First structure-activity relationship analysis of SARS-CoV-2 virus main protease (Mpro) inhibitors: an endeavor on COVID-19 drug discovery

Is it feasible to use AI-based drug design methods in the process of generating effective COVID-19 inhibitors? A validation study using molecular docking, molecular simulation, and pharmacophore methods

Although the COVID-19 pandemic has been brought under control to some extent globally, there is still debate in the industry about the feasibility of using artificial intelligence (AI) to generate COVID small-molecule inhibitors. In this study, we explored the feasibility of using AI to design effective inhibitors of COVID-19. By combining a generative model with reinforcement learning and molecular docking, we designed small-molecule inhibitors targeting the COVID-19 3CLpro enzyme. After screening based on molecular docking scores and physicochemical properties, we obtained five candidate inhibitors. Furthermore, theoretical calculations confirmed that these candidate inhibitors have significant binding stability with COVID-19 3CLpro, comparable to or better than existing COVID-19 inhibitors. Additionally, through ligand-based pharmacophore model screening, we validated the effectiveness of the generative model, demonstrating the potential value of AI in drug design.

Exploring the key structural attributes and chemico-biological interactions of pyridinone-based SARS-CoV-2 3CLpro inhibitors through validated structure-based drug design strategies

The global outbreak of COVID-19 infection is the first pandemic the world has experienced in this 21st century. The novel coronavirus 2019 (nCoV-19) also called the SARS-CoV-2 is the reason behind the severe acute respiratory syndrome (SARS) that led to this worldwide crisis. In this current post-pandemic situation, despite having effective vaccines, the paucity of orally administrable drug molecules for such infections is a major drawback in this current scenario. Among the different viral enzymes, the SARS-CoV-2 3CLpro is an encouraging target for effective drug discovery and development. In this context, the understanding of the requirements of the small molecules at the active site and their interactions is a crucial aspect of such drug candidate development. Here in this study, structure-based pharmacophore model development and molecular docking-dependent 2D-interaction-based and 3D-field-based QSAR studies have been carried out for a set of potential SARS-CoV-2 3CLpro inhibitors. This study exposed the importance of interactions with amino acids of the active site (such as Leu167 and Gln189 amino acid residues) as well as the importance of hydrogen bond acceptor groups at the S2 and S1' pockets. The presence of hydrophobic aromatic features as well as hydrophobic contacts at the S1 and S4 pockets were also found to have a key contribution to the SARS-CoV-2 3CLpro inhibition. Moreover, the screened drug candidate Elobixibat from the structure-based virtual screening also explored promising results as evidenced in MD simulation study and thus, can be a promising drug candidate that can be repurposed to assist in the development of effective anti-SARS-CoV-2 therapy.

Integrated study of Quercetin as a potent SARS-CoV-2 RdRp inhibitor: Binding interactions, MD simulations, and In vitro assays

To find an effective inhibitor for SARS-CoV-2, Quercetin's chemical structure was compared to nine ligands associated with nine key SARS-CoV-2 proteins. It was found that Quercetin closely resembles Remdesivir, the co-crystallized ligand of RNA-dependent RNA polymerase (RdRp). This similarity was confirmed through flexible alignment experiments and molecular docking studies, which showed that both Quercetin and Remdesivir bind similarly to the active site of RdRp. Molecular dynamics (MD) simulations over a 200 ns trajectory, analyzing various factors like RMSD, RG, RMSF, SASA, and hydrogen bonding were conducted. These simulations gave detailed insights into the binding interactions of Quercetin with RdRp compared to Remdesivir. Further analyses, including MM-GBSA, Protein-Ligand Interaction Fingerprints (ProLIF) and Profile PLIP studies, confirmed the stability of Quercetin's binding. Principal component analysis of trajectories (PCAT) provided insights into the coordinated movements within the systems studied. In vitro assays showed that Quercetin is highly effective in inhibiting RdRp, with an IC50 of 122.1 ±5.46 nM, which is better than Remdesivir's IC50 of 21.62 ±2.81 μM. Moreover, Quercetin showed greater efficacy against SARS-CoV-2 In vitro, with an IC50 of 1.149 μg/ml compared to Remdesivir's 9.54 μg/ml. The selectivity index (SI) values highlighted Quercetin's safety margin (SI: 791) over Remdesivir (SI: 6). In conclusion, our comprehensive study suggests that Quercetin is a promising candidate for further research as an inhibitor of SARS-CoV-2 RdRp, providing valuable insights for developing an effective anti-COVID-19 treatment.

Lessons learnt from broad-spectrum coronavirus antiviral drug discovery

INTRODUCTION

Highly pathogenic coronaviruses (CoVs), such as severe acute respiratory syndrome CoV (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV), and the most recent SARS-CoV-2 responsible for the COVID-19 pandemic, pose significant threats to human populations over the past two decades. These CoVs have caused a broad spectrum of clinical manifestations ranging from asymptomatic to severe distress syndromes (ARDS), resulting in high morbidity and mortality.

AREAS COVERED

The accelerated advancements in antiviral drug discovery, spurred by the COVID-19 pandemic, have shed new light on the imperative to develop treatments effective against a broad spectrum of CoVs. This perspective discusses strategies and lessons learnt in targeting viral non-structural proteins, structural proteins, drug repurposing, and combinational approaches for the development of antivirals against CoVs.

EXPERT OPINION

Drawing lessons from the pandemic, it becomes evident that the absence of efficient broad-spectrum antiviral drugs increases the vulnerability of public health systems to the potential onslaught by highly pathogenic CoVs. The rapid and sustained spread of novel CoVs can have devastating consequences without effective and specifically targeted treatments. Prioritizing the effective development of broad-spectrum antivirals is imperative for bolstering the resilience of public health systems and mitigating the potential impact of future highly pathogenic CoVs.

Employing comparative QSAR techniques for the recognition of dibenzofuran and dibenzothiophene derivatives toward MMP-12 inhibition

Among various matrix metalloproteinases (MMPs), MMP-12 is one of the potential targets for cancer and other diseases. However, none of the MMP-12 inhibitors has passed the clinical trials to date. Therefore, designing potential MMP-12 inhibitors as new drug molecules can provide effective therapeutic strategies for several diseases. In this study, a series of dibenzofuran and dibenzothiophene derivatives were subjected to different 2D and 3D-QSAR techniques to point out the crucial structural contributions highly influential toward the MMP-12 inhibitory activity. These techniques identified some structural attributes of these compounds that are responsible for influencing their MMP-12 inhibition. The carboxylic group may enhance proper binding with catalytic Zn2+ ion at the MMP-12 active site. Again, the i-propyl sulfonamido carboxylic acid function contributed positively toward MMP-12 inhibition. Moreover, the dibenzofuran moiety conferred stable binding at the S1' pocket for higher MMP-12 inhibition. The steric and hydrophobic groups were found favourable near the furan ring substituted at the dibenzofuran moiety. Besides these ligand-based approaches, molecular docking and molecular dynamic (MD) simulation studies not only elucidated the importance of several aspects of these MMP-12 inhibitors while disclosing the significance of the finding of these QSAR studies and their influences toward MMP-12 inhibition. The MD simulation study also revealed stable and compact binding between such compounds at the MMP-12 active site. Therefore, the findings of these validated ligand-based and structure-based molecular modeling studies can aid the development of selective and potent lead molecules that can be used for the treatment of MMP-12-associated diseases.Communicated by Ramaswamy H. Sarma.

Identification of Pyrazole Derivatives of Usnic Acid as Novel Inhibitor of SARS-CoV-2 Main Protease Through Virtual Screening Approaches

The infection produced by the SARS-CoV-2 virus remains a significant health crisis worldwide. The lack of specific medications for COVID-19 necessitates a concerted effort to find the much-desired therapies for this condition. The main protease (Mpro) of SARS-CoV-2 is a promising target, vital for virus replication and transcription. In this study, fifty pyrazole derivatives were tested for their pharmacokinetics and drugability, resulting in eight hit compounds. Subsequent molecular docking simulations on SARS-CoV-2 main protease afforded two lead compounds with strong affinity at the active site. Additionally, the molecular dynamics (MD) simulations of lead compounds (17 and 39), along with binding free energy calculations, were accomplished to validate the stability of the docked complexes and the binding poses achieved in docking experiments. Based on these findings, compound 17 and 39, with their favorable projected pharmacokinetics and pharmacological characteristics, are the proposed potential antiviral candidates which require further investigation to be used as anti-SARS-CoV-2 medication.

Fourteen immunomodulatory alkaloids and two prenylated phenylpropanoids with dual therapeutic approach for COVID-19: molecular docking and dynamics studies

The pandemic outbreak of COVID-19 caused by the new severe acute respiratory syndrome coronavirus (SARS-CoV-2) is a global health burden. To date, there is no highly effective antiviral therapy to eradicate the virus; as a result, researchers are racing to introduce new potential therapeutic agents. Alternatively, traditional immunity boosters and symptomatic treatment based on natural bioactive compounds are also an option. The 3-chymotrypsin-like protease (3CLpro) crystal structure, the main proteolytic enzyme of SARS-CoV-2, has been unraveled, allowing the development of effective protease inhibitors via in silico and biological studies. In COVID-19 infected patients, the loss of lung function, and mortality are reported to be linked to several inflammatory mediators and cytokines. In this context, the approach of introducing immunomodulatory agents may be considered a dual lifesaving strategy in combination with antiviral drugs. This study aims to provide immunomodulatory natural products exhibiting potential protease inhibitory activities. Selected groups of alkaloids of different classes and two prenylated phenylpropanoids from the Brazilian green propolis were in silico screened for their ability to inhibit COVID-19 3CLpro protease. Results showed that compounds exhibited binding energy scores with values ranging from -6.96 to -3.70 compared to the reference synthetic protease inhibitor O6K with a binding energy score of -7.57. O6K binding energy was found comparable with lead phytochemicals in our study, while their toxicity and drug-likeness criteria are better than that of O6K. The activities of these molecules are mainly ascribed to their ability to form hydrogen bonding with 3CLpro crucial amino acid residues of the catalytic site. In addition, the molecular dynamics simulations further showed that some of these compounds formed stable complexes as evidenced by the occupancy fraction measurements. The study suggested that the major immunomodulators 3β, 20α-diacetamido-5α-pregnane, (20S)-(benzamido)-3β-(N,N-dimethyamino)-pregnane, and baccharin are 3CLpro inhibitors. Biological screenings of these phytochemicals will be valuable to experimentally validate and consolidate the results of this study before a rigid conclusion is reached, which may pave the way for the development of efficient modulatory bioactive compounds with dual bioactions in COVID-19 intervention. Communicated by Ramaswamy H. Sarma.

Recent advances in chemometric modelling of inhibitors against SARS-CoV-2

The outbreak of the novel coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused great harm to all countries worldwide. This disease can be prevented by vaccination and managed using various treatment methods, including injections, oral medications, or aerosol therapies. However, the selection of suitable compounds for the research and development of anti-SARS-CoV-2 drugs is a daunting task because of the vast databases of available compounds. The traditional process of drug research and development is time-consuming, labour-intensive, and costly. The application of chemometrics can significantly expedite drug R&D. This is particularly necessary and important for drug development against pandemic public emergency diseases, such as COVID-19. Through various chemometric techniques, such as quantitative structure-activity relationship (QSAR) modelling, molecular docking, and molecular dynamics (MD) simulations, compounds with inhibitory activity against SARS-CoV-2 can be quickly screened, allowing researchers to focus on the few prioritised candidates. In addition, the ADMET properties of the screened candidate compounds should be further explored to promote the successful discovery of anti-SARS-CoV-2 drugs. In this case, considerable time and economic costs can be saved while minimising the need for extensive animal experiments, in line with the 3R principles. This paper focuses on recent advances in chemometric modelling studies of COVID-19-related inhibitors, highlights current limitations, and outlines potential future directions for development.

Novel designed analogues of quercetin against SARS-CoV2:an in-silico pharmacokinetic evaluation, molecular modeling, MD simulations based study

Here we present the design of the series of quercetin analogues and their molecular docking study involving the binding of quercetin and its analogues with SARS-CoV2 3CLpro. The scientific literature shows that quercetin compound has been successfully used against SARS-CoV by inhibiting the replication of virus in respiratory epithelial cell through the inhibition of the SARS-CoV main protease (3CLpro.) It was suggested that the modification at position 3 in quercetin structure may produce potent compounds against SARS-CoV2. A series of quercetin analogues were designed and screened for physicochemical and pharmacokinetics parameters. The activities of selected compounds against SARS-CoV2 were screened by molecular modelling and evaluated that analogues, Q5, Q6 and Q13 have the best docking scores (-8.01 to -8.17 kcal/mol) and also better than quercetin, α-ketoamide and current available inhibitors of the same target. The structure-activity relationship (SAR) study revealed that the introduction of the amino group in a designed molecule was highly promising for increasing the inhibitory activity against SARS-CoV2 3CL pro. Moreover, to check the stability and orientation of selected compounds inside the binding pocket, the molecular dynamic simulations were performed for 100 ns. Results revealed that the designed analogues Q1, Q6 and Q13 having lowest binding energies (-8.0, -8.17 and -8.06 kcal/mol respectively) as well as better physicochemical properties, pharmacokinetics, and toxicity profile show their potential to synthesize and develop as the therapeutic agents against corona virus.Communicated by Ramaswamy H. Sarma.

Computer-assisted drug discovery of potential natural inhibitors of the SARS-CoV-2 RNA-dependent RNA polymerase through a multi-phase in silico approach

BACKGROUND

The COVID-19 pandemic has led to significant loss of life and economic disruption worldwide. Currently, there are limited effective treatments available for this disease. SARS-CoV-2 RNA-dependent RNA polymerase (SARS-CoV-2 RdRp) has been identified as a potential target for drug development against COVID-19. Natural products have been shown to possess antiviral properties, making them a promising source for developing drugs against SARS-CoV-2.

OBJECTIVES

The objective of this study is to identify the most effective natural inhibitors of SARS-CoV-2 RdRp among a set of 4924 African natural products using a multi-phase in silico approach.

METHODS

The study utilized remdesivir (RTP), the co-crystallized ligand of RdRp, as a starting point to select compounds that have the most similar chemical structures among the examined set of compounds. Molecular fingerprints and structure similarity studies were carried out in the first part of the study. The second part of the study included molecular docking against SARS-CoV-2 RdRp (PDB ID: 7BV2) and Molecular Dynamics (MD) simulations including the calculation of RMSD, RMSF, Rg, SASA, hydrogen bonding, and PLIP. Moreover, the calculations of Molecular mechanics with generalised Born and surface area solvation (MM-GBSA) Lennard-Jones and Columbic electrostatic interaction energies have been conducted. Additionally, in silico ADMET and toxicity studies were performed to examine the drug likeness degrees of the selected compounds.

RESULTS

Eight compounds were identified as the most effective natural inhibitors of SARS-CoV-2 RdRp. These compounds are kaempferol 3-galactoside, kaempferol 3-O-β-D-glucopyranoside, mangiferin methyl ether, luteolin 7-O-β-D-glucopyranoside, quercetin-O-β-D-3-glucopyranoside, 1-methoxy-3-indolylmethyl glucosinolate, naringenin, and asphodelin A 4'-O-β-D-glucopyranoside.

CONCLUSION

The results of this study provide valuable information for the development of natural product-based drugs against COVID-19. However, the elected compounds should be further studied in vitro and in vivo to confirm their efficacy in treating COVID-19.

In silico identification of 1,2,4-triazoles as potential Candida Albicans inhibitors using 3D-QSAR, molecular docking, molecular dynamics simulations, and ADMET profiling

Fluconazole and Voriconazole are individual antifungal inhibitors broadly adopted for treating fungal infections, including Candida Albicans. Unfortunately, these medicines clinically used have significant side effects. Consequently, the improvement of safer and better therapy became more indispensable. In this study, a set of 27 1,2,4-triazole compounds have been tested as potential Candida Albicans inhibitors by using different theoretical methods. The created comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) contour maps significantly impacted the development of novel Candida Albicans inhibitors with valuable activities. The mode of interactions between the 1,2,4-triazole inhibitors and the targeted receptor was studied by molecular docking simulation. The proposed new molecule P1 showed satisfied stability in the active pocket of the targeted receptor compared to the more active molecule in the dataset compared to Fluconazole medication. Meanwhile, the binding energy obtained by molecular docking for molecule P1 is - 9.3 kcal/mol compared with - 6.7 kcal/mol for Fluconazole medication. Also, MM/GBSA value obtained by molecular dynamics simulations at 100 ns for molecule P1 is - 33.34 kcal/mol compared with - 15.85 kcal/mol for Fluconazole medication. In addition, molecule P1 showed good oral bioavailability and was non-toxic according to ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties. Therefore, the results indicated compound P1 might be a future inhibitor of Candida Albicans infection.

Novel CYP11A1-Derived Vitamin D and Lumisterol Biometabolites for the Management of COVID-19

Vitamin D deficiency is associated with a higher risk of SARS-CoV-2 infection and poor outcomes of the COVID-19 disease. However, a satisfactory mechanism explaining the vitamin D protective effects is missing. Based on the anti-inflammatory and anti-oxidative properties of classical and novel (CYP11A1-derived) vitamin D and lumisterol hydroxymetabolites, we have proposed that they would attenuate the self-amplifying damage in lungs and other organs through mechanisms initiated by interactions with corresponding nuclear receptors. These include the VDR mediated inhibition of NFκβ, inverse agonism on RORγ and the inhibition of ROS through activation of NRF2-dependent pathways. In addition, the non-receptor mediated actions of vitamin D and related lumisterol hydroxymetabolites would include interactions with the active sites of SARS-CoV-2 transcription machinery enzymes (M^pro;main protease and RdRp;RNA dependent RNA polymerase). Furthermore, these metabolites could interfere with the binding of SARS-CoV-2 RBD with ACE2 by interacting with ACE2 and TMPRSS2. These interactions can cause the conformational and dynamical motion changes in TMPRSS2, which would affect TMPRSS2 to prime SARS-CoV-2 spike proteins. Therefore, novel, CYP11A1-derived, active forms of vitamin D and lumisterol can restrain COVID-19 through both nuclear receptor-dependent and independent mechanisms, which identify them as excellent candidates for antiviral drug research and for the educated use of their precursors as nutrients or supplements in the prevention and attenuation of the COVID-19 disease.

A critical analysis of urea transporter B inhibitors: molecular fingerprints, pharmacophore features for the development of next-generation diuretics

Urea transporter is a membrane transport protein. It is involved in the transferring of urea across the cell membrane in humans. Along with urea transporter A, urea transporter B (UT-B) is also responsible for the management of urea concentration and blood pressure of human. The inhibitors of urea transporters have already generated a huge attention to be developed as alternate safe class of diuretic. Unlike conventional diuretics, these inhibitors are suitable for long-term therapy without hampering the precious electrolyte imbalance in the human body. In this study, UT-B inhibitors were analysed by using multi-chemometric modelling approaches. The possible pharmacophore features along with favourable and unfavourable sub-structural fingerprints for UT-B inhibition are extracted. This information will guide the medicinal chemist to design potent UT-B inhibitors in future.

Discovery of novel potential inhibitors of TMPRSS2 and Mpro of SARS-CoV-2 using E-pharmacophore and docking-based virtual screening combined with molecular dynamic and quantum mechanics

The pandemic of coronavirus disease is caused by the SARS-CoV-2 which is considered a global health issue. The main protease of COVID 19 (Mpro) has an important role in viral multiplication in the host cell. Inhibiting Mpro is a novel approach to drug discovery and development. Also, transmembrane serine proteases (TMPSS2) facilitate viral activation by cleavage S glycoproteins, thus considered one of the essential host factors for COVID-19 pathogenicity. Computational tools were widely used to reduce time and costs in search of effective inhibitors. A chemical library that contains over two million molecules was virtually screened against TMPRSS2. Also, XP docking for the top hits was screened against (Mpro) to identify dual-target inhibitors. Furthermore, MM-GBSA and predictive ADMET were performed. The top hits were further studied through density functional theory (DFT) calculation and showed good binding to the active sites. Moreover, molecular dynamics (MD) for the top hits were performed which gave information about the stability of the protein-ligand complex during the simulation period. This study has led to the discovery of potential dual-target inhibitors Z751959696, Z751954014, and Z56784282 for COVID-19 with acceptable pharmacokinetic properties. The outcome of this study can participate in the development of novel inhibitors to defeat SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Novel covalent and non-covalent complex-based pharmacophore models of SARS-CoV-2 main protease (Mpro) elucidated by microsecond MD simulations

As the world enters its second year of the pandemic caused by SARS-CoV-2, intense efforts have been directed to develop an effective diagnosis, prevention, and treatment strategies. One promising drug target to design COVID-19 treatments is the SARS-CoV-2 M^pro. To date, a comparative understanding of M^pro dynamic stereoelectronic interactions with either covalent or non-covalent inhibitors (depending on their interaction with a pocket called S1' or oxyanion hole) has not been still achieved. In this study, we seek to fill this knowledge gap using a cascade in silico protocol of docking, molecular dynamics simulations, and MM/PBSA in order to elucidate pharmacophore models for both types of inhibitors. After docking and MD analysis, a set of complex-based pharmacophore models was elucidated for covalent and non-covalent categories making use of the residue bonding point feature. The highest ranked models exhibited ROC-AUC values of 0.93 and 0.73, respectively for each category. Interestingly, we observed that the active site region of M^pro protein-ligand complex undergoes large conformational changes, especially within the S2 and S4 subsites. The results reported in this article may be helpful in virtual screening (VS) campaigns to guide the design and discovery of novel small-molecule therapeutic agents against SARS-CoV-2 M^pro protein.

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

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

Metal-based strategies for the fight against COVID-19

The emerging COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed over six million lives globally to date. Despite the availability of vaccines, the pandemic still cannot be fully controlled owing to rapid mutation of the virus that renders enhanced transmissibility and antibody evasion. This is thus an unmet need to develop safe and effective therapeutic options for COVID-19, in particular, remedies that can be used at home. Considering the great success of multi-targeted cocktail therapy for the treatment of viral infections, metal-based drugs might represent a unique and new source of antivirals that resemble a cocktail therapy in terms of their mode of actions. In this review, we first summarize the role that metal ions played in SARS-CoV-2 viral replication and pathogenesis, then highlight the chemistry of metal-based strategies in the fight against SARS-CoV-2 infection, including both metal displacement and chelation based approaches. Finally, we outline a perspective and direction on how to design and develop metal-based antivirals for the fight against the current or future coronavirus pandemic.

The effect of various compounds on the COVID mechanisms, from chemical to molecular aspects

The novel coronavirus that caused COVID-19 pandemic is SARS-CoV-2. Although various vaccines are currently being used to prevent the disease's severe consequences, there is still a need for medications for those who become infected. The SARS-CoV-2 has a variety of proteins that have been studied extensively since the virus's advent. In this review article, we looked at chemical to molecular aspects of the various structures studied that have pharmaceutical activity and attempted to find a link between drug activity and compound structure. For example, designing of the compounds which bind to the allosteric site and modify hydrogen bonds or the salt bridges can disrupt SARS-CoV2 RBD–ACE2 complex. It seems that quaternary ammonium moiety and quinolin-1-ium structure could act as a negative allosteric modulator to reduce the tendency between spike-ACE2. Pharmaceutical structures with amino heads and hydrophobic tails can block envelope protein to prevent making mature SARS-CoV-2. Also, structures based on naphthalene pharmacophores or isosteres can form a strong bond with the PLpro and form a π-π and the Mpro's active site can be occupied by octapeptide compounds or linear compounds with a similar fitting ability to octapeptide compounds. And for protein RdRp, it is critical to consider pH and pKa so that pKa regulation of compounds to comply with patients is very effective, thus, the presence of tetrazole, phenylpyrazole groups, and analogs of pyrophosphate in the designed drugs increase the likelihood of the RdRp active site inhibition. Finally, it can be deduced that designing hybrid drug molecules along with considering the aforementioned characteristics would be a suitable approach for developing medicines in order to accurate targeting and complete inhibition this virus.

Ligand and Structure-Based In Silico Determination of the Most Promising SARS-CoV-2 nsp16-nsp10 2'-o-Methyltransferase Complex Inhibitors among 3009 FDA Approved Drugs

As a continuation of our earlier work against SARS-CoV-2, seven FDA-approved drugs were designated as the best SARS-CoV-2 nsp16-nsp10 2'-o-methyltransferase (2'OMTase) inhibitors through 3009 compounds. The in silico inhibitory potential of the examined compounds against SARS-CoV-2 nsp16-nsp10 2'-o-methyltransferase (PDB ID: (6W4H) was conducted through a multi-step screening approach. At the beginning, molecular fingerprints experiment with SAM (S-Adenosylmethionine), the co-crystallized ligand of the targeted enzyme, unveiled the resemblance of 147 drugs. Then, a structural similarity experiment recommended 26 compounds. Therefore, the 26 compounds were docked against 2'OMTase to reveal the potential inhibitory effect of seven promising compounds (Protirelin, (1187), Calcium folinate (1913), Raltegravir (1995), Regadenoson (2176), Ertapenem (2396), Methylergometrine (2532), and Thiamine pyrophosphate hydrochloride (2612)). Out of the docked ligands, Ertapenem (2396) showed an ideal binding mode like that of the co-crystallized ligand (SAM). It occupied all sub-pockets of the active site and bound the crucial amino acids. Accordingly, some MD simulation experiments (RMSD, RMSF, Rg, SASA, and H-bonding) have been conducted for the 2'OMTase-Ertapenem complex over 100 ns. The performed MD experiments verified the correct binding mode of Ertapenem against 2'OMTase exhibiting low energy and optimal dynamics. Finally, MM-PBSA studies indicated that Ertapenem bonded advantageously to the targeted protein with a free energy value of -43 KJ/mol. Furthermore, the binding free energy analysis revealed the essential amino acids of 2'OMTase that served positively to the binding. The achieved results bring hope to find a treatment for COVID-19 via in vitro and in vivo studies for the pointed compounds.

Discovery of SARS-CoV-2 3CLPro Peptidomimetic Inhibitors through the Catalytic Dyad Histidine-Specific Protein-Ligand Interactions

As the etiological agent for the coronavirus disease 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) challenges the ongoing efforts of vaccine development and drug design. Due to the accumulating cases of breakthrough infections, there are urgent needs for broad-spectrum antiviral medicines. Here, we designed and examined five new tetrapeptidomimetic anti-SARS-CoV-2 inhibitors targeting the 3C-Like protease (3CL^Pro), which is highly conserved among coronaviruses and essential for viral replications. We significantly improved the efficacy of a ketoamide lead compound based on high-resolution co-crystal structures, all-atom simulations, and binding energy calculations. The inhibitors successfully engaged the catalytic dyad histidine residue (H41) of 3CLPro as designed, and they exhibited nanomolar inhibitory capacity as well as mitigated the viral loads of SARS-CoV-2 in cellular assays. As a widely applicable design principle, our results revealed that the potencies of 3CL^Pro-specific drug candidates were determined by the interplay between 3CL^Pro H41 residue and the peptidomimetic inhibitors.

Virus structure and structure-based antivirals

Structure-based antiviral developments in the past two years have been dominated by the structure determination and inhibition of SARS-CoV-2 proteins and new lead molecules for picornaviruses. The SARS-CoV-2 spike protein has been targeted successfully with antibodies, nanobodies, and receptor protein mimics effectively blocking receptor binding or fusion. The two most promising non-structural proteins sharing strong structural and functional conservation across virus families are the main protease and the RNA-dependent RNA polymerase, for which design and reuse of broad range inhibitors already approved for use has been an attractive avenue. For picornaviruses, the increasing recognition of the transient expansion of the capsid as a critical transition towards RNA release has been targeted through a newly identified, apparently widely conserved, druggable, interprotomer pocket preventing viral entry. We summarize some of the key papers in these areas and ponder the practical uses and contributions of molecular modeling alongside empirical structure determination.

Ligand-based quantitative structural assessments of SARS-CoV-2 3CLpro inhibitors: An analysis in light of structure-based multi-molecular modeling evidences

Due to COVID-19, the whole world is undergoing a devastating situation, but treatment with no such drug candidates still has been established exclusively. In that context, 69 diverse chemicals with potential SARS-CoV-2 3CL^pro inhibitory property were taken into consideration for building different internally and externally validated linear (SW-MLR and GA-MLR), non-linear (ANN and SVM) QSAR, and HQSAR models to identify important structural and physicochemical characters required for SARS-CoV-2 3CL^pro inhibition. Importantly, 2-oxopyrrolidinyl methyl and benzylester functions, and methylene (hydroxy) sulphonic acid warhead group, were crucial for retaining higher SARS-CoV-2 3CL^pro inhibition. These GA-MLR and HQSAR models were also applied to predict some already repurposed drugs. As per the GA-MLR model, curcumin, ribavirin, saquinavir, sepimostat, and remdesivir were found to be the potent ones, whereas according to the HQSAR model, lurasidone, saquinavir, lopinavir, elbasvir, and paritaprevir were the highly effective SARS-CoV-2 3CL^pro inhibitors. The binding modes of those repurposed drugs were also justified by the molecular docking, molecular dynamics (MD) simulation, and binding energy calculations conducted by several groups of researchers. This current work, therefore, may be able to find out important structural parameters to accelerate the COVID-19 drug discovery processes in the future.

The Effect of Allicin on the Proteome of SARS-CoV-2 Infected Calu-3 Cells

Allicin (diallyl thiosulfinate) is the major thiol-reactive organosulfur compound produced by garlic plants (Allium sativum) upon tissue damage. Allicin exerts its strong antimicrobial activity against bacteria and fungi via S-thioallylation of protein thiols and low molecular weight thiols. Here, we investigated the effect of allicin on SARS-CoV-2 infected Vero E6 and Calu-3 cells. Toxicity tests revealed that Calu-3 cells showed greater allicin tolerance, probably due to >4-fold higher GSH levels compared to the very sensitive Vero E6 cells. Exposure of infected Vero E6 and Calu-3 cells to biocompatible allicin doses led to a ∼60–70% decrease of viral RNA and infectious viral particles. Label-free quantitative proteomics was used to investigate the changes in the Calu-3 proteome after SARS-CoV-2 infection and the effect of allicin on the host-virus proteome. SARS-CoV-2 infection of Calu-3 cells caused a strong induction of the antiviral interferon-stimulated gene (ISG) signature, including several antiviral effectors, such as cGAS, Mx1, IFIT, IFIH, IFI16, IFI44, OAS, and ISG15, pathways of vesicular transport, tight junctions (KIF5A/B/C, OSBPL2, CLTCL1, and ARHGAP17) and ubiquitin modification (UBE2L3/5), as well as reprogramming of host metabolism, transcription and translation. Allicin treatment of infected Calu-3 cells reduced the expression of IFN signaling pathways and ISG effectors and reverted several host pathways to levels of uninfected cells. Allicin further reduced the abundance of the structural viral proteins N, M, S and ORF3 in the host-virus proteome. In conclusion, our data demonstrate the antiviral and immunomodulatory activity of biocompatible doses of allicin in SARS-CoV-2-infected cell cultures. Future drug research should be directed to exploit the thiol-reactivity of allicin derivatives with increased stability and lower human cell toxicity as antiviral lead compounds.

Antiviral evaluation of hydroxyethylamine analogs: Inhibitors of SARS-CoV-2 main protease (3CLpro), a virtual screening and simulation approach

The continued toll of COVID-19 has halted the smooth functioning of civilization on a global scale. With a limited understanding of all the essential components of viral machinery and the lack of structural information of this new virus, initial drug discovery efforts had limited success. The availability of high-resolution crystal structures of functionally essential SARS-CoV-2 proteins, including 3CLpro, supports the development of target-specific therapeutics. 3CLpro, the main protease responsible for the processing of viral polypeptide, plays a vital role in SARS-CoV-2 viral replication and translation and is an important target in other coronaviruses. Additionally, 3CLpro is the target of repurposed drugs, such as lopinavir and ritonavir. In this study, target proteins were retrieved from the protein data bank (PDB IDs: 6 M03, 6LU7, 2GZ7, 6 W63, 6SQS, 6YB7, and 6YVF) representing different open states of the main protease to accommodate macromolecular substrate. A hydroxyethylamine (HEA) library was constructed from harvested chemical structures from all the series being used in our laboratories for screening against malaria and Leishmania parasites. The database consisted of ∼1000 structure entries, of which 70% were new to ChemSpider at the time of screening. This in-house library was subjected to high throughput virtual screening (HTVS), followed by standard precision (SP) and then extra precision (XP) docking (Schrodinger LLC 2021). The ligand strain and complex energy of top hits were calculated by Molecular Mechanics Generalized Born Surface Area (MM/GBSA) method. Promising hit compounds (n = 40) specifically binding to 3CLpro with high energy and average MM/GBSA scores were then subjected to (100-ns) MD simulations. Using this sequential selection followed by an in-silico validation approach, we found a promising HEA-based compound (N,N'-((3S,3'S)-piperazine-1,4-diylbis(3-hydroxy-1-phenylbutane-4,2-diyl))bis(2-(5-methyl-1,3-dioxoisoindolin-2-yl)-3-phenylpropanamide)), which showed high in vitro antiviral activity against SARS-CoV-2. Further to reduce the size of the otherwise larger ligand, a pharmacophore-based predicted library of ∼42 derivatives was constructed, which were added to the previous compound library and rescreened virtually. Out of several hits from the predicted library, two compounds were synthesized, tested against SARS-CoV-2 culture, and found to have markedly improved antiviral activity.

A Mild and Highly Diastereoselective Preparation of N-Alkenyl-2-Pyridones via 2-Halopyridinium Salts and Aldehydes

An experimentally simple one-pot preparation of N-alkenyl-2-pyridones is reported. The reaction features mild conditions using readily available 2-halopyridinium salts and aldehydes. N-Alkenyl-2-pyridone formation proceeds with high diastereoselectivity, and a wide range of aldehyde reaction partners is tolerated. Pyridone products are also amenable to further manipulation, including conversion to N-alkyl pyridones and polycyclic ring systems.

Telaprevir is a potential drug for repurposing against SARS-CoV-2: computational and in vitro studies

Drug repurposing is an important approach to the assignment of already approved drugs for new indications. This technique bypasses some steps in the traditional drug approval system, which saves time and lives in the case of pandemics. Direct acting antivirals (DAAs) have repeatedly repurposed from treating one virus to another. In this study, 16 FDA-approved hepatitis C virus (HCV) DAA drugs were studied to explore their activities against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) human and viral targets. Among the 16 HCV DAA drugs, telaprevir has shown the best in silico evidence to work on both indirect human targets (cathepsin L [CTSL] and human angiotensin-converting enzyme 2 [hACE2] receptor) and direct viral targets (main protease [Mpro]). Moreover, the docked poses of telaprevir inside both hACE2 and Mpro were subjected to additional molecular dynamics simulations monitored by calculating the binding free energy using MM-GBSA. In vitro analysis of telaprevir showed inhibition of SARS-CoV-2 replication in cell culture (IC50 = 11.552 μM, CC50 = 60.865 μM, and selectivity index = 5.27). Accordingly, based on the in silico studies and supported by the presented in vitro analysis, we suggest that telaprevir may be considered for therapeutic development against SARS-CoV-2.

Computational strategies towards developing novel SARS-CoV-2 Mpro inhibitors against COVID-19

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains to be a serious threat due to the lack of a specific therapeutic agent. Computational methods are particularly suitable for rapidly fight against SARS-CoV-2. This present research aims to systematically explore the interaction mechanism of a series of novel bicycloproline-containing SARS-CoV-2 M^pro inhibitors through integrated computational approaches. We designed six structurally modified novel SARS-CoV-2 M^pro inhibitors based on the QSAR study. The four designed compounds with higher docking scores were further explored through molecular docking, molecular dynamics (MD) simulations, free energy calculations, and residual energy contributions estimated by the MM-PBSA approach, with comparison to compound 23(PDB entry 7D3I). This research not only provides robust QSAR models as valuable screening tools for the development of anti-COVID-19 drugs, but also proposes the newly designed SARS-CoV-2 M^pro inhibitors with nanomolar activities that can be potentially used for further characterization to treat SARS-CoV-2 virus.

A machine learning regression model for the screening and design of potential SARS-CoV-2 protease inhibitors

The widespread infection caused by the 2019 novel corona virus (SARS-CoV-2) has initiated global efforts to search for antiviral agents. Drug discovery is the first step in the development of commercially viable pharmaceutical products to deal with novel diseases. In an effort to accelerate the screening and drug discovery workflow for potential SARS-CoV-2 protease inhibitors, a machine learning model that can predict the binding free energies of compounds to the SARS-CoV-2 main protease is presented. The optimized multiple linear regression model, which was trained and tested on 226 natural compounds demonstrates reliable prediction performance (r 2 test = 0.81, RMSE test = 0.43), while only requiring five topological descriptors. The externally validated model can help conserve and maximize available resources by limiting biological assays to compounds that yielded favorable outcomes from the model. The emergence of highly infectious diseases will always be a threat to human health and development, which is why the development of computational tools for rapid response is very important.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13721-021-00326-2.

Support Vector Machine as a Supervised Learning for the Prioritization of Novel Potential SARS-CoV-2 Main Protease Inhibitors

In the last year, the COVID-19 pandemic has highly affected the lifestyle of the world population, encouraging the scientific community towards a great effort on studying the infection molecular mechanisms. Several vaccine formulations are nowadays available and helping to reach immunity. Nevertheless, there is a growing interest towards the development of novel anti-covid drugs. In this scenario, the main protease (Mpro) represents an appealing target, being the enzyme responsible for the cleavage of polypeptides during the viral genome transcription. With the aim of sharing new insights for the design of novel Mpro inhibitors, our research group developed a machine learning approach using the support vector machine (SVM) classification. Starting from a dataset of two million commercially available compounds, the model was able to classify two hundred novel chemo-types as potentially active against the viral protease. The compounds labelled as actives by SVM were next evaluated through consensus docking studies on two PDB structures and their binding mode was compared to well-known protease inhibitors. The best five compounds selected by consensus docking were then submitted to molecular dynamics to deepen binding interactions stability. Of note, the compounds selected via SVM retrieved all the most important interactions known in the literature.

Robust classification-based molecular modelling of diverse chemical entities as potential SARS-CoV-2 3CLpro inhibitors: theoretical justification in light of experimental evidences

COVID-19 is the most unanticipated incidence of 2020 affecting the human population worldwide. Currently, it is utmost important to produce novel small molecule anti-SARS-CoV-2 drugs urgently that can save human lives globally. Based on the earlier SARS-CoV and MERS-CoV infection along with the general characters of coronaviral replication, a number of drug molecules have been proposed. However, one of the major limitations is the lack of experimental observations with different drug molecules. In this article, 70 diverse chemicals having experimental SARS-CoV-2 3CL^proinhibitory activity were accounted for robust classification-based QSAR analysis statistically validated with 4 different methodologies to recognize the crucial structural features responsible for imparting the activity. Results obtained from all these methodologies supported and validated each other. Important observations obtained from these analyses were also justified with the ligand-bound crystal structure of SARS-CoV-2 3CL^pro enzyme. Our results suggest that molecules should contain a 2-oxopyrrolidine scaffold as well as a methylene (hydroxy) sulphonic acid warhead in proper orientation to achieve higher inhibitory potency against SARS-CoV-2 3CL^pro. Outcomes of our study may be able to design and discover highly effective SARS-CoV-2 3CL^pro inhibitors as potential anticoronaviral therapy to crusade against COVID-19.

Protease targeted COVID-19 drug discovery: What we have learned from the past SARS-CoV inhibitors?

The fascinating similarity between the SARS-CoV and SARS-CoV-2, inspires scientific community to investigate deeper into the SARS-CoV proteases such as main protease (Mpro) and papain-like protease (PLpro) and their inhibitors for the discovery of SARS-CoV-2 protease inhibitors. Because of the similarity in the proteases of these two corona viruses, there is a greater chance for the previous SARS-CoV Mpro and PLpro inhibitors to provide effective results against SARS-CoV-2. In this context, the molecular fragments from the SARS-CoV protease inhibitors through the fragment-based drug design and discovery technique can be useful guidance for COVID-19 drug discovery. Here, we have focused on the structure-activity relationship studies of previous SARS-CoV protease inhibitors and discussed about crucial fragments generated from previous SARS-CoV protease inhibitors important for the lead optimization of SARS-CoV-2 protease inhibitors. This study surely offers different strategic options of lead optimization to the medicinal chemists to discover effective anti-viral agent against the devastating disease, COVID-19.

Exploring naphthyl derivatives as SARS-CoV papain-like protease (PLpro) inhibitors and its implications in COVID-19 drug discovery

Abstract

Novel coronavirus disease 2019 (COVID-19) emerges as a serious threat to public health globally. The rapid spreading of COVID-19, caused by severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2), proclaimed the multitude of applied research needed not only to save the human health but also for the environmental safety. As per the recent World Health Organization reports, the novel corona virus may never be wiped out completely from the world. In this connection, the inhibitors already designed against different targets of previous human coronavirus (HCoV) infections will be a great starting point for further optimization. Pinpointing biochemical events censorious to the HCoV lifecycle has provided two proteases: a papain-like protease (PLpro) and a 3C-like protease (3CLpro) enzyme essential for viral replication. In this study, naphthyl derivatives inhibiting PLpro enzyme were subjected to robust molecular modelling approaches to understand different structural fingerprints important for the inhibition. Here, we cover two main aspects such as (a) exploration of naphthyl derivatives by classification QSAR analyses to find important fingerprints that module the SARS-CoV PLpro inhibition and (b) implications of naphthyl derivatives against SARS-CoV-2 PLpro enzyme through detailed ligand–receptor interaction analysis. The modelling insights will help in the speedy design of potent broad spectrum PLpro inhibitors against infectious SARS-CoV and SARS-CoV-2 in the future.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at(10.1007/s11030-021-10198-3) .