Molecular docking and molecular dynamics simulation study the mechanism of progesterone in the treatment of spinal cord injury.

PURPOSE: Spinal cord injury can lead to incomplete or complete loss of voluntary movement and sensory function, leading to serious complications. Numerous studies have shown that progesterone exhibits strong therapeutic potential for spinal cord injury. However, the mechanism by which progesterone treats spinal cord injury remains unclear. Therefore, this article explores the mechanism of progesterone in the treatment of spinal cord injury by means of molecular docking and molecular dynamics simulation. METHODS: We used bioinformatics to screen active pharmaceutical ingredients and potential targets, and molecular docking and molecular dynamics were used to validate and analysis by the supercomputer platform. RESULTS: Progesterone had 3606 gene targets, spinal cord injury had 6560 gene targets, the intersection gene targets were 2355. GO and KEGG analysis showed that the abundant pathways involved multiple pathways related to cell metabolism and inflammation. Molecular docking showed that progesterone played a role in treating spinal cord injury by acting on BDNF, AR, NGF and TNF. Molecular dynamics was used to prove and analyzed the binding stability of active ingredients and protein targets, and AR/Progesterone combination has the strongest binding energy. CONCLUSION: Progesterone promotes recovery from spinal cord injury by promoting axonal regeneration, remyelination, neuronal survival and reducing inflammation.

Exploring the mechanism of action of dapansutrile in the treatment of gouty arthritis based on molecular docking and molecular dynamics.

Purpose: Dapansutrile is an orally active ß-sulfonyl nitrile compound that selectively inhibits the NLRP3 inflammasome. Clinical studies have shown that dapansutrile is active in vivo and limits the severity of endotoxin-induced inflammation and joint arthritis. However, there is currently a lack of more in-depth research on the effect of dapansutrile on protein targets such as NLRP3 in gouty arthritis. Therefore, we used molecular docking and molecular dynamics to explore the mechanism of dapansutrile on NLRP3 and other related protein targets. Methods: We use bioinformatics to screen active pharmaceutical ingredients and potential disease targets. The disease-core gene target-drug network was established and molecular docking was used for verification. Molecular dynamics simulations were utilized to verify and analyze the binding stability of small molecule drugs to target proteins. The supercomputer platform was used to measure and analyze the binding free energy, the number of hydrogen bonds, the stability of the protein target at the residue level, the radius of gyration and the solvent accessible surface area. Results: The protein interaction network screened out the core protein targets (such as: NLRP3, TNF, IL1B) of gouty arthritis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that gouty arthritis mainly played a vital role by the signaling pathways of inflammation and immune response. Molecular docking showed that dapansutrile play a role in treating gouty arthritis by acting on the related protein targets such as NLRP3, IL1B, IL6, etc. Molecular dynamics was used to prove and analyze the binding stability of active ingredients and protein targets, the simulation results found that dapansutrile forms a very stable complex with IL1B. Conclusion: We used bioinformatics analysis and computer simulation system to comprehensively explore the mechanism of dapansutrile acting on NLRP3 and other protein targets in gouty arthritis. This study found that dapansutrile may not only directly inhibit NLRP3 to reduce the inflammatory response and pyroptosis, but also hinder the chemotaxis and activation of inflammatory cells by regulating IL1B, IL6, IL17A, IL18, MMP3, CXCL8, and TNF. Therefore, dapansutrile treats gouty arthritis by attenuating inflammatory response, inflammatory cell chemotaxis and extracellular matrix degradation by acting on multiple targets.

Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics.

Purpose: The research aims to investigate the mechanism of action of aspirin in the treatment of Kawasaki disease. Methods: We predicted the targets of aspirin with the help of the Drugbank and PharmMapper databases, the target genes of Kawasaki disease were mined in the GeneCards and Disgenet databases, the intersection targets were processed in the Venny database, and the gene expression differences were observed in the GEO database. The Drugbank and PharmMapper databases were used to predict the target of aspirin, and the target genes of Kawasaki disease were explored in the GeneCards and Disgenet databases, and the Venny was used for intersection processing. We observed the gene expression differences in the GEO database. The disease-core gene target-drug network was established and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the binding free energy, the number of hydrogen bonds, the stability of the protein target at the residue level, the radius of gyration, and the solvent accessible surface area. Results: Aspirin had 294 gene targets, Kawasaki disease had 416 gene targets, 42 intersecting targets were obtained, we screened 13 core targets by PPI; In the GO analysis, we learned that the biological process of Kawasaki disease involved the positive regulation of chemokine biosynthesis and inflammatory response; pathway enrichment involved PI3K-AKT signaling pathway, tumor necrosis factor signaling pathway, etc. After molecular docking, the data showed that CTSG, ELANE, and FGF1 had the best binding degree to aspirin. Molecular dynamics was used to prove and analyze the binding stability of active ingredients and protein targets, and Aspirin/ELANE combination has the strongest binding energy. Conclusion: In the treatment of Kawasaki disease, aspirin may regulate inflammatory response and vascular remodeling through CTSG, ELANE, and FGF1.

Exploring the mechanism of action of Xuanfei Baidu granule (XFBD) in the treatment of COVID-19 based on molecular docking and molecular dynamics.

Purpose: The Corona Virus Disease 2019 (COVID-19) pandemic has become a challenge of world. The latest research has proved that Xuanfei Baidu granule (XFBD) significantly improved patient's clinical symptoms, the compound drug improves immunity by increasing the number of white blood cells and lymphocytes, and exerts anti-inflammatory effects. However, the analysis of the effective monomer components of XFBD and its mechanism of action in the treatment of COVID-19 is currently lacking. Therefore, this study used computer simulation to study the effective monomer components of XFBD and its therapeutic mechanism. Methods: We screened out the key active ingredients in XFBD through TCMSP database. Besides GeneCards database was used to search disease gene targets and screen intersection gene targets. The intersection gene targets were analyzed by GO and KEGG. The disease-core gene target-drug network was analyzed and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the number of hydrogen bonds, the binding free energy, the stability of protein target at the residue level, the solvent accessible surface area, and the radius of gyration. Results: XFBD had 1308 gene targets, COVID-19 had 4600 gene targets, the intersection gene targets were 548. GO and KEGG analysis showed that XFBD played a vital role by the signaling pathways of immune response and inflammation. Molecular docking showed that I-SPD, Pachypodol and Vestitol in XFBD played a role in treating COVID-19 by acting on NLRP3, CSF2, and relieve the clinical symptoms of SARS-CoV-2 infection. Molecular dynamics was used to prove the binding stability of active ingredients and protein targets, CSF2/I-SPD combination has the strongest binding energy. Conclusion: For the first time, it was found that the important active chemical components in XFBD, such as I-SPD, Pachypodol and Vestitol, reduce inflammatory response and apoptosis by inhibiting the activation of NLRP3, and reduce the production of inflammatory factors and chemotaxis of inflammatory cells by inhibiting the activation of CSF2. Therefore, XFBD can effectively alleviate the clinical symptoms of COVID-19 through NLRP3 and CSF2.