In silico study of garlic (Allium sativum L.)-derived compounds molecular interactions with α-glucosidase

Unlocking the potential of chicken liver byproducts: Identification of antioxidant peptides through in silico approaches and anti-aging effects of a selected peptide in Caenorhabditis elegans

Chicken meat processing generates a substantial number of byproducts, which are either underutilized or improperly disposed. In this study, we employed in silico approaches to identify antioxidant peptides in chicken liver byproducts. Notably, the peptide WYR exhibited remarkable 2,2-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) radical scavenging activity with an IC50 of 0.13 ± 0.01 mg/mL and demonstrated stability under various conditions, including thermal, pH, NaCl, and simulated gastrointestinal digestion. Molecular docking analysis revealed significant hydrogen bonding interactions, while molecular dynamics showed differential stability with ABTS and 2,2-Diphenyl-1-picrylhydrazyl (DPPH). WYR exhibited improved stress resistance, decreased levels of reactive oxygen species (ROS), elevated the activities of superoxide dismutase (SOD) and catalase (CAT), and modulated the expression of crucial genes through the insulin/insulin-like growth factor (IIS) signaling pathway, mitogen-activated protein kinase (MAPK), and heat shock transcription factor-1 (HSF-1) pathways. These effects collectively contributed to the extension of Caenorhabditis elegans' lifespan. This study not only provides an effective method for antioxidant peptide analysis but also highlights the potential for enhancing the utilization of poultry byproducts.

Antidiabetic Activity, Molecular Docking, and ADMET Properties of Compounds Isolated from Bioactive Ethyl Acetate Fraction of Ficus lutea Leaf Extract

Diabetes contributes to the rising global death rate. Despite scientific advancements in understanding and managing diabetes, no single therapeutic agent has been identified to effectively treat and prevent its progression. Consequently, the exploration for new antidiabetic therapeutics continues. This study aimed to investigate the antidiabetic bioactive ethyl acetate fraction of F. lutea at the molecular level to understand the molecular interactions and ligand-protein binding. To do this, the fraction underwent column chromatography fractionation to yield five compounds: lupeol, stigmasterol, α-amyrin acetate, epicatechin, and epiafzelechin. These compounds were evaluated in vitro through α-glucosidase inhibition and glucose utilization assays in C2C12 muscle and H-4-11-E liver cells using standard methods. In silico analysis was conducted using molecular docking and ADMET studies. Epicatechin exhibited the most potent α-glucosidase inhibition (IC50 = 5.72 ± 2.7 µg/mL), while epiafzelechin stimulated superior glucose utilization in C2C12 muscle cells (33.35 ± 1.8%) and H-4-11-E liver cells (46.7 ± 1.2%) at a concentration of 250 µg/mL. The binding energies of the isolated compounds for glycogen phosphorylase (1NOI) and α-amylase (1OSE) were stronger (<-8.1) than those of the positive controls. Overall, all tested compounds exhibited characteristics indicative of their potential as antidiabetic agents; however, toxicity profiling predicted epiafzelechin and epicatechin as better alternatives. The ethyl acetate fraction and its compounds, particularly epiafzelechin, showed promise as antidiabetic agents. However, further comprehensive studies are necessary to validate these findings.

Influence of Garlic on the Glycemic Control and Lipid Profile in Animals with Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-analysis

Nonalcoholic fatty liver disease is the hepatic sign of metabolic syndrome. Here, we aimed to assess the effects of garlic and its major components on fasting plasma glucose, fasting insulin, and lipid profile levels in animal models of nonalcoholic fatty liver disease. A systematic search in PubMed, Scopus, ProQuest, and Web of Science was performed. After the screening process and data extraction, the pooled effect sizes were estimated using a random-effect model and stated as standardized mean differences and a 95% confidence interval. Out of 839 reports, 22 articles were included in the present study. The pooled results revealed that garlic and its components significantly decreased fasting plasma glucose (standardized mean difference: - 0.77, 95% confidence interval: - 1.42 to - 0.12, I2 : 58.85%), fasting insulin (standardized mean difference: - 1.88, 95% confidence interval: - 3.07 to - 0.69, I2 : 70.42%), serum triglyceride (standardized mean difference: - 1.01, 95% confidence interval: - 1.43 to - 0.59, I2 : 61.41%), cholesterol (standardized mean difference: - 1.00, 95% confidence interval: - 1.39 to - 0.60, I2 : 52.12%), and low-density lipoprotein cholesterol (standardized mean difference: - 0.98, 95% CI: - 1.63 to - 0.32, I2 : 71.58%) and increased high-density lipoprotein cholesterol (standardized mean difference: 1.05, 95% confidence interval: 0.52 to 1.58, I2 : 59.39%) levels. The type of animal, nonalcoholic fatty liver disease induction model, kind and duration of intervention, study model, and risk of bias were detected as possible sources of heterogeneity across studies. We conclude that garlic and its major components have a favorable impact on glycemic control and lipid profile in diet-induced nonalcoholic fatty liver disease animal models.

In-silico targeting TMPK from monkey pox virus: Molecular docking analysis, density functional theory studies and molecular dynamic simulation analysis

The World Health Organization (WHO) proclaimed the monkeypox epidemic a "public health emergency of worldwide significance" recently. The monkeypox virus is a member of the same Orthopoxvirus genus as the smallpox virus. Although smallpox medications are advised against monkeypox, no monkeypox-specific drugs are currently available. In the event of such an outbreak, in-silico medication identification is a practical and efficient strategy. As a result, we report a computational drug repurposing analysis to discover medicines that may be potential inhibitors of thymidylate kinase, a critical monkeypox viral enzyme. The target protein structure of the monkeypox virus was modeled using the vaccinia virus's homologous protein structure. Using molecular docking and density functional theory, we found 11 possible inhibitors of the monkeypox virus from an Asinex library of 261120 chemicals. The primary purpose of this in silico work is to find possible inhibitors of monkeypox viral proteins that can then be experimentally tested in order to develop innovative therapeutic medicines for monkeypox infection.Communicated by Ramaswamy H. Sarma.

Discovery of the new alpha-glucosidase inhibitor with therapeutic potential in type 2 diabetes mellitus by a novel high-throughput virtual screening and free energy evaluation

Type 2 diabetes can cause a variety of complications, significantly affecting people's health. Given their ability to suppress carbohydrate digestion, alpha-glucosidase inhibitors are effective treatments for diabetes. However, the current approved glucosidase inhibitors' side effects of abdominal discomfort limit their use. We used the compound Pg3R from the natural fruit berry as a reference, screening against a large database of 22 million compounds to identify potential health-friendly alpha-glucosidase inhibitors. Ligand-based screening enables us to identify 3968 ligands that exhibit structural similarity compared to the natural compound. These lead hits were used for LeDock, and their binding free energies were evaluated by MM/GBSA. Among the top-scoring candidates, ZINC263584304 exhibited the strongest binding affinity to alpha-glucosidase, with a "low-fat" structural characteristic. Its recognition mechanism was further investigated by microsecond MD simulations and free energy landscapes, exhibiting novel conformational changes during the binding process. Our study provided a novel alpha-glucosidase inhibitor with the potential to treat type 2 diabetes.

Control of eriocitrin release from pH-sensitive gelatin-based microgels to inhibit α-glucosidase: an experimental and computational study

α-Glucosidase is among the intestinal epithelial enzymes that produce absorbable glucose in the final stage of glycan catabolism. It leads to an increase in blood glucose levels as a result of high glucose uptake in diabetic patients. However, inhibition of this essential biochemical process can be a useful therapeutic approach to diabetes mellitus (DM). Eriocitrin (ER) is an abundant "flavanone glycoside" in citrus fruits with rich antioxidant properties whose effects on α-Glu inhibition in the small intestine remain to be determined. Herein, pH-sensitive microgels (MGs) were designed based on cross-linked methacrylate with acrylamide (AM) and acrylic acid (AAc) (molar ratio 70 : 30 of AAc : AM) as a controlled release system for sustained delivery of ER into the small intestine. The presence of amide and acrylate in MGs and the mechanical resistance were determined using FT-IR spectroscopy, rheology, and viscoelastometry. In vitro experiments showed that MGs could protect ER against diffusion in the gastric location and adjust its release in the intestinal milieu. The intestinal α-Glu activity was inhibited by ER (IC₅₀ value of 12.50 ± 0.73 μM) in an uncompetitive dose-dependent manner. The presence of ER altered the structure of α-Glu and reduced the hydrophobic pockets of the enzyme. Molecular docking analysis along with molecular dynamics simulation displayed that ER-α-Glu formation is directed by hydrogen binding with Asp69, Asp215, Glu411, Asp307, and Tyr347 residues. Moreover, in vivo assessment showed that rat blood glucose concentration decreased after ER administration compared with the control group. The results highlight that ER-loaded-MGs can be considered as a useful releasing strategy in treating DM via α-Glu inhibition.

Designing a Multi-Epitope Antigen for Serodiagnosis of Strongyloides stercoralis Based on L3Nie.01 and IgG Immunoreactive Epitopes

Background

Serological diagnosis of Strongyloides stercoralis (S. stercoralis) is fre-quently challenging because of cross-reactivity with other parasitic nematodes. Therefore, it is necessary to introduce novel serological tests with high performance to properly diagnose this neglected parasitic infection. The purpose of the current study was to design a multi-epitope construct for the diagnosis of S. stercoralis.

Methods

For the purpose of this study, first, highly antigenic segments and potential immunodominant epitopes of S. stercoralis were identified from two antigenic proteins, and then all of the selected parts were linked by an appropriate linker. Next, the physicochemical features of the designed construct were analyzed. Then, tertiary structures of the construct were built and evaluated to find out the best one. Lastly, the amino acid sequence was reverse-translated and optimized for over-expression in Escherchia coli (E. coli).

Results

The bioinformatic evaluation indicated that the designed protein construct could be hydrophilic, thermostable, and acidic and the estimated half-life was more than 10 hr in E. coli.

Conclusion

According to the results of the study, the designed construct could be used as an efficient antigen in the ELISA system for serological diagnosis of human strong-yloidiasis.

Inhibitory effects of selected isoquinoline alkaloids against main protease (Mpro) of SARS-CoV-2, in silico study

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global threat. Despite the production of various vaccines and different treatments, finding natural compounds to control COVID-19 is still a challenging task. Isoquinoline alkaloids are naturally occurring compounds known to have some potential antiviral activity. In this study, ten abundant isoquinoline alkaloids with antiviral activity were selected to analyze the preventive effect on COVID-19. A scrutinized evaluation based on Lipinski’s rule showed that one out of ten compounds was toxic. Based on molecular docking analysis using Autodock software one of the best molecules with maximum negative binding energy was selected for further analysis. The Gromacs simulation analysis revealed that Coptisine has more action against active site M^pro of COVID-19. Overall, to make a rational design of various preventive analogues that inhibit the COVID-19, associated in vitro and in vivo analyses are needed to confirm this claim.

A contemporary review on the important role of in silico approaches for managing different aspects of COVID-19 crisis

In the last century, the emergence of in silico tools has improved the quality of healthcare studies by providing high quality predictions. In the case of COVID-19, these tools have been advantageous for bioinformatics analysis of SARS-CoV-2 structures, studying potential drugs and introducing drug targets, investigating the efficacy of potential natural product components at suppressing COVID-19 infection, designing peptide-mimetic and optimizing their structure to provide a better clinical outcome, and repurposing of the previously known therapeutics. These methods have also helped medical biotechnologists to design various vaccines; such as multi-epitope vaccines using reverse vaccinology and immunoinformatics methods, among which some of them have showed promising results through in vitro, in vivo and clinical trial studies. Moreover, emergence of artificial intelligence and machine learning algorithms have helped to classify the previously known data and use them to provide precise predictions and make plan for future of the pandemic condition. At this contemporary review, by collecting related information from the collected literature on valuable data sources; such as PubMed, Scopus, and Web of Science, we tried to provide a brief outlook regarding the importance of in silico tools in managing different aspects of COVID-19 pandemic infection and how these methods have been helpful to biomedical researchers.

Screening cyclooxygenase-2 inhibitors from Allium sativum L. compounds: in silico approach

Inflammation is a natural protective response toward various simulators, including tissue damage or pathogens. The cyclooxygenase-2 (COX-2) is a very important protein in triggering pain and inflammation. Previous studies have claimed that Allium sativum offers a wide range of anti-inflammatory therapeutics for human consumption. Drug discovery is a complicated process, though in silico methods can make this procedure simpler and more cost-effective. At the current study, we performed the virtual screening of eight Allium sativum-derived compounds via molecular docking with COX-2 enzyme and confirmed the binding energy by docking score estimate followed by ADMET and drug-likeness investigation. The resulting highest-docking scored compound was exposed to molecular dynamics simulation (MDS) for evaluating stability of the docked enzyme-ligand complex and to gauge the oscillation and conformational alterations for the time of enzyme-ligand interaction. The factors of RMSD, RMSF, hydrogen bond interactions, and Rg after 100 ns of MDS proved the stability of alliin in the active site of COX-2 in comparison with celecoxib (CEL) as the control. Moreover, we investigated the binding affinity analysis of all compounds via MM/PBSA method. The results from this study suggest that alliin (a sulfuric compound) exhibits a higher binding affinity for the COX-2 enzyme compared to the other compounds and CEL. Alliin showed to be a possible anti-inflammatory therapeutic candidate for managing the inflammatory conditions.

Synthesis, antibacterial and antioxidant activities of Thiazole-based Schiff base derivatives: a combined experimental and computational study

BACKGROUND

Thiazole-based Schiff base compounds display significant pharmacological potential with an ability to modulate the activity of many enzymes involved in metabolism. They also demonstrated to have antibacterial, antifungal, anti-inflammatory, antioxidant, and antiproliferative activities. In this work, conventional and green approaches using ZnO nanoparticles as catalyst were used to synthesize thiazole-based Schiff base compounds.

RESULTS

Among the synthesized compounds, 11 showed good activities towards Gram-negative E. coli (14.40 ± 0.04), and Gram-positive S. aureus (15.00 ± 0.01 mm), respectively, at 200 μg/mL compared to amoxicillin (18.00 ± 0.01 mm and 17.00 ± 0.04). Compounds 7 and 9 displayed better DPPH radical scavenging potency with IC50 values of 3.6 and 3.65 μg/mL, respectively, compared to ascorbic acid (3.91 μg/mL). The binding affinity of the synthesized compounds against DNA gyrase B is within - 7.5 to - 6.0 kcal/mol, compared to amoxicillin (- 6.1 kcal/mol). The highest binding affinity was achieved for compounds 9 and 11 (- 6.9, and - 7.5 kcal/mol, respectively). Compounds 7 and 9 displayed the binding affinity values of - 5.3 to - 5.2 kcal/mol, respectively, against human peroxiredoxin 5. These values are higher than that of ascorbic acid (- 4.9 kcal/mol), in good agreement with the experimental findings. In silico cytotoxicity predictions showed that the synthesized compounds Lethal Dose (LD50) value are class three (50 ≤ LD50 ≤ 300), indicating that the compounds could be categorized under toxic class. Density functional theory calculations showed that the synthesized compounds have small band gap energies ranging from 1.795 to 2.242 eV, demonstrating that the compounds have good reactivities.

CONCLUSIONS

The synthesized compounds showed moderate to high antibacterial and antioxidant activities. The in vitro antibacterial activity and molecular docking analysis showed that compound 11 is a promising antibacterial therapeutics agent against E. coli, whereas compounds 7 and 9 were found to be promising antioxidant agents. Moreover, the green synthesis approach using ZnO nanoparticles as catalyst was found to be a very efficient method to synthesize biologically active compounds compared to the conventional method.

Pharmacokinetics and drug-likeness of antidiabetic flavonoids: Molecular docking and DFT study

Computer aided toxicity and pharmacokinetic prediction studies attracted the attention of pharmaceutical industries as an alternative means to predict potential drug candidates. In the present study, in-silico pharmacokinetic properties (ADME), drug-likeness, toxicity profiles of sixteen antidiabetic flavonoids that have ideal bidentate chelating sites for metal ion coordination were examined using SwissADME, Pro Tox II, vNN and ADMETlab web tools. Density functional theory (DFT) calculations were also employed to calculate quantum chemical descriptors of the compounds. Molecular docking studies against human alpha amylase were also conducted. The results were compared with the control drugs, metformin and acarbose. The drug-likeness prediction results showed that all flavonoids, except myricetin, were found to obey Lipinski's rule of five for their drug like molecular nature. Pharmacokinetically, chrysin, wogonin, genistein, baicalein, and apigenin showed best absorption profile with human intestinal absorption (HIA) value of ≥ 30%, compared to the other flavonoids. Baicalein, butein, ellagic acid, eriodyctiol, Fisetin and quercetin were predicted to show carcinogenicity. The flavonoid derivatives considered in this study are predicted to be suitable molecules for CYP3A probes, except eriodyctiol which interacts with P-glycoprotein (p-gp). The toxicological endpoints prediction analysis showed that the median lethal dose (LD50) values range from 159-3919 mg/Kg, of which baicalein and quercetin are found to be mutagenic whereas butein is found to be the only immunotoxin. Molecular docking studies showed that the significant interaction (-7.5 to -8.3 kcal/mol) of the studied molecules in the binding pocket of the α-amylase protein relative to the control metformin with the crucial amino acids Asp 197, Glu 233, Asp 197, Glu 233, Trp 59, Tyr 62, His 101, Leu 162, Arg 195, His 299 and Leu 165. Chrysin was predicted to be a ligand with high absorption and lipophilicity with 84.6% absorption compared to metformin (78.3%). Moreover, quantum chemical, ADMET, drug-likeness and molecular docking profiles predicted that chrysin is a good bidentate ligand.