the surface-functionalized MOFs can adsorb water, making them suitable for locally dehydrating microbial aerosols. Our findings highlight the immense potential of MOFs in deactivating respiratory coronaviruses to be better equipped to fight future pandemics.

Effect of an Inhibitor on the ACE2-Receptor-Binding Domain of SARS-CoV-2

The recent outbreak of COVID-19 infection started in Wuhan, China, and spread across China and beyond. Since the WHO declared COVID-19 a pandemic (March 11, 2020), three vaccines and only one antiviral drug (remdesivir) have been approved (Oct 22, 2020) by the FDA. The coronavirus enters human epithelial cells by the binding of the densely glycosylated fusion spike protein (S protein) to a receptor (angiotensin-converting enzyme 2, ACE2) on the host cell surface. Therefore, inhibiting the viral entry is a promising treatment pathway for preventing or ameliorating the effects of COVID-19 infection. In the current work, we have used all-atom molecular dynamics (MD) simulations to investigate the influence of the MLN-4760 inhibitor on the conformational properties of ACE2 and its interaction with the receptor-binding domain (RBD) of SARS-CoV-2. We have found that the presence of an inhibitor tends to completely/partially open the ACE2 receptor where the two subdomains (I and II) move away from each other, while the absence results in partial or complete closure. The current study increases our understanding of ACE inhibition by MLN-4760 and how it modulates the conformational properties of ACE2.

The Development of Pharmacophore Models for the Search of New Natural Inhibitors of SARS-CoV-2 Spike RBD-ACE2 Binding Interface

To date, some succeeding variants of SARS-CoV-2 have become more contagious. This virus is known to enter human cells by binding the receptor-binding domain (RBD) of spike protein with the angiotensin-converting enzyme 2 (ACE2), the latter being a membrane protein that regulates the renin-angiotensin system. Since the host cell receptor plays a critical role in viral entry, inhibition of the RBD-ACE2 complex is a promising strategy for preventing COVID-19 infection. In the present communication, we propose and utilize an approach based on the generation of a complex of pharmacophore models and subsequent Induced Fit Docking (IFD) to identify potential inhibitors of the main binding sites of the Omicron SARS-CoV-2 RBD(S1)-ACE2 complex (PDB ID: 7T9L) among a number of natural products of various types and origins. Several natural compounds have been found to provide a high affinity for the receptor of interest. It is expected that the present results will stimulate further research aimed at the development of specialized drugs against this virus.

Structural differences in 3C-like protease (Mpro) from SARS-CoV and SARS-CoV-2: molecular insights revealed by Molecular Dynamics Simulations

Novel coronavirus SARS-CoV-2 has infected millions of people with thousands of mortalities globally. The main protease (Mpro) is vital in processing replicase polyproteins. Both the CoV's Mpro shares 97% identity, with 12 mutations, but none are present in the active site. Although many therapeutics and vaccines are available to combat SARS-CoV-2, these treatments may not be practical due to their high mutational rate. On the other hand, Mpro has a high degree of conservation throughout variants, making Mpro a stout drug target. Here, we report a detailed comparison of both the monomeric Mpro and the biologically active dimeric Mpro using MD simulation to understand the impact of the 12 divergent residues (T35V, A46S, S65N, L86V, R88K, S94A, H134F, K180N, L202V, A267S, T285A and I286L) on the molecular microenvironment and the interaction between crucial residues. The present study concluded that the change in the microenvironment of residues at the entrance (T25, T26, M49 and Q189), near the catalytic site (F140, H163, H164, M165 and H172) and in the substrate-binding site (V35, N65, K88 and N180) is due to 12 mutations in the SARS-CoV-2 Mpro. Furthermore, the involvement of F140, E166 and H172 residues in dimerization stabilizes the Mpro dimer, which should be considered. We anticipate that networks and microenvironment changes identified here might guide repurposing attempts and optimization of new Mpro inhibitors.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11224-022-02089-6.

Understanding the role of water on temperature-dependent structural modifications of SARS CoV-2 main protease binding sites

Thermally stable and labile proteases are found in microorganisms. Protease mediates the cleavage of polyproteins in the virus replication and transcription process. 6 µs MD simulations were performed for monomer/dimer SARS CoV-2 main protease system in both SPC/E and mTIP3P water model to analyse the temperature-dependent behaviour of the protein. It is found that maximum conformational changes are observed at 348 K which is near the melting temperature. Network distribution of evolved conformations shows an increase in the number of communities with the rise in the temperature. The global conformation of the protein was found to be intact whereas a local conformational space evolved due to thermal fluctuations. The global conformational change in the free energy ΔΔG value for the monomer and the dimer between 278 K and 383 K is found to be 2.51 and 2.10 kJ/mol respectively. A detailed analysis was carried out on the effect of water on the temperature-dependent structural modifications of four binding pockets of SARS CoV-2 main protease namely, catalytic dyad, substrate-binding site, dimerization site and allosteric site. It is found that the water structure around the binding sites is altered with temperature. The water around the dimer sites is more ordered than the monomer sites regardless of the rise in temperature due to structural rigidity. The energy expense of binding the small molecules at substrate binding is less compared to the allosteric site. The water-water hydrogen bond lifetime is found to be more near the cavity of His41. Also, it is observed that mTIP3P water molecules have a similar effect to that of SPC/E water molecules on the main protease.

DeepBindBC: a practical deep learning method for identifying native-like protein-ligand complexes in virtual screening

Identifying native-like protein-ligand complexes (PLCs) from an abundance of docking decoys is critical for large-scale virtual drug screening in early-stage drug discovery lead searching efforts. Providing reliable prediction is still a challenge for most current affinity predicting models because of a lack of non-binding data during model training, lost critical physical-chemical features, and difficulties in learning abstract information with limited neural layers. In this work, we proposed a deep learning model, DeepBindBC, for classifying putative ligands as binding or non-binding. Our model incorporates information on non-binding interactions, making it more suitable for real applications. ResNet model architecture and more detailed atom type representation guarantee implicit features can be learned more accurately. Here, we show that DeepBindBC outperforms Autodock Vina, Pafnucy, and DLSCORE for three DUD.E testing sets. Moreover, DeepBindBC identified a novel human pancreatic α-amylase binder validated by a fluorescence spectral experiment (K_a= 1.0×10⁵ M). Furthermore, DeepBindBC can be used as a core component of a hybrid virtual screening pipeline that incorporating many other complementary methods, such as DFCNN, Autodock Vina docking, and pocket molecular dynamics simulation. Additionally, an online web server based on the model is available at http://cbblab.siat.ac.cn/DeepBindBC/index.php for the user's convenience. Our model and the web server provide alternative tools in the early steps of drug discovery by providing accurate identification of native-like PLCs.

Potential COVID-19 Therapies from Computational Repurposing of Drugs and Natural Products against the SARS-CoV-2 Helicase

Repurposing of existing drugs is a rapid way to find potential new treatments for SARS-CoV-2. Here, we applied a virtual screening approach using Autodock Vina and molecular dynamic simulation in tandem to screen and calculate binding energies of repurposed drugs against the SARS-CoV-2 helicase protein (non-structural protein nsp13). Amongst the top hits from our study were antivirals, antihistamines, and antipsychotics, plus a range of other drugs. Approximately 30% of our top 87 hits had published evidence indicating in vivo or in vitro SARS-CoV-2 activity. Top hits not previously reported to have SARS-CoV-2 activity included the antiviral agents, cabotegravir and RSV-604; the NK1 antagonist, aprepitant; the trypanocidal drug, aminoquinuride; the analgesic, antrafenine; the anticancer intercalator, epirubicin; the antihistamine, fexofenadine; and the anticoagulant, dicoumarol. These hits from our in silico SARS-CoV-2 helicase screen warrant further testing as potential COVID-19 treatments.

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).

Seeking antiviral drugs to inhibit SARS-CoV-2 RNA dependent RNA polymerase: A molecular docking analysis

COVID-19 outbreak associated with the severe acute respiratory syndrome coronavirus (SARS-CoV-2) raised health concerns across the globe and has been considered highly transmissible between people. In attempts for finding therapeutic treatment for the new disease, this work has focused on examining the polymerase inhibitors against the SARS-CoV-2 nsp12 and co-factors nsp8 and nsp7. Several polymerase inhibitors were examined against PDB ID: 6M71 using computational analysis evaluating the ligand's binding affinity to replicating groove to the active site. The findings of this analysis showed Cytarabine of -5.65 Kcal/mol with the highest binding probability (70%) to replicating groove of 6M71. The complex stability was then examined over 19 ns molecular dynamics simulation suggesting that Cytarabine might be possible potent inhibitor for the SARS-CoV-2 RNA Dependent RNA Polymerase.

Discovery of Natural Lead Compound from Dendrobium sp. against SARS-CoV-2 Infection

Since the pandemic of severe acute respiratory syndrome coronavirus (SARS-CoV-2) in December 2019, the infection cases have quickly increased by more than 511 million people. The long epidemic outbreak over 28 months has affected health and economies worldwide. An alternative medicine appears to be one choice to alleviate symptoms and reduce mortality during drug shortages. Dendrobium extract is one of the traditional medicines used for COVID-19 infection. Several compounds in Dendrobium sp. had been reported to exert pharmacological activities to treat common COVID-19-related symptoms. Herein, in silico screening of 83 compounds from Dendrobium sp. by using the SARS-CoV-2 spike protein receptor-binding domain (RBD) as a drug target was performed in searching for a new lead compound against SARS-CoV-2 infection. Four hit compounds showing good binding affinity were evaluated for antiviral infection activity. The new lead compound DB36, 5-methoxy-7-hydroxy-9,10-dihydro-1,4-phenanthrenequinone, was identified with the IC50 value of 6.87 ± 3.07 µM. The binding mode revealed that DB36 bound with the spike protein at the host receptor, angiotensin-converting enzyme 2 (ACE2) binding motif, resulted in antiviral activity. This study substantiated the use of Dendrobium extract for the treatment of SARS-CoV-2 infection and has identified new potential chemical scaffolds for further drug development of SARS-CoV-2 entry inhibitors.

Repurposing of Four Drugs as Anti-SARS-CoV-2 Agents and Their Interactions with Protein Targets

Although there are existing vaccines against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), new COVID-19 cases are increasing due to low immunization coverage and the emergence of new variants. For this reason, new drugs to treat and prevent severe COVID-19 are needed. Here, we provide four different FDA-approved drugs against SARS-CoV-2 proteins involved in the entry and replication process, aiming to identify potential drugs to treat COVID-19. We use the main protease (Mpro), the spike glycoprotein (S protein), and RNA-dependent RNA polymerase (RdRp) as protein targets for anti- SARS-CoV-2 drugs. In our constructed database, we selected different drugs against each target (Mpro, S protein, and RdRp) based on their common interactions with relevant residues involved in viral entry at the host cell and replication. Furthermore, their stability inside the binding pocket, as well as their predicted binding-free energy, allow us to provide new insight into the possible drug repurposing of viomycin (interacting with Mpro) due to its interactions with key residues, such as Asn 143, Glu 166, and Gln 189 at the same time as hesperidin (interacting with the S protein) is interacting with residues Tyr 449, Ser 494, and Thr 500, keeping inside the predicted binding pocket, as well as interacting with residues in different variants of concern. Finally, we also suggest nystatin and elvitegravir (interacting with RdRp) as possible drugs due to their stability within the predicted pocket along the simulation and their interaction with key residues, such as Asp 760, Asp 761, and Asp 618. Altogether our results provide new knowledge about the possible mechanism of the inhibition of viomycin, hesperidin, elvitegravir, and nystatin to inhibit the viral life cycle of SARS-CoV-2 and some of its variants of concern (VOC). Additionally, some iodide-based contrast agents were also found to bind the S protein strongly, i.e., iohexol (−58.99 Kcal/mol), iotrolan (−76.19 Kcal/mol), and ioxilan (−62.37 Kcal/mol). Despite the information we report here as the possible strong interaction between these contrast agents and the SARS-CoV-2′s S protein, Mpro, and RdRp, we believe that further investigation, including chemical modifications in their structures, are needed for COVID-19 treatment.

Molecular Docking as a Potential Approach in Repurposing Drugs Against COVID-19: a Systematic Review and Novel Pharmacophore Models

Purpose of Review

This article provides a review of the recent literature related to the FDA-approved drugs that had been repurposed as potential drug candidates against COVID-19. Moreover, we performed a quality pharmacophore study for frequently studied targets, namely, the main protease, RNA-dependent RNA polymerase, and spike protein.

Recent Findings

Ever since the COVID-19 pandemic, the whole spectrum of scientific community is still unable to invent an absolute therapeutic agent for COVID-19. Considering such a fact, drug repurposing strategies seem a truly viable approach to develop novel therapeutic interventions.

Summery

Drug repurposing explores previously approved drugs of known safety and pharmacokinetics profile for possible new effects, reducing the cost, time, and predicting prospective side effects and drug interactions. COVID-19 virulent machinery appeared similar to other viruses, making antiviral agents widely repurposed in pursuit for curative candidates. Our main protease pharmacophoric study revealed multiple features and could be a probable starting point for upcoming research.

A Generalized Attraction-Repulsion Potential and Revisited Fragment Library Improves PEP-FOLD Peptide Structure Prediction

Fast and accurate structure prediction is essential to the study of peptide function, molecular targets, and interactions and has been the subject of considerable efforts in the past decade. In this work, we present improvements to the popular simplified PEP-FOLD technique for small peptide structure prediction. PEP-FOLD originality is threefold: (i) it uses a predetermined structural alphabet, (ii) it uses a sequential algorithm to reconstruct the tridimensional structures of these peptides in a discrete space using a fragment library, and (iii) it assesses the energy of these structures using a coarse-grained representation in which all of the backbone atoms but the α-hydrogen are present, and the side chain corresponds to a unique bead. In former versions of PEP-FOLD, a van der Waals formulation was used for non-bonded interactions, with each side chain being associated with a fixed radius. Here, we explore the relevance of using instead a generalized formulation in which not only the optimal distance of interaction and the energy at this distance are parameters but also the distance at which the potential is zero. This allows each side chain to be associated with a different radius and potential energy shape, depending on its interaction partner, and in principle to make more effective the coarse-grained representation. In addition, the new PEP-FOLD version is associated with an updated library of fragments. We show that these modifications lead to important improvements for many of the problematic targets identified with the former PEP-FOLD version while maintaining already correct predictions. The improvement is in terms of both model ranking and model accuracy. We also compare the PEP-FOLD enhanced version to state-of-the-art techniques for both peptide and structure predictions: APPTest, RaptorX, and AlphaFold2. We find that the new predictions are superior, in particular with respect to the prediction of small β-targets, to those of APPTest and RaptorX and bring, with its original approach, additional understanding on folded structures, even when less precise than AlphaFold2. With their strong physical influence, the revised structural library and coarse-grained potential offer, however, the means for a deeper understanding of the nature of folding and open a solid basis for studying flexibility and other dynamical properties not accessible to IA structure prediction approaches.

Vasopressin and Its Analogues: From Natural Hormones to Multitasking Peptides

Human neurohormone vasopressin (AVP) is synthesized in overlapping regions in the hypothalamus. It is mainly known for its vasoconstricting abilities, and it is responsible for the regulation of plasma osmolality by maintaining fluid homeostasis. Over years, many attempts have been made to modify this hormone and find AVP analogues with different pharmacological profiles that could overcome its limitations. Non-peptide AVP analogues with low molecular weight presented good affinity to AVP receptors. Natural peptide counterparts, found in animals, are successfully applied as therapeutics; for instance, lypressin used in treatment of diabetes insipidus. Synthetic peptide analogues compensate for the shortcomings of AVP. Desmopressin is more resistant to proteolysis and presents mainly antidiuretic effects, while terlipressin is a long-acting AVP analogue and a drug recommended in the treatment of varicose bleeding in patients with liver cirrhosis. Recently published results on diverse applications of AVP analogues in medicinal practice, including potential lypressin, terlipressin and ornipressin in the treatment of SARS-CoV-2, are discussed.

Halogenated Baicalein as a Promising Antiviral Agent toward SARS-CoV-2 Main Protease

The coronavirus disease pandemic is a constant reminder that global citizens are in imminent danger of exposure to emerging infectious diseases. Therefore, developing a technique for inhibitor discovery is essential for effective drug design. Herein, we proposed fragment molecular orbital (FMO)-based virtual screening to predict the molecular binding energy of potential severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease inhibitors. The integration of quantum mechanical approaches and trajectory analysis from a microsecond molecular dynamics simulation was used to identify potential inhibitors. We identified brominated baicalein as a potent inhibitor of the SARS-CoV-2 main protease and confirmed its inhibitory activity in an in vitro assay. Brominated baicalein did not demonstrate significant toxicity in either in vitro or in vivo studies. The pair interaction energy from FMO-RIMP2/PCM and inhibitory constants based on the protease enzyme assay suggested that the brominated baicalein could be further developed into novel SARS-CoV-2 protease inhibitors.

In silico screening of potent inhibitors against COVID-19 key targets from a library of FDA-approved drugs

Coronavirus disease (COVID-19) is an emerging pandemic that threatens the world since the early days of 2020. Development of vaccines or new drugs against COVID-19 comprises several stages of investigation including efficacy, safety, and approval studies. A shortcut to this delicate pathway is computational-based analysis of FDA-approved drugs against assigned molecular targets of the coronavirus. In this study, we virtually screened a library of FDA-approved drugs prescribed for different therapeutic purposes against versatile COVID-19 specific proteins which are crucial for the virus life cycle. Three antibiotics in our screening polymyxin B, bafilomycin A, and rifampicin show motivating binding stability with more than one target of the virus. Another category of tested drugs is oral antiseptics of mouth rinsing solutions that unexpectedly exhibited significant affinity to the target proteins employed by the virus for attachment and cell internalization. Other OTC drugs widely used and tested in our study are heartburn drugs and they show no significant binding. We tested also some other drugs falling under the scope of investigation regarding interference with a degree of severity of COVID-19 like angiotensin II blockers used as antihypertensive, and our study suggests a therapeutic rather than predisposing effect of these drugs against COVID-19.

The Inhibition of SARS-CoV-2 3CL Mpro by Graphene and Its Derivatives from Molecular Dynamics Simulations

At present, the most powerful new drugs for COVID-19 are antibody proteins. In addition, there are some star small molecule drugs. However, there are few studies on nanomaterials. Here, we study the intact graphene (IG), defective graphene (DG), and graphene oxide (GO) interacting with COVID-19 protein. We find that they show progressive inhibition of COVID-19 protein. By using molecular dynamics simulations, we study the interactions between SARS-CoV-2 3CL Mpro and graphene-related materials (GRMs): IG, DG, and GO. The results show that Mpro can be absorbed onto the surfaces of investigated materials. DG and GO interacted with Mpro more intensely, causing the decisive part of Mpro to become more flexible. Further analysis shows that compared to IG and GO, DG can inactivate Mpro and inhibit its expression effectively by destroying the active pocket of Mpro. Our work not only provides detailed and reliable theoretical guidance for the application of GRMs in treating with SARS-CoV-2 but also helps in developing new graphene-based anti-COVID-19 materials.

A new glimpse on the active site of SARS-CoV-2 3CLpro, coupled with drug repurposing study

Coronavirus disease 2019 (COVID-19) is caused by novel severe acute respiratory syndrome coronavirus (SARS-CoV-2). Its main protease, 3C-like protease (3CLpro), is an attractive target for drug design, due to its importance in virus replication. The analysis of the radial distribution function of 159 3CLpro structures reveals a high similarity index. A study of the catalytic pocket of 3CLpro with bound inhibitors reveals that the influence of the inhibitors is local, perturbing dominantly only residues in the active pocket. A machine learning based model with high predictive ability against SARS-CoV-2 3CLpro is designed and validated. The model is used to perform a drug-repurposing study, with the main aim to identify existing drugs with the highest 3CLpro inhibition power. Among antiviral agents, lopinavir, idoxuridine, paritaprevir, and favipiravir showed the highest inhibition potential. Enzyme - ligand interactions as a key ingredient for successful drug design.

Targeting SARS-CoV-2 main protease by teicoplanin: A mechanistic insight by docking, MM/GBSA and molecular dynamics simulation

First emerged in late December 2019, the outbreak of novel severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) pandemic has instigated public-health emergency around the globe. Till date there is no specific therapeutic agent for this disease and hence, the world is craving to identify potential antiviral agents against SARS-CoV-2. The main protease (M^Pro) is considered as an attractive drug target for rational drug design against SARS-CoV-2 as it is known to play a crucial role in the viral replication and transcription. Teicoplanin is a glycopeptide class of antibiotic which is regularly used for treating Gram-positive bacterial infections, has shown potential therapeutic efficacy against SARS-CoV-2 in vitro. Therefore, in this study, a mechanistic insight of intermolecular interactions between teicoplanin and SARS-CoV-2 M^Pro has been scrutinized by molecular docking. Both monomeric and dimeric forms of M^Pro was used in docking involving blind as well as defined binding site based on the known inhibitor. Binding energies of teicoplanin-M^Pro complexes were estimated by Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) computations from docking and simulated trajectories. The dynamic and thermodynamics constraints of docked drug in complex with target proteins under specific physiological conditions was ascertained by all-atom molecular dynamics simulation of 100 ns trajectory. Root mean square deviation and fluctuation of carbon α chain justified the stability of the bound complex in biological environments. The outcomes of current study are supposed to be fruitful in rational design of antiviral drugs against SARS-CoV-2.

Network analytics for drug repurposing in COVID-19

To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein–protein interaction (PPI) networks integrating the top-ranked host factors, the drug target proteins and directed PPI data. We analyzed the networks to identify drug targets and combinations thereof that offer efficient control over the host factors. We validated our findings against clinical studies data and bioinformatics studies. Our method offers a new insight into the molecular details of the disease and into potentially new therapy targets for it. Our approach for drug repurposing is significant beyond COVID-19 and may be applied also to other diseases.

SARS-CoV-2 cell entry and targeted antiviral development

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the pandemic coronavirus disease 2019 (COVID-19), which threatens human health and public safety. In the urgent campaign to develop anti-SARS-CoV-2 therapies, the initial entry step is one of the most appealing targets. In this review, we summarize the current understanding of SARS-CoV-2 cell entry, and the development of targeted antiviral strategies. Moreover, we speculate upon future directions toward next-generation of SARS-CoV-2 entry inhibitors during the upcoming post-pandemic era.

Exploring the Regulatory Function of the N-terminal Domain of SARS-CoV-2 Spike Protein through Molecular Dynamics Simulation

SARS-CoV-2 is what has caused the COVID-19 pandemic. Early viral infection is mediated by the SARS-CoV-2 homo-trimeric Spike (S) protein with its receptor binding domains (RBDs) in the receptor-accessible state. Molecular dynamics simulation on the S protein with a focus on the function of its N-terminal domains (NTDs) is performed. The study reveals that the NTD acts as a "wedge" and plays a crucial regulatory role in the conformational changes of the S protein. The complete RBD structural transition is allowed only when the neighboring NTD that typically prohibits the RBD's movements as a wedge detaches and swings away. Based on this NTD "wedge" model, it is proposed that the NTD-RBD interface should be a potential drug target.

An overview of potential inhibitors targeting non-structural proteins 3 (PLpro and Mac1) and 5 (3CLpro/Mpro) of SARS-CoV-2

There is an urgent need to develop effective treatments for coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The rapid spread of SARS-CoV-2 has resulted in a global pandemic that has not only affected the daily lives of individuals but also had a significant impact on the global economy and public health. Although extensive research has been conducted to identify inhibitors targeting SARS-CoV-2, there are still no effective treatment strategies to combat COVID-19. SARS-CoV-2 comprises two important proteolytic enzymes, namely, the papain-like proteinase, located within non-structural protein 3 (nsp3), and nsp5, both of which cleave large replicase polypeptides into multiple fragments that are required for viral replication. Moreover, a domain within nsp3, known as the macrodomain (Mac1), also plays an important role in viral replication. Inhibition of their functions should be able to significantly interfere with the replication cycle of the virus, and therefore these key proteins may serve as potential therapeutic targets. The functions of the above viral targets and their corresponding inhibitors have been summarized in the current review. This review provides comprehensive updates of nsp3 and nsp5 inhibitor development and would help advance the discovery of novel anti-viral therapeutics against SARS-CoV-2.

Comprehensive Consensus Analysis of SARS-CoV-2 Drug Repurposing Campaigns

The current COVID-19 pandemic has elicited extensive repurposing efforts (both small and large scale) to rapidly identify COVID-19 treatments among approved drugs. Herein, we provide a literature review of large-scale SARS-CoV-2 antiviral drug repurposing efforts and highlight a marked lack of consistent potency reporting. This variability indicates the importance of standardizing best practices-including the use of relevant cell lines, viral isolates, and validated screening protocols. We further surveyed available biochemical and virtual screening studies against SARS-CoV-2 targets (Spike, ACE2, RdRp, PLpro, and Mpro) and discuss repurposing candidates exhibiting consistent activity across diverse, triaging assays and predictive models. Moreover, we examine repurposed drugs and their efficacy against COVID-19 and the outcomes of representative repurposed drugs in clinical trials. Finally, we propose a drug repurposing pipeline to encourage the implementation of standard methods to fast-track the discovery of candidates and to ensure reproducible results.

Drug repurposing against SARS-CoV-2 receptor binding domain using ensemble-based virtual screening and molecular dynamics simulations

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused worldwide pandemic and is responsible for millions of worldwide deaths due to -a respiratory disease known as COVID-19. In the search for a cure of COVID-19, drug repurposing is a fast and cost-effective approach to identify anti-COVID-19 drugs from existing drugs. The receptor binding domain (RBD) of the SARS-CoV-2 spike protein has been a main target for drug designs to block spike protein binding to ACE2 proteins. In this study, we probed the conformational plasticity of the RBD using long molecular dynamics (MD) simulations, from which, representative conformations were identified using clustering analysis. Three simulated conformations and the original crystal structure were used to screen FDA approved drugs (2466 drugs) against the predicted binding site at the ACE2-RBD interface, leading to 18 drugs with top docking scores. Notably, 16 out of the 18 drugs were obtained from the simulated conformations, while the crystal structure suggests poor binding. The binding stability of the 18 drugs were further investigated using MD simulations. Encouragingly, 6 drugs exhibited stable binding with RBD at the ACE2-RBD interface and 3 of them (gonadorelin, fondaparinux and atorvastatin) showed significantly enhanced binding after the MD simulations. Our study shows that flexibility modeling of SARS-CoV-2 RBD using MD simulation is of great help in identifying novel agents which might block the interaction between human ACE2 and the SARS-CoV-2 RBD for inhibiting the virus infection.

Benchmarking the Ability of Common Docking Programs to Correctly Reproduce and Score Binding Modes in SARS-CoV-2 Protease Mpro

The coronavirus SARS-CoV-2 main protease, Mpro, is conserved among coronaviruses with no human homolog and has therefore attracted significant attention as an enzyme drug target for COVID-19. The number of studies targeting Mpro for in silico screening has grown rapidly, and it would be of great interest to know in advance how well docking methods can reproduce the correct ligand binding modes and rank these correctly. Clearly, current attempts at designing drugs targeting Mpro with the aid of computational docking would benefit from a priori knowledge of the ability of docking programs to predict correct binding modes and score these correctly. In the current work, we tested the ability of several leading docking programs, namely, Glide, DOCK, AutoDock, AutoDock Vina, FRED, and EnzyDock, to correctly identify and score the binding mode of Mpro ligands in 193 crystal structures. None of the codes were able to correctly identify the crystal structure binding mode (lowest energy pose with root-mean-square deviation < 2 Å) in more than 26% of the cases for noncovalently bound ligands (Glide: top performer), whereas for covalently bound ligands the top score was 45% (EnzyDock). These results suggest that one should perform in silico campaigns of Mpro with care and that more comprehensive strategies including ligand free energy perturbation might be necessary in conjunction with virtual screening and docking.

Combined use of the hepatitis C drugs and amentoflavone could interfere with binding of the spike glycoprotein of SARS-CoV-2 to ACE2: the results of a molecular simulation study

The worldwide rapid spread of the COVID-19 disease necessitates the search for fast and effective treatments. The repurposing of existing drugs seems to be the best solution in this situation. In this study, the molecular docking method was used to test 248 drugs against the receptor-binding domain (RBD) of spike glycoprotein of SARS-CoV-2, which is responsible for viral entry into the host cell. Among the top-ranked ligands are drugs that are used for hepatitis C virus (HCV) treatments (paritaprevir, ledipasvir, simeprevir) and a natural biflavonoid amentoflavone. The binding sites of the HCV drugs and amentoflavone are different. Therefore, the ternary complexes of the HCV drug, amentoflavone, and RBD can be created. For the 5 top-ranked ligands, the validating molecular dynamics simulations of binary and ternary complexes with RBD were performed. According to the MMPBSA-binding free energies, the HCV drugs ledipasvir and paritaprevir (in a neutral form) are the most efficient binders of the RBD when used in combination with amentoflavone.Communicated by Ramaswamy H. Sarma.