Multi-stage virtual screening of natural products against p38α mitogen-activated protein kinase: predictive modeling by machine learning, docking study and molecular dynamics simulation

Development of Potent Type V MAPK Inhibitors: Design, Synthesis, and Biological Evaluation of Benzothiazole Derivatives Targeting p38α MAPK in Breast Cancer Cells

Type V MAPK inhibitors are distinguished by their capacity to target both the ATP binding site and a specific allosteric site on the enzyme. The present work utilized in silico analysis with Maestro 13.8.135 (Schrodinger) software in conjunction with experimental investigations to enhance the antiproliferative efficacy and forecast the likely mechanism of action of benzothiazole derivatives. Approximately 28 compounds were developed, produced, and assessed for their antiproliferative properties against two breast cancer cell lines: ER+ (MCF7) and ER- (MDA-MB-231), in addition to one normal mouse fibroblast cell line (L929). Their antiproliferative activities were evaluated via the MTT test, with doxorubicin and cisplatin serving as reference drugs for comparison. Consequently, the compounds with the greatest activity against the MCF7 cell line were chosen, and their inhibitory effects on the p38α MAPK enzyme were examined. The molecular docking studies of compounds 15 and 19 demonstrated significant binding affinities for p38α MAPK. Molecular dynamics simulations conducted over 100 ns revealed that compounds 15 and 19 exhibit stability inside both the ATP-binding domain and the lipid domain of p38α MAPK. The research focused on creating effective Type V MAPK inhibitors demonstrate that compounds 15 and 19 possess considerable ability to inhibit p38α MAPK, hence establishing them as promising anticancer agents.

Computational analysis of Urolithin A as a potential compound for anti-inflammatory, antioxidant, and neurodegenerative pathways

Urolithin A, an active precursor derived from the metabolism of ellagitanins in rats and humans, is known for its potential health benefits, including stimulating mitophagy and promoting muscular skeletal function. While experimental studies have demonstrated Urolithin A's potential to enhance cellular health, the detailed molecular interactions through which Urolithin A exerts its effects are not fully elucidated. In this study, we investigated the anti-inflammatory, antioxidation and neuroprotective abilities of Urolithin A in selected targets using molecular docking and molecular dynamics simulation methods. Molecular docking studies revealed the strong affinity for receptors involved in inflammation activities, including human p38 MAP kinase (4DLI) with -10.1 kcal/mol interacting with SER252, LYS249, and ASP294 residues. The binding energy in the 5KIR target was -8.6 kcal/mol, interacting with GLN203 through hydrogen bond, and lastly, 1A9U with an affinity of -6.8 with no hydrogen bond formed with Urolithin A and interacts with van der Waals interactions. In oxidant targets, the influence of Urolithin was observed in 1OG5 with -7.9 kcal/mol interacting with GLN185, PHE447. For the 1M17 target, the binding affinity was -7.7 kcal/mol interacting with THR95 residue and 1ZXM target at -7.4 kcal/mol interacting with TYR36, TYR216, and LEU234 residues. The neuroprotective ability of urolithin A was observed in selected targets for acetylcholinesterase; the binding energy was -9.7 kcal/mol interacting with van der Waals and π interactions; for the 1GQR target, the binding energy was -9.9 kcal/mol interacting with van der Waals and π interactions and for β-amylase (1iyt) the binding energy was -5.5 forming hydrogen bond with SER8, GLN15 residues. Molecular Dynamics simulations at 100 ns of Urolithin A compared with reference 4DLI. The Urolithin A-4DLI complex exhibited greater stability than the reference receptor, as confirmed by RMSD, RMSF, Radius of Gyration, Hydrogen bond, and SASA analyses.

Eliciting Callus Cultures for the Production of Cytotoxic Polyphenolics from Maesa indica Roxb. Sweet

Maesa indica Roxb. Sweet is a shrub known for its richness in secondary metabolites. A callus culture protocol was established to enhance its chemical profile. Sixteen elicitation culture treatments were evaluated, and we confirmed that the treatment of 200 mg/L polyethylene glycol (4000) coupled with exposure to 30 W UV irradiation for 60 min (PEG4) resulted in the highest total phenolic and total flavonoid contents, which were 4.1 and 4.9 times those of the plant ethanolic extract and 4.9 and 4.8 times those of a control sample, respectively. The phenolic compounds in the different treatments were identified qualitatively and quantitatively using the LC-ESI-MS/MS-MRM technique. Molecular docking studies of the phenolic compounds were conducted using MOE software and revealed that rutin showed the highest binding affinity toward the anti-cancer target (p38α MAPK). The cytotoxicity of the ME and PEG 4 treatment was tested against colon, breast, prostate, lung, and liver cell lines using an MTT assay. The highest cytotoxic effect of PEG4 was against prostate cancer with an IC50 value of 25.5 µg/mL. Hence, this study showed enhanced secondary metabolite accumulation and identified the phenolic compounds in the 16 treatments. The cytotoxicity assay highlighted the possible cytotoxic effect of the PEG4 treatment, and we recommend further investigations into its activity.

Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review

Traditional Chinese medicine (TCM) is the practical experience and summary of the Chinese nation for thousands of years. It shows great potential in treating various chronic diseases, complex diseases and major infectious diseases, and has gradually attracted the attention of people all over the world. However, due to the complexity of prescription and action mechanism of TCM, the development of TCM industry is still in a relatively conservative stage. With the rise of artificial intelligence technology in various fields, many scholars began to apply artificial intelligence technology to traditional Chinese medicine industry and made remarkable progress. This paper comprehensively summarizes the important role of artificial intelligence in the development of traditional Chinese medicine industry from various aspects, including new drug discovery, data mining, quality standardization and industry technology of traditional Chinese medicine. The limitations of artificial intelligence in these applications are also emphasized, including the lack of pharmacological research, database quality problems and the challenges brought by human-computer interaction. Nevertheless, the development of artificial intelligence has brought new opportunities and innovations to the modernization of traditional Chinese medicine. Integrating artificial intelligence technology into the comprehensive application of Chinese medicine industry is expected to overcome the major problems faced by traditional Chinese medicine industry and further promote the modernization of the whole traditional Chinese medicine industry.

Function and inhibition of P38 MAP kinase signaling: Targeting multiple inflammation diseases

Inflammation is a natural host defense mechanism that protects the body from pathogenic microorganisms. A growing body of research suggests that inflammation is a key factor in triggering other diseases (lung injury, rheumatoid arthritis, etc.). However, there is no consensus on the complex mechanism of inflammatory response, which may include enzyme activation, mediator release, and tissue repair. In recent years, p38 MAPK, a member of the MAPKs family, has attracted much attention as a central target for the treatment of inflammatory diseases. However, many p38 MAPK inhibitors attempting to obtain marketing approval have failed at the clinical trial stage due to selectivity and/or toxicity issues. In this paper, we discuss the mechanism of p38 MAPK in regulating inflammatory response and its key role in major inflammatory diseases and summarize the synthetic or natural products targeting p38 MAPK to improve the inflammatory response in the last five years, which will provide ideas for the development of novel clinical anti-inflammatory drugs based on p38 MAPK inhibitors.

Targeting Melanoma with a phytochemical pool: Tailing Makisterone C

BACKGROUND AND OBJECTIVE

According to World Health Organization, melanoma claims the lives of about 48000 people worldwide each year. The purpose of this study was to identify potential phytochemical pool from Diplazium esculentum against proteins that contribute to melanoma development.

METHODS

The research was carried to locate potentially bioactive molecules and conduct a theoretical analysis of active ingredients from DE to impact melanoma. Network pharmacology, pharmacokinetics, protein network interaction, gene enrichment, survival, and infiltration analysis were conducted. Furthermore, molecular docking and molecular dynamics simulation was carried out for makisterone C-MAPK1, MAPK3, and AKT1 complexes.

RESULTS

The potential phytochemical pool were identified (stigmast-5-en-3-ol, esculentic acid, rutin, and makisterone C) and based on network pharmacology and molecular docking studies, makisterone-C was proposed to be the most promising ingredient. Furthermore, the investigation revealed 14 genes as critical "hubs" involved in combating melanoma that are manipulated by the above-mentioned 4 active ingredients and modulate multiple signaling in melanoma development.

CONCLUSION

This study insights into the potential anti-melanoma effects of phytochemical pool from Diplazium esculentum using network pharmacology analysis, molecular docking, and simulation tailing makisterone C as a lead moiety and suggests the need for makisterone C further evaluation in intervening melanoma progression.