Molecular dynamics and in silico mutagenesis on the reversible inhibitor-bound SARS-CoV-2 main protease complexes reveal the role of lateral pocket in enhancing the ligand affinity

Mapping protein conformational landscapes from crystallographic drug fragment screens

Proteins are dynamic macromolecules. Knowledge of a protein's thermally accessible conformations is critical to determining important transitions and designing therapeutics. Accessible conformations are highly constrained by a protein's structure such that concerted structural changes due to external perturbations likely track intrinsic conformational transitions. These transitions can be thought of as paths through a conformational landscape. Crystallographic drug fragment screens are high-throughput perturbation experiments, in which thousands of crystals of a drug target are soaked with small-molecule drug precursors (fragments) and examined for fragment binding, mapping potential drug binding sites on the target protein. Here, we describe an open-source Python package, COLAV (COnformational LAndscape Visualization), to infer conformational landscapes from such large-scale crystallographic perturbation studies. We apply COLAV to drug fragment screens of two medically important systems: protein tyrosine phosphatase 1B (PTP-1B), which regulates insulin signaling, and the SARS CoV-2 Main Protease (MPro). With enough fragment-bound structures, we find that such drug screens also enable detailed mapping of proteins' conformational landscapes.

In Silico Exploration of Isoxazole Derivatives of Usnic Acid: Novel Therapeutic Prospects Against α-Amylase for Diabetes Treatment

Diabetes mellitus (DM) a metabolic disorder characterized by high blood sugar levels causing damage to various organs over time. Current anti-diabetic drugs have limitations and side effects, prompting a search for new inhibitors targeting the α-amylase enzyme. This study aims to discover such inhibitors from thirty isoxazole derivatives of usnic acid using in silico approaches. The potential inhibitory effects of compounds were investigated using ADMET, molecular docking, molecular dynamic simulation, principal component analysis and density functional theory studies. ADMET analysis exhibited a wide range of physicochemical, pharmacokinetic, and drug-like qualities with no significant side effects which were then investigated using molecular docking experiment to determine the lead compound with the best binding affinity for the α-amylase enzyme. All compounds showed good binding affinity against α-amylase enzyme (-7.9 to -9.2 kcal/mol) where compound-13 showed the best binding affinity of -9.2 kcal/mol forming hydrogen bonds with Leu162, Tyr62, Glu233 and Asp300 amino acids. Furthermore, the binding posture and the stability of the compound-13-α-amylase enzyme complex was confirmed by molecular dynamic simulation experiment. Moreover, compound-13 showed binding energy value of -27.92 ± 5.61 kcal/mol, which indicated it could be an α-amylase inhibitor. Additionally, the reactivity of compound-13 was further confirmed by density functional theory analysis. The above findings suggest compound-13 to be a potential α-amylase inhibitor in DM. And setting the stage for further in vitro and in vivo experimental validation.

Interaction of systemic drugs causing ocular toxicity with organic cation transporter: an artificial intelligence prediction

Chronic disease patients (cancer, arthritis, cardiovascular diseases) undergo long-term systemic drug treatment. Membrane transporters in ocular barriers could falsely recognize these drugs and allow their trafficking into the eye from systemic circulation. Hence, despite their pharmacological activity, these drugs accumulate and cause toxicity at the non-target site, such as the eye. Since around 40% of clinically used drugs are organic cation in nature, it is essential to understand the role of organic cation transporter (OCT1) in ocular barriers to facilitate the entry of systemic drugs into the eye. We applied machine learning techniques and computer simulation models (molecular dynamics and metadynamics) in the current study to predict the potential OCT1 substrates. Artificial intelligence models were developed using a training dataset of a known substrates and non-substrates of OCT1 and predicted the potential OCT1 substrates from various systemic drugs causing ocular toxicity. Computer simulation studies was performed by developing the OCT1 homology model. Molecular dynamic simulations equilibrated the docked protein-ligand complex. And metadynamics revealed the movement of substrates across the transporter with minimum free energy near the binding pocket. The machine learning model showed an accuracy of about 80% and predicted the potential substrates for OCT1 among systemic drugs causing ocular toxicity - not known earlier, such as cyclophosphamide, bupivacaine, bortezomib, sulphanilamide, tosufloxacin, topiramate, and many more. However, further invitro and invivo studies are required to confirm these predictions.Communicated by Ramaswamy H. Sarma.

Characterization of thiamine pyrophosphokinase of vitamin B1 biosynthetic pathway as a drug target of Leishmania donovani

Vitamin B1 is an essential cofactor for enzymes involved in the metabolism of carbohydrates, particularly Transketolases. These enzymes are amenable to therapeutic interventions because of their specificity. In the final step of the Vitamin B1 biosynthesis pathway, Thiamine Pyrophosphokinase (TPK) converts thiamin into its active form, Thiamin Pyrophosphate (TPP), allowing researchers to investigate the functional importance of this enzyme and the pathway's dispensability in Leishmania donovani, a protozoan parasite that causes visceral leishmaniasis. In this study, various in silico, biochemical, biophysical, and cellular assays-based experiments have been conducted to identify and characterize LdTPK, and to provide a sound platform for the discovery of potential LdTPK inhibitors. LdTPK structural modelling ensured high protein quality. Oxythiamine and pyrithiamine were found to bind well with LdTPK with considerable binding energies, and MD simulation-based experiments indicated the stability of the complexation. Additionally, LdTPK1 was found to activate ROS defense in amastigotes, and its inhibition using oxythiamine and pyrithiamine led to the growth inhibition of L. donovani promastigotes and intracellular amastigotes. These findings highlight LdTPK as a promising target for the development of new anti-leishmanial agents. An in-depth analysis of the enzymes involved in TPP biosynthesis in L. donovani has the potential to yield novel therapeutic strategies for Leishmaniasis.Communicated by Ramaswamy H. Sarma.

Structure-Based Discovery of Allosteric Inhibitors Targeting a New Druggable Site in the Respiratory Syncytial Virus Polymerase

Respiratory syncytial virus (RSV) is a major cause of severe lower respiratory infections for which effective treatment options remain limited. Herein, we employed a computational structure-based design strategy aimed at identifying potential targets for a new class of allosteric inhibitors. Our investigation led to the discovery of a previously undisclosed allosteric binding site within the RSV polymerase, the large (L) protein. This discovery was achieved through a combination of virtual screening and molecular dynamics simulations. Subsequently, we identified two inhibitors, 6a and 10b, which both exhibited promising antiviral activity in the low micromolar range. Resistance profiling revealed a distinctive pattern in how RSV evaded treatment with this class of inhibitors. This pattern strongly suggested that this class of small molecules was targeting a new binding site in the RSV L protein, aligning with the computational predictions made in our study. This study paves the way for the development of more potent inhibitors for combating RSV infections by targeting a new druggable pocket within the RdRp which does not overlap with previously known resistance sites.

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

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

Computational methods meet in vitro techniques: A case study on fusaric acid and its possible detoxification through cytochrome P450 enzymes

Mycotoxins are known environmental pollutants that may contaminate food and feed chains. Some mycotoxins are regulated in many countries to limit the trading of contaminated and harmful commodities. However, the so-called emerging mycotoxins are poorly understood and need to be investigated further. Fusaric acid is an emerging mycotoxin, noxious to plants and animals, but is known to be less toxic to plants when hydroxylated. The detoxification routes effective in animals have not been elucidated yet. In this context, this study integrated in silico and in vitro techniques to discover potential bioremediation routes to turn fusaric acid to its less toxic metabolites. The toxicodynamics of these forms in humans have also been addressed. An in silico screening process, followed by molecular docking and dynamics studies, identified CYP199A4 from the bacterium Rhodopseudomonas palustris HaA2 as a potential fusaric acid biotransforming enzyme. Its activity was confirmed in vitro. However, the effect of hydroxylation seemed to have a limited impact on the modelled toxicodynamics against human targets. This study represents a starting point to develop a hybrid in silico/in vitro pipeline to find bioremediation agents for other food, feed and environmental contaminants.

Identification of Phytochemicals from Arabian Peninsula Medicinal Plants as Strong Binders to SARS-CoV-2 Proteases (3CLPro and PLPro) by Molecular Docking and Dynamic Simulation Studies

We provide promising computational (in silico) data on phytochemicals (compounds 1-10) from Arabian Peninsula medicinal plants as strong binders, targeting 3-chymotrypsin-like protease (3CLPro) and papain-like proteases (PLPro) of SARS-CoV-2. Compounds 1-10 followed the Lipinski rules of five (RO5) and ADMET analysis, exhibiting drug-like characters. Non-covalent (reversible) docking of compounds 1-10 demonstrated their binding with the catalytic dyad (CYS145 and HIS41) of 3CLPro and catalytic triad (CYS111, HIS272, and ASP286) of PLPro. Moreover, the implementation of the covalent (irreversible) docking protocol revealed that only compounds 7, 8, and 9 possess covalent warheads, which allowed the formation of the covalent bond with the catalytic dyad (CYS145) in 3CLPro and the catalytic triad (CYS111) in PLPro. Root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and radius of gyration (Rg) analysis from molecular dynamic (MD) simulations revealed that complexation between ligands (compounds 7, 8, and 9) and 3CLPro and PLPro was stable, and there was less deviation of ligands. Overall, the in silico data on the inherent properties of the above phytochemicals unravel the fact that they can act as reversible inhibitors for 3CLPro and PLPro. Moreover, compounds 7, 8, and 9 also showed their novel properties to inhibit dual targets by irreversible inhibition, indicating their effectiveness for possibly developing future drugs against SARS-CoV-2. Nonetheless, to confirm the theoretical findings here, the effectiveness of the above compounds as inhibitors of 3CLPro and PLPro warrants future investigations using suitable in vitro and in vivo tests.

Molecular insights into the anti-inflammatory activity of fermented pineapple juice using multimodal computational studies

Pineapple has been recognized for its potential to enhance health and well-being. This study aimed to gain molecular insights into the anti-inflammatory properties of fermented pineapple juice using multimodal computational studies. In this study, pineapple juice was fermented using Lactobacillus paracasei, and the solution underwent liquid chromatography-mass spectrometry analysis. Network pharmacology was applied to investigate compound interactions and targets. In silico methods assessed compound bioactivities. Protein-protein interactions, network topology, and enrichment analysis identified key compounds. Molecular docking explored compound-receptor interactions in inflammation regulation. Molecular dynamics simulations were conducted to confirm the stability of interactions between the identified crucial compounds and their respective receptors. The study revealed several compounds including short-chain fatty acids, peptides, dihydroxyeicosatrienoic acids, and glycerides that exhibited promising anti-inflammatory properties. Leucyl-leucyl-norleucine and Leu-Leu-Tyr exhibited robust and stable interactions with mitogen-activated protein kinase 14 and IκB kinase β, respectively, indicating their potential as promising therapeutic agents for inflammation modulation. This proposition is grounded in the pivotal involvement of these two proteins in inflammatory signaling pathways. These findings provide valuable insights into the anti-inflammatory potential of these compounds, serving as a foundation for further experimental validation and exploration. Future studies can build upon these results to advance the development of these compounds as effective anti-inflammatory agents.

Molecular docking and dynamic simulation studies of isoflavones inhibiting Lox-2 activity for reducing beany flavor in soybean seeds

Low-lipoxygenase soybean cultivars are highly desirable because lower lipoxygenase content in soybean seeds leads to better quality soybean-based products and oils that are free from off-flavor or beany flavor. The expression of the Lox-2 gene is mainly responsible for this flavor. Over the years, natural antioxidants have been tested biochemically to inhibit Lox-2 activity, but in-silico studies are still lacking. To investigate the structural basis of inhibition, site-specific docking, as well as molecular dynamics (MD) simulations, were performed. Molecular docking analysis revealed that daidzein and genistein could be effective Lox2 receptor inhibitors. Furthermore, docked complexes were subjected to 100 ns MD simulation studies to analyze the structural conformations and stability of the complex. The analysis demonstrated that daidzein formed a more stable complex with the Lox-2 receptor and showed a higher H-bond propensity with the Asp775 residue. We discovered that the initial conformation of Lox2-daidzein complex changed to a more stable conformation at the beginning of the MD simulation and remained stable until the end with minor fluctuations. Furthermore, our analysis suggested that daidzein acts as a potential Lox-2 inhibitor and is a better candidate compared to genistein, which could be used to solve the beany flavor problem in soybean.Communicated by Ramaswamy H. Sarma.

The H163A mutation unravels an oxidized conformation of the SARS-CoV-2 main protease

The main protease of SARS-CoV-2 (Mpro) is an important target for developing COVID-19 therapeutics. Recent work has highlighted Mpro's susceptibility to undergo redox-associated conformational changes in response to cellular and immune-system-induced oxidation. Despite structural evidence indicating large-scale rearrangements upon oxidation, the mechanisms of conformational change and its functional consequences are poorly understood. Here, we present the crystal structure of an Mpro point mutant (H163A) that shows an oxidized conformation with the catalytic cysteine in a disulfide bond. We hypothesize that Mpro adopts this conformation under oxidative stress to protect against over-oxidation. Our metadynamics simulations illustrate a potential mechanism by which H163 modulates this transition and suggest that this equilibrium exists in the wild type enzyme. We show that other point mutations also significantly shift the equilibrium towards this state by altering conformational free energies. Unique avenues of SARS-CoV-2 research can be explored by understanding how H163 modulates this equilibrium.

Exploring potential SARS-CoV-2 Mpro non-covalent inhibitors through docking, pharmacophore profile matching, molecular dynamic simulation, and MM-GBSA

CONTEXT

In the replication of SARS-CoV-2, the main protease (Mpro/3CLpro) is significant. It is conserved in a number of novel coronavirus variations, and no known human proteases share its cleavage sites. Therefore, 3CLpro is an ideal target. In the report, we screened five potential inhibitors (1543, 2308, 3717, 5606, and 9000) of SARS-CoV-2 Mpro through a workflow. The calculation of MM-GBSA binding free energy showed that three of the five potential inhibitors (1543, 2308, 5606) had similar inhibitor effects to X77 against Mpro of SARS-CoV-2. In conclusion, the manuscript lays the groundwork for the design of Mpro inhibitors.

METHODS

In the virtual screening phase, we used structure-based virtual screening (Qvina2.1) and ligand-based virtual screening (AncPhore). In the molecular dynamic simulation part, we used the Amber14SB + GAFF force field to perform molecular dynamic simulation of the complex for 100 ns (Gromacs2021.5) and performed MM-GBSA binding free energy calculation according to the simulation trajectory.

Diphenyl Diselenide and SARS-CoV-2: in silico Exploration of the Mechanisms of Inhibition of Main Protease (Mpro) and Papain-like Protease (PLpro)

The SARS-CoV-2 pandemic has prompted global efforts to develop therapeutics. The main protease of SARS-CoV-2 (M^pro) and the papain-like protease (PL^pro) are essential for viral replication and are key targets for therapeutic development. In this work, we investigate the mechanisms of SARS-CoV-2 inhibition by diphenyl diselenide (PhSe)₂ which is an archetypal model of diselenides and a renowned potential therapeutic agent. The in vitro inhibitory concentration of (PhSe)₂ against SARS-CoV-2 in Vero E6 cells falls in the low micromolar range. Molecular dynamics (MD) simulations and density functional theory (DFT) calculations [level of theory: SMD-B3LYP-D3(BJ)/6-311G(d,p), cc-pVTZ] are used to inspect non-covalent inhibition modes of both proteases via π-stacking and the mechanism of covalent (PhSe)₂ + M^pro product formation involving the catalytic residue C145, respectively. The in vitro CC₅₀ (24.61 μM) and EC₅₀ (2.39 μM) data indicate that (PhSe)₂ is a good inhibitor of the SARS-CoV-2 virus replication in a cell culture model. The in silico findings indicate potential mechanisms of proteases' inhibition by (PhSe)₂; in particular, the results of the covalent inhibition here discussed for M^pro, whose thermodynamics is approximatively isoergonic, prompt further investigation in the design of antiviral organodiselenides.

Multi-ligand molecular docking, simulation, free energy calculations and wavelet analysis of the synergistic effects between natural compounds baicalein and cubebin for the inhibition of the main protease of SARS-CoV-2

Combination drugs have been used for several diseases for many years since they produce better therapeutic effects. However, it is still a challenge to discover candidates to form a combination drug. This study aimed to investigate whether using a comprehensive in silico approach to identify novel combination drugs from a Chinese herbal formula is an appropriate and creative strategy. We, therefore, used Toujie Quwen Granules for the main protease (M^pro) of SARS-CoV-2 as an example. We first used molecular docking to identify molecular components of the formula which may inhibit M^pro. Baicalein (HQA004) is the most favorable inhibitory ligand. We also identified a ligand from the other component, cubebin (CHA008), which may act to support the proposed HQA004 inhibitor. Molecular dynamics simulations were then performed to further elucidate the possible mechanism of inhibition by HQA004 and synergistic bioactivity conferred by CHA008. HQA004 bound strongly at the active site and that CHA008 enhanced the contacts between HQA004 and M^pro. However, CHA008 also dynamically interacted at multiple sites, and continued to enhance the stability of HQA004 despite diffusion to a distant site. We proposed that HQA004 acted as a possible inhibitor, and CHA008 served to enhance its effects via allosteric effects at two sites. Additionally, our novel wavelet analysis showed that as a result of CHA008 binding, the dynamics and structure of M^pro were observed to have more subtle changes, demonstrating that the inter-residue contacts within M^pro were disrupted by the synergistic ligand. This work highlighted the molecular mechanism of synergistic effects between different herbs as a result of allosteric crosstalk between two ligands at a protein target, as well as revealed that using the multi-ligand molecular docking, simulation, free energy calculations and wavelet analysis to discover novel combination drugs from a Chinese herbal remedy is an innovative pathway.

In silico bioprospecting of antiviral compounds from marine fungi and mushroom for rapid development of nutraceuticals against SARS-CoV-2

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) affects human respiratory function that causes COVID-19 disease. COVID-19 has spread rapidly all over the world and became a pandemic within no time. Therefore, it is the need of hour to screen potential lead candidates from natural resources like edible mushrooms and marine fungi. These natural resources are very less explored till now and known to be the source for many medicinal compounds with several health benefits. These medicinal compounds can be easily exploited for the faster development of nutraceuticals for controlling SARS-CoV-2 infections. Our Insilico research suggests, bioactive compounds originating from mushroom and marine fungi shows strong potential to interact with ACE2 receptor or main protease of SARS-CoV-2, showing the inhibition activity towards the enzymatic protease. We performed a series of Insilico studies for the validation of our results, which includes Molecular docking, drug likeness property investigation by Swiss ADME tools, MD simulation, and thermodynamically stable free binding energy calculation. Overall, these results suggest that Ganodermadiol and Heliantriol F bioactive compounds originating from edible mushroom has strong potential to be developed as low-cost nutraceutical against SARS-CoV-2 viral infection. The drug candidate isolated from marine fungi and edible mushroom are highly unexplored for the development of potential alternative drug against SARS-CoV-2 virus with minimum side effects. Though our in silico studies of these compounds are showing a promising results against SARS-CoV-2 main protease and ACE2 receptor binding domain, the effectiveness of these bioactive compounds should be further validated by proper clinical trials.Communicated by Ramaswamy H. Sarma.

Traditional herbal compounds as candidates to inhibit the SARS-CoV-2 main protease: an in silico study

COVID-19, a disease caused by the SARS-CoV-2 virus, is responsible for a pandemic since March 2020 and it has no cure. Therefore, herein, different theoretical methods were used to obtain potential candidates from herbal compounds to inhibit the SARS-CoV-2 main protease (M^pro). Initially, the 16 best-scored compounds were selected from a library containing 4066 ligands using virtual screening by molecular docking. Among them, six molecules (physalin B 5,6-epoxide (PHY), methyl amentoflavone (MAM), withaphysalin C (WPC), daphnoline or trilobamine (TRI), cepharanoline (CEP) and tetrandrine (TET)) were selected based on Lipinski's rule and ADMET analysis as criteria. These compounds complexed with the M^pro were submitted to triplicate 100 ns molecular dynamics simulations. RMSD, RMSF, and radius of gyration results show that the overall protein structure is preserved along the simulation time. The average ΔG_binding values, calculated by the MM/PBSA method, were -41.7, -55.8, -45.2, -38.7, -49.3, and -57.9 kcal/mol for the PHY-M^pro, MAM-M^pro, WPC-M^pro, CEP-M^pro, TRI-M^pro, and TET-M^pro complexes, respectively. Pairwise decomposition analyses revealed that the binding pocket is formed by His41-Val42, Met165-Glu166-Leu167, Asp187, and Gln189. The PLS regression model generated by QSPR analysis indicated that non-polar and polar groups with the presence of hydrogen bond acceptors play an important role in the herbal compounds-M^pro interactions. Overall, we found six potential candidates to inhibit the SARS-CoV-2 M^pro and highlighted key residues from the binding pocket that can be used for future drug design. Communicated by Ramaswamy H. Sarma.

SARS-CoV-2 proteases Mpro and PLpro: Design of inhibitors with predicted high potency and low mammalian toxicity using artificial neural networks, ligand-protein docking, molecular dynamics simulations, and ADMET calculations

The main (Mpro) and papain-like (PLpro) proteases are highly conserved viral proteins essential for replication of the COVID-19 virus, SARS-COV-2. Therefore, a logical plan for producing new drugs against this pathogen is to discover inhibitors of these enzymes. Accordingly, the goal of the present work was to devise a computational approach to design, characterize, and select compounds predicted to be potent dual inhibitors - effective against both Mpro and PLpro. The first step employed LigDream, an artificial neural network, to create a virtual ligand library. Ligands with computed ADMET profiles indicating drug-like properties and low mammalian toxicity were selected for further study. Initial docking of these ligands into the active sites of Mpro and PLpro was done with GOLD, and the highest-scoring ligands were redocked with AutoDock Vina to determine binding free energies (ΔG). Compounds 89-00, 89-07, 89-32, and 89-38 exhibited favorable ΔG values for Mpro (-7.6 to -8.7 kcal/mol) and PLpro (-9.1 to -9.7 kcal/mol). Global docking of selected compounds with the Mpro dimer identified prospective allosteric inhibitors 89-00, 89-27, and 89-40 (ΔG -8.2 to -8.9 kcal/mol). Molecular dynamics simulations performed on Mpro and PLpro active site complexes with the four top-scoring ligands from Vina demonstrated that the most stable complexes were formed with compounds 89-32 and 89-38. Overall, the present computational strategy generated new compounds with predicted drug-like characteristics, low mammalian toxicity, and high inhibitory potencies against both target proteases to form stable complexes. Further preclinical studies will be required to validate the in silico findings before the lead compounds could be considered for clinical trials.

MD simulation and MM/PBSA identifies phytochemicals as bifunctional inhibitors of SARS-CoV-2

The global spread of SARS-CoV-2 has resulted in millions of fatalities worldwide, making it crucial to identify potent antiviral therapeutics to combat this virus. We employed structure-assisted virtual screening to identify phytochemicals that can target the two proteases which are essential for SARS-CoV-2 replication and transcription, the main protease and papain-like protease. Using virtual screening and molecular dynamics, we discovered new phytochemicals with inhibitory activity against the two proteases. Isoginkgetin, kaempferol-3-robinobioside, methyl amentoflavone, bianthraquinone, podocarpusflavone A, and albanin F were shown to have the best affinity and inhibitory potential among the compounds, and can be explored clinically for use as inhibitors of novel coronavirus SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Computational exploration of the dual role of the phytochemical fortunellin: Antiviral activities against SARS-CoV-2 and immunomodulatory abilities against the host

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections generate approximately one million virions per day, and the majority of available antivirals are ineffective against it due to the virus's inherent genetic mutability. This necessitates the investigation of concurrent inhibition of multiple SARS-CoV-2 targets. We show that fortunellin (acacetin 7-O-neohesperidoside), a phytochemical, is a promising candidate for preventing and treating coronavirus disease (COVID-19) by targeting multiple key viral target proteins. Fortunellin supports protective immunity while inhibiting pro-inflammatory cytokines and apoptosis pathways and protecting against tissue damage. Fortunellin is a phytochemical found in Gojihwadi kwath, an Indian traditional Ayurvedic formulation with an antiviral activity that is effective in COVID-19 patients. The mechanistic action of its antiviral activity, however, is unknown. The current study comprehensively evaluates the potential therapeutic mechanisms of fortunellin in preventing and treating COVID-19. We have used molecular docking, molecular dynamics simulations, free-energy calculations, host target mining of fortunellin, gene ontology enrichment, pathway analyses, and protein-protein interaction analysis. We discovered that fortunellin reliably binds to key targets that are necessary for viral replication, growth, invasion, and infectivity including Nucleocapsid (N-CTD) (-54.62 kcal/mol), Replicase-monomer at NSP-8 binding site (-34.48 kcal/mol), Replicase-dimer interface (-31.29 kcal/mol), Helicase (-30.02 kcal/mol), Papain-like-protease (-28.12 kcal/mol), 2'-O-methyltransferase (-23.17 kcal/mol), Main-protease (-21.63 kcal/mol), Replicase-monomer at dimer interface (-22.04 kcal/mol), RNA-dependent-RNA-polymerase (-19.98 kcal/mol), Nucleocapsid-NTD (-16.92 kcal/mol), and Endoribonuclease (-16.81 kcal/mol). Furthermore, we identify and evaluate the potential human targets of fortunellin and its effect on the SARS-CoV-2 infected tissues, including normal-human-bronchial-epithelium (NHBE) and lung cells and organoids such as pancreatic, colon, liver, and cornea using a network pharmacology approach. Thus, our findings indicate that fortunellin has a dual role; multi-target antiviral activities against SARS-CoV-2 and immunomodulatory capabilities against the host.

Comprehensive fitness landscape of SARS-CoV-2 Mpro reveals insights into viral resistance mechanisms

With the continual evolution of new strains of SARS-CoV-2 that are more virulent, transmissible, and able to evade current vaccines, there is an urgent need for effective anti-viral drugs SARS-CoV-2 main protease (M^pro) is a leading target for drug design due to its conserved and indispensable role in the viral life cycle. Drugs targeting M^pro appear promising but will elicit selection pressure for resistance. To understand resistance potential in M^pro, we performed a comprehensive mutational scan of the protease that analyzed the function of all possible single amino acid changes. We developed three separate high-throughput assays of M^pro function in yeast, based on either the ability of M^pro variants to cleave at a defined cut-site or on the toxicity of their expression to yeast. We used deep sequencing to quantify the functional effects of each variant in each screen. The protein fitness landscapes from all three screens were strongly correlated, indicating that they captured the biophysical properties critical to M^pro function. The fitness landscapes revealed a non-active site location on the surface that is extremely sensitive to mutation making it a favorable location to target with inhibitors. In addition, we found a network of critical amino acids that physically bridge the two active sites of the M^pro dimer. The clinical variants of M^pro were predominantly functional in our screens, indicating that M^pro is under strong selection pressure in the human population. Our results provide predictions of mutations that will be readily accessible to M^pro evolution and that are likely to contribute to drug resistance. This complete mutational guide of M^pro can be used in the design of inhibitors with reduced potential of evolving viral resistance.

Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case

Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under:Data Science > Computer Algorithms and ProgrammingData Science > Databases and Expert SystemsMolecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods.

Dynamic Allostery Highlights the Evolutionary Differences between the CoV-1 and CoV-2 Main Proteases

The SARS-CoV-2 coronavirus has become one of the most immediate and widely-studied systems since its identification and subsequent global outbreak from 2019-2021. In an effort to understand the biophysical changes as a result of mutations, the mechanistic details of multiple different proteins within the SARS-CoV-2 virus have been studied and compared with SARS-CoV-1. Focusing on the main protease (mPro), we first explored the long-range dynamics using the Dynamic Coupling Index (DCI) to investigate the dynamic coupling between the catalytic site residues and the rest of the protein, both inter and intra chain, for the CoV-1 and CoV-2 mPro. We found that there is significant cross-chain coupling between these active sites and specific distal residues in the CoV-2 mPro not present in CoV-1. The enhanced long distance interactions, particularly between the two chains, suggest subsequently enhanced cooperativity for CoV-2. A further comparative analysis of the dynamic flexibility using the Dynamic Flexibility Index (DFI) between the CoV-1 and CoV-2 mPros shows that the inhibitor binding near active sites induces change in flexibility to a distal region of the protein, opposite in behavior between the two systems; this region becomes more flexible upon inhibitor binding in CoV-1 while it becomes less flexible in the CoV-2 mPro. Upon inspection, we show that, on average, the dynamic flexibility of the sites substituted from CoV-1 to CoV-2 changes significantly less than the average calculated across all residues within the structure, indicating that the differences in behaviors between the two systems is likely the result of allosteric influence, where the new substitutions in CoV-2 induce flexibility and dynamical changes elsewhere in the structure.

Recent Development of Small Molecules for SARS-CoV-2 and the Opportunity for Fragment-Based Drug Discovery

Abstract:

The ongoing pandemic of Covid-19 caused by SARS-CoV-2 is a major threat to global public health, drawing attention to develop new therapeutics for treatment. Much research work is focused on identifying or repurposing new small molecules to serve as potential inhibitors by interacting with viral or host-cell molecular targets and understanding the nature of the virus in the host cells. Identifying small molecules as potent inhibitors at an early stage is advantageous to make a molecule with higher potency and then find a lead compound for the development of drug discovery. Small molecules can show their inhibition property by targeting either SARS-CoV-2 main protease (Mpro) enzyme, papain-like protease (PLpro) enzyme, or helicase (Hel), or blocking the spike (S) protein angiotensin-converting enzyme 2 (ACE2) receptor. A very recent outbreak of a new variant (B.1.617.2—termed as Delta variant) of SARS-CoV-2 worldwide posed a greater challenge as it is resistant to clinically undergoing vaccine trials. Thus, the development of new drug molecules is of potential interest to combat SARS-CoV-2 disease, and for that, fragment-based drug discovery (FBDD) approach could be one of the ways to bring out an effective solution. Two cysteine protease enzymes would be an attractive choice of target for fragment-based drug discovery to tune the molecular structure at an early stage with suitable functionality. In this short review, the recent development of small-molecule as inhibitors against Covid-19 are discussed and the opportunity for FBDD is envisioned optimistically to provide an outlook regarding Covid-19 that may pave the way in the direction of the Covid-19 drug development paradigm.

Mechanistic Insights into SARS-CoV-2 Main Protease Inhibition Reveals Hotspot Residues

The main protease (M^pro) is a key enzyme responsible for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication that causes the spread of the global pandemic novel coronavirus (nCOVID-19) infection. In the present study, multiple computational approaches such as docking, long-range molecular dynamics (MD) simulations, and binding free-energy (BFE) estimation techniques were employed to investigate the mechanistic basis of the high-affinity inhibitors─GC-376, Calpain XII, and Calpain II (hereafter Calpain as Cal) from the literature─binding to M^pro. Redocking GC-376 and docking Cal XII and Cal II inhibitors to M^pro were able to reproduce all crucial interactions like the X-ray conformation. Subsequently, the apo (ligand-free) and three holo (ligand-bound) complexes were subjected to extensive MD simulations, which revealed that the ligand binding did not alter the overall M^pro structural features, whereas the heatmap analysis showed that the residues located in subsites S1 and S2, the catalytic dyad, and the ⁴⁵TSEDMLN⁵¹ loop in M^pro exhibit a conformational deviation. Moreover, the BFE estimation method was used to elucidate the crucial thermodynamic properties, which revealed that Coulomb, solvation surface accessibility (Solv_SA), and lipophilic components contributed significant energies for complex formation. The decomposition of the total BFE to per-residue showed that H41, H163, M165, Q166, and Q189 residues contributed maximum energies. The overall results from the current investigation might be valuable for designing novel anti-M^pro inhibitors.

Virus structure and structure-based antivirals

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

Supervised Molecular Dynamics (SuMD) Insights into the mechanism of action of SARS-CoV-2 main protease inhibitor PF-07321332

The chemical structure of PF-07321332, the first orally available Covid-19 clinical candidate, has recently been revealed by Pfizer. No information has been provided about the interaction pattern between PF-07321332 and its biomolecular counterpart, the SARS-CoV-2 main protease (M^pro). In the present work, we exploited Supervised Molecular Dynamics (SuMD) simulations to elucidate the key features that characterise the interaction between this drug candidate and the protease, emphasising similarities and differences with other structurally related inhibitors such as Boceprevir and PF-07304814. The structural insights provided by SuMD will hopefully be able to inspire the rational discovery of other potent and selective protease inhibitors.