Molecular dynamic study of SARS-CoV-2 with various S protein mutations and their effect on thermodynamic properties

Computational screening of chemical constituents derived from berry fruits as allosteric caspace-3/-7 inhibitors

With the aim of finding the plant-derived allosteric inhibitors of caspase-3/-7, we conducted computational investigations of bioactive compounds present in various berry fruits. In a molecular docking study, perulactone demonstrated excellent binding affinity scores of -12.1 kcal/mol and -9.1 kcal/mol for caspase 7 and 3, respectively, whereas FDA-approved allosteric inhibitors (DICA and FICA) were found to show lower docking scores (-5.6 and -6.1 kcal/mol) against caspase 7 while (-5.0 and -5.1 kcal/mol) for caspase 3, respectively. MD simulations were used to validate the binding stability of perulactone in the active sites of caspase-7/-3, and the results showed outstanding stability with lower ligand RMSDs of 1.270-3.088 Å and 2.426-9.850 Å against the targeted receptor. Furthermore, we performed MMGBSA free binding energy, where the perulactone values of ΔG Bind were determined to be -63.98 kcal/mol and -66.32 kcal/mol for both receptors (3IBF and 1NME), which are significantly better than the -45.16 kcal/mol and -39.51 kcal/mol for DICA as well as -26.37 kcal/mol and -15.50 kcal/mol for FICA, respectively. The drug resemblance of perulactone was effectively evaluated by ADMET. Thus, our findings indicated that perulactone could be an orally administered therapeutic candidate for regulating apoptosis in a variety of disorders. However, there may be an urgent need to study using in vitro and in vivo experiments.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04067-7.

In-silico screening of Acacia pennata and Bridelia retusa reveals pinocembrin-7-O-β-D-glucopyranoside as a promising β-lactamase inhibitor to combat antibiotic resistance

The β-lactamase of Pseudomonas aeruginosa is known to degrade β-lactam antibiotics such as penicillins, cephalosporins, monobactams, and carbapenems. With the discovery of an extended-spectrum β-lactamase in a clinical isolate of P. aeruginosa, the bacterium has become multi-drug resistant. In this study, we aim to identify new β-lactamase inhibitors by virtually screening a total of 43 phytocompounds from two Indian medicinal plants. In the molecular docking studies, pinocembrin-7-O-β-D-glucopyranoside (P7G) (-9.6 kcal/mol) from Acacia pennata and ellagic acid (EA) (-9.2 kcal/mol) from Bridelia retusa had lower binding energy than moxalactam (-8.4 kcal/mol). P7G and EA formed 5 (Ser62, Asn125, Asn163, Thr209, and Ser230) and 4 (Lys65, Ser123, Asn125, and Glu159) conventional hydrogens bonds with the active site residues. 100 ns MD simulations revealed that moxalactam and P7G (but not EA) were able to form a stable complex. The binding free energy calculations further revealed that P7G (-59.6526 kcal/mol) formed the most stable complex with β-lactamase when compared to moxalactam (-46.5669 kcal/mol) and EA (-28.4505 kcal/mol). The HOMO-LUMO and other DFT parameters support the stability and chemical reactivity of P7G at the active site of β-lactamase. P7G passed all the toxicity tests and bioavailability tests indicating that it possesses drug-likeness. Among the studied compounds, we identified P7G of A. pennata as the most promising phytocompound to combat antibiotic resistance by potentially inhibiting the β-lactamase of P. aeruginosa.Communicated by Ramaswamy H. Sarma.

Computational evaluation of phytochemicals targeting DNA topoisomerase I in Leishmania donovani: molecular docking and molecular dynamics simulation studies

DNA topoisomerase I (Topo I) is a ubiquitous enzyme that plays a crucial role in resolving the topological constraints of supercoiled DNA during various cellular activities, including repair, replication, recombination, transcription, and chromatin remodeling. Multiple studies have confirmed the essential role of Topo I in nucleic acid metabolism of Leishmania donovani, the kinetoplastid parasite responsible for visceral leishmaniasis or kala-azar. Inhibition of this enzyme has shown promise as a strategy for therapy against visceral leishmaniasis. However, current treatment options suffer from limitations related to effectiveness, cost, and side effects. To address these challenges, computational methods have been employed in this study to investigate the inhibition of Leishmania donovani DNA topoisomerase I (LdTopo I) by phytochemicals derived from Indian medicinal plants known for their anti-leishmanial activity. A library of phytochemicals and known inhibitors was assembled, and virtual screening based on docking binding affinities was conducted to identify potent phytochemical inhibitors. To assess the drug-likeness of the docked phytochemicals, their physicochemical properties were predicted. Additionally, molecular dynamics (MD) simulations were performed on the docked complexes for a duration of 100 ns to evaluate their stability, intermolecular interactions, and dynamic behavior. Among all the docked phytochemicals, three compounds, namely CID23266147 (withanolide N), CID5488537 (fagopyrine), and CID100947536 (isozeylanone), exhibited the highest inhibitory potential against LdTopo I. These findings hold promise for the development of novel inhibitors targeting LdTopo I, which could potentially lead to improved therapies for visceral leishmaniasis.Communicated by Ramaswamy H. Sarma.

Evaluation of Potential Furin Protease Inhibitory Properties of Pioglitazone, Rosiglitazone, and Pirfenidone: An In Silico Docking and Molecular Dynamics Simulation Approach

Furin (Fur) is a member of the protease convertase family; its expression is crucial for cleaving and maturing many proteins. Fur also represents a therapeutic target in cancer, autoimmune diseases, and viral infections. Pioglitazone (PGZ) and rosiglitazone (RGZ) are thiazolidinediones prescribed to type 2 diabetes patients and are structurally similar to the known Fur inhibitors naphthofluorescein (NPF) and pirfenidone (PFD). Thus, this study used molecular docking and molecular dynamics to assess and compare the affinities and the molecular interactions of these four ligands with the Fur active site (FurAct) and the recently described Fur allosteric site (FurAll). The 7QXZ Fur structure was used for molecular dockings, and for the best pose complexes, molecular dynamics were run for 100 ns. The best affinities of the ligand/FurAct and ligand/FurAll complexes were with NPF, PGZ, and RGZ, while PFD presented the lowest affinity. Asp154 was the central residue involved in FurAct complex formation, while Glu488 and Asn310 were the central residues involved in FurAll complex formation. This study shows the potential of RGZ, PGZ, and PFD as Fur competitive (FurAct) and non-competitive (FurAll) inhibitors. Therefore, they are candidates for repurposing in response to future emerging diseases through the modulation of Fur activity.

Explainable artificial intelligence-assisted virtual screening and bioinformatics approaches for effective bioactivity prediction of phenolic cyclooxygenase-2 (COX-2) inhibitors using PubChem molecular fingerprints

Cyclooxygenase-2 (COX-2) inhibitors are nonsteroidal anti-inflammatory drugs that treat inflammation, pain and fever. This study determined the interaction mechanisms of COX-2 inhibitors and the molecular properties needed to design new drug candidates. Using machine learning and explainable AI methods, the inhibition activity of 1488 molecules was modelled, and essential properties were identified. These properties included aromatic rings, nitrogen-containing functional groups and aliphatic hydrocarbons. They affected the water solubility, hydrophobicity and binding affinity of COX-2 inhibitors. The binding mode, stability and ADME properties of 16 ligands bound to the Cyclooxygenase active site of COX-2 were investigated by molecular docking, molecular dynamics simulation and MM-GBSA analysis. The results showed that ligand 339,222 was the most stable and effective COX-2 inhibitor. It inhibited prostaglandin synthesis by disrupting the protein conformation of COX-2. It had good ADME properties and high clinical potential. This study demonstrated the potential of machine learning and bioinformatics methods in discovering COX-2 inhibitors.

Identification of potential biogenic chalcones against antibiotic resistant efflux pump (AcrB) via computational study

The cases of bacterial multidrug resistance are increasing every year and becoming a serious concern for human health. Multidrug efflux pumps are key players in the formation of antibiotic resistance, which transfer out a broad spectrum of drugs from the cell and convey resistance to the host. Efflux pumps have significantly reduced the efficacy of the previously available antibiotic armory, thereby increasing the frequency of therapeutic failures. In gram-negative bacteria, the AcrAB-TolC efflux pump is the principal transporter of the substrate and plays a major role in the formation of antibiotic resistance. In the current work, advanced computer-aided drug discovery approaches were utilized to find hit molecules from the library of biogenic chalcones against the bacterial AcrB efflux pump. The results of the performed computational studies via molecular docking, drug-likeness prediction, pharmacokinetic profiling, pharmacophore mapping, density functional theory, and molecular dynamics simulation study provided ZINC000004695648, ZINC000014762506, ZINC000014762510, ZINC000095099506, and ZINC000085510993 as stable hit molecules against the AcrB efflux pumps. Identified hits could successfully act against AcrB efflux pumps after optimization as lead molecules.Communicated by Ramaswamy H. Sarma.

Comprehensive bioinformatics analysis of structural and functional consequences of deleterious missense mutations in the human QDPR gene

Quinonoid dihydropteridine reductase (QDPR) is an enzyme that regulates tetrahydrobiopterin (BH4), a cofactor for enzymes involved in neurotransmitter synthesis and blood pressure regulation. Reduced QDPR activity can cause dihydrobiopterin (BH2) accumulation and BH4 depletion, leading to impaired neurotransmitter synthesis, oxidative stress, and increased risk of Parkinson's disease. A total of 10,236 SNPs were identified in the QDPR gene, with 217 being missense SNPs. Over 18 different sequence-based and structure-based tools were employed to assess the protein's biological activity, with several computational tools identifying deleterious SNPs. Additionally, the article provides detailed information about the QDPR gene and protein structure and conservation analysis. The results showed that 10 mutations were harmful and linked to brain and central nervous system disorders, and were predicted to be oncogenic by Dr. Cancer and CScape. Following conservation analysis, the HOPE server was used to analyse the effect of six selected mutations (L14P, V15G, G23S, V54G, M107K, G151S) on the protein structure. Overall, the study provides insights into the biological and functional impact of nsSNPs on QDPR activity and the potential induced pathogenicity and oncogenicity. In the future, research can be conducted to systematically evaluate QDPR gene variation through clinical studies, investigate mutation prevalence across different geographical regions, and validate computational results with conclusive experiments.Communicated by Ramaswamy H. Sarma.

An insight for the inhibition of anxiolytic and anti-convulsant effects in zebrafish using the curcumins via exploring molecular docking and molecular dynamics simulations

In the contemporary landscape, anxiety and seizures stand as major areas of concern, prompting researchers to explore potential drugs against them. While numerous drugs have shown the potential to treat these two neurological conditions, certain adverse effects emphasize the need for development of safer alternatives. This study seeks to employ an in silico approach to evaluate natural compounds, particularly curcumins, as potential inhibitors of GABA-AT to mitigate anxiety and seizures. The proposed methodology includes generating a compound library, minimizing energy, conducting molecular docking using AutoDock, molecular dynamics simulations using Amber, and MM-GBSA calculations. Remarkably, CMPD50 and CMPD88 exhibited promising binding affinities of - 9.0 kcal/mol and - 9.1 kcal/mol with chains A and C of GABA-AT, respectively. Further, MM-GBSA calculations revealed binding free energies of - 10.88 kcal/mol and - 10.72 kcal/mol in CMPD50 and CMPD88, respectively. ADME analysis showed that these compounds contain drug-likeness properties and might be considered as potential drug candidates. The findings from this study will have practical applications in the field of drug discovery for the development of safer and effective drugs for treatment of anxiety and seizures. Overall, this study will lay the groundwork for providing valuable insights into the potential therapeutic effects of curcumins in alleviating anxiety and seizures, establishing a computational framework for future experimental validation.

6-Octadecenoic and Oleic Acid in Liquid Smoke Rice Husk Showed COVID-19 Inhibitor Properties

In recent years, liquid smoke rice husk (LSRH) has shown its therapeutic potency to diabetes, wound healing, stomatitis, and periodontitis. The phenol, 6-octadecenoic acid, oleic acid, and 9-octadecanoic acid were responsible for their therapeutic effect. The LSRH also demonstrated their potential for infectious diseases such as coronavirus disease (COVID-19). Therefore, the molecular dynamics (MDs) simulation and pharmacophore analysis was performed to analyse the binding stability of 6-octadecenoic and oleic acid. Based on MD simulation, 6-octadecenoic and oleic acids seemed to retain their interactions with Ser144 and Thr24, respectively, with hydrogen bond distance less than 2.9 Å. This interaction was stable during the simulation and has hydrophobic and hydrogen bonds/acceptors. The 6-octadecenoic acid and oleic acid were confirmed to have great potency as inhibitors for COVID-19. These compounds also showed that the existence of hydrophobic and hydrogen bonds/acceptors could increase biological activity.

Astaxanthin targets IL-6 and alleviates the LPS-induced adverse inflammatory response of macrophages

Numerous natural compounds are recognized for their anti-inflammatory properties attributed to antioxidant effects and the modulation of key inflammatory factors. Among them, astaxanthin (AST), a potent carotenoid antioxidant, remains relatively underexplored regarding its anti-inflammatory mechanisms and specific molecular targets. In this study, human monocytic leukemia cell-derived macrophages (THP-1) were selected as experimental cells, and lipopolysaccharides (LPS) served as inflammatory stimuli. Upon LPS treatment, the oxidative stress was significantly increased, accompanied by remarkable cellular damage. Moreover, LPSs escalated the expression of inflammation-related molecules. Our results demonstrate that AST intervention could effectively alleviate LPS-induced oxidative stress, facilitate cellular repair, and significantly attenuate inflammation. Further exploration of the anti-inflammatory mechanism revealed AST could substantially inhibit NF-κB translocation and activation, and mitigate inflammatory factor production by hindering NF-κB through the antioxidant mechanism. We further confirmed that AST exhibited protective effects against cell damage and reduced the injury from inflammatory cytokines by activating p53 and inhibiting STAT3. In addition, utilizing network pharmacology and in silico calculations based on molecular docking, molecular dynamics simulation, we identified interleukin-6 (IL-6) as a prominent core target of AST anti-inflammation, which was further validated by the RNA interference experiment. This IL-6 binding capacity actually enabled AST to curb the positive feedback loop of inflammatory factors, averting the onset of possible inflammatory storms. Therefore, this study offers a new possibility for the application and development of astaxanthin as a popular dietary supplement of anti-inflammatory or immunomodulatory function.

Molecular dynamic analyses of the interaction of SARS-CoV-1 or 2 variants with various angiotensin-converting enzyme-2 species

The transmembrane glycoprotein angiotensin-converting enzyme 2 (ACE2) is a key component of the renin-angiotensin system (RAS). It was shown to be the receptor of severe acute respiratory syndrome coronavirus 2 in the COVID-19 outbreak (SARS-COV-2). Furthermore, ACE2 aids in the transport of amino acids across the membrane. ACE2 is lost from the membrane, resulting in soluble ACE2 (sACE2). We aim to examine the structural conformation alterations between SARS-CoV-1 or 2 variants at various periods with ACE2 from various sources, particularly in the area where it interacts with the viral protein and the receptor. It is important to study the molecular dynamics of ACE2/SARS-COV RBD when the structure is available on the database. Here we analyzed the crystal structure of ACE2 from Human, Dog, Mus, Cat, and Bat ACE2 in complex with RBD from SARS-COV-1 and SARS-COV-2. The result shows, there is a variation in the type of residues, number of contact atoms and hydrogen bonds in ACE2 and RBD during the interaction interfaces. By using molecular dynamics simulation, we can measure RMSD, RMSF, SASA, Rg and the difference in the percentage of α helix and β strand. As bat ACE2 & SARS-CoV-2 RBD found to have a high amount of β strand compared to another structure complex, while hACE2 & SARS-CoV-1 RBD has fewer amounts of β strand. Our study provides a deep view of the structure which is available and a summary of many works around ACE2/SARS-CoV RBD interaction.Communicated by Ramaswamy H. Sarma.

High-throughput computational screening for identification of potential hits against bacterial Acriflavine resistance protein B (AcrB) efflux pump

Antibiotic resistance is a pressing global health challenge, driven in part by the remarkable efflux capabilities of efflux pump in AcrB (Acriflavine Resistance Protein B) protein in Gram-negative bacteria. In this study, a multi-approached computational screening strategy encompassing molecular docking, In silico absorption, distribution, metabolism, excretion and toxicity (ADMET) analysis, druglikeness assessment, molecular dynamics simulations and density functional theory studies was employed to identify novel hits capable of acting against AcrB-mediated antibiotic resistance. Ligand library was acquired from the COCONUT database. Performed computational analyses unveiled four promising hit molecules (CNP0298667, CNP0399927, CNP0321542 and CNP0269513). Notably, CNP0298667 exhibited the highest negative binding affinity of -11.5 kcal/mol, indicating a possibility of strong potential to disrupt AcrB function. Importantly, all four hits met stringent druglikeness criteria and demonstrated favorable in silico ADMET profiles, underscoring their potential for further development. MD simulations over 100 ns revealed that the CNP0321542-4DX5 and CNP0269513-4DX5 complexes formed robust and stable interactions with the AcrB efflux pump. The identified hits represent a promising starting point for the design and optimization of novel therapeutics aimed at combating AcrB-mediated antibiotic resistance in Gram-negative bacteria.Communicated by Ramaswamy H. Sarma.

Inhibition of respiratory syncytial virus by Daclatasvir and its derivatives: synthesis of computational derivatives as a new drug development

The most common cause of respiratory tract illness in newborns and young children is the respiratory syncytial virus (RSV). There is no approved vaccination or specific antiviral medication for RSV infections. Here, an attempt has been made to explore the potential of currently marketed drugs as well as their probable derivatives to improve the possibility of developing stronger medications against RSV. From the 100 synthetic drug compounds library, the best drug molecule was identified through drug-likeness properties, toxicity, molecular docking and molecular dynamics simulations. Molecular Mechanics Generalized Born Surface Area (MM-GBSA) was also a method that was applied in this study. Daclatasvir showed the highest binding energy and appeared as the best drug to inhibit matrix protein and a fusion protein of RSV. Based on Daclatasvir, 40 computational derivatives were made. D28, D34 and D40 showed far better results than the actual drug. Changes in lipophilicity character increase the binding energy of derivatives. Molecular dynamic simulations showed their non-deviated, non-fluctuated and stable complex formation with target proteins. The high number of amino acid contacts throughout the trajectory increases the stability and effectiveness of derivatives. The key to producing a novel medicine to eradicate RSV is provided by derivatives. Daclatasvir will be employed as a potential RSV inhibitor up until that point.Communicated by Ramaswamy H. Sarma.

Cheminformatics-based discovery of new organoselenium compounds with potential for the treatment of cutaneous and visceral leishmaniasis

Leishmaniasis affects more than 12 million humans globally and a further 1 billion people are at risk in leishmaniasis endemic areas. The lack of a vaccine for leishmaniasis coupled with the limitations of existing anti-leishmanial therapies prompted this study. Cheminformatic techniques are widely used in screening large libraries of compounds, studying protein-ligand interactions, analysing pharmacokinetic properties, and designing new drug molecules with great speed, accuracy, and precision. This study was undertaken to evaluate the anti-leishmanial potential of some organoselenium compounds by quantitative structure-activity relationship (QSAR) modeling, molecular docking, pharmacokinetic analysis, and molecular dynamic (MD) simulation. The built QSAR model was validated (R2train = 0.8646, R2test = 0.8864, Q2 = 0.5773) and the predicted inhibitory activity (pIC50) values of the newly designed compounds were higher than that of the template (Compound 6). The new analogues (6a, 6b, and 6c) showed good binding interactions with the target protein (Pyridoxal kinase, PdxK) while also presenting excellent drug-likeness and pharmacokinetic profiles. The results of density functional theory, MD simulation, and molecular mechanics generalized Born surface area (MM/GBSA) analyses suggest the favourability and stability of protein-ligand interactions of the new analogues with PdxK, comparing favourably well with the reference drug (Pentamidine). Conclusively, the newly designed compounds could be synthesized and tested experimentally as potential anti-leishmanial drug molecules.Communicated by Ramaswamy H. Sarma.

Computational screening of natural products to identify potential inhibitors for human neuropilin-1 (NRP1) receptor to abrogate the binding of SARS-CoV-2 and host cell

Recently, a new variant B.1.1.529 or Omicron variant and its sub-variants (BA2.75, BA.5) of SARS-CoV-2 (Severe acute respiratory virus 2) have been reported with a larger number of mutations in the spike protein and particularly in the RBD (receptor-binding domain). The omicron (B.1.1.529) variant has aggravated the pandemic situation further and needs more analysis for therapeutic development. Keeping in view the urgency of the required data, the current study used molecular modeling and simulation-based methods to target the NRP1 (Neuropilin 1) protein to halt the entry into the host cell. Employing a molecular screening approach to screen the North-East African natural compounds database (NEANCDB) revealed Subereamine B with a docking score of -8.44 kcal/mol, Zinolol with the docking score of -8.05 while Subereamine A with a docking score of -7.88 kcal/mol as the best hits against NRP1. Molecular simulation-based further validation revealed stable dynamics, good structural packing, and dynamic residues flexibility index. Moreover, hydrogen bonding fraction analysis demonstrated the interactions remained sustained during the simulation. Furthermore, the total binding free energy for Subereamine B was -44.24 ±0.91 kcal/mol, for Zinolol -34.32 ±0.40 kcal/mol while for Subereamine A the TBE was calculated to be -41.78 ± 0.36 kcal/mol respectively. This shows that the two arginine-based alkaloids, i.e. Subereamine B and Subereamine A could inhibit the NRP1 more strongly than Zinolol. In conclusion, this study provides a basis for the development of novel drugs against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Identification of novel dual acting ligands targeting the adenosine A2A and serotonin 5-HT1A receptors

GPCRs are a family of transmembrane receptors that are profoundly linked to various neurological disorders, among which is Parkinson's disease (PD). PD is the second most ubiquitous neurological disorder after Alzheimer's disease, characterized by the depletion of dopamine in the central nervous system due to the impairment of dopaminergic neurons, leading to involuntary movements or dyskinesia. The current standard of care for PD is Levodopa, a dopamine precursor, yet the chronic use of this agent can exacerbate motor symptoms. Recent studies have investigated the effects of combining A2AR antagonist and 5-HT1A agonist on dyskinesia and motor complications in animal models of PD. It has been proved that the drug combination has significantly improved involuntary movements while maintaining motor activity, highlighting as a result new lines of therapy for PD treatments, through the regulation of both receptors. Using a combination of ligand-based pharmacophore modelling, virtual screening, and molecular dynamics simulation, this study intends on identifying potential dual-target compounds from IBScreen. Results showed that the selected models displayed good enrichment metrics with a near perfect receiver operator characteristic (ROC) and Area under the accumulation curve (AUAC) values, signifying that the models are both specific and sensitive. Molecular docking and ADMET analysis revealed that STOCK2N-00171 could be potentially active against A2AR and 5-HT1A. Post-MD analysis confirmed that the ligand exhibits a stable behavior throughout the simulation while maintaining crucial interactions. These results imply that STOCK2N-00171 can serve as a blueprint for the design of novel and effective dual-acting ligands targeting A2AR and 5-HT1A.Communicated by Ramaswamy H. Sarma.

Potential Effect of Baobab's Polyphenols as Antihyperlipidemic Agents: In Silico Study

Adansonia digitata L. is an African tree commonly called baobab. This tree is effectively used in traditional medicine to treat cardiovascular disorders. Hyperlipidemia is a well-known cardiovascular risk factor associated with the increased incidence of mortality worldwide. This study aimed to demonstrate the mechanism of baobab polyphenols in the activities of hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase and pancreatic lipase as lipid metabolic enzymes. Molecular docking and an incentive for drug design showed that all the polyphenols in baobab bound to the proteins with higher affinity and a lower binding energy compared with simvastatin as the positive control (ΔG: from -5.5 kcal/mol to -6.5 kcal/mol). The same polyphenols exhibited a considerable binding affinity to pancreatic lipase (ΔG: from -7.5 kcal/mol to -9.8 kcal/mol) in comparison with the control and HMG-CoA reductase. Quercetin showed the best docking score from the selected Baobab polyphenols (ΔG = -9.8 kcal/mol). The root mean square deviation (RMSD) results indicated that stable epicatechin and quercetin complexes were demonstrated with HMG-CoA reductase, and other less stable complexes were developed using rutin and chlorogenic acid. Moreover, the analysis of the root mean square fluctuation (RMSF) simulation results was consistent with that of the RMSD. The RMSF value for all the baobab polyphenols, including the crystal control ligand, was kept between 0.80 and 8.00 Å, similarly to simvastatin, and less than 4.8 Å for pancreatic lipase. Chlorogenic acid, quercetin, epicatechin, and rutin had negative ΔG binding scores from highest to lowest. The same ligands displayed more negative ΔG binding scores than those observed in HMG-CoA reductase and crystal control ligand (methoxyundecyl phosphinic acid) in their simulation with pancreatic lipase. In conclusion, baobab polyphenols interact with HMG-CoA reductase and pancreatic lipase to inhibit their substrate binding and block their activity.

Molecular dynamic and bioinformatic studies of metformin-induced ACE2 phosphorylation in the presence of different SARS-CoV-2 S protein mutations

The SARS-CoV-2 infection activates host kinases and causes high phosphorylation in both the host and the virus. There were around 70 phosphorylation sites found in SARS-CoV-2 viral proteins. Besides, almost 15,000 host phosphorylation sites were found in SARS-CoV-2-infected cells. COVID-19 is thought to enter cells via the well-known receptor Angiotensin-Converting Enzyme 2 (ACE2) and the serine protease TMPRSS2. Substantially, the COVID-19 infection doesn't induce phosphorylation of the ACE2 receptor at Serin-680(s680). Metformin's numerous pleiotropic properties and extensive use in medicine including COVID-19, have inspired experts to call it the "aspirin of the twenty-first century". Metformin's impact on COVID-19 has been verified in clinical investigations via ACE2 receptor phosphorylation at s680. In the infection of COVID-19, sodium-dependent transporters including the major neutral amino acid (B0AT1) is regulated by ACE2. The structure of B0AT1 complexing with the COVID-19 receptor ACE2 enabled significant progress in the creation of mRNA vaccines. We aimed to study the impact of the interaction of the phosphorylation form of ACE2-s680 with wild-type (WT) and different mutations of SARS-CoV-2 infection such as delta, omicron, and gamma (γ) on their entrance of host cells as well as the regulation of B0AT1by the SARS-CoV-2 receptor ACE2. Interestingly, compared to WT SARS-CoV-2, ACE2 receptor phosphorylation at s680 produces conformational alterations in all types of SARS-CoV-2. Furthermore, our results showed for the first time that this phosphorylation significantly influences ACE2 sites K625, K676, and R678, which are key mediators for ACE2-B0AT1 complex.

Post-COVID-19 effect on biochemical parameters in children: Should we take heed?

The aim of this research is to analyze the potential impact of the COVID-19 infection on the serum biochemical concentration of children 6 months after recovery from the infection. The study included 72 children with a median age of 11 years. The case group consisted of 37 children who had contracted COVID-19 6 months prior to the analysis. They reported no other pre- or post-covid chronic or systemic diseases. The control group consisted of 35 children who had no prior record of COVID-19 infection. The analysis showed a substantial variation (P = 0.026) in the mean urea values (mmol/L) between the case group (4.513 ± 0.839) and the control group (5.425 ± 1.173). However, both groups' urea levels were within the normal range of their age group. No statistical differences were found analyzing the variations between the two groups in the levels of LDH, AST, ALT, BiliT, GGT, AlbBCG2, CRP, CK, AlKP, UA, Phos, Crea2, Gluc, Ca, Na, K, Cl, TP, TC, TG, and HDL (P > 0.05). The DMFT score was substantially greater (P < 0.002) in the infected team (5.38 ± 2.841) in comparison to the non-infected group (2.6 ± 2.257). The study indicates that COVID-19 infection does not leave biochemical alterations among children who did not have pre-existing conditions. The biochemical analysis suggests that children recover better than adults from COVID-19. Furthermore, it calls for investigating non-lethal COVID-19 infection as a tool to discover underlying conditions. The DMFT score shows a correlation between COVID-19 infection and caries. However, the nature of the correlation is yet to be investigated.

AI-driven Discovery of Celecoxib and Dexamethasone for Exploring their Mode of Action as Human Interleukin (IL-6) Inhibitors to Treat COVID-19-induced Cytokine Storm in Humans

BACKGROUND

In the case of COVID-19 patients, it has been observed that the immune system of the infected person exhibits an extreme inflammatory response known as cytokine release syndrome (CRS) where the inflammatory cytokines are swiftly produced in quite large amounts in response to infective stimuli. Numerous case studies of COVID-19 patients with severe symptoms have documented the presence of higher plasma concentrations of human interleukin-6 (IL-6), which suggests that IL-6 is a crucial factor in the pathophysiology of the disease. In order to prevent CRS in COVID-19 patients, the drugs that can exhibit binding interactions with IL-6 and block the signaling pathways to decrease the IL-6 activity may be repurposed.

METHODS

This research work focused on molecular docking-based screening of the drugs celecoxib (CXB) and dexamethasone (DME) to explore their potential to interact with the binding sites of IL-6 protein and reduce the hyper-activation of IL-6 in the infected personnel.

RESULTS

Both of the drugs were observed to bind with the IL-6 (IL-6 receptor alpha chain) and IL-6Rα receptor with the respective affinities of -7.3 kcal/mol and -6.3 kcal/mol, respectively, for CXB and DME. Moreover, various types of binding interactions of the drugs with the target proteins were also observed in the docking studies. The dynamic behaviors of IL-6/IL-6Rα in complex with the drugs were also explored through molecular dynamics simulation analysis. The results indicated significant stabilities of the acquired drug-protein complexes up to 100 ns.

CONCLUSION

The findings of this study have suggested the potential of the drugs studied to be utilized as antagonists for countering CRS in COVID-19 ailment. This study presents the studied drugs as promising candidates both for the clinical and pre-clinical treatment of COVID-19.

Marine Alga Ulva fasciata-Derived Molecules for the Potential Treatment of SARS-CoV-2: An In Silico Approach

SARS-CoV-2 is the causative agent of the COVID-19 pandemic. This in silico study aimed to elucidate therapeutic efficacies against SARS-CoV-2 of phyco-compounds from the seaweed, Ulva fasciata. Twelve phyco-compounds were isolated and toxicity was analyzed by VEGA QSAR. Five compounds were found to be nonmutagenic, noncarcinogenic and nontoxic. Moreover, antiviral activity was evaluated by PASS. Binding affinities of five of these therapeutic compounds were predicted to possess probable biological activity. Fifteen SARS-CoV-2 target proteins were analyzed by the AutoDock Vina program for molecular docking binding energy analysis and the 6Y84 protein was determined to possess optimal binding affinities. The Desmond program from Schrödinger's suite was used to study high performance molecular dynamic simulation properties for 3,7,11,15-Tetramethyl-2-hexadecen-1-ol-6Y84 for better drug evaluation. The ligand with 6Y84 had stronger binding affinities (-5.9 kcal/mol) over two standard drugs, Chloroquine (-5.6 kcal/mol) and Interferon α-2b (-3.8 kcal/mol). Swiss ADME calculated physicochemical/lipophilicity/water solubility/pharmacokinetic properties for 3,7,11,15-Tetramethyl-2-hexadecen-1-ol, showing that this therapeutic agent may be effective against SARS-CoV-2.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Computational Study of Asian Propolis Compounds as Potential Anti-Type 2 Diabetes Mellitus Agents by Using Inverse Virtual Screening with the DIA-DB Web Server, Tanimoto Similarity Analysis, and Molecular Dynamic Simulation

Propolis contains a wide range of pharmacological activities because of their various bioactive compounds. The beneficial effect of propolis is interesting for treating type-2 diabetes mellitus (T2DM) owing to dysregulation of multiple metabolic processes. In this study, 275 of 658 Asian propolis compounds were evaluated as potential anti-T2DM agents using the DIA-DB web server towards 18 known anti-diabetes protein targets. More than 20% of all compounds could bind to more than five diabetes targets with high binding affinity (<−9.0 kcal/mol). Filtering with physicochemical and pharmacokinetic properties, including ADMET parameters, 12 compounds were identified as potential anti-T2DM with favorable ADMET properties. Six of those compounds, (2R)-7,4′-dihydroxy-5-methoxy-8-methylflavone; (RR)-(+)-3′-senecioylkhellactone; 2′,4′,6′-trihydroxy chalcone; alpinetin; pinobanksin-3-O-butyrate; and pinocembrin-5-methyl ether were first reported as anti-T2DM agents. We identified the significant T2DM targets of Asian propolis, namely retinol-binding protein-4 (RBP4) and aldose reductase (AKR1B1) that have important roles in insulin sensitivity and diabetes complication, respectively. Molecular dynamic simulations showed stable interaction of selected propolis compounds in the active site of RBP4 and AKR1B1. These findings suggest that Asian propolis compound may be effective for treatment of T2DM by targeting RBP4 and AKR1B1.