Virtual screening, ADMET prediction and dynamics simulation of potential compounds targeting the main protease of SARS-CoV-2

SARS-CoV-2 proteins show great binding affinity to resin composite monomers and polymerized chains

BACKGROUND

Due to saliva and salivary glands are reservoir to severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), aerosols and saliva droplets are primary sources of cross-infection and are responsible for the high human–human transmission of SARS-CoV-2. However, there is no evidence about how SARS-CoV-2 interacts with oral structures, particularly resin composites.

AIM

To evaluate the interaction of SARS-CoV-2 proteins with monomers present in resin composites using in silico analysis.

METHODS

Four SARS-CoV-2 proteins [i.e. main protease, 3C-like protease, papain-like protease (PLpro), and glycoprotein spike] were selected along with salivary amylase as the positive control, and their binding affinity with bisphenol-A glycol dimethacrylate, bisphenol-A ethoxylated dimethacrylate, triethylene glycol dimethacrylate, and urethane dimethacrylate was evaluated. Molecular docking was performed using AutoDock Vina and visualised in Chimera UCSF 1.14. The best ligand–protein model was identified based on the binding energy (ΔG–kcal/moL).

RESULTS

Values for the binding energies ranged from -3.6 kcal/moL to -7.3 kcal/moL. The 3-monomer chain had the lowest binding energy (i.e. highest affinity) to PLpro and the glycoprotein spike. Non-polymerised monomers and polymerised chains interacted with SARS-CoV-2 proteins via hydrogen bonds and hydrophobic interactions. Those findings suggest an interaction between SARS-CoV-2 proteins and resin composites.

CONCLUSION

SARS-CoV-2 proteins show affinity to non-polymerised and polymerised resin composite chains.

Elucidating the potential of bioactive of Trichoderma sp.. in combating pathogenesis by Fusarium sp.. by targeting pectin lyases: a bioinformatics approach

Pectin lyase is an industrially important enzyme, predominately used in fruit juice clarification and retting of fibers. It also promotes pathogenesis via the degradation of the pectin. The phytopathogen, Fusarium infects various crops and causes several diseases. Trichoderma sp. is a promising biocontrol agent that is vital in maintaining plant health and disease prevention. In the current study, a computational approach utilizing structure prediction, molecular docking, molecular dynamics, and MM-PBSA analysis was used to analyze the potential role of bioactive compounds secreted by Trichoderma sp. in inhibiting the pectin lyase enzyme from Fusarium proliferatum, F. fujikuroi, F. graminearum, F. oxysporum and F. verticillioides. Molecular docking with secondary metabolites revealed that Viridiofungin A secreted by Trichoderma harzianum and Virone secreted by T. virens are bioactive compounds with immense potential to inhibit PNLs of Fusarium species. Further, the rigidity of the structure and stability of the docked complex were confirmed via Molecular dynamic simulations assessed through multiple parameters from the simulation trajectory data. Dual culture assay of T. harzianum and T. virens with F. proliferatum, F. fujikuroi, F. graminearum, F. oxysporum, and F. verticillioides showed variable mycelial inhibition. The research provides insight into the potential of the bioactive compounds secreted by Trichoderma species as an effective agent for the inhibition of pectin lyases produced by phytopathogens, especially Fusarium species. The proposed research can be used to develop bioformulations that function as biopesticides, offering a sustainable replacement for chemical products.

Identification of Novel Drug Molecules Against NS3-Like Helicase Enzyme of Alongshan Virus

Alongshan virus (ALSV) is a novel tick-borne virus associated with human diseases. The ALSV is a segmented flavivirus from the family Flaviviridae. It is currently considered as tick-borne arbovirus. There is a high incidence of fever and headache among patients with ALSV infection, and some patients also present with fatigue, coma, depression, nausea, myalgia/arthralgia, and skin rashes. Neither a licensed vaccine nor a drug is currently available to treat ALSV. The development of new, practical, and innovative therapeutic approaches is needed to overcome the emergence of the pathogen. Research on drugs remains a complex, time-consuming, and expensive. The field of drug development has undergone a revolution due to the use of computational approaches, which provide several benefits that speed up and improve the process of developing novel drugs. The goal of this study is to identify novel drug-like molecules against NS3-like helicase enzyme of Alongshan virus. Using molecular docking, the binding potential of the top three ligands to the specified target was determined. Molecular dynamic simulations were used to identify the stabilities of the best-docked conformations followed by energy calculations and ADMET analysis. Three potential and promising compounds were identified by performing structure-based virtual screening of non-structural protein 3 (NS3) like helicase of Alongshan virus. The best-docked complexes identified through virtual screening were BDC-23169381, BDB-26412846, BDB-2641954. All these compounds had good pharmacokinetics characteristics and were identified as drug like.

Neurotoxic and developmental effects of scented incense stick smoke: Network toxicology and zebrafish model study

Burning incense sticks is a traditional practice in many cultures, especially in Southeast Asia. While it is often regarded as sacred and beneficial, modern incense sticks contain various chemicals that can pose health risks. A GCMS analysis of the ICS revealed potential compounds. Network toxicology revealed that ICS contains compounds violating Lipinski's rule of five, leading to potential neurotoxic effects. Key pathways affected include neuroactive ligand-receptor interaction and calcium signaling, associated with neurodegenerative diseases like Parkinson's and Alzheimer's. Significant genes involved are STAT3, BCL2, and MTOR, emphasizing the chemical hazards of ICS exposure. We investigated the toxicity of ICS using zebrafish (Danio rerio) embryos as a mode. ICS exposure resulted in a dose-dependent increase in toxicity. High concentrations (7 and 14 µg/ml) led to immediate mortality, while lower concentrations (0.1, 0.3, 0.5, and 1 µg/ml) caused developmental defects such as yolk sac edema, skeletal malformations, and pericardial edema. Mortality rates increased with higher concentrations, confirming dose-dependent ICS exposure caused hypoactive locomotion, with reduced distance traveled and velocity toxicity. Higher concentrations of ICS led to increased ROS levels and cellular damage, as evidenced by enhanced staining levels. A dose-dependent increase in lipid peroxidation (DPPP assay) and lipid accumulation (Nile red assay) was observed. Higher ICS concentrations led to significant oxidative damage to lipids and increased lipid deposition. Enzymatic assays showed that ICS exposure significantly decreased the activities of antioxidant enzymes SOD and CAT, indicating impaired antioxidant defense, while increasing LDH activity, signaling tissue damage and cytotoxicity. Gene expression analysis revealed downregulation of SOD1 and CAT genes, upregulation of inflammatory genes TNF-α and IL-1β, and increased expression of the apoptotic gene p53 with decreased expression of Bcl-2 and BDNF. These findings highlight ICS's potential to cause oxidative stress, inflammation, apoptosis, and neurodevelopmental impairments.

Rapid discovery of Transglutaminase 2 inhibitors for celiac disease with boosting ensemble machine learning

Celiac disease poses a significant health challenge for individuals consuming gluten-containing foods. While the availability of gluten-free products has increased, there is still a need for therapeutic treatments. The advancement of computational drug design, particularly using bio-cheminformatics-oriented machine learning, offers promising avenues for developing such therapies. One promising target is Transglutaminase 2 (TG2), a protein involved in the autoimmune response triggered by gluten consumption. In this study, we utilized data from approximately 1100 TG2 inhibition assays to develop ligand-based molecular screening techniques using ensemble machine-learning models and extensive molecular feature libraries. Various classifiers, including tree-based methods, artificial neural networks, and graph neural networks, were evaluated to identify primary systems for predictive analysis and feature significance assessment. Boosting ensembles of perceptron deep learning and low-depth random forest weak learners emerged as the most effective, achieving over 90 % accuracy, significantly outperforming a baseline of 64 %. Key features, such as the presence of a terminal Michael acceptor group and a sulfonamide group, were identified as important for activity. Additionally, a regression model was created to rank active compounds. We developed a web application, Celiac Informatics (https://celiac-informatics-v1-2b0a85e75868.herokuapp.com), to facilitate the screening of potential therapeutic molecules for celiac disease. The web app also provides drug-likeness reports, supporting the development of novel drugs.

Discovery of novel pyrrolo[2,3-d]pyrimidine derivatives as anticancer agents: virtual screening and molecular dynamic studies

CDK/Cyclins are dysregulated in several human cancers. Recent studies showed inhibition of CDK4/6 was responsible for controlling cell cycle progression and cancer cell growth. In the present study, atom-based and field-based 3D-QSAR, virtual screening, molecular docking and molecular dynamics studies were done for the development of novel pyrrolo[2,3-d]pyrimidine (P2P) derivatives as anticancer agents. The developed models showed good Q2 and r2 values for atom-based 3D-QSAR, which were equal to 0.7327 and 0.8939, whereas for field-based 3D-QSAR the values were 0.8552 and 0.6255, respectively. Molecular docking study showed good-binding interactions with amino acid residues such as VAL-101, HIE-100, ASP-104, ILE-19, LYS-147 and GLU-99, important for CDK4/6 inhibitory activity by using PDB ID: 5L2S. Pharmacophore hypothesis (HHHRR_1) was used in the screening of ZINC database. The top scored ZINC compound ZINC91325512 showed binding interactions with amino acid residues VAL-101, ILE-19, and LYS-147. Enumeration study revealed that the screened compound R1 showed binding interactions with VAL 101 and GLN 149 residues. Furthermore, the Molecular dynamic study showed compound R1, ZINC91325512 and ZINC04000264 having RMSD values of 1.649, 1.733 and 1.610 Å, respectively. These ZINC and enumerated compounds may be used for the development of novel pyrrolo[2,3-d]pyrimidine derivatives as anticancer agent.

Phytoconstituents of Citrus limon (Lemon) as Potential Inhibitors Against Multi Targets of SARS-CoV-2 by Use of Molecular Modelling and In Vitro Determination Approaches

In the present work, phytoconstituents from Citrus limon are computationally tested against SARS-CoV-2 target protein such as Mpro - (5R82.pdb), Spike - (6YZ5.pdb) &RdRp - (7BTF.pdb) for COVID-19. Docking was done by glide model, QikProp was performed by in silico ADMET screening & Prime MM-GB/SA modules were used to define binding energy. When compared with approved COVID-19 drugs such as Remdesivir, Ritonavir, Lopinavir, and Hydroxychloroquine, plant-based constituents such as Quercetin, Rutoside, Naringin, Eriocitrin, and Hesperidin. bind with significant G-scores to the active SARS-CoV-2 place. The constituents Rutoside and Eriocitrin were studied in each MD simulation in 100 ns against 3 proteins 5R82.pdb, 6YZ5.pdb and 7BTF.pdb.We performed an assay with significant natural compounds from contacts and in silico results (Rutin, Eriocitrin, Naringin, Hesperidin) using 3CL protease assay kit (B.11529 Omicron variant). This kit contained 3CL inhibitor GC376 as Control. The IC50 value of the test compound was found to be Rutin -17.50 μM, Eriocitrin-37.91 μM, Naringin-39.58 μM, Hesperidine-140.20 μM, the standard inhibitory concentration of GC376 was 38.64 μM. The phytoconstituents showed important interactions with SARS-CoV-2 targets, and potential modifications could be beneficial for future development.

Unveiling promising phytocompounds from Moringa oleifera as dual inhibitors of EGFR(T790M/C797S) and VEGFR-2 in non-small cell lung cancer through in silico screening, ADMET, dynamics simulation, and DFT analysis

Non-small cell lung cancer (NSCLC) is among the main causes of mortality from cancer around the globe, affecting all genders. Current treatments mainly focus on tyrosine kinase inhibitors (TKIs) targeting the epidermal growth factor receptor (EGFR). However, resistance mechanisms, such as the emergence of T790M and C797S EGFR mutations and upregulation of VEGFR-2, often hinder the effectiveness of TKIs. Thereby, EGFR and VEGFR-2 present an intriguing opportunity for the treatment of NSCLC by developing dual-acting drugs. This research aims to evaluate prospective Moringa oleifera L. (MO)-originated compounds to efficiently block both of these receptors. In our research, we screened a library of 200 compounds sourced from MO, a plant known for its remarkable therapeutic potential. We identified five intriguing phytocompounds: hesperetin, gossypetin, quercetin, gallocatechin, and epigallocatechin, as potential anti-cancer agents. The compounds have demonstrated notable binding affinity in virtual screening and multi-stage molecular docking analysis, surpassing the controls, Erlotinib and Bevacizumab + Rituximab. In addition, these compounds demonstrate top-notch drug-likeness and ADMET properties. The five promising drug candidates also had a strong ability to bind to receptors and stayed stable with them during the 200 ns molecular dynamics (MD) simulation and MM-GBSA calculation. Furthermore, DFT analysis indicates that hesperetin, gossypetin, and quercetagetin stand out as the most promising drug candidates among all others. The findings of our study suggest that these three therapeutic candidates can precisely target both EGFR and VEGFR-2 and can potentially act on both of these pathways as a single agent.

Virtual screening of FOXO3a activators from natural product-like compound library

FOXO3a is an inevitable transcription factor, which is involved in the regulation of biological processes such as proliferation, DNA damage repair, cell cycle arrest and cell death. Previous studies confirmed that FOXO3a is an excellent tumor suppressor and in cancer cells, it gets phosphorylated followed by proteasomal degradation. FOXO3a is found to be inactivated in cancer cells, whereas in normal cells it gets activated and upregulates its downstream targets, which induces apoptotic pathways. Hence, activation of FOXO3a can be implicated in cancer prevention and treatment. A variety of commercially available FOXO3a activators such as doxorubicin and metformin possess undesirable adverse effects to normal cells and tissues, which are their major limitations. Natural bioactive compounds, eliminating the limitations of such compounds, become an excellent choice for the treatment and prevention of cancer. In this study, a library of natural product-like compounds was screened for their FOXO3a activation potential through in silico approach, which included the use of several bioinformatics tools and processes. Other molecular interaction studies as well as binding and specificity studies were carried out with the help of molecular dynamics simulation. Virtual screening of 7700 small molecules from the Natural Products-like Compound Library revealed the top three FOXO3a activators F3385-6269, F2183-0033 and F3351-0330. Further validation studies are warranted to confirm these findings.

Repurposing FDA-approved drugs as NLRP3 inhibitors against inflammatory diseases: machine learning and molecular simulation approaches

Activation of NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) has been associated with multiple chronic pathologies, including diabetes, atherosclerosis, and rheumatoid arthritis. Moreover, histone deacetylases (HDACs), specifically HDAC6 is required for the NLRP3 inflammasome to assemble and activate. Thus, NLRP3 serves as an attractive target for the development of novel therapeutic approaches. Several companies are now attempting to develop specific modulators of the NLRP3 inflammasome, but only a handful of small molecules of NLRP3 inflammasome inhibitors, such as MCC950 and Tranilast, are currently available for clinical use. However, their use is limited due to severe side effects and short half-lives. Thus, the repurposing of FDA-approved drugs with NLRP3 inhibitory activity is needed. The present study was aimed at repurposing preexisting drugs that might act as safe and effective NLRP3 inhibitors. A library of 2,697 FDA-approved drugs was screened for binding with NLRP3 (PDB: 7ALV) using Glide (Schrödinger). The top seven FDA-approved drugs with potential binding affinities were selected based on docking scores and subjected to ADMET profiling using pkCSM and SwissADME. The binding of the ADMET-favorable FDA-approved drugs to NLRP3 was validated using MMGBSA (Prime) and Molecular Dynamics (Desmond) in the Schrödinger suite. ADMET profiling revealed that of the seven best docking drugs, empagliflozin and citicoline had good drug-likeness properties. Moreover, MMGBSA analysis and molecular dynamics demonstrated that empagliflozin and citicoline exhibited stable ligand-NLRP3 interactions in the presence of solvents. This study sheds light on the ability of various FDA-approved drugs to act as NLRP3 inhibitors.Communicated by Ramaswamy H. Sarma.

In silico study of inhibition activity of boceprevir drug against 2019-nCoV main protease

Boceprevir drug is a ketoamide serine protease inhibitor with a linear peptidomimetic structure that exhibits inhibition activity against 2019-nCoV main protease. This paper reports electronic properties of boceprevir and its molecular docking as well as molecular dynamics simulation analysis with protein receptor. For this, the equilibrium structure of boceprevir has been obtained by DFT at B3LYP and ωB97XD levels with 6-311+G(d,p) basis set in gas and water mediums. HOMO-LUMO and absorption spectrum analysis have been used to evaluate the boceprevir's toxicity and photosensitivity, respectively. Molecular docking simulation has been performed to test the binding affinity of boceprevir with 2019-nCoV MPRO; which rendered a variety of desirable binding locations between the ligand and target protein's residue positions. The optimum binding location has been considered for molecular dynamics simulation. The findings have been addressed to clarify the boceprevir drug efficacy against the 2019-nCoV MPRO.

In silico study of polyphenols as potential inhibitors of MALT1 protein in non-Hodgkin lymphoma

Non-Hodgkin lymphoma (NHL) is one of the most common cancer types. Deregulated signaling pathways can trigger certain NHL subtypes, including Diffuse Large B-cell lymphoma. NF-ĸB signaling pathway, which is responsible for the proliferation, growth, and survival of cells, has an essential role in lymphoma development. Although different signals control NF-ĸB activation in various lymphoid malignancies, the characteristic one is the CARD11-BCL10-MALT1 (CBM) complex. The CBM complex is responsible for the initiation of adaptive immune response. Our study is focused on the molecular docking of ten polyphenols as potential CARD11-BCL10-MALT1 complex inhibitors, essentially through MALT1 inhibition. Molecular docking was performed by Auto Dock Tools and AutoDock Vina tool, while SwissADME was used for drug-likeness and absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis of the ligands. Out of 66 ligands that were used in this study, we selected and visualized five. Selection criteria were based on the binding energy score and position of the ligands on the used protein. 2D and 3D visualizations showed interactions of ligands with the protein. Five ligands are considered potential inhibitors of MALT1, thus affecting NF-ĸB signaling pathway. However, additional in vivo and in vitro studies are required to confirm their mechanism of inhibition.

Evaluation of Myocilin Variant Protein Structures Modeled by AlphaFold2

Deep neural network-based programs can be applied to protein structure modeling by inputting amino acid sequences. Here, we aimed to evaluate the AlphaFold2-modeled myocilin wild-type and variant protein structures and compare to the experimentally determined protein structures. Molecular dynamic and ligand binding properties of the experimentally determined and AlphaFold2-modeled protein structures were also analyzed. AlphaFold2-modeled myocilin variant protein structures showed high similarities in overall structure to the experimentally determined mutant protein structures, but the orientations and geometries of amino acid side chains were slightly different. The olfactomedin-like domain of the modeled missense variant protein structures showed fewer folding changes than the nonsense variant when compared to the predicted wild-type protein structure. Differences were also observed in molecular dynamics and ligand binding sites between the AlphaFold2-modeled and experimentally determined structures as well as between the wild-type and variant structures. In summary, the folding of the AlphaFold2-modeled MYOC variant protein structures could be similar to that determined by the experiments but with differences in amino acid side chain orientations and geometries. Careful comparisons with experimentally determined structures are needed before the applications of the in silico modeled variant protein structures.

Artificial Intelligence-based database for prediction of protein structure and their alterations in ocular diseases

The aim of the study is to establish an online database for predicting protein structures altered in ocular diseases by Alphafold2 and RoseTTAFold algorithms. Totally, 726 genes of multiple ocular diseases were collected for protein structure prediction. Both Alphafold2 and RoseTTAFold algorithms were built locally using the open-source codebases. A dataset with 48 protein structures from Protein Data Bank (PDB) was adopted for algorithm set-up validation. A website was built to match ocular genes with the corresponding predicted tertiary protein structures for each amino acid sequence. The predicted local distance difference test-Cα (pLDDT) and template modeling (TM) scores of the validation protein structure and the selected ocular genes were evaluated. Molecular dynamics and molecular docking simulations were performed to demonstrate the applications of the predicted structures. For the validation dataset, 70.8% of the predicted protein structures showed pLDDT greater than 90. Compared to the PDB structures, 100% of the AlphaFold2-predicted structures and 97.9% of the RoseTTAFold-predicted structure showed TM score greater than 0.5. Totally, 1329 amino acid sequences of 430 ocular disease-related genes have been predicted, of which 75.9% showed pLDDT greater than 70 for the wildtype sequences and 76.1% for the variant sequences. Small molecule docking and molecular dynamics simulations revealed that the predicted protein structures with higher confidence scores showed similar molecular characteristics with the structures from PDB. We have developed an ocular protein structure database (EyeProdb) for ocular disease, which is released for the public and will facilitate the biological investigations and structure-based drug development for ocular diseases. Database URL:  http://eyeprodb.jsiec.org.

Synthesis of novel 5-[3-(4-chlorophenyl)-substituted-1,3-dimethylpyrimidine-2,4,6(1H,3H,5H)-trione derivatives as potential anti-diabetic and anticancer agents

In this work, we developed a series of novel 5-[3-(4-chlorophenyl)-substituted-1,3-dimethylpyrimidine-2,4,6(1H,3H,5H)-trione derivatives 4(a-e) via a one-pot multicomponent reaction. The structures of the compounds were confirmed using analytical and spectroscopic techniques. Also, the synthesized compounds were screened for their anti-diabetic activity, cytotoxicity and in silico studies. The activity results suggested that the compound 4e exhibited least IC50 values of 0.055 ± 0.002 µM, 0.050 ± 0.002 µM and 0.009 ± 0.001 µM for α-amylase, α-glucosidase and cytotoxicity respectively. Further, in silico molecular docking results revealed that all the obtained compounds effectively interacted with exo-β-D-glucosaminidase and P38 MAP kinase proteins with good binding energies. In that, 4e compound established the least binding energy of -9.6 and -9.1 kcal/mol, respectively. Moreover, our synthesized compounds were subjected to ADME studies, which suggested that all the synthesized compounds obeyed all five rules with good bioavailability and were suitable as drug leads against anti-diabetic and anticancer treatment.

Revolutionizing anti-cancer drug discovery against breast cancer and lung cancer by modification of natural genistein: an advanced computational and drug design approach

Breast and lung cancer are two of the most lethal forms of cancer, responsible for a disproportionately high number of deaths worldwide. Both doctors and cancer patients express alarm about the rising incidence of the disease globally. Although targeted treatment has achieved enormous advancements, it is not without its drawbacks. Numerous medicines and chemotherapeutic drugs have been authorized by the FDA; nevertheless, they can be quite costly and often fall short of completely curing the condition. Therefore, this investigation has been conducted to identify a potential medication against breast and lung cancer through structural modification of genistein. Genistein is the active compound in Glycyrrhiza glabra (licorice), and it exhibits solid anticancer efficiency against various cancers, including breast cancer, lung cancer, and brain cancer. Hence, the design of its analogs with the interchange of five functional groups-COOH, NH2 and OCH3, Benzene, and NH-CH2-CH2-OH-have been employed to enhance affinities compared to primary genistein. Additionally, advanced computational studies such as PASS prediction, molecular docking, ADMET, and molecular dynamics simulation were conducted. Firstly, the PASS prediction spectrum was analyzed, revealing that the designed genistein analogs exhibit improved antineoplastic activity. In the prediction data, breast and lung cancer were selected as primary targets. Subsequently, other computational investigations were gradually conducted. The mentioned compounds have shown acceptable results for in silico ADME, AMES toxicity, and hepatotoxicity estimations, which are fundamental for their oral medication. It is noteworthy that the initial binding affinity was only -8.7 kcal/mol against the breast cancer targeted protein (PDB ID: 3HB5). However, after the modification of the functional group, when calculating the binding affinities, it becomes apparent that the binding affinities increase gradually, reaching a maximum of -11.0 and -10.0 kcal/mol. Similarly, the initial binding affinity was only -8.0 kcal/mol against lung cancer (PDB ID: 2P85), but after the addition of binding affinity, it reached -9.5 kcal/mol. Finally, a molecular dynamics simulation was conducted to study the molecular models over 100 ns and examine the stability of the docked complexes. The results indicate that the selected complexes remain highly stable throughout the 100-ns molecular dynamics simulation runs, displaying strong correlations with the binding of targeted ligands within the active site of the selected protein. It is important to further investigate and proceed to clinical or wet lab experiments to determine the practical value of the proposed compounds.

Virtual screening of natural products inspired in-house library to discover potential lead molecules against the SARS-CoV-2 main protease

SARS-CoV-2, a new coronavirus emerged in 2019, causing a global healthcare epidemic. Although a variety of drug targets have been identified as potential antiviral therapies, and effective candidate against SARS-CoV-2 remains elusive. One of the most promising targets for combating COVID-19 is SARS-CoV-2 Main protease (M^pro, a protein responsible for viral replication. In this work, an in-house curated library was thoroughly evaluated for druggability against M^pro. We identified four ligands (FG, Q5, P5, and PJ4) as potential inhibitors based on docking scores, predicted binding energies (MMGBSA), in silico ADME, and RMSD trajectory analysis. Among the selected ligands, FG, a natural product from Andrographis nallamalayana, exhibited the highest binding energy of -10.31 kcal/mol close to the docking score of clinical candidates Boceprevir and GC376. Other ligands (P5, natural product from cardiospermum halicacabum and two synthetic molecules Q5 and PJ4) have shown comparable docking scores ranging -7.65 kcal/mol to -7.18 kcal/mol. Interestingly, we found all four top ligands had Pi bond interaction with the main amino acid residues HIS41 and CYS145 (catalytic dyad), H-bonding interactions with GLU166, ARG188, and GLN189, and hydrophobic interactions with MET49 and MET165 in the binding site of M^pro. According to the ADME analysis, Q5 and P5 are within the acceptable range of drug likeliness, compared to FG and PJ4. The interaction stability of the lead molecules with viral protease was verified using replicated MD simulations. Thus, the present study opens up the opportunity of developing drug candidates targeting SARS-CoV-2 main protease (M^pro) to mitigate the disease.Communicated by Ramaswamy H. Sarma.

High-Throughput Screening for the Potential Inhibitors of SARS-CoV-2 with Essential Dynamic Behavior

Global health security has been challenged by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Due to the lengthy process of generating vaccinations, it is vital to reposition currently available drugs in order to relieve anti-epidemic tensions and accelerate the development of therapies for Coronavirus Disease 2019 (COVID-19), the public threat caused by SARS-CoV-2. High throughput screening techniques have established their roles in the evaluation of already available medications and the search for novel potential agents with desirable chemical space and more cost-effectiveness. Here, we present the architectural aspects of highthroughput screening for SARS-CoV-2 inhibitors, especially three generations of virtual screening methodologies with structural dynamics: ligand-based screening, receptor-based screening, and machine learning (ML)-based scoring functions (SFs). By outlining the benefits and drawbacks, we hope that researchers will be motivated to adopt these methods in the development of novel anti- SARS-CoV-2 agents.

Evolving ribonucleocapsid assembly/packaging signals in the genomes of the human and animal coronaviruses: targeting, transmission and evolution

A world-wide COVID-19 pandemic intensified strongly the studies of molecular mechanisms related to the coronaviruses. The origin of coronaviruses and the risks of human-to-human, animal-to-human and human-to-animal transmission of coronaviral infections can be understood only on a broader evolutionary level by detailed comparative studies. In this paper, we studied ribonucleocapsid assembly-packaging signals (RNAPS) in the genomes of all seven known pathogenic human coronaviruses, SARS-CoV, SARS-CoV-2, MERS-CoV, HCoV-OC43, HCoV-HKU1, HCoV-229E and HCoV-NL63 and compared them with RNAPS in the genomes of the related animal coronaviruses including SARS-Bat-CoV, MERS-Camel-CoV, MHV, Bat-CoV MOP1, TGEV and one of camel alphacoronaviruses. RNAPS in the genomes of coronaviruses were evolved due to weakly specific interactions between genomic RNA and N proteins in helical nucleocapsids. Combining transitional genome mapping and Jaccard correlation coefficients allows us to perform the analysis directly in terms of underlying motifs distributed over the genome. In all coronaviruses, RNAPS were distributed quasi-periodically over the genome with the period about 54 nt biased to 57 nt and to 51 nt for the genomes longer and shorter than that of SARS-CoV, respectively. The comparison with the experimentally verified packaging signals for MERS-CoV, MHV and TGEV proved that the distribution of particular motifs is strongly correlated with the packaging signals. We also found that many motifs were highly conserved in both characters and positioning on the genomes throughout the lineages that make them promising therapeutic targets. The mechanisms of encapsidation can affect the recombination and co-infection as well.Communicated by Ramaswamy H. Sarma.

S, Joy MN. Substituted benzocoumarin derivatives: synthesis, characterization, biological activities and molecular docking with ADME studies

Herein, an efficient and convenient method for the synthesis of 4-(substitutedphenyl)-1,2-dihydro-2-oxo-6-(2-oxo-2H-benzo[g]chromen-3-yl)pyridine-3-carbonitrile derivatives have been reported using ammonium acetate as catalyst. The structures of synthesized compounds were confirmed using FT-IR, 1H, 13C-NMR and LC-MS spectroscopic techniques. The synthesized compounds have been evaluated for antibacterial activity against bacterial strains by agar diffusion method at different concentrations. Further, all the targeted compounds were screened for anti-oxidant and anti-cancer studies by DPPH and MTT assay methods at different concentrations. Compound 4b displayed good antioxidant and anticancer (against MCF-7 cell line) activity. Further, the binding capability for the synthesized compounds (4a–j) was analyzed by molecular docking studies using human peroxiredoxin 5 (PDB ID: 1HD2) and P38 MAP kinase (PDB ID: 1OUK) protein. Further, the physicochemical properties were analysed from ADME studies respectively.

Virtual screening and molecular dynamics simulation for identification of natural antiviral agents targeting SARS-CoV-2 NSP10

New variations of SARS-CoV-2 continue to emerge in the global pandemic, which may be resistant to at least some vaccines in COVID-19, indicating that drug and vaccine development must be continuously strengthened. NSP10 plays an essential role in SARS-CoV-2 viral life cycle. It stimulates the enzymatic activities of NSP14-ExoN and NSP16-O-MTase by the formation of NSP10/NSP14 and NSP10/NSP16 complexes. Inhibiting NSP10 can block the binding of NSP10 to NSP14 and NSP16. This study has identified potential natural NSP10 inhibitors from ZINC database. The protein druggable pocket was identified for screening candidates. Molecular docking of the selected compounds was performed and MM-GBSA binding energy was calculated. After ADMET assessment, 4 hits were obtained for favorable druggability. The analysis of site interactions suggested that the hits all had excellent binding. Molecular dynamics studies revealed that selected natural compounds stably bind to NSP10. These compounds were identified as potential leads against NSP10 for the development of strategies to combat SARS-CoV-2 replication and could serve as the basis for further studies.

Potential of Natural Alkaloids From Jadwar (Delphinium denudatum) as Inhibitors Against Main Protease of COVID-19: A Molecular Modeling Approach

The ongoing pandemic coronavirus disease (COVID-19) caused by a novel corona virus, namely, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has had a major impact on global public health. COVID-19 cases continue to increase across the globe with high mortality rates in immunocompromised patients. There is still a pressing demand for drug discovery and vaccine development against this highly contagious disease. To design and develop antiviral drugs against COVID-19, the main protease (M^pro) has emerged as one of the important drug targets. In this context, the present work explored Jadwar (Delphinium denudatum)-derived natural alkaloids as potential inhibitors against M^pro of SARS-CoV-2 by employing a combination of molecular docking and molecular dynamic simulation-based methods. Molecular docking and interaction profile analysis revealed strong binding on the M^pro functional domain with four natural alkaloids viz. panicutine (-7.4 kcal/mol), vilmorrianone (-7.0 kcal/mol), denudatine (-6.0 kcal/mol), and condelphine (-5.9 kcal/mol). The molecular docking results evaluated by using the MD simulations on 200 nanoseconds confirmed highly stable interactions of these compounds with the M^pro. Additionally, mechanics/generalized Born/Poisson-Boltzmann surface area (MM/G/P/BSA) free energy calculations also affirmed the docking results. Natural alkaloids explored in the present study possess the essential drug-likeness properties, namely, absorption, distribution, metabolism, and excretion (ADME), and are in accordance with Lipinski's rule of five. The results of this study suggest that these four bioactive molecules, namely, condelphine, denudatine, panicutine, and vilmorrianone, might be effective candidates against COVID-19 and can be further investigated using a number of experimental methods.

In search of HIV entry inhibitors using molecular docking, ADME and toxicity studies of some Thiazolidinone-Pyrazine derivatives against CXCR4 co-receptor

BACKGROUND

Entry inhibitors prevent binding of human immunodeficiency virus protein to the chemokine receptor CXCR4 and are used along with conventional anti-HIV therapy. They aid in restoring immunity and can prevent the development of HIV-TB co-infection.

AIM

In the present study various thiazolidinone-pyrazine derivatives earlier studied for NNRT inhibition activity were gauged for their entry inhibitor potential.

OBJECTIVE

Objective of the study is to perform molecular docking, ADME, toxicity studies of some Thiazolidinone-Pyrazine Derivatives as entry inhibitors targeting CXCR4 co-receptors.

METHODS

In-silico docking studies were performed using AutoDock Vina software and compounds were further studied for ADME and toxicity using SwissADME and pkCSM software respectively.

RESULTS

Taking into consideration the docking results, pharmacokinetic behaviour and toxicity profile four molecules (compound 1, 9, 11 and 16) have shown potential as entry inhibitors.

CONCLUSION

These compounds have shown potential as both NNRTI and entry inhibitors and hence can be used in management of immune compromised diseases like TB-HIV coinfection.

Ribonucleocapsid assembly/packaging signals in the genomes of the coronaviruses SARS-CoV and SARS-CoV-2: detection, comparison and implications for therapeutic targeting

The genomic ssRNA of coronaviruses is packaged within a helical nucleocapsid. Due to transitional symmetry of a helix, weakly specific cooperative interaction between ssRNA and nucleocapsid proteins leads to the natural selection of specific quasi-periodic assembly/packaging signals in the related genomic sequence. Such signals coordinated with the nucleocapsid helical structure were detected and reconstructed in the genomes of the coronaviruses SARS-CoV and SARS-CoV-2. The main period of the signals for both viruses was about 54 nt, that implies 6.75 nt per N protein. The complete coverage of the ssRNA genome of length about 30,000 nt by the nucleocapsid would need 4.4 × 103 N proteins, that makes them the most abundant among the structural proteins. The repertoires of motifs for SARS-CoV and SARS-CoV-2 were divergent but nearly coincided for different isolates of SARS-CoV-2. We obtained the distributions of assembly/packaging signals over the genomes with nonoverlapping windows of width 432 nt. Finally, using the spectral entropy, we compared the load from point mutations and indels during virus age for SARS-CoV and SARS-CoV-2. We found the higher mutational load on SARS-CoV. In this sense, SARS-CoV-2 can be treated as a 'newborn' virus. These observations may be helpful in practical medical applications and are of basic interest. Communicated by Ramaswamy H. Sarma.

Synthesis, crystal structure, computational study and anti-virus effect of mixed ligand copper (II) complex with ONS donor Schiff base and 1, 10-phenanthroline

This work deals with the synthesis, crystal structure, computational study and antiviral potential of mixed ligand copper(II) complex [Cu(L)(phen)](1), (where, H₂L = (Z)-N'-((E)-2-hydroxy-3,5-diiodobenzylidene)-N,N-dimethylcarbamohydrazonothioic acid, phen = 1,10-phenanthroline). The Schiff base ligand (H₂L) is coordinated with Cu(II) ion in O, N, S-tridentate mode. The copper complex (1) crystallized in the monoclinic system of the space group P21/c with eight molecules in the unit cell and reveals a square pyramidal geometry. Furthermore, we also perform quantum chemical calculations to get insights into the structure-property relationship and functional properties of ligand (H₂L) and its copper (II) complex [Cu(L)(phen)](1). Complex [Cu(L)(phen)](1) was also virtually designed in-silico evaluation by Swiss-ADME. Additionally, inspiring by recent developments to find a potential inhibitor for the COVID-19 virus, we have also performed molecular docking study of ligand and its copper complex (1) to see if our compounds shows an affinity for the main protease (M^pro) of COVID-19 spike protein (PDB ID: 7C8U). Interestingly, the results are found quite encouraging where the binding affinity and inhibition constant were found to be -7.14 kcal/mol and 5.82 μM for ligand (H₂L) and -6.18 kcal/mol and 0.76 μM for complex [Cu(L)(phen)](1) with M^pro protein. This binding affinity is reasonably well as compared to recently known antiviral drugs. For instance, the binding affinity of ligand and complex was found to be better than docking results of chloroquine (-6.293 kcal/mol), hydroxychloroquine (-5.573 kcal/mol) and remdesivir (-6.352 kcal/mol) with M^pro protein. The present study may offer the technological solutions and potential inhibition to the COVID-19 virus in the ongoing and future challenges of the global community. In the framework of synthesis and characterization of mixed ligand copper (II) complex; the major conclusions can be drawn as follow.

Insights into COVID-19 Vaccine Development Based on Immunogenic Structural Proteins of SARS-CoV-2, Host Immune Responses, and Herd Immunity

The first quarter of the 21st century has remarkably been characterized by a multitude of challenges confronting human society as a whole in terms of several outbreaks of infectious viral diseases, such as the 2003 severe acute respiratory syndrome (SARS), China; the 2009 influenza H1N1, Mexico; the 2012 Middle East respiratory syndrome (MERS), Saudi Arabia; and the ongoing coronavirus disease 19 (COVID-19), China. COVID-19, caused by SARS-CoV-2, reportedly broke out in December 2019, Wuhan, the capital of China’s Hubei province, and continues unabated, leading to considerable devastation and death worldwide. The most common target organ of SARS-CoV-2 is the lungs, especially the bronchial and alveolar epithelial cells, culminating in acute respiratory distress syndrome (ARDS) in severe patients. Nevertheless, other tissues and organs are also known to be critically affected following infection, thereby complicating the overall aetiology and prognosis. Excluding H1N1, the SARS-CoV (also referred as SARS-CoV-1), MERS, and SARS-CoV-2 are collectively referred to as coronaviruses, and taxonomically placed under the realm Riboviria, order Nidovirales, suborder Cornidovirineae, family Coronaviridae, subfamily Orthocoronavirinae, genus Betacoronavirus, and subgenus Sarbecovirus. As of 23 September 2021, the ongoing SARS-CoV-2 pandemic has globally resulted in around 229 million and 4.7 million reported infections and deaths, respectively, apart from causing huge psychosomatic debilitation, academic loss, and deep economic recession. Such an unprecedented pandemic has compelled researchers, especially epidemiologists and immunologists, to search for SARS-CoV-2-associated potential immunogenic molecules to develop a vaccine as an immediate prophylactic measure. Amongst multiple structural and non-structural proteins, the homotrimeric spike (S) glycoprotein has been empirically found as the most suitable candidate for vaccine development owing to its immense immunogenic potential, which makes it capable of eliciting both humoral and cell-mediated immune responses. As a consequence, it has become possible to design appropriate, safe, and effective vaccines, apart from related therapeutic agents, to reduce both morbidity and mortality. As of 23 September 2021, four vaccines, namely, Comirnaty, COVID-19 vaccine Janssen, Spikevax, and Vaxzevria, have received the European Medicines Agency’s (EMA) approval, and around thirty are under the phase three clinical trial with emergency authorization by the vaccine-developing country-specific National Regulatory Authority (NRA). In addition, 100–150 vaccines are under various phases of pre-clinical and clinical trials. The mainstay of global vaccination is to introduce herd immunity, which would protect the majority of the population, including immunocompromised individuals, from infection and disease. Here, we primarily discuss category-wise vaccine development, their respective advantages and disadvantages, associated efficiency and potential safety aspects, antigenicity of SARS-CoV-2 structural proteins and immune responses to them along with the emergence of SARS-CoV-2 VOC, and the urgent need of achieving herd immunity to contain the pandemic.

Host Cell and SARS-CoV-2-Associated Molecular Structures and Factors as Potential Therapeutic Targets

Coronavirus disease 19 (COVID-19) is caused by an enveloped, positive-sense, single-stranded RNA virus, referred to as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which belongs to the realm Riboviria, order Nidovirales, family Coronaviridae, genus Betacoronavirus and the species Severe acute respiratory syndrome-related coronavirus. This viral disease is characterized by a myriad of varying symptoms, such as pyrexia, cough, hemoptysis, dyspnoea, diarrhea, muscle soreness, dysosmia, lymphopenia and dysgeusia amongst others. The virus mainly infects humans, various other mammals, avian species and some other companion livestock. SARS-CoV-2 cellular entry is primarily accomplished by molecular interaction between the virus’s spike (S) protein and the host cell surface receptor, angiotensin-converting enzyme 2 (ACE2), although other host cell-associated receptors/factors, such as neuropilin 1 (NRP-1) and neuropilin 2 (NRP-2), C-type lectin receptors (CLRs), as well as proteases such as TMPRSS2 (transmembrane serine protease 2) and furin, might also play a crucial role in infection, tropism, pathogenesis and clinical outcome. Furthermore, several structural and non-structural proteins of the virus themselves are very critical in determining the clinical outcome following infection. Considering such critical role(s) of the abovementioned host cell receptors, associated proteases/factors and virus structural/non-structural proteins (NSPs), it may be quite prudent to therapeutically target them through a multipronged clinical regimen to combat the disease.

Molecular docking, DFT analysis, and dynamics simulation of natural bioactive compounds targeting ACE2 and TMPRSS2 dual binding sites of spike protein of SARS CoV-2

The scientific community is continuously working to discover drug candidates against potential targets of SARS-CoV-2, but effective treatment has not been discovered yet. The virus enters the host cell through molecular interaction with its enzymatic receptors i.e., ACE2 and TMPRSS2, which, if, synergistically blocked can lead to the development of novel drug candidates. In this study, 1503 natural bioactive compounds were screened by HTVS, followed by SP and XP docking using Schrodinger Maestro software. Bio-0357 (protozide) and Bio-597 (chrysin) were selected for dynamics simulation based on synergistic binding affinity on S1 (docking score −9.642 and −8.78 kcal/mol) and S2 domains (-5.83 and −5.3 kcal/mol), and the RMSD, RMSF and Rg analyses showed stable interaction. The DFT analysis showed that the adsorption of protozide/chrysin, the band gap of protozide/chrysin-F/G reduced significantly. From SERS, results, it can be concluded that QDs nanocluster will act as a sensor for the detection of drugs. The docking study showed Bio-0357 and Bio-0597 bind to both S1 and S2 domains through stable molecular interactions, which can lead to the discovery of new drug candidates to prevent the entry of SARS-CoV-2. This in-silico study may be helpful to researchers for further in vitro experimental validation and development of new therapy for COVID-19.

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

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

Druggability of cavity pockets within SARS-CoV-2 spike glycoprotein and pharmacophore-based drug discovery

Aim: Virus spike glycoprotein of SARS-CoV-2 is a good target for drug discovery. Objective: To examine the potential for druggability of spike protein for pharmacophore-based drug discovery and to investigate the binding affinity of natural products with SARS-CoV-2 spike protein. Methods: Druggable cavities were searched though CavityPlus. A pharmacophore was built and used for hit identification. Autodock Vina was used to evaluate the hits' affinities. 10 chemical derivatives were also made from the chemical backbone to optimize the lead compound. Results: 10 druggable cavities were found within the glycoprotein spike. Only one cavity with the highest score at the binding site was selected for pharmacophore extraction. Hit identification resulted in the identification of 410 hits. Discussion: This study provides a druggable region within viral glycoprotein and a candidate compound to block viral entry.

Indian contribution toward biomedical research and development in COVID-19: A systematic review

COVID-19 pandemic led to an unprecedented collaborative effort among industry, academia, regulatory bodies, and governments with huge financial investments. Scientists and researchers from India also left no stone unturned to find therapeutic and preventive measures against COVID-19. Indian pharmaceutical companies are one of the leading manufacturers of vaccine in the world, are utilizing its capacity to its maximum, and are one among the forerunners in vaccine research against COVID-19 across the globe. In this systematic review, the information regarding contribution of Indian scientists toward COVID-19 research has been gathered from various news articles across Google platform apart from searching PubMed, WHO site, COVID-19 vaccine tracker, CTRI, clinicaltrials.gov, and websites of pharmaceutical companies. The article summarizes and highlights the various therapeutic and vaccine candidates, diagnostic kits, treatment agents, and technology being developed and tested by Indian researcher community against COVID-19.