In silico investigation and potential therapeutic approaches of natural products for COVID-19: Computer-aided drug design perspective

Repositioning of anti-infective compounds against monkeypox virus core cysteine proteinase: a molecular dynamics study

Monkeypox virus (MPXV) core cysteine proteinase (CCP) is one of the major drug targets used to examine the inhibitory action of chemical moieties. In this study, an in silico technique was applied to screen 1395 anti-infective compounds to find out the potential molecules against the MPXV-CCP. The top five hits were selected after screening and processed for exhaustive docking based on the docked score of ≤ -9.5 kcal/mol. Later, the top three hits based on the exhaustive-docking score and interaction profile were selected to perform MD simulations. The overall RMSD suggested that two compounds, SC75741 and ammonium glycyrrhizinate, showed a highly stable complex with a standard deviation of 0.18 and 0.23 nm, respectively. Later, the MM/GBSA binding free energies of complexes showed significant binding strength with ΔGTOTAL from -21.59 to -15 kcal/mol. This report reported the potential inhibitory activity of SC75741 and ammonium glycyrrhizinate against MPXV-CCP by competitively inhibiting the binding of the native substrate.

In silico Molecular Docking Approach to Identify Potential Antihypertensive Compounds from Ajuga integrifolia Buch.-Ham. Ex D. Don (Armagusa)

Background

Ajuga integrifolia (Armagusa) is used as a decoction to treat high blood pressure and diabetes, widely in Ethiopia. Specific compounds for anti-hypertension activity were not identified so far. This study aims to provide a scientific basis for the therapeutic use of A. integrifolia as an antihypertension agent.

Methods

In silico studies were used to evaluate the antihypertensive components of A. integrifolia. Flavonoids identified using HPLC analysis and iridoid glycosides isolated from A. integrifolia in this study and those isolated from synonyms (A. remota and A. bractosa) were considered in the molecular docking study. Interactions were studied by using Autodock vina (1.2) on PyRx 0.8 and visualizing in 2D and 3D using ligPlot+ and Discovery studio software. Activities like vasoprotection and druglikeness properties were predicted using online servers.

Results

Flavonoids such as quercetin, myricetin, and rutin were identified and quantified by HPLC analysis from different extracts of A. integrifolia. Reptoside and 8-O-acetylharpgide isolated from the aerial part of A. integrifolia. The binding energies of all 17 candidates considered in this study range from -10.2 kcal/mol to -7.5 kcal/mol and are lower than enalapril (reference drug: -5.9 kcal/mol). The binding energies, in most case, constitute hydrogen bonding. Biological activity predicted using PASS test also showed that the flavonoids have more probability of activity than the iridoid glycosides. Druglikeness properties of the candidate molecules showed that most follow the Lipinski rule of five with few violations.

Conclusion

Lower binding energies involving hydrogen bonding and predicted activities concerning hypertension confirm the traditional use of the aerial part of the medicinal plant concerned. Flavonoids: rutin, myricetin, quercetin, and kaempferol take the leading role in the antihypertensive activity of the aerial part of A. integrifolia. The iridoid glycosides studied are almost similar in their effect on their antihypertensive activity and still better than the reference drug.

Application of temperature-dependent and steered molecular dynamics simulation to screen anti-dengue compounds against Marburg virus

Marburg virus infections are extremely fatal with a fatality range of 23% to 90%, therefore there is an urgent requirement to design and develop efficient therapeutic molecules. Here, a comprehensive temperature-dependent molecular dynamics (MD) simulation method was implemented to identify the potential molecule from the anti-dengue compound library that can inhibit the function of the VP24 protein of Marburg. Virtual high throughput screening identified five effective binders of VP24 after screening 484 anti-dengue compounds. These compounds were treated in MD simulation at four different temperatures: 300, 340, 380, and 420 K. Higher temperatures showed dissociation of hit compounds from the protein. Further, triplicates of 100 ns MD simulation were conducted which showed that compounds ID = 118717693, and ID = 5361 showed strong stability with the protein molecule. These compounds were further validated using Δ G binding free energies and they showed: -30.38 kcal/mol, and -67.83 kcal/mol binding free energies, respectively. Later, these two compounds were used in steered MD simulation to detect its dissociation. Compound ID = 5361 showed the maximum pulling force of 199.02 kcal/mol/nm to dissociate the protein-ligand complex while ID = 118717693 had a pulling force of 101.11 kcal/mol/nm, respectively. This ligand highest number of hydrogen bonds with varying occupancies at 89.93%, 69.80%, 57.93%, 52.33%, and 50.63%. This study showed that ID = 5361 can bind with the VP24 strongly and has the potential to inhibit its function which can be validated in the in-vitro experiment.Communicated by Ramaswamy H. Sarma.

Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations

The COVID-19 pandemic has necessitated the development of reliable diagnostic methods for accurately detecting the novel coronavirus and its variants. Deep learning (DL) techniques have shown promising potential as screening tools for COVID-19 detection. In this study, we explore the realistic development of DL-driven COVID-19 detection methods and focus on the fully automatic framework using available resources, which can effectively investigate various coronavirus variants through modalities. We conducted an exploration and comparison of several diagnostic techniques that are widely used and globally validated for the detection of COVID-19. Furthermore, we explore review-based studies that provide detailed information on synergistic medicine combinations for the treatment of COVID-19. We recommend DL methods that effectively reduce time, cost, and complexity, providing valuable guidance for utilizing available synergistic combinations in clinical and research settings. This study also highlights the implication of innovative diagnostic technical and instrumental strategies, exploring public datasets, and investigating synergistic medicines using optimised DL rules. By summarizing these findings, we aim to assist future researchers in their endeavours by providing a comprehensive overview of the implication of DL techniques in COVID-19 detection and treatment. Integrating DL methods with various diagnostic approaches holds great promise in improving the accuracy and efficiency of COVID-19 diagnostics, thus contributing to effective control and management of the ongoing pandemic.

Cheminformatics Strategies Unlock Marburg Virus VP35 Inhibitors from Natural Compound Library

The Ebola virus and its close relative, the Marburg virus, both belong to the family Filoviridae and are highly hazardous and contagious viruses. With a mortality rate ranging from 23% to 90%, depending on the specific outbreak, the development of effective antiviral interventions is crucial for reducing fatalities and mitigating the impact of Marburg virus outbreaks. In this investigation, a virtual screening approach was employed to evaluate 2042 natural compounds for their potential interactions with the VP35 protein of the Marburg virus. Average and worst binding energies were calculated for all 20 poses, and compounds that exhibited binding energies <-6 kcal/mol in both criteria were selected for further analysis. Based on binding energies, only six compounds (Estradiol benzoate, INVEGA (paliperidone), Isosilybin, Protopanaxadiol, Permethrin, and Bufalin) were selected for subsequent investigations, focusing on interaction analysis. Among these selected compounds, Estradiol benzoate, INVEGA (paliperidone), and Isosilybin showed strong hydrogen bonds, while the others did not. In this study, the compounds Myricetin, Isosilybin, and Estradiol benzoate were subjected to a molecular dynamics (MD) simulation and free binding energy calculation using MM/GBSA analysis. The reference component Myricetin served as a control. Estradiol benzoate exhibited the most stable and consistent root-mean-square deviation (RMSD) values, whereas Isosilybin showed significant fluctuations in RMSD. The compound Estradiol benzoate exhibited the lowest ΔG binding free energy (-22.89 kcal/mol), surpassing the control compound's binding energy (-9.29 kcal/mol). Overall, this investigation suggested that Estradiol benzoate possesses favorable binding free energies, indicating a potential inhibitory mechanism against the VP35 protein of the Marburg virus. The study proposes that these natural compounds could serve as a therapeutic option for preventing Marburg virus infection. However, experimental validation is required to further corroborate these findings.

In Silico Discovery of Small-Molecule Inhibitors Targeting SARS-CoV-2 Main Protease

The COVID-19 pandemic has caused severe health threat globally, and novel SARS-Cov-2 inhibitors are urgently needed for antiviral treatment. The main protease (M^pro) of the virus is one of the most effective and conserved targets for anti-SARS-CoV-2 drug development. In this study, we utilized a molecular docking-based virtual screening approach against the conserved catalytic site to identify small-molecule inhibitors of SARS-CoV-2 M^pro. Further biological evaluation helped us identify two compounds, AF-399/40713777 and AI-942/42301830, with moderate inhibitory activity. Besides that, the in silico data, including molecular dynamics (MD) simulation, binding free energy calculations, and AMDET profiles, suggested that these two hits could serve as the starting point for the future development of COVID-19 intervention treatments.

Target specific inhibition of West Nile virus envelope glycoprotein and methyltransferase using phytocompounds: an in silico strategy leveraging molecular docking and dynamics simulation

Mosquitoes are the primary vector for West Nile virus, a flavivirus. The virus's ability to infiltrate and establish itself in increasing numbers of nations has made it a persistent threat to public health worldwide. Despite the widespread occurrence of this potentially fatal disease, no effective treatment options are currently on the market. As a result, there is an immediate need for the research and development of novel pharmaceuticals. To begin, molecular docking was performed on two possible West Nile virus target proteins using a panel of twelve natural chemicals, including Apigenin, Resveratrol, Hesperetin, Fungisterol, Lucidone, Ganoderic acid, Curcumin, Kaempferol, Cholic acid, Chlorogenic acid, Pinocembrin, and Sanguinarine. West Nile virus methyltransferase (PDB ID: 2OY0) binding affinities varied from -7.4 to -8.3 kcal/mol, whereas West Nile virus envelope glycoprotein affinities ranged from -6.2 to -8.1 kcal/mol (PDB ID: 2I69). Second, substances with larger molecular weights are less likely to be unhappy with the Lipinski rule. Hence, additional research was carried out without regard to molecular weight. In addition, compounds 01, 02, 03, 05, 06, 07, 08, 09, 10 and 11 are more soluble in water than compound 04 is. Besides, based on maximum binding affinity, best three compounds (Apigenin, Curcumin, and Ganoderic Acid) has been carried out molecular dynamic simulation (MDs) at 100 ns to determine their stability. The MDs data is also reported that these mentioned molecules are highly stable. Finally, advanced principal component analysis (PCA), dynamics cross-correlation matrices (DCCM) analysis, binding free energy and dynamic cross correlation matrix (DCCM) theoretical study is also included to established mentioned phytochemical as a potential drug candidate. Research has indicated that the aforementioned natural substances may be an effective tool in the battle against the dangerous West Nile virus. This study aims to locate a bioactive natural component that might be used as a pharmaceutical.

Integrating Computational Methods in Network Pharmacology and In Silico Screening to Uncover Multi-targeting Phytochemicals against Aberrant Protein Glycosylation in Lung Cancer

Glycoproteins are an underexploited drug target for cancer therapeutics. In this work, we integrated computational methods in network pharmacology and in silico docking approaches to identify phytochemical compounds that could potentially interact with several cancer-associated glycoproteins. We first created a database of phytochemicals from selected plant species, Manilkara zapota (sapodilla/chico), Mangifera indica (mango), Annona muricata (soursop/guyabano), Artocarpus heterophyllus (jackfruit/langka), Lansium domesticum (langsat/lanzones), and Antidesma bunius (bignay), and performed pharmacokinetic analysis to determine their drug-likeness properties. We then constructed a phytochemical-glycoprotein interaction network and characterized the degree of interactions between the phytochemical compounds and with cancer-associated glycoproteins and other glycosylation-related proteins. We found a high degree of interactions from α-pinene (Mangifera indica), cyanomaclurin (Artocarpus heterophyllus), genistein (Annona muricata), kaempferol (Annona muricata and Antidesma bunius), norartocarpetin (Artocarpus heterophyllus), quercetin (Annona muricata, Antidesma bunius, Manilkara zapota, Mangifera indica), rutin (Annona muricata, Antidesma bunius, Lansium domesticum), and ellagic acid (Antidesma bunius and Mangifera indica). Subsequent docking analysis confirmed that these compounds could potentially bind to EGFR, AKT1, KDR, MMP2, MMP9, ERBB2, IGF1R, MTOR, and HRAS proteins, which are known cancer biomarkers. In vitro cytotoxicity assays of the plant extracts showed that the n-hexane, ethyl acetate, and methanol leaf extracts from A. muricata, L. domesticum and M. indica gave the highest growth inhibitory activity against A549 lung cancer cells. These may help further explain the reported cytotoxic activities of select compounds from these plant species.

Microwave and Cs+-assisted chemo selective reaction protocol for synthesizing 2-styryl quinoline biorelevant molecules

The reaction protocols and their continuous development to achieve the desired selectivity remain a primary target of organic chemistry, which is addressed here with the specific role of the cesium ion. The pharmacophore “2-styryl quinoline” was taken as a reference here because of the continuation of our work, where it was found fit as fusion inhibitors and anti-viral agents. The present protocol defines its importance for the synthesis of O-alkylated products. However, in most cases, N-alkylation proceeds because of nitrogen atoms’ more nucleophilic nature and electronic density. The cesium effect makes this possible because of the large cationic size and its affection for the oxygen atom. The plausible mechanism and its progression were demonstrated here with the help of density function theory calculation by analyzing the energy of intermediates. The protocol is also found suitable with microwave irradiation. Moreover, it gives the product a better yield in less reaction time. The present reaction protocol and its importance will address some of the crucial issues related to the synthesis of the complex molecule, and the present protocol will open up hope, where the selectivity and product yield would be a concern.

A potential host and virus targeting tool against COVID-19: Chemical characterization, antiviral, cytoprotective, antioxidant, respiratory smooth muscle relaxant effects of Paulownia tomentosa Steud

COronaVIrus Disease 2019 (COVID-19) is a newly emerging infectious disease that spread across the world, caused by the novel coronavirus Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2). Despite the advancements in science that led to the creation of the vaccine, there is still an urgent need for new antiviral drugs effective against SARS-CoV-2. This study aimed to investigate the antiviral effect of Paulownia tomentosa Steud extract against SARS-CoV-2 and to evaluate its antioxidant properties, including respiratory smooth muscle relaxant effects. Our results showed that P. tomentosa extract can inhibit viral replication by directly interacting with both the 3-chymotrypsin-like protease and spike protein. In addition, the phyto complex does not reduce lung epithelial cell viability and exerts a protective action in those cells damaged by tert-butyl hydroperoxide , a toxic agent able to alter cells' functions via increased oxidative stress. These data suggest the potential role of P. tomentosa extract in COVID-19 treatment, since this extract is able to act both as an antiviral and a cytoprotective agent in vitro.

Modified coptisine derivatives as an inhibitor against pathogenic Rhizomucor miehei, Mycolicibacterium smegmatis (Black Fungus), Monkeypox, and Marburg virus by molecular docking and molecular dynamics simulation-based drug design approach

During the second phase of SARS-CoV-2, an unknown fungal infection, identified as black fungus, was transmitted to numerous people among the hospitalized COVID-19 patients and increased the death rate. The black fungus is associated with the Mycolicibacterium smegmatis, Mucor lusitanicus, and Rhizomucor miehei microorganisms. At the same time, other pathogenic diseases, such as the Monkeypox virus and Marburg virus, impacted global health. Policymakers are concerned about these pathogens due to their severe pathogenic capabilities and rapid spread. However, no standard therapies are available to manage and treat those conditions. Since the coptisine has significant antimicrobial, antiviral, and antifungal properties; therefore, the current investigation has been designed by modifying coptisine to identify an effective drug molecule against Black fungus, Monkeypox, and Marburg virus. After designing the derivatives of coptisine, they have been optimized to get a stable molecular structure. These ligands were then subjected to molecular docking study against two vital proteins obtained from black fungal pathogens: Rhizomucor miehei (PDB ID: 4WTP) and Mycolicibacterium smegmatis (PDB ID 7D6X), and proteins found in Monkeypox virus (PDB ID: 4QWO) and Marburg virus (PDB ID 4OR8). Following molecular docking, other computational investigations, such as ADMET, QSAR, drug-likeness, quantum calculation and molecular dynamics, were also performed to determine their potentiality as antifungal and antiviral inhibitors. The docking score reported that they have strong affinities against Black fungus, Monkeypox virus, and Marburg virus. Then, the molecular dynamic simulation was conducted to determine their stability and durability in the physiological system with water at 100 ns, which documented that the mentioned drugs were stable over the simulated time. Thus, our in silico investigation provides a preliminary report that coptisine derivatives are safe and potentially effective against Black fungus, Monkeypox virus, and Marburg virus. Hence, coptisine derivatives may be a prospective candidate for developing drugs against Black fungus, Monkeypox and Marburg viruses.