Structural insight to hydroxychloroquine-3C-like proteinase complexation from SARS-CoV-2: inhibitor modelling study through molecular docking and MD-simulation study

Critical assessment of popular biomolecular force fields for molecular dynamics simulations of folding and enzymatic activity of main protease of coronavirus SARS-CoV-2

The main cysteine protease (Mpro) of coronavirus SARS-CoV-2 has become a promising target for computational development in anti-COVID-19 treatments. Here, we benchmarked the performance of six biomolecular molecular dynamics (MD) force fields (OPLS-AA, CHARMM27, CHARMM36, AMBER03, AMBER14SB and GROMOS G54A7) and three water models (TIP3P, TIP4P and SPC) for reproducing the native fold and the enzymatic activity of Mpro as monomeric and dimeric units. The MD sampling up to 1 μs suggested that the proper choice of the force fields and water models plays an essential role in reproducing the tertiary structure and the inter-residue distance between the catalytic dyad His41-Cys145. We found that while most benchmarked all-atom force fields reproduce well the native fold of Mpro, the CHARMM27/TIP3P and OPLS-AA/TIP4P setups revealed a good performance in reproducing the structure of the catalytic domain. In addition, these FF setups were also well-adopted for MD sampling of Mpro at the physiologic conditions by mimicking the presence of 100 mM NaCl and the elevated temperature of 310 K. Finally, both FFs were also performed well in reproducing the native fold of Mpro in a dimeric form. Therefore, comparing the preservation of the native fold of Mpro and the stability of its catalytic site architecture, our MD benchmarking suggests that the OPLS-AA/TIP4P and CHARMM27/TIP3P MD setups at the physiologic conditions may be well-suited for rapid in silico screening and developing broad-spectrum anti-coronaviral therapeutic agents.

Exploring Scoring Function Space: Developing Computational Models for Drug Discovery

BACKGROUND

The idea of scoring function space established a systems-level approach to address the development of models to predict the affinity of drug molecules by those interested in drug discovery.

OBJECTIVE

Our goal here is to review the concept of scoring function space and how to explore it to develop machine learning models to address protein-ligand binding affinity.

METHODS

We searched the articles available in PubMed related to the scoring function space. We also utilized crystallographic structures found in the protein data bank (PDB) to represent the protein space.

RESULTS

The application of systems-level approaches to address receptor-drug interactions allows us to have a holistic view of the process of drug discovery. The scoring function space adds flexibility to the process since it makes it possible to see drug discovery as a relationship involving mathematical spaces.

CONCLUSION

The application of the concept of scoring function space has provided us with an integrated view of drug discovery methods. This concept is useful during drug discovery, where we see the process as a computational search of the scoring function space to find an adequate model to predict receptor-drug binding affinity.

Expediting the drug discovery for ideal leads against SARS-CoV-2 via molecular docking of repurposed drugs

SARS-CoV-2, the novel coronavirus spreading worldwide urges the need to repurpose drugs that can quickly enter clinical trials to combat the on-going global pandemic. A cluster of proteins are encoded for by the viral genome, each assuming a critical role in pathogen endurance inside the host. To handle the adverse circumstances, robust virtual strategies such as repurposing are coming to the fore due to being economical, efficient and rapid. Five FDA approved repurposed drugs proposed to act as inhibitors by targeting SARS-CoV-2 were used for initial evaluation via molecular docking. Moreover, a comparative analysis of the selected SARS-CoV-2 proteins against five ligands (Clemizole hydrochloride, Exemestane, Nafamostat, Pregnenolone and Umifenovir) was designed. In this regard, non-structural proteins (nsp3, nsp5, nsp10, nsp12 and nsp15), structural proteins (Spike, Nucleocapsid protein) and accessory proteins (ORF 3a, ORF 7a and ORF 9 b) were selected. Here, we aim to expedite the search for a potential drug from the five FDA approved repurposing drugs already in use for treatment of multiple diseases. Based on docking analysis, Umifenovir and Pregnenolone are suggested to show potential inhibitory effects against most of the SARS-CoV-2 proteins. These drugs are noteworthy since they exhibit high binding towards target proteins and should be used as lead compounds towards in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.

Antiviral drug design based on structural insights into the N-terminal domain and C-terminal domain of the SARS-CoV-2 nucleocapsid protein

Nucleocapsid (N) protein plays crucial roles in the life cycle of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including the formation of ribonucleoprotein (RNP) complex with the viral RNA. Here we reported the crystal structures of the N-terminal domain (NTD) and C-terminal domain (CTD) of the N protein and an NTD-RNA complex. Our structures reveal a unique tetramer organization of NTD and identify a distinct RNA binding mode in the NTD-RNA complex, which could contribute to the formation of the RNP complex. We also screened small molecule inhibitors of N-NTD and N-CTD and discovered that ceftriaxone sodium, an antibiotic, can block the binding of RNA to NTD and inhibit the formation of the RNP complex. These results together could facilitate the further research of antiviral drug design targeting N 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.

Perceiving SARS-CoV-2 Mpro and PLpro dual inhibitors from pool of recognized antiviral compounds of endophytic microbes: an in silico simulation study

Coronavirus disease 2019 (COVID-19) persists and shook the global population where the endgame to this pandemic is brought on by developing vaccines in record-breaking time. Nevertheless, these vaccines are far from perfect where their efficiency ranges from 65 to 90%; therefore, vaccines are not the one only solution to overcome this situation, and apart from administration of vaccines, the scientific community is at quest for finding alternative solutions to incumber SARS-CoV-2 infection. In this study, our research group is keen on identifying a bioactive molecule that is independent in its mode of action from existing vaccines which can potentially target the SARS-CoV-2 virus replicative efficacy. Papain-like protease (PLpro) and main protease (Mpro) are the most lucrative targets of COVIDs against which the drugs can be developed, as these proteases play a vital role in the replication and development of viral particles. Researchers have modelled a compound such as GRL0617 and X77 as an inhibitor of Mpro and PLpro, respectively, but use of these compounds has several limitations on hosts like toxicity and solubility. Under the current study by deploying rigorous computational assessments, pool of microbial secondary metabolites was screened and handpicked to search a structural or functional analogue of GRL0617 and X77, with an idea to identify a compound that can serve as dual inhibitor for both PLpro and Mpro. From the manually curated database of known antiviral compounds from fungal origin, we found cytonic acids A and B to potentially serve as dual inhibitor of PLpro and Mpro.

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

Purpose of Review

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

Recent Findings

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

Summery

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

Repurposing the antibacterial drugs for inhibition of SARS-CoV2-PLpro using molecular docking, MD simulation and binding energy calculation

Papain-like protease (nsp-3; non-structural protein) of novel corona virus is an ideal target for developing drugs as it plays multiple important functions for viral growth and replication. For instance, role of nsp-3 has been recognized in cleavage of viral polyprotein; furthermore, in infected host it weakens the immune system via downregulating the production of type I interferon. This downregulation is promoted by removal of ubiquitin-like interferon-stimulated gene 15 protein (ISG15) from interferon-responsive factor 3 (IRF3) protein. Among known inhibitors of SARS-CoV-PLpro GRL0617 is by far the most effective inhibitor. As PLpro of SARS-CoV2 is having more than 80% similarity with SARS-CoV-PLpro, GRL0617 is reported to be effective even against SARS-CoV2. Owing to this similarity, certain key amino acids remain the same/conserved in both proteins. Among conserved amino acids Tyr268 for SARS-CoV2 and Tyr269 for SARS-CoV produce important hydrophobic interactions with aromatic rings of GRL0617. Here, in this study antibacterial compounds were collected from ZINC database, and they were filtered to select compounds that are having similar structural features as GRL0617. This filtered library of compound was then docked with SARS-CoV and CoV2-PLpro. Five hits were noted that were able to interact with Tyr268 (SARS-CoV2) and Tyr269 (SARS-CoV). Further, best hit 2-(2-((benzofuran-2-carboxamido)methyl)-5-methoxy-1H-indol-1-yl)acetic acid (ZINC44459905) was studied using molecular dynamic simulation where stability of protein–ligand complex as well as stability of produced interactions was noted.

Inhibition of interferon-stimulated gene 15 and lysine 48-linked ubiquitin binding to the SARS-CoV-2 papain-like protease by small molecules: In silico studies

The SARS-CoV-2 papain-like protease (PL^pro) is a suitable target for drug development, and its deubiquitinating and deISGylating activities have also been reported. In this study, molecular docking was used to investigate the binding properties of a selection of dietary compounds and naphthalene-based inhibitors to the previously characterised binding site of GRL-0617. The structures of the SARS-CoV-2 and SARS-CoV PL^pro in complex with interferon-stimulated gene 15 (ISG15) and lysine 48 (K48)-linked diubiquitin were utilised. To predict whether compounds could potentially interfere with the binding of these cellular modifiers, docking was conducted in the absence and presence of ISG15 and K48-linked diubiquitin.

Structure-based design approach of potential BCL-2 inhibitors for cancer chemotherapy

B-cell lymphoma 2 (BCL-2) family is one of the chief regulators of cellular apoptosis. The intricate interactions between pro-apoptotic and anti-apoptotic genes of the BCL-2 family dictate the apoptotic balance of the cell. An overexpression of the anti-apoptotic members of BCL-2 is indicative of cell death evasion and cancer metastasis. Among the four BCL-2 homology domains, the BH3 domain plays a key role in the suppression of BCL-2 expression. Therefore, BH3-mimetic drugs are currently investigated for their suitability as BCL-2 inhibitors. In the present study, we followed a structure-based pharmacophore modelling approach to identify BH3-mimetic small molecules, to formulate a more precise and targeted cancer treatment regimen. To identify proteins with similar binding features, a structure-based pharmacophore model was generated based on the structure of Bcl-2 complexed with Venetoclax (PDB-ID:6O0K). Compounds with good fitness score and pharmacophore features, screened from the ZINC database, were subjected to (i) molecular docking studies, (ii) molecular mechanics-generalized Born surface area (MM-GBSA), and (iii) absorption, distribution, metabolism, excretion and toxicity (ADMET) prediction. From the analysis, two molecules were identified: ZINC68728276 and ZINC14166367, with docking scores of -7.323 and -8.649 kcal/mol and free binding energies (MM-GBSA) of -72.913 and -72.291 kcal/mol, respectively. The structural parameters and binding affinity of these complexes were validated through molecular dynamics simulation and molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) free energy calculations and compared with Venetoclax. The results indicated stability and good binding affinity of both the compounds. The study identified ZINC68728276 and ZINC14166367 as in silico potential Bcl-2 inhibitors, which can be further considered for in vitro studies.

Identifying structural-functional analogue of GRL0617, the only well-established inhibitor for papain-like protease (PLpro) of SARS-CoV2 from the pool of fungal metabolites using docking and molecular dynamics simulation

Abstract

The non-structural protein (nsp)-3 of SARS-CoV2 coronavirus is sought to be an essential target protein which is also named as papain-like protease (PLpro). This protease cleaves the viral polyprotein, but importantly in human host it also removes ubiquitin-like interferon-stimulated gene 15 protein (ISG15) from interferon responsive factor 3 (IRF3) protein which ultimately downregulates the production of type I interferon leading to weakening of immune response. GRL0617 is the most potent known inhibitor for PLpro that was initially developed for SARS outbreak of 2003. The PLpro of SARS-CoV and CoV2 share 83% sequence identity but interestingly have several identical conserved amino acids that suggests GRL0617 to be an effective inhibitor for PLpro of SARS-CoV2. GRL0617 is a naphthalene-based molecule and interacts with Tyr268 of SARS-CoV2-PLpro (and Tyr269 of SARS-CoV-PLpro). To identify PLpro inhibitors, we prepared a library of secondary metabolites from fungi with aromatic nature and docked them with PLpro of SARS-CoV and SARS-CoV2. We found six hits which interacts with Tyr268 of SARS-CoV2-PLpro (and Tyr269 of SARS-CoV-PLpro). More surprisingly the top hit, Fonsecin, has naphthalene moiety in its structure, which recruits Tyr268 of SARS-CoV2-PLpro (and Tyr269 of SARS-CoV-PLpro) and has binding energy at par with control (GRL0617). Molecular dynamics (MD) simulation showed Fonsecin to interact with Tyr268 of SARS-CoV2-PLpro more efficiently than control (GRL0617) and interacting with a greater number of amino acids in the binding cleft of PLpro.

Graphic abstract

In silico screening of therapeutic potentials from Strychnos nux-vomica against the dimeric main protease (Mpro) structure of SARS-CoV-2

The novel coronavirus also referred to as SARS-CoV-2 causes COVID-19 and became global epidemic since its initial outbreak in Wuhan, China, in December 2019. Research efforts are still been endeavoured towards discovering/designing of potential drugs and vaccines against this virus. In the present studies, we have contributed to the development of a drug based on natural products to combat the newly emerged and life-threatening disease. The main protease (M^Pro) of SARS-CoV-2 is a homodimer and a key component involved in viral replication, and is considered as a prime target for anti-SARS-CoV-2 drug development. Literature survey revealed that the phytochemicals present in Strychnos nux-vomica possess several therapeutic activities. Initially, in the light of drug likeness laws, the ligand library of phytoconstituents was subjected to drug likeness analysis. The resulting compounds were taken to binding site-specific consensus-based molecular docking studies and the results were compared with the positive control drug, lopinavir, which is a main protease inhibitor. The top compounds were tested for ADME-Tox properties and antiviral activity. Further molecular dynamics simulations and MM-PBSA-based binding affinity estimation were carried out for top two lead compounds' complexes along with the apo form of main protease and positive control drug lopinavir complex, and the results were comparatively analysed. The results revealed that the two analogues of same scaffold, namely demethoxyguiaflavine and strychnoflavine, have potential against M^pro and can be validated through clinical studies.Communicated by Ramaswamy H. Sarma.

Repurposing of anticancer phytochemicals for identifying potential fusion inhibitor for SARS-CoV-2 using molecular docking and molecular dynamics (MD) simulations

The viral particle, SARS-CoV-2 is responsible for causing the epidemic of Coronavirus disease 2019 (COVID-19). To combat this situation, numerous strategies are being thought for either creating its antidote, vaccine, or agents that can prevent its infection. For enabling research on these strategies, several target proteins are identified where, Spike (S) protein is of great potential. S-protein interacts with human angiotensin-converting-enzyme-2 (ACE2) for entering the cell. S-protein is a large protein and a portion of it designated as a receptor-binding domain (RBD) is the key region that interacts with ACE2, following to which the viral membrane fuses with the alveolar membrane to enter the human cell. The hypothesis is to identify molecules from the pool of anticancer phytochemicals as a lead possessing the ability to interact and mask the amino acids of RBD, making them unavailable to form associations with ACE2. Such a molecule is termed as 'fusion inhibitor'. We hypothesized to identify fusion inhibitors from the NPACT library of anticancer phytochemicals. For this, all the molecules from the NPACT were screened using molecular docking, the five top hits (Theaflavin, Ginkgetin, Ursolic acid, Silymarin and Spirosolane) were analyzed for essential Pharmacophore features and their ADMET profiles were studied following to which the best two hits were further analyzed for their interaction with RBD using Molecular Dynamics (MD) simulation. Binding free energy calculations were performed using MM/GBSA, proving these phytochemicals containing anticancer properties to serve as fusion inhibitors.Communicated by Ramaswamy H. Sarma.

Pinpointing the potential hits for hindering interaction of SARS-CoV-2 S-protein with ACE2 from the pool of antiviral phytochemicals utilizing molecular docking and molecular dynamics (MD) simulations

SARS-CoV-2, the viral particle, is responsible for triggering the 2019 Coronavirus disease outbreak (COVID-19). To tackle this situation, a number of strategies are being devised to either create an antidote, a vaccine, or agents capable of preventing its infection. To enable research on these strategies, numerous target proteins are identified where Spike (S) protein is presumed to be of immense potential. S-protein interacts with human angiotensin-converting-enzyme-2 (ACE2) for cell entry. The key region of S-protein that interacts with ACE2 is a portion of it designated as a receptor-binding domain (RBD), following whereby the viral membrane fuses with the alveolar membrane to enter the human cell. The proposition is to recognize molecules from the bundle of phytochemicals of medicinal plants known to possess antiviral potentials as a lead that could interact and mask RBD, rendering them unavailable to form ACE2 interactions. Such a molecule is called the 'S-protein blocker'. A total of 110 phytochemicals from Withania somnifera, Asparagus racemosus, Zinziber officinalis, Allium sativum, Curcuma longa and Adhatoda vasica were used in the study, of which Racemoside A, Ashwagandhanolide, Withanoside VI, Withanoside IV and Racemoside C were identified as top five hits using molecular docking. Further, essential Pharmacophore features and their ADMET profiles of these compounds were studied following to which the best three hits were analyzed for their interaction with RBD using Molecular Dynamics (MD) simulation. Binding free energy calculations were performed using MM/GBSA, proving these phytochemicals can serve as S-protein blocker.

Computational investigation of binding of chloroquinone and hydroxychloroquinone against PLPro of SARS-CoV-2

Novel coronavirus SARS-CoV-2 has infected 18 million people with 700,000+ mortalities worldwide and this deadly numeric figure is rapidly rising. With very few success stories, the therapeutic targeting of this epidemic has been mainly attributed to main protease (Mpro), whilst Papain-like proteases (PLpro) also plays a vital role in the processing of replicase polyprotein. Multifunctional roles of PLpro such as viral polypeptide cleavage, de-ISGlyation and immune suppression have made it a promising drug target for therapeutic interventions. Whilst there have been a number of studies and others are on-going on repurposing and new-small molecule screening, albeit previously FDA approved drugs viz. Chloroquine (CQ) and Hydroxychloroquine (HCQ) have only been found effective against this pandemic. Inspired by this fact, we have carried out molecular docking and dynamics simulation studies of FDA approved CQ and HCQ against SARS-CoV-2 PLpro. The end aim is to characterise the binding mode of CQ and HCQ and identify the key amino acid residues involved in the mechanism of action. Further, molecular dynamics simulations (MDS) were carried out with the docked complex to search for the conformational space and for understanding the integrity of binding mode. We showed that the CQ and HCQ can bind with better binding affinity with PLpro as compared to reference known PLpro inhibitor. Based on the presented findings, it can be anticipated that the SARS-CoV-2 PLpro may act as molecular target of CQ and HCQ, and can be projected for further exploration to design potent inhibitors of SARS-CoV-2 PLpro in the near future.

Identification of potential inhibitors of SARS-CoV-2 papain-like protease from tropane alkaloids from Schizanthus porrigens: A molecular docking study

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Antivirals against SARS-CoV-2 are needed.

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The papain-like protease represents an important target for antivirals.

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We investigated tropane alkaloids from Schizanthus porrigens.

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By molecular docking and MS simulations we identified two leads.

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Shizanthine Z has favorable ADME properties and can be considered a lead.

This paper presents identification of potential inhibitors of SARS-CoV-2 papain-like protease from tropane alkaloids from Schizanthus porrigens, using molecular docking method. Binding affinities were compared with those obtained with Lopinavir as a SARS-CoV-2 papain-like protease inhibitor. Overall, our findings indicate that Schizanthine Z binds to the SARS-CoV-2 papain-like protease with relatively high affinity and favorable ADME properties. Therefore, Schizanthine Z may represent an appropriate compound for further evaluation in antiviral assays.