A Comprehensive Survey of Prospective Structure-Based Virtual Screening for Early Drug Discovery in the Past Fifteen Years.

Structure-based virtual screening (SBVS), also known as molecular docking, has been increasingly applied to discover small-molecule ligands based on the protein structures in the early stage of drug discovery. In this review, we comprehensively surveyed the prospective applications of molecular docking judged by solid experimental validations in the literature over the past fifteen years. Herein, we systematically analyzed the novelty of the targets and the docking hits, practical protocols of docking screening, and the following experimental validations. Among the 419 case studies we reviewed, most virtual screenings were carried out on widely studied targets, and only 22% were on less-explored new targets. Regarding docking software, GLIDE is the most popular one used in molecular docking, while the DOCK 3 series showed a strong capacity for large-scale virtual screening. Besides, the majority of identified hits are promising in structural novelty and one-quarter of the hits showed better potency than 1 µM, indicating that the primary advantage of SBVS is to discover new chemotypes rather than highly potent compounds. Furthermore, in most studies, only in vitro bioassays were carried out to validate the docking hits, which might limit the further characterization and development of the identified active compounds. Finally, several successful stories of SBVS with extensive experimental validations have been highlighted, which provide unique insights into future SBVS drug discovery campaigns.

Virtual and In Vitro Screening of Natural Products Identifies Indole and Benzene Derivatives as Inhibitors of SARS-CoV-2 Main Protease (Mpro).

The rapid spread of the coronavirus disease 2019 (COVID-19) resulted in serious health, social, and economic consequences. While the development of effective vaccines substantially reduced the severity of symptoms and the associated deaths, we still urgently need effective drugs to further reduce the number of casualties associated with SARS-CoV-2 infections. Machine learning methods both improved and sped up all the different stages of the drug discovery processes by performing complex analyses with enormous datasets. Natural products (NPs) have been used for treating diseases and infections for thousands of years and represent a valuable resource for drug discovery when combined with the current computation advancements. Here, a dataset of 406,747 unique NPs was screened against the SARS-CoV-2 main protease (Mpro) crystal structure (6lu7) using a combination of ligand- and structural-based virtual screening. Based on 1) the predicted binding affinities of the NPs to the Mpro, 2) the types and number of interactions with the Mpro amino acids that are critical for its function, and 3) the desirable pharmacokinetic properties of the NPs, we identified the top 20 candidates that could potentially inhibit the Mpro protease function. A total of 7 of the 20 top candidates were subjected to in vitro protease inhibition assay and 4 of them (4/7; 57%), including two beta carbolines, one N-alkyl indole, and one Benzoic acid ester, had significant inhibitory activity against Mpro protease. These four NPs could be developed further for the treatment of COVID-19 symptoms.

Proposing lead compounds for the development of SARS-CoV-2 receptor-binding inhibitors.

The COVID-19 pandemic has had deleterious effects on the world and demands urgent measures to find therapeutic agents to combat the current and related future outbreaks. The entry of SARS-CoV-2 into the host's cell is facilitated by the interaction between the viral spike receptor-binding domain (sRBD) and the human angiotensin-converting enzyme 2 (hACE2). Although the interface of sRBD involved in the sRBD-hACE2 interaction has been projected as a primary vaccine and drug target, currently no small-molecule drugs have been approved for covid-19 treatment targeting sRBD. Herein structure-based virtual screening and molecular dynamics (MD) simulation strategies were applied to identify novel potential small-molecule binders of the SARS-CoV-2 sRBD from an sRBD-targeted compound library as leads for the development of anti-COVID-19 drugs. The library was initially screened against sRBD by using the GOLD docking program whereby 19 compounds were shortlisted based on docking scores after using a control compound to set the selection cutoff. The stability of each compound in MD simulations was used as a further standard to select four hits namely T4S1820, T4589, E634-1449, and K784-7078. Analyses of simulations data showed that the four compounds remained stably bound to sRBD for ≥ 80 ns with reasonable affinities and interacted with pharmacologically important amino acid residues. The compounds exhibited fair solubility, lipophilicity, and toxicity-propensity characteristics that could be improved through lead optimization regimes. The overall results suggest that the scaffolds of T4S1820, E634-1449, and K784-7078 could serve as seeds for developing potent small-molecule inhibitors of SARS-CoV-2 receptor binding and cell entry.Communicated by Ramaswamy H. Sarma.

Virtual screening campaigns and ADMET evaluation to unlock the potency of flavonoids from Erythrina as 3CLpro SARS-COV-2 inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the coronavirus disease 2019 (COVID-19) pandemic with more than 6 million deaths worldwide. Flavonoids from the genus Erythrina may inhibit SARS-CoV-2, targeting 3C-like protease (3CLpro), an enzyme essential in the virus's growth. Hence, this study aimed to screen 378 flavonoids from Erythrina against 3CLpro, using molecular docking, Lipinski's rule of five, and in silico absorption, distribution, metabolism, excretion, and toxicity. These virtual screening campaigns suggest that 108 flavonoids have stronger binding energy values (−13.23 to −10.20 kcal/mol) than the N3 inhibitor (−10.14 kcal/mol) as the reference ligand. Some 33 of these flavonoids may be hepatoxicity and mutagenicity-free. They are also non-hERG I and II inhibitors. Two of them, orientanol E (171) and erycaffra F (57), have binding energy values in the top 10 hits and good absorption profiles, despite their poor distribution properties. They may have a high bioavailability in the body and be excreted from the body through feces. Conducted molecular dynamics simulations also support orientanol E (171) and erycaffra F (57) as 3CLpro inhibitor candidates. Our study suggests that flavonoids from Erythrina have potential as 3CLpro inhibitors, which help guide further in vitro and in vivo experiments in COVID-19 drug development © 2023 Vicki Nishinarizki et al. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/)

Identification of Four New Chemical Series of Small Drug-Like Natural Products as Potential Neuropilin-1 Inhibitors by Structure-Based Virtual Screening: Pharmacophore-Based Molecular Docking and Dynamics Simulation.

Neuropilin-1 (NRP-1), a surface transmembrane glycoprotein, is one of the most important co-receptors of VEGF-A165 (vascular endothelial growth factor) responsible for pathological angiogenesis. In general, NRP-1 overexpression in cancer correlates with poor prognosis and more tumor aggressiveness. NRP-1 role in cancer has been mainly explained by mediating VEGF-A165-induced effects on tumor angiogenesis. NRP-1 was recently identified as a co-receptor and an independent gateway for SARS-CoV-2 through binding subunit S2 of Spike protein in the same way as VEGF-A165. Thus, NRP-1 is of particular value as a target for cancer therapy and other angiogenesis-dependent diseases as well as for SARS-CoV-2 antiviral intervention. Herein, The Super Natural II, the largest available database of natural products (∼0.33 M), pre-filtered with drug-likeness criteria (absorption, distribution, metabolism and excretion/toxicity), was screened against NRP-1. NRP-1/VEGF-A165 interaction is one of protein-protein interfaces (PPIs) known to be challenging when approached in-silico. Thus, a PPI-suited multi-step virtual screening protocol, incorporating a derived pharmacophore with molecular docking and followed by MD (molecular dynamics) simulation, was designed. Two stages of pharmacophorically constrained molecular docking (standard and extra precisions), a mixed Torsional/Low-mode conformational search and MM-GBSA ΔG binding affinities calculation, resulted in the selection of 100 hits. These 100 hits were subjected to 20 ns MD simulation, that was extended to 100 ns for top hits (20) and followed by post-dynamics analysis (atomic ligand-protein contacts, RMSD, RMSF, MM-GBSA ΔG, Rg, SASA and H-bonds). Post-MD analysis showed that 19 small drug-like nonpeptide natural molecules, grouped in four chemical scaffolds (purine, thiazole, tetrahydropyrimidine and dihydroxyphenyl), well verified the derived pharmacophore and formed stable and compact complexes with NRP-1. The discovered molecules are promising and can serve as a base for further development of new NRP-1 inhibitors.

Advanced simulations and screening to repurposing a 3C protease inhibitor against the rupintrivir-resistant human norovirus-induced gastroenteritis.

Human norovirus (HuNoV) causes acute viral gastroenteritis in all age groups, and dehydration and severe diarrhea in the elderly. The World Health Organization reports ∼1.45 million deaths from acute gastroenteritis annually in the world. Rupintrivir, an inhibitory medicine against the human rhinovirus C3 protease, has been reported to inhibit HuNoV 3C protease. However, several HuNoV 3C protease mutations have been revealed to reduce the susceptibility of HuNoV to rupintrivir. The structural details behind rupintrivir-resistance of these single-point mutations (A105V and I109V) are not still clear. Hence, in this study, a combination of computational techniques were used to determine the rupintrivir-resistance mechanism and to propose an inhibitor against wild-type and mutant HuNoV 3C protease through structure-based virtual screening. Dynamic structural results indicated the unstable binding of rupintrivir at the cleft binding site of the wild-type and mutant 3C proteases, leading to its detachment. Our findings presented that the domain II of the HuNoV 3C protease had a critical role in binding of inhibitory molecules. Binding energy computations, steered molecular dynamics and umbrella sampling simulations confirmed that amentoflavone, the novel suggested inhibitor, strongly binds to the cleft site of all protease models and has a good structural stability in the complex system along the molecular dynamic simulations. Our in silico study proposed the selected compound as a potential inhibitor against the HuNoV 3C protease. However, additional experimental and clinical studies are required to corroborate the therapeutic efficacy of the compound.

In-Silico Lead Druggable Compounds Identification against SARS COVID-19 Main Protease Target from In-House, Chembridge and Zinc Databases by Structure-Based Virtual Screening, Molecular Docking and Molecular Dynamics Simulations.

Pharmacological strategies to lower the viral load among patients suffering from severe diseases were researched in great detail during the SARS-CoV-2 outbreak. The viral protease Mpro (3CLpro) is necessary for viral replication and is among the main therapeutic targets proposed, thus far. To stop the pandemic from spreading, researchers are working to find more effective Mpro inhibitors against SARS-CoV-2. The 33.8 kDa Mpro protease of SARS-CoV-2, being a nonhuman homologue, has the possibility of being utilized as a therapeutic target against coronaviruses. To develop drug-like compounds capable of preventing the replication of SARS-main CoV-2's protease (Mpro), a computer-aided drug design (CADD) approach is extremely viable. Using MOE, structure-based virtual screening (SBVS) of in-house and commercial databases was carried out using SARS-CoV-2 proteins. The most promising hits obtained during virtual screening (VS) were put through molecular docking with the help of MOE. The virtual screening yielded 3/5 hits (in-house database) and 56/66 hits (commercial databases). Finally, 3/5 hits (in-house database), 3/5 hits (ZINC database), and 2/7 hits (ChemBridge database) were chosen as potent lead compounds using various scaffolds due to their considerable binding affinity with Mpro protein. The outcomes of SBVS were then validated using an analysis based on molecular dynamics simulation (MDS). The complexes' stability was tested using MDS and post-MDS. The most promising candidates were found to exhibit a high capacity for fitting into the protein-binding pocket and interacting with the catalytic dyad. At least one of the scaffolds selected will possibly prove useful for future research. However, further scientific confirmation in the form of preclinical and clinical research is required before implementation.

Structure-Based Virtual Screening and Functional Validation of Potential Hit Molecules Targeting the SARS-CoV-2 Main Protease.

The recent global health emergency caused by the coronavirus disease 2019 (COVID-19) pandemic has taken a heavy toll, both in terms of lives and economies. Vaccines against the disease have been developed, but the efficiency of vaccination campaigns worldwide has been variable due to challenges regarding production, logistics, distribution and vaccine hesitancy. Furthermore, vaccines are less effective against new variants of the SARS-CoV-2 virus and vaccination-induced immunity fades over time. These challenges and the vaccines' ineffectiveness for the infected population necessitate improved treatment options, including the inhibition of the SARS-CoV-2 main protease (Mpro). Drug repurposing to achieve inhibition could provide an immediate solution for disease management. Here, we used structure-based virtual screening (SBVS) to identify natural products (from NP-lib) and FDA-approved drugs (from e-Drug3D-lib and Drugs-lib) which bind to the Mpro active site with high-affinity and therefore could be designated as potential inhibitors. We prioritized nine candidate inhibitors (e-Drug3D-lib: Ciclesonide, Losartan and Telmisartan; Drugs-lib: Flezelastine, Hesperidin and Niceverine; NP-lib: three natural products) and predicted their half maximum inhibitory concentration using DeepPurpose, a deep learning tool for drug-target interactions. Finally, we experimentally validated Losartan and two of the natural products as in vitro Mpro inhibitors, using a bioluminescence resonance energy transfer (BRET)-based Mpro sensor. Our study suggests that existing drugs and natural products could be explored for the treatment of COVID-19.

Identification of 1H-purine-2,6-dione derivative as a potential SARS-CoV-2 main protease inhibitor: molecular docking, dynamic simulations, and energy calculations.

The rapid spread of the coronavirus since its first appearance in 2019 has taken the world by surprise, challenging the global economy, and putting pressure on healthcare systems across the world. The introduction of preventive vaccines only managed to slow the rising death rates worldwide, illuminating the pressing need for developing effective antiviral therapeutics. The traditional route of drug discovery has been known to require years which the world does not currently have. In silico approaches in drug design have shown promising results over the last decade, helping to decrease the required time for drug development. One of the vital non-structural proteins that are essential to viral replication and transcription is the SARS-CoV-2 main protease (Mpro). Herein, using a test set of recently identified COVID-19 inhibitors, a pharmacophore was developed to screen 20 million drug-like compounds obtained from a freely accessible Zinc database. The generated hits were ranked using a structure based virtual screening technique (SBVS), and the top hits were subjected to in-depth molecular docking studies and MM-GBSA calculations over SARS-COV-2 Mpro. Finally, the most promising hit, compound (1), and the potent standard (III) were subjected to 100 ns molecular dynamics (MD) simulations and in silico ADME study. The result of the MD analysis as well as the in silico pharmacokinetic study reveal compound 1 to be a promising SARS-Cov-2 MPro inhibitor suitable for further development.

The Discovery of Small Allosteric and Active Site Inhibitors of the SARS-CoV-2 Main Protease via Structure-Based Virtual Screening and Biological Evaluation.

The main protease enzyme (Mpro) of SARS-CoV-2 is one of the most promising targets for COVID-19 treatment. Accordingly, in this work, a structure-based virtual screening of 3.8 million ligand libraries was carried out. After rigorous filtering, docking, and post screening assessments, 78 compounds were selected for biological evaluation, 3 of which showed promising inhibition of the Mpro enzyme. The obtained hits (CB03, GR04, and GR20) had reasonable potencies with Ki values in the medium to high micromolar range. Interestingly, while our most potent hit, GR20, was suggested to act via a reversible covalent mechanism, GR04 was confirmed as a noncompetitive inhibitor that seems to be one of a kind when compared to the other allosteric inhibitors discovered so far. Moreover, all three compounds have small sizes (~300 Da) with interesting fittings in their relevant binding sites, and they possess lead-like characteristics that can introduce them as very attractive candidates for the future development of COVID-19 treatments.

Discovery of Epipodophyllotoxin-Derived B2 as Promising XooFtsZ Inhibitor for Controlling Bacterial Cell Division: Structure-Based Virtual Screening, Synthesis, and SAR Study.

The emergence of phytopathogenic bacteria resistant to antibacterial agents has rendered previously manageable plant diseases intractable, highlighting the need for safe and environmentally responsible agrochemicals. Inhibition of bacterial cell division by targeting bacterial cell division protein FtsZ has been proposed as a promising strategy for developing novel antibacterial agents. We previously identified 4'-demethylepipodophyllotoxin (DMEP), a naturally occurring substance isolated from the barberry species Dysosma versipellis, as a novel chemical scaffold for the development of inhibitors of FtsZ from the rice blight pathogen Xanthomonas oryzae pv. oryzae (Xoo). Therefore, constructing structure-activity relationship (SAR) studies of DMEP is indispensable for new agrochemical discovery. In this study, we performed a structure-activity relationship (SAR) study of DMEP derivatives as potential XooFtsZ inhibitors through introducing the structure-based virtual screening (SBVS) approach and various biochemical methods. Notably, prepared compound B2, a 4'-acyloxy DMEP analog, had a 50% inhibitory concentration of 159.4 µM for inhibition of recombinant XooFtsZ GTPase, which was lower than that of the parent DMEP (278.0 µM). Compound B2 potently inhibited Xoo growth in vitro (minimum inhibitory concentration 153 mg L-1) and had 54.9% and 48.4% curative and protective control efficiencies against rice blight in vivo. Moreover, compound B2 also showed low toxicity for non-target organisms, including rice plant and mammalian cell. Given these interesting results, we provide a novel strategy to discover and optimize promising bactericidal compounds for the management of plant bacterial diseases.

In Silico Drug Repositioning to Target the SARS-CoV-2 Main Protease as Covalent Inhibitors Employing a Combined Structure-Based Virtual Screening Strategy of Pharmacophore Models and Covalent Docking.

The epidemic caused by the SARS-CoV-2 coronavirus, which has spread rapidly throughout the world, requires urgent and effective treatments considering that the appearance of viral variants limits the efficacy of vaccines. The main protease of SARS-CoV-2 (Mpro) is a highly conserved cysteine proteinase, fundamental for the replication of the coronavirus and with a specific cleavage mechanism that positions it as an attractive therapeutic target for the proposal of irreversible inhibitors. A structure-based strategy combining 3D pharmacophoric modeling, virtual screening, and covalent docking was employed to identify the interactions required for molecular recognition, as well as the spatial orientation of the electrophilic warhead, of various drugs, to achieve a covalent interaction with Cys145 of Mpro. The virtual screening on the structure-based pharmacophoric map of the SARS-CoV-2 Mpro in complex with an inhibitor N3 (reference compound) provided high efficiency by identifying 53 drugs (FDA and DrugBank databases) with probabilities of covalent binding, including N3 (Michael acceptor) and others with a variety of electrophilic warheads. Adding the energy contributions of affinity for non-covalent and covalent docking, 16 promising drugs were obtained. Our findings suggest that the FDA-approved drugs Vaborbactam, Cimetidine, Ixazomib, Scopolamine, and Bicalutamide, as well as the other investigational peptide-like drugs (DB04234, DB03456, DB07224, DB7252, and CMX-2043) are potential covalent inhibitors of SARS-CoV-2 Mpro.

Virtual screening and molecular docking studies o certain lead-like compounds from ZINC15 database against COVID-19 Mpro enzyme Potential lead-like compounds against COVID-19 Mpro

Aim: The COVID-19 epidemic, which first emerged in Wuhan in December 2019, rapidly affected the globe in the form of a pandemic, and currently millions of people are classified as active cases in terms of this infection, while tens of thousands of people are in serious or critical conditions. Material and Methods: In this study, 100 lead-like chemical entities were downloaded from the ZINC15 database and subjected to structure-based virtual screening (SBVS) in terms of their potential to be used in combating COVID-19. In our molecular docking study, the Mpro (3CLpro) enzyme encoded by the COVID-19 genome was selected as the receptor molecule that could be targeted in the treatment. Results: A total of 3 small molecules (ZINC000000011271, ZINC000000026220 and ZINC000000006645) were identified as potential inhibitors due to their high binding affinities to this enzyme. Physicochemical profiles of the top-ranked ligands, determined in our study, showed that these compounds were safe and had drug-like features. Furthermore, in molecular dynamics (MD) simulations, the top-ranked compound ZINC000000011271 was found to strongly bound to the Mpro enzyme and preserved its hydrogen bonding stability throughout the whole trajectory. Discussion: In this study, three orphaned drugs (ZINC000000011271, ZINC000000026220 and ZINC000000006646) were found to strongly inhibit Mpro in molecular simulations. These compounds also displayed hit features according to the SwissADME database. Therefore, these hits defined in this study may be used In the development and advanced optimization of potent COVID-19 inhibitors.

Structure-Based Virtual Screening and Identification of Potential Inhibitors of SARS-CoV-2 S-RBD and ACE2 Interaction.

The emergence and rapid spread of SARS-CoV-2 have caused a worldwide public health crisis. Designing small molecule inhibitors targeting SARS-CoV-2 S-RBD/ACE2 interaction is considered as a potential strategy for the prevention and treatment of SARS-CoV-2. But to date, only a few compounds have been reported as SARS-CoV-2 S-RBD/ACE2 interaction inhibitors. In this study, we described the virtual screening and experimental validation of two novel inhibitors (DC-RA016 and DC-RA052) against SARS-CoV-2 S-RBD/ACE2 interaction. The NanoBiT assays and surface plasmon resonance (SPR) assays demonstrated their capabilities of blocking SARS-CoV-2 S-RBD/ACE2 interaction and directly binding to both S-RBD and ACE2. Moreover, the pseudovirus assay revealed that these two compounds possessed significant antiviral activity (about 50% inhibition rate at maximum non-cytotoxic concentration). These results indicate that the compounds DC-RA016 and DC-RA052 are promising inhibitors against SARS-CoV-2 S-RBD/ACE2 interaction and deserve to be further developed.

In Silico Prediction of Novel Inhibitors of SARS-CoV-2 Main Protease through Structure-Based Virtual Screening and Molecular Dynamic Simulation.

The unprecedented pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is threatening global health. SARS-CoV-2 has caused severe disease with significant mortality since December 2019. The enzyme chymotrypsin-like protease (3CLpro) or main protease (Mpro) of the virus is considered to be a promising drug target due to its crucial role in viral replication and its genomic dissimilarity to human proteases. In this study, we implemented a structure-based virtual screening (VS) protocol in search of compounds that could inhibit the viral Mpro. A library of >eight hundred compounds was screened by molecular docking into multiple structures of Mpro, and the result was analyzed by consensus strategy. Those compounds that were ranked mutually in the 'Top-100' position in at least 50% of the structures were selected and their analogous binding modes predicted simultaneously in all the structures were considered as bioactive poses. Subsequently, based on the predicted physiological and pharmacokinetic behavior and interaction analysis, eleven compounds were identified as 'Hits' against SARS-CoV-2 Mpro. Those eleven compounds, along with the apo form of Mpro and one reference inhibitor (X77), were subjected to molecular dynamic simulation to explore the ligand-induced structural and dynamic behavior of Mpro. The MM-GBSA calculations reflect that eight out of eleven compounds specifically possess high to good binding affinities for Mpro. This study provides valuable insights to design more potent and selective inhibitors of SARS-CoV-2 Mpro.

In silico Screening of Natural Phytocompounds Towards Identification of Potential Lead Compounds to Treat COVID-19.

COVID-19 is one of the members of the coronavirus family that can easily assail humans. As of now, 10 million people are infected and above two million people have died from COVID-19 globally. Over the past year, several researchers have made essential advances in discovering potential drugs. Up to now, no efficient drugs are available on the market. The present study aims to identify the potent phytocompounds from different medicinal plants (Zingiber officinale, Cuminum cyminum, Piper nigrum, Curcuma longa, and Allium sativum). In total, 227 phytocompounds were identified and screened against the proteins S-ACE2 and M pro through structure-based virtual screening approaches. Based on the binding affinity score, 30 active phytocompounds were selected. Amongst, the binding affinity for beta-sitosterol and beta-elemene against S-ACE2 showed -12.0 and -10.9 kcal/mol, respectively. Meanwhile, the binding affinity for beta-sitosterol and beta-chlorogenin against M pro was found to be -9.7 and -8.4 kcal/mol, respectively. Further, the selected compounds proceeded with molecular dynamics simulation, prime MM-GBSA analysis, and ADME/T property checks to understand the stability, interaction, conformational changes, binding free energy, and pharmaceutical relevant parameters. Moreover, the hotspot residues such as Lys31 and Lys353 for S-ACE2 and catalytic dyad His41 and Cys145 for M pro were actively involved in the inhibition of viral entry. From the in silico analyses, we anticipate that this work could be valuable to ongoing novel drug discovery with potential treatment for COVID-19.

Docking-based virtual screening and identification of potential COVID-19 main protease inhibitors from brown algae.

COVID-19 (SARS-CoV-2) is a viral disease that causes acute respiratory syndrome, which has increased the morbidity and mortality rate throughout the world. World Health Organization has declared this COVID-19 outbreak as pandemic and classified health emergency throughout the world. In the recent past, outbreaks of SARS and MERS have shown the interspecies transmission potential of coronaviruses and limitations of already prescribed drugs to overcome this global public health issue. Therefore, there is a dire need to identify a new regimen of targeted drugs from natural compounds having anti-COVID19 potential. This study aimed at screening 1018 brown algal natural compounds (many of them previously reported to have immunomodulatory effects) having probable anti-COVID19 potentials. The source compounds were extracted from MarinLit, a database dedicated to marine natural products and screened against COVID-19 main protease. The top seven compounds were further analysed, and their interactions with the active site were visualized. This study will further warrant screening the potent compounds against the virus in-vitro conditions.

Corilagin inhibits SARS-CoV-2 replication by targeting viral RNA-dependent RNA polymerase.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become one major threat to human population health. The RNA-dependent RNA polymerase (RdRp) presents an ideal target of antivirals, whereas nucleoside analogs inhibitor is hindered by the proofreading activity of coronavirus. Herein, we report that corilagin (RAI-S-37) as a non-nucleoside inhibitor of SARS-CoV-2 RdRp, binds directly to RdRp, effectively inhibits the polymerase activity in both cell-free and cell-based assays, fully resists the proofreading activity and potently inhibits SARS-CoV-2 infection with a low 50% effective concentration (EC50) value of 0.13 µmol/L. Computation modeling predicts that RAI-S-37 lands at the palm domain of RdRp and prevents conformational changes required for nucleotide incorporation by RdRp. In addition, combination of RAI-S-37 with remdesivir exhibits additive activity against anti-SARS-CoV-2 RdRp. Together with the current data available on the safety and pharmacokinetics of corilagin as a medicinal herbal agent, these results demonstrate the potential of being developed into one of the much-needed SARS-CoV-2 therapeutics.

SARS-CoV-2 Mpro inhibitors: identification of anti-SARS-CoV-2 Mpro compounds from FDA approved drugs.

Recent outbreak of COVID-19 pandemic caused by severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) has raised serious global concern for public health. The viral main 3-chymotrypsin-like cysteine protease (Mpro), known to control coronavirus replication and essential for viral life cycle, has been established as an essential drug discovery target for SARS-CoV-2. Herein, we employed computationally screening of Druglib database containing FDA approved drugs against active pocket of SARS-CoV-2 Mpro using MTiopen screen web server, yields a total of 1051 FDA approved drugs with docking energy >-7 kcal/mol. The top 10 screened potential compounds against SARS-CoV-2 Mpro were then studied by re-docking, binding affinity, intermolecular interaction, and complex stability via 100 ns all atoms molecular dynamics (MD) simulation followed by post-simulation analysis, including end point binding free energy, essential dynamics, and residual correlation analysis against native crystal structure ligand N3 inhibitor. Based on comparative molecular simulation and interaction profiling of the screened drugs with SARS-CoV-2 Mpro revealed R428 (-10.5 kcal/mol), Teniposide (-9.8 kcal/mol), VS-5584 (-9.4 kcal/mol), and Setileuton (-8.5 kcal/mol) with stronger stability and affinity than other drugs and N3 inhibitor; and hence, these drugs are advocated for further validation using in vitro enzyme inhibition and in vivo studies against SARS-CoV-2 infection.Communicated by Ramaswamy H. Sarma.

A comprehensive review on promising anti-viral therapeutic candidates identified against main protease from SARS-CoV-2 through various computational methods.

BACKGROUND: The COVID-19 pandemic caused by SARS-CoV-2 has shown an exponential trend of infected people across the planet. Crediting its virulent nature, it becomes imperative to identify potential therapeutic agents against the deadly virus. The 3-chymotrypsin-like protease (3CLpro) is a cysteine protease which causes the proteolysis of the replicase polyproteins to generate functional proteins, which is a crucial step for viral replication and infection. Computational methods have been applied in recent studies to identify promising inhibitors against 3CLpro to inhibit the viral activity. This review provides an overview of promising drug/lead candidates identified so far against 3CLpro through various in silico approaches such as structure-based virtual screening (SBVS), ligand-based virtual screening (LBVS) and drug-repurposing/drug-reprofiling/drug-retasking. Further, the drugs have been classified according to their chemical structures or biological activity into flavonoids, peptides, terpenes, quinolines, nucleoside and nucleotide analogues, protease inhibitors, phenalene and antibiotic derivatives. These are then individually discussed based on the various structural parameters namely estimated free energy of binding (ΔG), key interacting residues, types of intermolecular interactions and structural stability of 3CLpro-ligand complexes obtained from the results of molecular dynamics (MD) simulations. CONCLUSION: The review provides comprehensive information of potential inhibitors identified through several computational methods thus far against 3CLpro from SARS-CoV-2 and provides a better understanding of their interaction patterns and dynamic states of free and ligand-bound 3CLpro structures.