Virtual screening of approved drugs as potential SARS-CoV-2 main protease inhibitors

Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds

To date, the COVID-19 pandemic has still been infectious around the world, continuously causing social and economic damage on a global scale. One of the most important therapeutic targets for the treatment of COVID-19 is the main protease (Mpro) of SARS-CoV-2. In this study, we combined machine-learning (ML) model with atomistic simulations to computationally search for highly promising SARS-CoV-2 Mpro inhibitors from the representative natural compounds of the National Cancer Institute (NCI) Database. First, the trained ML model was used to scan the library quickly and reliably for possible Mpro inhibitors. The ML output was then confirmed using atomistic simulations integrating molecular docking and molecular dynamic simulations with the linear interaction energy scheme. The results turned out to show that there was evidently good agreement between ML and atomistic simulations. Ten substances were proposed to be able to inhibit SARS-CoV-2 Mpro. Seven of them have high-nanomolar affinity and are very potential inhibitors. The strategy has been proven to be reliable and appropriate for fast prediction of SARS-CoV-2 Mpro inhibitors, benefiting for new emerging SARS-CoV-2 variants in the future accordingly.

Consensus Pharmacophore Strategy For Identifying Novel SARS-Cov-2 Mpro Inhibitors from Large Chemical Libraries

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main Protease (Mpro) is an enzyme that cleaves viral polyproteins translated from the viral genome and is critical for viral replication. Mpro is a target for anti-SARS-CoV-2 drug development, and multiple Mpro crystals complexed with competitive inhibitors have been reported. In this study, we aimed to develop an Mpro consensus pharmacophore as a tool to expand the search for inhibitors. We generated a consensus model by aligning and summarizing pharmacophoric points from 152 bioactive conformers of SARS-CoV-2 Mpro inhibitors. Validation against a library of conformers from a subset of ligands showed that our model retrieved poses that reproduced the crystal-binding mode in 77% of the cases. Using models derived from a consensus pharmacophore, we screened >340 million compounds. Pharmacophore-matching and chemoinformatics analyses identified new potential Mpro inhibitors. The candidate compounds were chemically dissimilar to the reference set, and among them, demonstrating the relevance of our model. We evaluated the effect of 16 candidates on Mpro enzymatic activity finding that seven have inhibitory activity. Three compounds (1, 4, and 5) had IC50 values in the midmicromolar range. The Mpro consensus pharmacophore reported herein can be used to identify compounds with improved activity and novel chemical scaffolds against Mpro. The method developed for its generation is provided as an open-access code (https://github.com/AngelRuizMoreno/ConcensusPharmacophore) and can be applied to other pharmacological targets.

'Synthesis, antiviral activity, molecular docking, and molecular dynamics studies of ethoxy phthalimide pyrazole derivatives against Cytomegalovirus and Varicella-Zoster virus: potential consequences and strategies for developing new antiviral treatments'

Substituted ethoxy phthalimide pyrazole derivatives (6a-e) have been produced using a one-pot synthesis technique. Spectral analysis was used to establish the molecular structure of the synthesized compounds, and they were examined in silico and in vitro for their ability to bind to and inhibit replication of the AD-169 strain, the Davis strain of CMV, the OKA strain and the 07/1 strain of Varicella-Zoster virus (VZV). Molecular Docking was used to estimate the binding mechanism and energy of compounds 4, 6a-e to their respective target proteins, thymidine kinase (TK), Varicella-Zoster protease (VZP) of VZV and tegument protein pp71 (TPpp71) of Cytomegalovirus (CMV). The MIC50 and EC50 were utilized to evaluate the antiviral and cytotoxic activities of test compounds in human embryonic lung (HEL) cells against the two reference medicines, Ganciclovir and Acyclovir. The chemicals studied showed a high affinity for binding sites and near binding sites of target proteins by generating H-bonds, carbon-hydrogen bonds, π-anion, π-sulfur, π-sigma, alkyl and π-alkyl interactions. All of the test compounds (6a-e) had higher binding energy than the standard medications. The ADME/T data suggests that these potential inhibitors are less toxic. Drug-protein complexes are structurally compact and demonstrate minimal conformational change in molecular dynamics (MDs) simulations, indicating stability and stiffness. MM-PBSA and post-simulation analysis can predict lead compound active cavity binding stability. By inhibiting multitargeted proteins, these synthetic compounds may improve antiviral therapy. Our research suggests that these unique synthesized chemicals may be useful and accessible adjuvant antiviral therapy for Varicella Zoster and CMV. HighlightsTwo components synthesis of substituted ethoxy phthalimide pyrazole derivatives (6a-e).Tested compounds (6a-e) have antiviral and cytotoxicity activity against CMV and Varicella-Zoster virus (VZV) in HEL cells.Compounds bind to TK, Varicella-Zoster protease (VZP) of VZV, and modeled TPpp71 of Cytomegalovirus (CMV).In comparison to reference drugs, compounds have strong binding free energy and interactions with VZV and CMV protein complexes.The RMSD, RMSF, Rg, residual correlative motion (RCM), No. of hydrogen bonds, protein secondary structure content, per-residue protein secondary structure and MM/PBSA energy calculated for the selected compound with thymidine kinase (TK), VZP of VZV, and modeled tegument protein pp71 (TPpp71) of CMV through MD simulation studies for 50 ns.In comparison to the two reference drugs, ligands/compounds were found to meet the Lipinski rule of five and to have strong biological activity.Communicated by Ramaswamy H. Sarma.

Systemic computational investigation to identify potential inhibitors against cancer by targeting P21-activated kinase 4 and D(CGATCG)

Cancer accounts for more than 10 million deaths in the year 2020. Development of drugs that specifically target cancer signaling pathways and proteins attain significant importance in the recent past. The p21-activated kinase 4 enzyme, which plays diverse functions in cancer and is reported in elevated expression makes this enzyme an attractive anti-cancer drug target. Similarly, cancer cells' DNA could also serve as a good platform for anti-cancer drug development. Herein, a robust in silico framework is designed to virtually screen multiple drug libraries from diverse sources to identify potential binders of the mentioned cancer targets. The virtual screening process identified three compounds (BAS_01059603, ASN_10027856, and ASN_06916672) as best docked molecules with a binding energy score of ≤ -10 kcal/mol for p21-activated kinase 4 and ≤ -6 kcal/mol for D(CGATCG). In the docking analysis, the filtered compounds revealed stable binding to the same site to which controls bind in X-ray structures. The binding interactions of the compounds with receptors are dominated by van der Waals interactions. The average root mean square deviation (rmsd) value for p21-activated kinase 4 systems is noticed at ∼2 Å, while for D(CGATCG), the average rmsd is 2.7 Å. The MMGB/PBSA interpreted ASN_12674021 to show strong intermolecular binding energy compared to the other two systems and control in both receptors. Moreover, the entropy energy contribution is less than the mean binding energy. In short, the compounds are showing promising binding to the biomolecules and therefore must be evaluated for anti-cancer activity in experimental studies.Communicated by Ramaswamy H. Sarma.

A review on in silico virtual screening methods in COVID-19 using anticancer drugs and other natural/chemical inhibitors

The present coronavirus disease 2019 (COVID-19) pandemic scenario has posed a difficulty for cancer treatment. Even under ideal conditions, malignancies like small cell lung cancer (SCLC) are challenging to treat because of their fast development and early metastases. The treatment of these patients must not be jeopardized, and they must be protected as much as possible from the continuous spread of the COVID-19 infection. Initially identified in December 2019 in Wuhan, China, the contagious coronavirus illness 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Finding inhibitors against the druggable targets of SARS-CoV-2 has been a significant focus of research efforts across the globe. The primary motivation for using molecular modeling tools against SARS-CoV-2 was to identify candidates for use as therapeutic targets from a pharmacological database. In the published study, scientists used a combination of medication repurposing and virtual drug screening methodologies to target many structures of SARS-CoV-2. This virus plays an essential part in the maturation and replication of other viruses. In addition, the total binding free energy and molecular dynamics (MD) modeling findings showed that the dynamics of various medications and substances were stable; some of them have been tested experimentally against SARS-CoV-2. Different virtual screening (VS) methods have been discussed as potential means by which the evaluated medications that show strong binding to the active site might be repurposed for use against SARS-CoV-2.

Identifying inhibitors of NSP16-NSP10 of SARS-CoV-2 from large databases

The COVID-19 pandemic, which has already claimed millions of lives, continues to pose a serious threat to human health, requiring the development of new effective drugs. Non-structural proteins of SARS-CoV-2 play an important role in viral replication and infection. Among them, NSP16 (non-structured protein 16) and its cofactor NSP10 (non-structured protein 10) perform C2'-O methylation at the 5' end of the viral RNA, which promotes efficient virus replication. Therefore, the NSP16-NSP10 complex becomes an attractive target for drug development. Using a multi-step virtual screening protocol which includes Lipinski's rule, docking, steered molecular dynamics and umbrella sampling, we searched for potential inhibitors from the PubChem and anti-HIV databases. It has been shown that CID 135566620 compound from PubChem is the best candidate with an inhibition constant in the sub-μM range. The Van der Waals interaction was found to be more important than the electrostatic interaction in the binding affinity of this compound to NSP16-NSP10. Further in vitro and in vivo studies are needed to test the activity of the identified compound against COVID-19.Communicated by Ramaswamy H. Sarma.

COVID-19 associated thyroid dysfunction and other comorbidities and its management using phytochemical-based therapeutics: a natural way

The present severe acute respiratory syndrome-2 (SARS-CoV-2) mediated Coronavirus pandemic (COVID-19) and post-COVID-19 complications affect human life drastically. Patients who have been cured of COVID-19 infection are now experiencing post-COVID-19 associated comorbidities, which have increased mortality rates. The SARS-CoV-2 infection distresses the lungs, kidneys, gastrointestinal tract, and various endocrine glands, including the thyroid. The emergence of variants which includes Omicron (B.1.1.529) and its lineages threaten the world severely. Among different therapeutic approaches, phytochemical-based therapeutics are not only cost-effective but also have lesser side effects. Recently a plethora of studies have shown the therapeutic efficacy of various phytochemicals for the treatment of COVID-19. Besides this, various phytochemicals have been found efficacious in treating several inflammatory diseases, including thyroid-related anomalies. The method of the phytochemical formulation is quick and facile and the raw materials for such herbal preparations are approved worldwide for human use against certain disease conditions. Owing to the advantages of phytochemicals, this review primarily discusses the COVID-19-related thyroid dysfunction and the role of key phytochemicals to deal with thyroid anomaly and post-COVID-19 complications. Further, this review shed light on the mechanism via which COVID-19 and its related complication affect organ function of the body, along with the mechanistic insight into the way by which phytochemicals could help to cure post-COVID-19 complications in thyroid patients. Considering the advantages offered by phytochemicals as a safer and cost-effective medication they can be potentially used to combat COVID-19-associated comorbidities.

Evolutionary aspects of mutation in functional motif and post-translational modifications in SARS-CoV-2 3CLpro (Mpro): an in-silico study

SARS CoV-2 is the virus that caused the COVID-19 pandemic. The main protease is one of the most prominent pharmacological targets for developing anti-COVID-19 therapeutic drugs (Mpro); SARS-CoV-2 replication is dependent on this component. SARS CoV-2's Mpro/cysteine protease is quite identical to SARS CoV-1's Mpro/cysteine protease. However, there is limited information on its structural and conformational properties. The present study aims to perform a complete in silico evaluation of Mpro protein's physicochemical properties. The motif prediction, post-translational modifications, effect of point mutation, and phylogenetic links were studied with other homologs to understand the molecular and evolutionary mechanisms of these proteins. The Mpro protein sequence was obtained in FASTA format from the RCSB Protein Data Bank. The structure of this protein was further characterized and analyzed using standard bioinformatics methods. According to Mpro's in-silico characterization, the protein is a basic, non-polar, and thermally stable globular protein. The outcomes of the phylogenetic and synteny study showed that the protein's functional domain amino acid sequence is substantially conserved. Furthermore, it has undergone many changes at the motif level over time from porcine epidemic diarrhoea virus to SARS-CoV 2, possibly to achieve various functions. Several post-translational modifications (PTMs) were also observed, and the possibilities of changes in Mpro protein exhibit additional orders of peptidase function regulation. During heatmap development, the effect of a point mutation on the Mpro protein was seen. This protein's structural characterization will aid in a better understanding of its function and mechanism of action.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42485-023-00105-9.

In silico assessment of diterpenes as potential inhibitors of SARS-COV-2 main protease

Aim

We aimed to investigate the potential inhibitory effects of diterpenes on SARS-CoV-2 main protease (Mpro).

Materials & methods

We performed a virtual screening of diterpenoids against Mpro using molecular docking, molecular dynamics simulation and absorption, distribution, metabolism and excretion) analysis.

Results

Some tested compounds followed Lipinski's rule and showed drug-like properties. Some diterpenoids possessed remarkable binding affinities with SARS-CoV-2 Mpro and drug-like pharmacokinetic properties. Three derivatives exhibited structural deviations lower than 1 Å.

Conclusion

The findings of the study suggest that some of the diterpenes could be candidates as potential inhibitors for Mpro of SARS-CoV-2.

Exploiting the co-crystal ligands shape, features and structure-based approaches for identification of SARS-CoV-2 Mpro inhibitors

SARS-CoV-2 enters the host cell through the ACE2 receptor and replicates its genome using an RNA-Dependent RNA Polymerase (RDRP). The functional RDRP is released from pro-protein pp1ab by the proteolytic activity of Main protease (Mpro) which is encoded within the viral genome. Due to its vital role in proteolysis of viral polyprotein chains, it has become an attractive potential drug target. We employed a hierarchical virtual screening approach to identify small synthetic protease inhibitors. Statistically optimized molecular shape and color-based features (various functional groups) from co-crystal ligands were used to screen different databases through various scoring schemes. Then, the electrostatic complementarity of screened compounds was matched with the most active molecule to further reduce the hit molecules' size. Finally, five hundred eighty-seven molecules were docked in Mpro catalytic binding site, out of which 29 common best hits were selected based on Glide and FRED scores. Five best-fitting compounds in complex with Mpro were subjected to MD simulations to analyze their structural stability and binding affinities with Mpro using MM/GB(PB)SA models. Modeling results suggest that identified hits can act as the lead compounds for designing better active Mpro inhibitors to enhance the chemical space to combat COVID-19.Communicated by Ramaswamy H. Sarma.

Elucidation of the inhibitory activity of plant-derived SARS-CoV inhibitors and their potential as SARS-CoV-2 inhibitors

Several drugs are now being tested as possible therapies due to the necessity of treating SARS-CoV-2 infection. Although approved vaccines bring much hope, a vaccination program covering the entire global population will take a very long time, making the development of effective antiviral drugs an effective solution for the immediate treatment of this dangerous infection. Previous studies found that three natural compounds, namely, tannic acid, 3-isotheaflavin-3-gallate and theaflavin-3,3-digallate, are effective proteinase (3CL^pro) inhibitors of SARS-CoV (IC₅₀ <10 µM). Based on this information and due to the high sequence identity between SARS-CoV and SARS-CoV-2 3CL^pro, these three compounds could be candidate inhibitors of SARS-CoV-2 3CL^pro. This paper explores the structural and energetic features that guided the molecular recognition of these three compounds for dimeric SARS-CoV-2 and SARS-CoV 3CL^pro, the functional state of this enzyme, using docking and MD simulations with the molecular mechanics-generalized-born surface area (MMGBSA) approach. Energetic analysis demonstrated that the three compounds reached good affinities in both systems in the following order: tannic acid > 3-isotheaflavin-3-gallate > theaflavin-3,3-digallate. This tendency is in line with that experimentally reported between these ligands and SARS-CoV 3CL^pro. Therefore, tannic acid may have clinical usefulness against COVID-19 by acting as a potent inhibitor of SARS-CoV-2 3CL^pro.Communicated by Ramaswamy H. Sarma.

Molecular docking-based virtual screening: Challenges in hits identification for Anti-SARS-Cov-2 activity

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) requires finding new drugs or repurposing drugs for clinical use. Molecular docking belongs to structure-based drug design providing a fast method for identifying the hit compounds with antiviral activity against SARS-Cov-2. However, the weakness of the docking method is compounded by the limited crystallographic information and comparison drugs due to the novelty of this virus can present challenges in identifying hits of anti-SARS-Cov-2. In the current review, we highlighted several aspects, especially those related to the target structure, docking validation, and virtual hit selection, that need to be considered to obtain reliable docking results. Here, we discussed several cases pertaining to the issue highlighted and approaches that could be used to solve them.

DFT, molecular docking and ADME prediction of tenofovir drug as a promising therapeutic inhibitor of SARS-CoV-2 Mpro

In the present work, at first, DFT calculations were carried out to study the molecular structure of the tenofovir at B3LYP/MidiX level of theory and in the water as solvent. The HOMO/LUMO molecular orbitals, excitation energies and oscillator strengths of investigated drug were also calculated and presented. NBO analysis was performed to illustrate the intramolecular rehybridization and electron density delocalization. In the following, a molecular docking study was performed for screening of effective available tenofovir drug which may act as an efficient inhibitor for the SARS-CoV-2 Mpro. The binding energy value showed a good binding affinity between the tenofovir and SARS-CoV-2 Mpro with binding energy of-47.206 kcal/mol. Therefore, tenofovir can be used for possible application against the SARS-CoV-2 Mpro.

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.

Molecular interactions and inhibition of the SARS‐CoV‐2 main protease by a thiadiazolidinone derivative

We report molecular interactions and inhibition of the main protease (M^Pro) of SARS‐CoV‐2, a key enzyme involved in the viral life cycle. By using a thiadiazolidinone (TDZD) derivative as a chemical probe, we explore the conformational dynamics of M^Pro via docking protocols and molecular dynamics simulations in all‐atom detail. We reveal the local and global dynamics of M^Pro in the presence of this inhibitor and confirm the inhibition of the enzyme with an IC₅₀ value of 1.39 ± 0.22 μM, which is comparable to other known inhibitors of this enzyme.

COVID-19: The question of genetic diversity and therapeutic intervention approaches

Coronavirus disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2), is the largest pandemic in modern history with very high infection rates and considerable mortality. The disease, which emerged in China's Wuhan province, had its first reported case on December 29, 2019, and spread rapidly worldwide. On March 11, 2020, the World Health Organization (WHO) declared the COVID-19 outbreak a pandemic and global health emergency. Since the outbreak, efforts to develop COVID-19 vaccines, engineer new drugs, and evaluate existing ones for drug repurposing have been intensively undertaken to find ways to control this pandemic. COVID-19 therapeutic strategies aim to impair molecular pathways involved in the virus entrance and replication or interfere in the patients' overreaction and immunopathology. Moreover, nanotechnology could be an approach to boost the activity of new drugs. Several COVID-19 vaccine candidates have received emergency-use or full authorization in one or more countries, and others are being developed and tested. This review assesses the different strategies currently proposed to control COVID-19 and the issues or limitations imposed on some approaches by the human and viral genetic variability.

Plant Source Derived Compound Exhibited In Silico Inhibition of Membrane Glycoprotein In SARS-CoV-2: Paving the Way to Discover a New Class of Compound For Treatment of COVID-19

SARS-CoV-2 is the virus responsible for causing COVID-19 disease in humans, creating the recent pandemic across the world, where lower production of Type I Interferon (IFN-I) is associated with the deadly form of the disease. Membrane protein or SARS-CoV-2 M proteins are known to be the major reason behind the lower production of human IFN-I by suppressing the expression of IFNβ and Interferon Stimulated Genes. In this study, 7,832 compounds from 32 medicinal plants of India possessing traditional knowledge linkage with pneumonia-like disease treatment, were screened against the Homology-Modelled structure of SARS-CoV-2 M protein with the objective of identifying some active phytochemicals as inhibitors. The entire study was carried out using different modules of Schrodinger Suite 2020-3. During the docking of the phytochemicals against the SARS-CoV-2 M protein, a compound, ZIN1722 from Zingiber officinale showed the best binding affinity with the receptor with a Glide Docking Score of −5.752 and Glide gscore of −5.789. In order to study the binding stability, the complex between the SARS-CoV-2 M protein and ZIN1722 was subjected to 50 ns Molecular Dynamics simulation using Desmond module of Schrodinger suite 2020-3, during which the receptor-ligand complex showed substantial stability after 32 ns of MD Simulation. The molecule ZIN1722 also showed promising results during ADME-Tox analysis performed using Swiss ADME and pkCSM. With all the findings of this extensive computational study, the compound ZIN1722 is proposed as a potential inhibitor to the SARS-CoV-2 M protein, which may subsequently prevent the immunosuppression mechanism in the human body during the SARS-CoV-2 virus infection. Further studies based on this work would pave the way towards the identification of an effective therapeutic regime for the treatment and management of SARS-CoV-2 infection in a precise and sustainable manner.

Computer aided identification of potential SARS CoV-2 main protease inhibitors from diterpenoids and biflavonoids of Torreya nucifera leaves

SARS CoV-2 is the causative agent of the pandemic disease COVID-19. There is an urgent need for effective drugs or vaccines which can effectively combat this outbreak. The main protease (Mpro), a key component for the SARS CoV-2 replication, is considered to be one of the important drug targets for developing anti-COVID-19 drugs. This SARS CoV-2 Mpro/cysteine protease has high sequence similarity with the same protease from SARS CoV-1. Previously, it has been shown experimentally that eight diterpenoids and four biflavonoids derived from the leaf of Torreya nucifera show inhibitory effect on the cleavage/catalytic activity of the SARS CoV-1 Mpro. But whether these phytochemicals exhibit any inhibitory effect on SARS CoV-2 Mpro is unclear. To understand this fact, here, we have adopted various in-silico approaches. Diterpenoids and biflavonoids those qualified pharmacological test (hinokiol, amentoflavone, bilobetin and ginkgetin) and two well-known Mpro inhibitors (N3 and lopinavir) were subjected for molecular docking studies. Only three biflavonoids (amentoflavone, bilobetin and ginkgetin) were selected by comparing their binding affinities with N3 and lopinavir. They interacted with two most important catalytic residues of Mpro (His41 and Cys145). Molecular dynamics studies further revealed that these three Mpro-biflavonoid complexes are highly stable and share a similar degree of compactness. Besides, these complexes experience less conformational fluctuations and more expansion than Mpro-N3 and/or Mpro-lopinavir complex. MM-GBSA and H-bond analysis further corroborated these findings. Altogether, our study suggested that these three biflavonoids could possibly inhibit the proteolytic/catalytic activity of SARS CoV-2 Mpro and might be useful for COVID-19 treatment.Communicated by Ramaswamy H. Sarma.

Repurposing drugs for treatment of SARS-CoV-2 infection: computational design insights into mechanisms of action

The COVID-19 pandemic has negatively affected human life globally. It has led to economic crises and health emergencies across the world, spreading rapidly among the human population and has caused many deaths. Currently, there are no treatments available for COVID-19 so there is an urgent need to develop therapeutic interventions that could be used against the novel coronavirus infection. In this research, we used computational drug design technologies to repurpose existing drugs as inhibitors of SARS-CoV-2 viral proteins. The Broad Institute's Drug Repurposing Hub consists of in-development/approved drugs and was computationally screened to identify potential hits which could inhibit protein targets encoded by the SARS-CoV-2 genome. By virtually screening the Broad collection, using rationally designed pharmacophore features, we identified molecules which may be repurposed against viral nucleocapsid and non-structural proteins. The pharmacophore features were generated after careful visualisation of the interactions between co-crystalised ligands and the protein binding site. The ChEMBL database was used to determine the compound's level of inhibition of SARS-CoV-2 and correlate the predicted viral protein target with whole virus in vitro data. The results from this study may help to accelerate drug development against COVID-19 and the hit compounds should be progressed through further in vitro and in vivo studies on SARS-CoV-2.

Machine learning prediction of 3CLpro SARS-CoV-2 docking scores

Molecular docking results of two training sets containing 866 and 8,696 compounds were used to train three different machine learning (ML) approaches. Neural network approaches according to Keras and TensorFlow libraries and the gradient boosted decision trees approach of XGBoost were used with DScribe’s Smooth Overlap of Atomic Positions molecular descriptors. In addition, neural networks using the SchNetPack library and descriptors were used. The ML performance was tested on three different sets, including compounds for future organic synthesis. The final evaluation of the ML predicted docking scores was based on the ZINC in vivo set, from which 1,200 compounds were randomly selected with respect to their size. The results obtained showed a consistent ML prediction capability of docking scores, and even though compounds with more than 60 atoms were found slightly overestimated they remain valid for a subsequent evaluation of their drug repurposing suitability.

Evaluation of Xa inhibitors as potential inhibitors of the SARS-CoV-2 Mpro protease

Based on previous large-scale in silico screening several factor Xa inhibitors were proposed to potentially inhibit SARS-CoV-2 Mpro. In addition to their known anticoagulants activity this potential inhibition could have an additional therapeutic effect on patients with COVID-19 disease. In this study we examined the binding of the Apixaban, Betrixaban and Rivaroxaban to the SARS-CoV-2 Mpro with the use of the MicroScale Thermophoresis technique. Our results indicate that the experimentally measured binding affinity is weak and the therapeutic effect due to the SARS-CoV-2 Mpro inhibition is rather negligible.

Repurposing FDA-approved Drugs Targeting SARS-CoV2 3CLpro: a study by applying Virtual Screening, Molecular Dynamics, MM-PBSA Calculations and Covalent Docking

Background:

Since the end of 2019, the etiologic agent SAR-CoV-2 responsible for one of the most significant epidemics in history has caused severe global economic, social, and health damages. The drug repurposing approach and application of Structure-based Drug Discovery (SBDD) using in silico techniques are increasingly frequent, leading to the identification of several molecules that may represent promising potential.

Method:

In this context, here we use in silico methods of virtual screening (VS), pharmacophore modeling (PM), and fragment-based drug design (FBDD), in addition to molecular dynamics (MD), molecular mechanics/Poisson-Boltzmann surface area (MM -PBSA) calculations, and covalent docking (CD) for the identification of potential treatments against SARS-CoV-2. We initially validated the docking protocol followed by VS in 1,613 FDA-approved drugs obtained from the ZINC database. Thus, we identified 15 top hits, of which three of them were selected for further simulations. In parallel, for the compounds with a fit score value ≤ of 30, we performed the FBDD protocol, where we designed 12 compounds

Result:

By applying a PM protocol in the ZINC database, we identified three promising drug candidates. Then, the 9 top hits were evaluated in simulations of MD, MM-PBSA, and CD. Subsequently, MD showed that all identified hits showed stability at the active site without significant changes in the protein's structural integrity, as evidenced by the RMSD, RMSF, Rg, SASA graphics. They also showed interactions with the catalytic dyad (His41 and Cys145) and other essential residues for activity (Glu166 and Gln189) and high affinity for MM-PBSA, with possible covalent inhibition mechanism.

Conclution:

Finally, our protocol helped identify potential compounds wherein ZINC896717 (Zafirlukast), ZINC1546066 (Erlotinib), and ZINC1554274 (Rilpivirine) were more promising and could be explored in vitro, in vivo, and clinical trials to prove their potential as antiviral agents.

Non-clinical safety assessment and in vivo biodistribution of CoviFab, an RBD-specific F(ab')2 fragment derived from equine polyclonal antibodies

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has required the urgent development of new therapies, among which passive immunotherapy is contemplated. CoviFab (INM005) is a RBD-specific F(ab′)2 fragment derived from equine polyclonal antibodies. We investigate their preclinical security and biodistribution by in vivo and ex vivo NIR imaging after intravenous administration of a dose of 4 mg/kg at time 0 and 48 h. Images were taken at 1, 12, 24, 36, 48, 49, 60, 72, 84, 96, 108, 120, 132 and 144 h after the first intravenous injection. At 96 and 144 h, mice were sacrificed for haematology, serum chemistry, clinical pathology, histopathology and ex vivo imaging. The biodistribution profile was similar in all organs studied, with the highest fluorescence at 1 h after each injection, gradually decreasing after that each one and until the end of the study (144 h). The toxicology study revealed no significant changes in the haematology and serum chemistry parameters. Further, there were no changes in the gross and histological examination of organs. Nonclinical data of the current study confirm that CoviFab is safe, without observable adverse effects in mice. Furthermore, we confirm that bioimaging studies are a useful approach in preclinical trials to determine biodistribution.

Computational Simulation of HIV Protease Inhibitors to the Main Protease (Mpro) of SARS-CoV-2: Implications for COVID-19 Drugs Design

SARS-CoV-2 is highly homologous to SARS-CoV. To date, the main protease (Mpro) of SARS-CoV-2 is regarded as an important drug target for the treatment of Coronavirus Disease 2019 (COVID-19). Some experiments confirmed that several HIV protease inhibitors present the inhibitory effects on the replication of SARS-CoV-2 by inhibiting Mpro. However, the mechanism of action has still not been studied very clearly. In this work, the interaction mechanism of four HIV protease inhibitors Darunavir (DRV), Lopinavir (LPV), Nelfinavir (NFV), and Ritonavire (RTV) targeting SARS-CoV-2 Mpro was explored by applying docking, molecular dynamics (MD) simulations, and MM-GBSA methods using the broad-spectrum antiviral drug Ribavirin (RBV) as the negative and nonspecific control. Our results revealed that LPV, RTV, and NFV have higher binding affinities with Mpro, and they all interact with catalytic residues His41 and the other two key amino acids Met49 and Met165. Pharmacophore model analysis further revealed that the aromatic ring, hydrogen bond donor, and hydrophobic group are the essential infrastructure of Mpro inhibitors. Overall, this study applied computational simulation methods to study the interaction mechanism of HIV-1 protease inhibitors with SARS-CoV-2 Mpro, and the findings provide useful insights for the development of novel anti-SARS-CoV-2 agents for the treatment of COVID-19.

In Silico End-to-End Protein-Ligand Interaction Characterization Pipeline: The Case of SARS-CoV-2

SARS-CoV-2 triggered a worldwide pandemic disease, COVID-19, for which an effective treatment has not yet been settled. Among the most promising targets to fight this disease is SARS-CoV-2 main protease (Mpro), which has been extensively studied in the last few months. There is an urgency for developing effective computational protocols that can help us tackle these key viral proteins. Hence, we have put together a robust and thorough pipeline of in silico protein-ligand characterization methods to address one of the biggest biological problems currently plaguing our world. These methodologies were used to characterize the interaction of SARS-CoV-2 Mpro with an α-ketoamide inhibitor and include details on how to upload, visualize, and manage the three-dimensional structure of the complex and acquire high-quality figures for scientific publications using PyMOL (Protocol 1); perform homology modeling with MODELLER (Protocol 2); perform protein-ligand docking calculations using HADDOCK (Protocol 3); run a virtual screening protocol of a small compound database of SARS-CoV-2 candidate inhibitors with AutoDock 4 and AutoDock Vina (Protocol 4); and, finally, sample the conformational space at the atomic level between SARS-CoV-2 Mpro and the α-ketoamide inhibitor with Molecular Dynamics simulations using GROMACS (Protocol 5). Guidelines for careful data analysis and interpretation are also provided for each Protocol.

Investigation of Thiocarbamates as Potential Inhibitors of the SARS-CoV-2 Mpro

In the present study we tested, using the microscale thermophoresis technique, a small library of thionocarbamates, thiolocarbamates, sulfide and disulfide as potential lead compounds for SARS-CoV-2 Mpro drug design. The successfully identified binder is a representative of the thionocarbamates group with a high potential for future modifications aiming for higher affinity and solubility. The experimental analysis was extended by computational studies that show insufficient accuracy of the simplest and widely applied approaches and underline the necessity of applying more advanced methods to properly evaluate the affinity of potential SARS-CoV-2 Mpro binders.

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.

Drugs repurposing against SARS-CoV2 and the new variant B.1.1.7 (alpha strain) targeting the spike protein: molecular docking and simulation studies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) is responsible for the global COVID-19 pandemic and millions of deaths worldwide. In December 2020, a new alpha strain of SARS-CoV2 was identified in the United Kingdom. It was referred to as VUI 202012/01 (Alpha strain modelled under investigation, 2020, month 12, number 01). The interaction between spike protein and ACE2 receptor is a prerequisite for entering virion into the host cell. The present study is focussed on the spike protein of the SARS-COV 2, involving the comparison of binding affinity of new alpha strain modelled spike with previous strain spike (PDB ID:7DDN) using in silico molecular docking, dynamics and simulation studies. The molecular docking studies of the alpha strain modelled spike protein confirmed its higher affinity for the ACE2 receptor than the spike protein of the dominant strain. Similar computational approaches have also been used to investigate the potency of FDA approved drugs from the ZINC Database against the spike protein of new alpha strain modelled and old ones. The drug molecules which showed strong affinity for both the spike proteins are then subjected to ADME analysis. The overall binding energy of Conivaptan (-107.503 kJ/mol) and Trosec (-94.029 kJ/mol) is indicative of their strong binding affinities, well supported by interactions with critical residues.

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We investigated the potential FDA drugs for repurposing against the spike protein of alpha strain modelled of SARS-CoV-2.

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Spike protein of alpha strain modelled of SARS-CoV-2 has more affinity for the ACE2 receptor of host cell than previous strains and, therefore, is more contagious.

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Conivaptan, Ecamsule and Trosec are common drugs that bind strongly with spike protein of both the strains .

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Molecular Docking and simulation studies show that Conivaptan and Trosec emerged as potential inhibitors of the alpha strain modelled spike protein.

Structure-Based Discovery of Novel Nonpeptide Inhibitors Targeting SARS-CoV-2 Mpro

The continual spread of novel coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), posing a severe threat to the health worldwide. The main protease (Mpro, alias 3CLpro) of SARS-CoV-2 is a crucial enzyme for the maturation of viral particles and is a very attractive target for designing drugs to treat COVID-19. Here, we propose a multiple conformation-based virtual screening strategy to discover inhibitors that can target SARS-CoV-2 Mpro. Based on this strategy, nine Mpro structures and a protein mimetics library with 8960 commercially available compounds were prepared to carry out ensemble docking for the first time. Five of the nine structures are apo forms presented in different conformations, whereas the other four structures are holo forms complexed with different ligands. The surface plasmon resonance assay revealed that 6 out of 49 compounds had the ability to bind to SARS-CoV-2 Mpro. The fluorescence resonance energy transfer experiment showed that the biochemical half-maximal inhibitory concentration (IC50) values of the six compounds could hamper Mpro activities ranged from 0.69 ± 0.05 to 2.05 ± 0.92 μM. Evaluation of antiviral activity using the cell-based assay indicated that two compounds (Z1244904919 and Z1759961356) could strongly inhibit the cytopathic effect and reduce replication of the living virus in Vero E6 cells with the half-maximal effective concentrations (EC50) of 4.98 ± 1.83 and 8.52 ± 0.92 μM, respectively. The mechanism of the action for the two inhibitors were further elucidated at the molecular level by molecular dynamics simulation and subsequent binding free energy analysis. As a result, the discovered noncovalent reversible inhibitors with novel scaffolds are promising antiviral drug candidates, which may be used to develop the treatment of COVID-19.

Accelerating COVID-19 Research Using Molecular Dynamics Simulation

The COVID-19 pandemic has emerged as a global medico-socio-economic disaster. Given the lack of effective therapeutics against SARS-CoV-2, scientists are racing to disseminate suggestions for rapidly deployable therapeutic options, including drug repurposing and repositioning strategies. Molecular dynamics (MD) simulations have provided the opportunity to make rational scientific breakthroughs in a time of crisis. Advancements in these technologies in recent years have become an indispensable tool for scientists studying protein structure, function, dynamics, interactions, and drug discovery. Integrating the structural data obtained from high-resolution methods with MD simulations has helped in comprehending the process of infection and pathogenesis, as well as the SARS-CoV-2 maturation in host cells, in a short duration of time. It has also guided us to identify and prioritize drug targets and new chemical entities, and to repurpose drugs. Here, we discuss how MD simulation has been explored by the scientific community to accelerate and guide translational research on SARS-CoV-2 in the past year. We have also considered future research directions for researchers, where MD simulations can help fill the existing gaps in COVID-19 research.

Synthesis and molecular docking study of novel COVID-19 inhibitors

In 2020, the world tried to combat the corona virus (COVID-19) pandemic. A proven treatment method specific to Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is still not found. In this study, seven new antiviral compounds were designed for COVID-19 treatment. The ability of these compounds to inhibit COVID-19's RNA processing was calculated by the molecular docking study. It has been observed that the compounds can have high binding affinities especially against NSP12 (between -9.06 and -8.00 kcal/mol). The molecular dynamics simulation of NSP12-ZG 7 complex proved the stability of interaction. The synthesis of two most active molecules was performed by one-pot reaction and characterized by FT-IR, 1H-NMR, 13C-NMR, and mass spectroscopy. The compounds presented with their synthesis are inhibitory core structures against SARS-CoV-2 infection.

Synthesis of hydroxy benzoin/benzil analogs and investigation of their antioxidant, antimicrobial, enzyme inhibition, and cytotoxic activities

In this study, hydroxy benzoin ( 1-7 ), benzil ( 8-14 ), and benzoin/benzil-O-β-D-glucosides ( 15-25 ) were synthesized to investigate their biological activities. An efficient method for synthesizing hydroxy benzoin compounds ( 1 - 7 ) was prepared from four different benzaldehydes using an ultrasonic bath. Then, antioxidant (FRAP, CUPRAC, and DPPH), antimicrobial (3 Gram (-), 4/6 Gram (+), one tuberculosis and one fungus), and enzyme inhibition (acetylcholinesterase, butyrylcholine esterase, tyrosinase, α-amylase, and α- glucosidase) for the all synthesized compounds ( 1-25 ) were evaluated. And also, four most active compounds ( 4 , 12 , 18a+b , and 25 ) from each group were evaluated to the human cervical cancer cell line (HeLa) and anticancer screening tests against the human retinal normal cell line (RPE). Compound 4 showed HeLa and RPE cancer cell activities as much as cisplatin. The synthesized compounds were characterized by spectroscopic methods (NMR, FT-IR, UV, LC-QTOF-MS) and the ACD NMR program's help.

De novo ssRNA Aptamers against the SARS-CoV-2 Main Protease: In Silico Design and Molecular Dynamics Simulation

Herein, we have generated ssRNA aptamers to inhibit SARS-CoV-2 M^pro, a protease necessary for the SARS-CoV-2 coronavirus replication. Because there is no aptamer 3D structure currently available in the databanks for this protein, first, we modeled an ssRNA aptamer using an entropic fragment-based strategy. We refined the initial sequence and 3D structure by using two sequential approaches, consisting of an elitist genetic algorithm and an RNA inverse process. We identified three specific aptamers against SARS-CoV-2 M^pro, called MApta^pro, MApta^pro-IR1, and MApta^pro-IR2, with similar 3D conformations and that fall in the dimerization region of the SARS-CoV-2 M^pro necessary for the enzymatic activity. Through the molecular dynamic simulation and binding free energy calculation, the interaction between the MApta^pro-IR1 aptamer and the SARS-CoV-2 M^pro enzyme resulted in the strongest and the highest stable complex; therefore, the ssRNA MApta^pro-IR1 aptamer was selected as the best potential candidate for the inhibition of SARS-CoV-2 M^pro and a perspective therapeutic drug for the COVID-19 disease.

COVID-19: In silico identification of potent α-ketoamide inhibitors targeting the main protease of the SARS-CoV-2

The COVID-19 has been creating a global crisis, causing countless deaths and unbearable panic. Despite the progress made in the development of the vaccine, there is an urge need for the discovery of antivirals that may better work at different stages of SARS-CoV-2 reproduction. The main protease (M^pro) of the SARS-CoV-2 is a crucial therapeutic target due to its critical function in virus replication. The α-ketoamide derivatives represent an important class of inhibitors against the M^pro of the SARS-CoV. While there is 99% sequence similarity between SARS-CoV and SARS-CoV-2 main proteases, anti-SARS-CoV compounds may have a huge demonstration's prospect of their effectiveness against the SARS-CoV-2. In this study, we applied various computational approaches to investigate the inhibition potency of novel designed α-ketoamide-based compounds. In this regard, a set of 21 α-ketoamides was employed to construct a QSAR model, using the genetic algorithm-multiple linear regression (GA-MLR), as well as a pharmacophore fit model. Based on the GA-MLR model, 713 new designed molecules were reduced to 150 promising hits, which were later subject to the established pharmacophore fit model. Among the 150 compounds, the best selected compounds (3 hits) with greater pharmacophore fit score were further studied via molecular docking, molecular dynamic simulations along with the Absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis. Our approach revealed that the three hit compounds could serve as potential inhibitors against the SARS-CoV-2 M^pro target.

Screening of world approved drugs against highly dynamical spike glycoprotein of SARS-CoV-2 using CaverDock and machine learning

The new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes pathological pulmonary symptoms. Most efforts to develop vaccines and drugs against this virus target the spike glycoprotein, particularly its S1 subunit, which is recognised by angiotensin-converting enzyme 2. Here we use the in-house developed tool CaverDock to perform virtual screening against spike glycoprotein using a cryogenic electron microscopy structure (PDB-ID: 6VXX) and the representative structures of five most populated clusters from a previously published molecular dynamics simulation. The dataset of ligands was obtained from the ZINC database and consists of drugs approved for clinical use worldwide. Trajectories for the passage of individual drugs through the tunnel of the spike glycoprotein homotrimer, their binding energies within the tunnel, and the duration of their contacts with the trimer's three subunits were computed for the full dataset. Multivariate statistical methods were then used to establish structure-activity relationships and select top candidate for movement inhibition. This new protocol for the rapid screening of globally approved drugs (4359 ligands) in a multi-state protein structure (6 states) showed high robustness in the rate of finished calculations. The protocol is universal and can be applied to any target protein with an experimental tertiary structure containing protein tunnels or channels. The protocol will be implemented in the next version of CaverWeb (https://loschmidt.chemi.muni.cz/caverweb/) to make it accessible to the wider scientific community.

An insight into the inhibitory mechanism of phytochemicals and FDA-approved drugs on the ACE2-Spike complex of SARS-CoV-2 using computational methods

The S-glycoprotein (Spike) of the SARS-CoV-2 forms a complex with the human transmembrane protein angiotensin-converting enzyme 2 (ACE2) during infection. It forms the first line of contact with the human cell. The FDA-approved drugs and phytochemicals from Indian medicinal plants were explored. Molecular docking and simulations of these molecules targeting the ACE2–Spike complex were performed. Rutin DAB10 and Swertiapuniside were obtained as the top-scored drugs as per the docking protocol. The MD simulations of ligand-free, Rutin DAB10-bound, and Swertiapuniside-bound ACE2–Spike complex revealed abrogation of the hydrogen bonding network between the two proteins. The principal component and dynamic cross-correlation analysis pointed out conformational changes in both the proteins unique to the ligand-bound systems. The interface residues, His34, and Lys353 from ACE2 and Arg403, and Tyr495 from the Spike protein formed significant strong interactions with the ligand molecules, inferring the inhibition of ACE2–Spike complex. Few novel interactions specific to Rutin-DAB10 and Swertiapuniside were also identified. The conformational flexibility of the drug-binding pocket was captured using the RMSD-based clustering of the ligand-free simulations. Ensemble docking was performed wherein the FDA-approved database and phytochemical dataset were docked on each of the cluster representatives of the ACE2–Spike. The phytochemicals identified belonged to Withania somnifera, Swertia chirayita, Tinospora cordifolia and Rutin DAB10, fulvestrant, elbasvir from FDA.

Identification of high affinity and low molecular alternatives of boceprevir against SARS-CoV-2 main protease: A virtual screening approach

SARS-CoV-2 has posed global challenge for healthcare due to COVID-19. The main protease (M^pro) of this virus is considered as a major target for drug development efforts. In this work, we have used virtual screening approach with molecular dynamics simulations to identify high affinity and low molecular weight alternatives of boceprevir, a repurposed drug currently being evaluated against M^pro. Out of 180 compounds screened, two boceprevir analogs (PubChem ID: 57841991 and 58606278) were reported as potential alternatives with comparable predicted protease inhibitor potential and pharmacological properties. Further experimental validation of the reported compounds may contribute to the ongoing investigation of boceprevir.

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.

A review on drug repurposing applicable to COVID-19

Drug repurposing involves the identification of new applications for existing drugs at a lower cost and in a shorter time. There are different computational drug-repurposing strategies and some of these approaches have been applied to the coronavirus disease 2019 (COVID-19) pandemic. Computational drug-repositioning approaches applied to COVID-19 can be broadly categorized into (i) network-based models, (ii) structure-based approaches and (iii) artificial intelligence (AI) approaches. Network-based approaches are divided into two categories: network-based clustering approaches and network-based propagation approaches. Both of them allowed to annotate some important patterns, to identify proteins that are functionally associated with COVID-19 and to discover novel drug–disease or drug–target relationships useful for new therapies. Structure-based approaches allowed to identify small chemical compounds able to bind macromolecular targets to evaluate how a chemical compound can interact with the biological counterpart, trying to find new applications for existing drugs. AI-based networks appear, at the moment, less relevant since they need more data for their application.

Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates

Since the emergence of the new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) at the end of December 2019 in China, and with the urge of the coronavirus disease 2019 (COVID-19) pandemic, there have been huge efforts of many research teams and governmental institutions worldwide to mitigate the current scenario. Reaching more than 1,377,000 deaths in the world and still with a growing number of infections, SARS-CoV-2 remains a critical issue for global health and economic systems, with an urgency for available therapeutic options. In this scenario, as drug repurposing and discovery remains a challenge, computer-aided drug design (CADD) approaches, including machine learning (ML) techniques, can be useful tools to the design and discovery of novel potential antiviral inhibitors against SARS-CoV-2. In this work, we describe and review the current knowledge on this virus and the pandemic, the latest strategies and computational approaches applied to search for treatment options, as well as the challenges to overcome COVID-19.

Repurposing novel therapeutic candidate drugs for coronavirus disease-19 based on protein-protein interaction network analysis

BACKGROUND

The coronavirus disease-19 (COVID-19) emerged in Wuhan, China and rapidly spread worldwide. Researchers are trying to find a way to treat this disease as soon as possible. The present study aimed to identify the genes involved in COVID-19 and find a new drug target therapy. Currently, there are no effective drugs targeting SARS-CoV-2, and meanwhile, drug discovery approaches are time-consuming and costly. To address this challenge, this study utilized a network-based drug repurposing strategy to rapidly identify potential drugs targeting SARS-CoV-2. To this end, seven potential drugs were proposed for COVID-19 treatment using protein-protein interaction (PPI) network analysis. First, 524 proteins in humans that have interaction with the SARS-CoV-2 virus were collected, and then the PPI network was reconstructed for these collected proteins. Next, the target miRNAs of the mentioned module genes were separately obtained from the miRWalk 2.0 database because of the important role of miRNAs in biological processes and were reported as an important clue for future analysis. Finally, the list of the drugs targeting module genes was obtained from the DGIDb database, and the drug-gene network was separately reconstructed for the obtained protein modules.

RESULTS

Based on the network analysis of the PPI network, seven clusters of proteins were specified as the complexes of proteins which are more associated with the SARS-CoV-2 virus. Moreover, seven therapeutic candidate drugs were identified to control gene regulation in COVID-19. PACLITAXEL, as the most potent therapeutic candidate drug and previously mentioned as a therapy for COVID-19, had four gene targets in two different modules. The other six candidate drugs, namely, BORTEZOMIB, CARBOPLATIN, CRIZOTINIB, CYTARABINE, DAUNORUBICIN, and VORINOSTAT, some of which were previously discovered to be efficient against COVID-19, had three gene targets in different modules. Eventually, CARBOPLATIN, CRIZOTINIB, and CYTARABINE drugs were found as novel potential drugs to be investigated as a therapy for COVID-19.

CONCLUSIONS

Our computational strategy for predicting repurposable candidate drugs against COVID-19 provides efficacious and rapid results for therapeutic purposes. However, further experimental analysis and testing such as clinical applicability, toxicity, and experimental validations are required to reach a more accurate and improved treatment. Our proposed complexes of proteins and associated miRNAs, along with discovered candidate drugs might be a starting point for further analysis by other researchers in this urgency of the COVID-19 pandemic.

Designing a natural inhibitor against human kynurenine aminotransferase type II and a comparison with PF-04859989: a computational effort against schizophrenia

The Kynurenine aminotransferase II (KATII) enzyme has an essential role in L-kynurenine transmission to kynurenic acid (KYNA). High concentration of kynurenic acid associates with schizophrenia and some neurocognitive disorders. Decreasing KYNA production via inhibiting KATII would be an effective method for treating and understanding the related central nervous system (CNS) diseases. This study aimed to discover a potent inhibitor against human KATII (hKATII) in comparison with PF-04859989. We utilized the computational methods of molecular dynamics, virtual screening, docking, and binding free-energy calculations. Initially, the 58722 compounds from three drug libraries, including IBS library, DrugBank library, and Analyticon library, were obtained. At the next stage, these sets of compounds were screened by AutoDock Vina software, and a potent inhibitor (ZINC35466084) was selected. Following the screening, molecular dynamics simulations for both ZINC35466084 and PF-04859989 were performed by GROMACS software. MM-PBSA analysis showed that the amount of binding free energy for ZINC35466084 (-61.26 KJ mol^-1) is more potent than PF-04859989 (-43.14 KJ mol^-1). Furthermore, the ADME analysis results revealed that the pharmacokinetic parameters of ZINC35466084 are acceptable for human use. Eventually, our data demonstrated that ZINC35466084 is suitable for hKATII inhibition, and it is an appropriate candidate for further studies in the laboratory. Communicated by Ramaswamy H. Sarma.

Cordifolioside: potent inhibitor against Mpro of SARS-CoV-2 and immunomodulatory through human TGF-β and TNF-α

Therapeutic options for SARS-CoV-2 are limited merely to the symptoms or repurposed drugs and non-specific interventions to promote the human immune system. In the present study, chromatographic and in silico approaches were implemented to identify bioactive compounds which might play pivotal role as inhibitor for SARS-CoV-2 and human immunomodulator (TGF-β and TNF-α). Tinospora cordifolia (Willd.) Miers was evaluated for phenolic composition and explored for bioactive compounds by high-performance thin layer chromatography (HPTLC). Furthermore, the bioactive compounds such as cordifolioside, berberine, and magnoflorine were appraised as human immunomodulatory and potent inhibitor against Main Protease (M^pro) of SARS-CoV-2 through multiple docking strategies. Cordifolioside formed six stable H-bonds with His41, Ser144, Cys145, His163, His164, and Glu166 of M^pro of SARS-CoV-2, which displayed a significant role in the viral replication/transcription during infection acting towards the common conserved binding cleft among all strains of coronavirus. Overall, the study emphasized that the proposed cordifolioside might use for future investigations, which hold as a promising scaffold for developing anti-COVID-19 drug and reduce human cytokine storm.

Identification of the binding interactions of some novel antiviral compounds against Nsp1 protein from SARS-CoV-2 (COVID-19) through high throughput screening

The SARS-CoV-2 pandemic has become a global threat. It has become very difficult to control the spreading of the virus. The virus is a RNA virus and the virulence of the virus is mediated by three virulence causing proteins, viz., Nsp1, Nsp3c and ORF7. So far the drug designing endeavors against the virus have been being targeted towards the spike protein which is responsible for the entry of the virus inside human host as well as the RNA dependent RNA polymerase. However, no effective treatment against the virus has so far been developed. In the present situation, an attempt has been made to target the virulence protein factor Nsp1 which binds to the 40S ribosomal subunit of the human host. We tried to target the Nsp1 by in-silico virtual screening of ligand libraries. We built the three dimensional structure of Nsp1 and used the structure to screen the ChEMBL drug library. We used molecular docking simulations of the top6 screened ligands with Nsp1 and subjected the liagnd-Nsp1 complexes to molecular dynamics simulations to analyze the behaviors of the ligands in a virtual cell. From our analysis we could predict that the ligands bearing the ChEMBL identifiers, CHEMBL1096281, CHEMBL2022920, CHEMBL175656, had the best binding affinity values with Nsp1. Therefore, these ligand molecules may be tested in wet-lab for further analysis. This is the first report to target the virulence factor Nsp1 from SARS-CoV-2. Communicated by Ramaswamy H. Sarma.

Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2

SARS-CoV-2 caused the current COVID-19 pandemic and there is an urgent need to explore effective therapeutics that can inhibit enzymes that are imperative in virus reproduction. To this end, we computationally investigated the MPD3 phytochemical database along with the pool of reported natural antiviral compounds with potential to be used as anti-SARS-CoV-2. The docking results demonstrated glycyrrhizin followed by azadirachtanin, mycophenolic acid, kushenol-w and 6-azauridine, as potential candidates. Glycyrrhizin depicted very stable binding mode to the active pocket of the Mpro (binding energy, -8.7 kcal/mol), PLpro (binding energy, -7.9 kcal/mol), and Nucleocapsid (binding energy, -7.9 kcal/mol) enzymes. This compound showed binding with several key residues that are critical to natural substrate binding and functionality to all the receptors. To test docking prediction, the compound with each receptor was subjected to molecular dynamics simulation to characterize the molecule stability and decipher its possible mechanism of binding. Each complex concludes that the receptor dynamics are stable (Mpro (mean RMSD, 0.93 Å), PLpro (mean RMSD, 0.96 Å), and Nucleocapsid (mean RMSD, 3.48 Å)). Moreover, binding free energy analyses such as MMGB/PBSA and WaterSwap were run over selected trajectory snapshots to affirm intermolecular affinity in the complexes. Glycyrrhizin was rescored to form strong affinity complexes with the virus enzymes: Mpro (MMGBSA, -24.42 kcal/mol and MMPBSA, -10.80 kcal/mol), PLpro (MMGBSA, -48.69 kcal/mol and MMPBSA, -38.17 kcal/mol) and Nucleocapsid (MMGBSA, -30.05 kcal/mol and MMPBSA, -25.95 kcal/mol), were dominated mainly by vigorous van der Waals energy. Further affirmation was achieved by WaterSwap absolute binding free energy that concluded all the complexes in good equilibrium and stability (Mpro (mean, -22.44 kcal/mol), PLpro (mean, -25.46 kcal/mol), and Nucleocapsid (mean, -23.30 kcal/mol)). These promising findings substantially advance our understanding of how natural compounds could be shaped to counter SARS-CoV-2 infection.

Candidate Binding Sites for Allosteric Inhibition of the SARS-CoV-2 Main Protease from the Analysis of Large-Scale Molecular Dynamics Simulations

We analyzed a 100 μs MD trajectory of the SARS-CoV-2 main protease by a non-parametric data analysis approach which allows characterizing a free energy landscape as a simultaneous function of hundreds of variables. We identified several conformations that, when visited by the dynamics, are stable for several hundred nanoseconds. We explicitly characterize and describe these metastable states. In some of these configurations, the catalytic dyad is less accessible. Stabilizing them by a suitable binder could lead to an inhibition of the enzymatic activity. In our analysis we keep track of relevant contacts between residues which are selectively broken or formed in the states. Some of these contacts are formed by residues which are far from the catalytic dyad and are accessible to the solvent. Based on this analysis we propose some relevant contact patterns and three possible binding sites which could be targeted to achieve allosteric inhibition.

The roles of signaling pathways in SARS-CoV-2 infection; lessons learned from SARS-CoV and MERS-CoV

The number of descriptions of emerging viruses has grown at an unprecedented rate since the beginning of the 21^st century. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), is the third highly pathogenic coronavirus that has introduced itself into the human population in the current era, after SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Molecular and cellular studies of the pathogenesis of this novel coronavirus are still in the early stages of research; however, based on similarities of SARS-CoV-2 to other coronaviruses, it can be hypothesized that the NF-κB, cytokine regulation, ERK, and TNF-α signaling pathways are the likely causes of inflammation at the onset of COVID-19. Several drugs have been prescribed and used to alleviate the adverse effects of these inflammatory cellular signaling pathways, and these might be beneficial for developing novel therapeutic modalities against COVID-19. In this review, we briefly summarize alterations of cellular signaling pathways that are associated with coronavirus infection, particularly SARS-CoV and MERS-CoV, and tabulate the therapeutic agents that are currently approved for treating other human diseases.

Potential SARS-CoV-2 main protease inhibitors

The coronavirus disease 2019 (COVID-19) pandemic has prompted an urgent need for new treatment strategies. No target-specific drugs are currently available for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but new drug candidates targeting the viral replication cycle are being explored. A prime target of drug-discovery efforts is the SARS-CoV-2 main protease (M^pro). The main proteases of different coronaviruses, including SARS-CoV-2, SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), share a structurally conserved substrate-binding region that can be exploited to design new protease inhibitors. With the recent reporting of the X-ray crystal structure of the SARS-CoV-2 M^pro, studies to discover M^pro inhibitors using both virtual and in vitro screening are progressing rapidly. This review focusses on the recent developments in the search for small-molecule inhibitors targeting the SARS-CoV-2 M^pro.