Network Pharmacology Integrated Molecular Docking Reveals the Mechanism of Anisodamine Hydrobromide Injection against Novel Coronavirus Pneumonia

Background. The Coronavirus Disease 2019 (COVID-19) outbreak in Wuhan, China, was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Anisodamine hydrobromide injection (AHI), the main ingredient of which is anisodamine, is a listed drug for improving microcirculation in China. Anisodamine can improve the condition of patients with COVID-19. Materials and Methods. Protein-protein interactions obtained from the String databases were used to construct the protein interaction network (PIN) of AHI using Cytoscape. The crucial targets of AHI PIN were screened by calculating three topological parameters. Gene ontology and pathway enrichment analyses were performed. The intersection between the AHI component proteins and angiotensin-converting enzyme 2 (ACE2) coexpression proteins was analyzed. We further investigated our predictions of crucial targets by performing molecular docking studies with anisodamine. Results. The PIN of AHI, including 172 nodes and 1454 interactions, was constructed. A total of 54 crucial targets were obtained based on topological feature calculations. The results of Gene Ontology showed that AHI could regulate cell death, cytokine-mediated signaling pathways, and immune system processes. KEGG disease pathways were mainly enriched in viral infections, cancer, and immune system diseases. Between AHI targets and ACE2 coexpression proteins, 26 common proteins were obtained. The results of molecular docking showed that anisodamine bound well to all the crucial targets. Conclusion. The network pharmacological strategy integrated molecular docking to explore the mechanism of action of AHI against COVID-19. It provides protein targets associated with COVID-19 that may be further tested as therapeutic targets of anisodamine.

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Studies on the Mechanism of Gegen Qinlian Decoction in Treating Diabetes Mellitus Based on Network Pharmacology

Natural Product Communications ◽

10.1177/1934578x20982138 ◽

2021 ◽

Vol 16 (1) ◽

pp. 1934578X2098213

Author(s):

Xiaodong Deng ◽

Yuhua Liang ◽

Jianmei Hu ◽

Yuhui Yang

Keyword(s):

Diabetes Mellitus ◽

Molecular Docking ◽

Protein Interaction ◽

Protein Interaction Network ◽

Interaction Network ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Network Pharmacology ◽

Hub Genes ◽

Topological Parameters

Diabetes mellitus (DM) is a chronic disease that is very common and seriously threatens patient health. Gegen Qinlian decoction (GQD) has long been applied clinically, but its mechanism in pharmacology has not been extensively and systematically studied. A GQD protein interaction network and diabetes protein interaction network were constructed based on the methods of system biology. Functional module analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Gene Ontology (GO) enrichment analysis were carried out on the 2 networks. The hub nodes were filtered by comparative analysis. The topological parameters, interactions, and biological functions of the 2 networks were analyzed in multiple ways. By applying GEO-based external datasets to verify the results of our analysis that the Gene Set Enrichment Analysis (GSEA) displayed metabolic pathways in which hub genes played roles in regulating different expression states. Molecular docking is used to verify the effective components that can be combined with hub nodes. By comparing the 2 networks, 24 hub targets were filtered. There were 7 complex relationships between the networks. The results showed 4 topological parameters of the 24 selected hub targets that were much higher than the median values, suggesting that these hub targets show specific involvement in the network. The hub genes were verified in the GEO database, and these genes were closely related to the biological processes involved in glucose metabolism. Molecular docking results showed that 5,7,2', 6'-tetrahydroxyflavone, magnograndiolide, gancaonin I, isoglycyrol, gancaonin A, worenine, and glyzaglabrin produced the strongest binding effect with 10 hub nodes. This compound–target mode of interaction may be the main mechanism of action of GQD. This study reflected the synergistic characteristics of multiple targets and multiple pathways of traditional Chinese medicine and discussed the mechanism of GQD in the treatment of DM at the molecular pharmacological level.

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Network Pharmacology Approach uncovering Pathways involved in targeting Hsp90 through Curcumin and Epigallocatechin to control Inflammation.

Current Drug Discovery Technologies ◽

10.2174/1570163816666191210145652 ◽

2019 ◽

Vol 16 ◽

Author(s):

Umme Hani ◽

Shivananda Kandagalla ◽

B.S. Sharath ◽

K Jyothsna. ◽

H Manjunatha.

Keyword(s):

Gene Ontology ◽

Molecular Chaperones ◽

Curcuma Longa ◽

Interaction Network ◽

Network Pharmacology ◽

Heme Oxygenase 1 ◽

Nrf2 Pathway ◽

Functional Behavior ◽

Inflammatory Proteins ◽

Prime Target

: Hsp90 are molecular chaperones of chronic inflammatory proteins and have emerged as prime target for treatment of inflammation. Principal components from Curcuma longa and Camellia sinensis, Curcumin and EGC respectively possesses anti-inflammatory properties inhibiting cytokines responsible for inflammation. Both act on common pathways in upregulation of heme oxygenase 1 through Pkcδ-Nrf2 pathway and downregulation of Tlr4, which in turn suppress expression of Hsp90. Curcumin and EGC were also found to bind -N and -C terminal domain of Hsp90 respectively. Based on this, work was designed with network pharmacological approach. Hsp90 associated gene targets of Curcumin and EGC were collected from databases, and gene ontology studies were done. PPI were obtained from string database for specific genes involved in Pkcδ-Nrf2 and Tlr4 pathway. Protein interaction network was constructed by cytoscape, and networks of Hsp90, Curcumin and EGC were merged to get common genes involved in Pkcδ-Nrf2 and Tlr4 pathway. Cluego analysis was done for obtained common genes to identify functional behavior in human diseases. Main proteins involved were identified as key regulators in Pkcδ-Nrf2 and Tlr4 pathway for controlling expression of Hsp90 from Curcumin and EGC in inflammation. Docking was performed on main proteins, Hsp90, Pkcδ and Tlr4 with Curcumin and EGC, significant binding energy was obtained for docked complexes. Combinatorial effects of Curcumin and EGC were observed in Pkcδ-Nrf2 and Tlr4pathway. Present study is an attempt to unravel common pathways mediated in intervention of Curcumin and EGC for suppression of Hsp90 associated with inflammation.

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Mechanism of Compound Houttuynia Mixture as an Anti-COVID-19 Drug Based on Network Pharmacology and Molecular Docking

Natural Product Communications ◽

10.1177/1934578x211016727 ◽

2021 ◽

Vol 16 (5) ◽

pp. 1934578X2110167

Author(s):

Xing-Pan Wu ◽

Tian-Shun Wang ◽

Zi-Xin Yuan ◽

Yan-Fang Yang ◽

He-Zhen Wu

Keyword(s):

Molecular Docking ◽

Target Prediction ◽

Interaction Network ◽

Scientific Basis ◽

Network Pharmacology ◽

Chemical Components ◽

Active Components ◽

Discovery Studio ◽

The Core ◽

Pathway Annotation

Objective To explore the anti-COVID-19 active components and mechanism of Compound Houttuynia mixture by using network pharmacology and molecular docking. Methods First, the main chemical components of Compound Houttuynia mixture were obtained by using the TCMSP database and referring to relevant chemical composition literature. The components were screened for OB ≥30% and DL ≥0.18 as the threshold values. Then Swiss Target Prediction database was used to predict the target of the active components and map the targets of COVID-19 obtained through GeneCards database to obtain the gene pool of the potential target of COVID-19 resistance of the active components of Compound Houttuynia mixture. Next, DAVID database was used for GO enrichment and KEGG pathway annotation of targets function. Cytoscape 3.8.0 software was used to construct a “components-targets-pathways” network. Then String database was used to construct a “protein-protein interaction” network. Finally, the core targets, SARS-COV-2 3 Cl, ACE2 and the core active components of Compound Houttuyna Mixture were imported into the Discovery Studio 2016 Client database for molecular docking verification. Results Eighty-two active compounds, including Xylostosidine, Arctiin, ZINC12153652 and ZINC338038, were screened from Compound Houttuyniae mixture. The key targets involved 128 targets, including MAPK1, MAPK3, MAPK8, MAPK14, TP53, TNF, and IL6. The HIF-1 signaling, VEGF signaling, TNF signaling and another 127 signaling pathways associated with COVID-19 were affected ( P < 0.05). From the results of molecular docking, the binding ability between the selected active components and the core targets was strong. Conclusion Through the combination of network pharmacology and molecular docking technology, this study revealed that the therapeutic effect of Compound Houttuynia mixture on COVID-19 was realized through multiple components, multiple targets and multiple pathways, which provided a certain scientific basis of the clinical application of Compound Houttuynia mixture.

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IN SILICO STUDIES ON FUNCTIONALIZED AZAGLYCINE DERIVATIVES CONTAINING 2, 4-THIAZOLIDINEDIONE SCAFFOLD ON MULTIPLE TARGETS

International Journal of Pharmacy and Pharmaceutical Sciences ◽

10.22159/ijpps.2017v9i8.19835 ◽

2017 ◽

Vol 9 (8) ◽

pp. 209 ◽

Cited By ~ 4

Author(s):

Arifa Begum ◽

Shaheen Begum ◽

Prasad Kvsrg ◽

Bharathi K.

Keyword(s):

Molecular Docking ◽

Oral Bioavailability ◽

In Silico ◽

Viral Infections ◽

Target Prediction ◽

Docking Studies ◽

Antidiabetic Activity ◽

Molecular Docking Studies ◽

In Silico Studies ◽

Glycine Derivative

Objective: The 2, 4-thiazolidinedione containing compounds could lead to most promising scaffolds with higher efficiency toward the targets recognized for its antidiabetic activity when combined with azaglycine moiety. The objective of the present work was to merge functionalized aza glycines with 2, 4-thiazolidinediones, perform in silico evaluation by molecular properties prediction and undertake the molecular docking studies with targets relevant to diabetes, bacterial and viral infections using Swiss Dock programme for unraveling the target identification which can be used for further designing.Methods: (i) In silico studies were performed using Molinspiration online tool, Swiss ADME website and Swiss Target Prediction websites to compute the physicochemical descriptors, oral bioavailability and brain penetration. (ii) Molecular docking studies were performed using Swiss Dock web service for enumeration of binding affinities and assess their biological potentiality.Results: The results predicted good drug likeness, solubility, permeability and oral bioavailability for the compounds. All the compounds showed good docking scores as compared to the reference drugs. The N-oleoyl functionalized aza glycine derivative demonstrated superior binding properties towards all the studied target reference proteins, suggesting its significance in pharmacological actions.Conclusion: The binding interactions observed in the molecular docking studies suggest good binding affinity of the oleoyl functionalized aza glycine derivative, indicating that this derivative would be a promising lead for further investigations of anti-viral, anti-inflammatory and anti-diabetic activities.

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Elucidating the Mechanisms of Action of Lianhua Qingwen decoction for the Treatment of COVID-19 via Systems Pharmacology Approaches

10.21203/rs.3.rs-21103/v2 ◽

2021 ◽

Author(s):

Xiting Wang ◽

Tao Lu

Keyword(s):

Molecular Docking ◽

Blood Circulation ◽

Interaction Network ◽

Enrichment Analysis ◽

Detection Algorithm ◽

Network Pharmacology ◽

Systems Pharmacology ◽

Protein Protein Interaction ◽

Further Development ◽

Protein Protein Interaction Network

Abstract Due to the severity of the COVID-19 epidemic, to identify a proper treatment for COVID-19 is of great significance. Traditional Chinese Medicine (TCM) has shown its great potential in the prevention and treatment of COVID-19. One of TCM decoction, Lianhua Qingwen decoction displayed promising treating efficacy. Nevertheless, the underlying molecular mechanism has not been explored for further development and treatment. Through systems pharmacology and network pharmacology approaches, we explored the potential mechanisms of Lianhua Qingwen treating COVID-19 and acting ingredients of Lianhua Qingwen decoction for COVID-19 treatment. Through this way, we generated an ingredients-targets database. We also used molecular docking to screen possible active ingredients. Also, we applied the protein-protein interaction network and detection algorithm to identify relevant protein groupings of Lianhua Qingwen. Totally, 605 ingredients and 1,089 targets were obtained. Molecular Docking analyses revealed that 35 components may be the promising acting ingredients, 7 of which were underlined according to the comprehensive analysis. Our enrichment analysis of the 7 highlighted ingredients showed relevant significant pathways that could be highly related to their potential mechanisms, e.g. oxidative stress response, inflammation, and blood circulation. In summary, this study suggests the promising mechanism of the Lianhua Qingwen decoction for COVID-19 treatment. Further experimental and clinical verifications are still needed.

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Network Pharmacology and Molecular Docking Suggest the Mechanism for Biological Activity of Rosmarinic Acid

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/5190808 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Minglong Guan ◽

Lan Guo ◽

Hengli Ma ◽

Huimei Wu ◽

Xiaoyun Fan

Keyword(s):

Biological Activity ◽

Molecular Docking ◽

Protein Interaction ◽

Protein Interaction Network ◽

Rosmarinic Acid ◽

Target Genes ◽

Interaction Network ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis

Rosmarinic acid (RosA) is a natural phenolic acid compound, which is mainly extracted from Labiatae and Arnebia. At present, there is no systematic analysis of its mechanism. Therefore, we used the method of network pharmacology to analyze the mechanism of RosA. In our study, PubChem database was used to search for the chemical formula and the Chemical Abstracts Service (CAS) number of RosA. Then, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to evaluate the pharmacodynamics of RosA, and the Comparative Toxicogenomics Database (CTD) was used to identify the potential target genes of RosA. In addition, the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of target genes were carried out by using the web-based gene set analysis toolkit (WebGestalt). At the same time, we uploaded the targets to the STRING database to obtain the protein interaction network. Then, we carried out a molecular docking about targets and RosA. Finally, we used Cytoscape to establish a visual protein-protein interaction network and drug-target-pathway network and analyze these networks. Our data showed that RosA has good biological activity and drug utilization. There are 55 target genes that have been identified. Then, the bioinformatics analysis and network analysis found that these target genes are closely related to inflammatory response, tumor occurrence and development, and other biological processes. These results demonstrated that RosA can act on a variety of proteins and pathways to form a systematic pharmacological network, which has good value in drug development and utilization.

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Mechanistic Investigation of Glycyrrhiza uralensis Effects against Respiratory Ailments: Application of Network Pharmacology and Molecular Docking Approaches

Letters in Drug Design & Discovery ◽

10.2174/1570180818666211119113853 ◽

2021 ◽

Vol 18 ◽

Author(s):

Munazza Ijaz ◽

Xianju Huang ◽

Manal Buabeid ◽

Tahir Ali Chohan ◽

Ghulam Murtaza ◽

...

Keyword(s):

Gene Ontology ◽

Molecular Docking ◽

Herbal Remedy ◽

Database Search ◽

Glycyrrhiza Uralensis ◽

Network Pharmacology ◽

Careful Study ◽

Protein Targets ◽

Go Enrichment ◽

Mechanistic Investigation

Background: Glycyrrhiza uralensis, also known as liquorice, is a herbal remedy that is traditionally used worldwide for treating respiratory ailments and ameliorating breathing. Objective: The objective of this systematic study was to investigate active ingredients of Glycyrrhiza uralensis and determine its mode of action in silico against severe and acute respiratory complications of respiratory ailments through network pharmacology and molecular docking studies. Methods: TCMSP database search helped retrieve the compounds of Glycyrrhiza uralensis and their protein targets, especially related to respiratory ailments. Subsequently, the protein-protein association was attained as a network by using the STITCH database. Cytoscape and its ClueGO plugin were used to study gene ontology (GO) enrichment. In addition, seven natural compounds were docked in the active site of four different molecular targets; JUN-FOS, COX2, MAPK14 and IL-6, to identify the binding mechanism of ligands under study. Results: TCMSP database search resulted in the retrieval of 280 compounds of Glycyrrhiza uralensis (including formononetin, naringenin, sitosterol, isorhamnetin, kaempferol, quercetin and Glycyrrhizin) and 135 protein targets. A careful study of targets showed that 26 prospective targets (including JUN, FOS, IL6, MAPK14 and PTGS2) related to respiratory ailments were identified. Gene ontology (GO) enrichment analysis resulted in the retrieval of 176 GO terms, which were associated with respiratory ailments. This study proposed that Glycyrrhiza uralensis acts against respiratory ailments through various proteins, such as JUN, FOS, IL6, MAPK14 and PTGS2. Docking results revealed that among all studied ligands, the flavonoid-based compounds isorhamnetin and kaempferol form stronger complexes with JUN-FOS-DNA, MAPK-14, and IL-6 proteins (Cscore=6.81, 4.27, and 4.77, respectively) and the saponin based compound glycyrrhizin (Cscore=13.07) demonstrated stronger binding affinity towards COX2 enzyme. Conclusion: Conclusively, isorhamnetin, kaempferol and glycyrrhizin in Glycyrrhiza uralensis may regulate several signaling pathways through JUN-FOS-DNA, MAPK-14, and IL-6, which might play a therapeutic role against respiratory ailments.

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Potential Molecular Target Prediction and Docking Verification of Hua-Feng-Dan in Stroke Based on Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/8872593 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Ping Yang ◽

Haifeng He ◽

Shangfu Xu ◽

Ping Liu ◽

Xinyu Bai

Keyword(s):

Molecular Docking ◽

Signaling Pathways ◽

Target Genes ◽

Target Prediction ◽

Interaction Network ◽

Network Pharmacology ◽

Core Network ◽

Active Ingredients ◽

Protein Protein Interaction ◽

Highly Correlated

Objective. Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology. Methods. The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database. Results. Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target (CASP8, CASP9, MDM2, CYCS, RELA, and CCND1) and the active ingredients (beta-sitosterol, luteolin, baicalein, and wogonin). The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets. Conclusion. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines.

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The Mechanism Research of Qishen Yiqi Formula by Module-Network Analysis

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2015/497314 ◽

2015 ◽

Vol 2015 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Shichao Zheng ◽

Yanling Zhang ◽

Yanjiang Qiao

Keyword(s):

Protein Interactions ◽

Blood Circulation ◽

Blood Stasis ◽

Interaction Network ◽

Enrichment Analysis ◽

Small World ◽

Blood Stasis Syndrome ◽

Active Components ◽

Scale Free ◽

Topological Parameters

Qishen Yiqi formula (QSYQ) has the effect of tonifying Qi and promoting blood circulation, which is widely used to treat the cardiovascular diseases with Qi deficiency and blood stasis syndrome. However, the mechanism of QSYQ to tonify Qi and promote blood circulation is rarely reported at molecular or systems level. This study aimed to elucidate the mechanism of QSYQ based on the protein interaction network (PIN) analysis. The targets’ information of the active components was obtained from ChEMBL and STITCH databases and was further used to search against protein-protein interactions by String database. Next, the PINs of QSYQ were constructed by Cytoscape and were analyzed by gene ontology enrichment analysis based on Markov Cluster algorithm. Finally, based on the topological parameters, the properties of scale-free, small world, and modularity of the QSYQ’s PINs were analyzed. And based on function modules, the mechanism of QSYQ was elucidated. The results indicated that Qi-tonifying efficacy of QSYQ may be partly attributed to the regulation of amino acid metabolism, carbohydrate metabolism, lipid metabolism, and cAMP metabolism, while QSYQ improves the blood stasis through the regulation of blood coagulation and cardiac muscle contraction. Meanwhile, the “synergy” of formula compatibility was also illuminated.

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Investigation of the Mechanisms of Neuroprotection Mediated by Lobelia Species via Computational Network Pharmacology and Molecular Modeling

10.21203/rs.3.rs-61537/v1 ◽

2020 ◽

Author(s):

Qinfang Zheng ◽

Liangzi Fang ◽

Xiaolong Huang ◽

Ye Wang ◽

Shuihan Zhang

Keyword(s):

Molecular Modeling ◽

Neurodegenerative Diseases ◽

Interaction Network ◽

Enrichment Analysis ◽

Docking Studies ◽

Network Pharmacology ◽

Active Ingredients ◽

Active Components ◽

Neuroprotective Actions ◽

Gaba Transporter 1

Abstract BackgroundSeveral species of the medicinally valuable genus Lobelia (Campanulaceae) exhibit neuroprotection. While the neuroprotective mechanisms of some components (e.g. lobeline, lobelanine, and lobelanidine) belonging to the L. nicotianaefolia or L. inflata are extensively characterized, there remains the need to study and elucidate the mechanism of action of other species and their active components. In this work, we have studied the neuroprotective mechanism of the pharmacokinetically favorable active compounds of 17 Lobelia species.MethodsNetwork pharmacology approach and molecular modeling were employed. We have conducted drug-likeness evaluation, oral bioavailability prediction followed by the Gene Ontology (GO) terms and pathways enrichment analysis, protein-protein and protein-compound interaction network construction and analysis, and molecular docking studies. Five neurodegenerative diseases viz. Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, epilepsy, and Amyotrophic lateral sclerosis along with the common neuroprotection mechanism-associated genes were evaluated.ResultsWe revealed the neuroprotective mechanism of the active ingredients of Lobelia species. Our study strongly indicates that 12 unique active ingredients viz. luteolin, kaempferol, acacetin, chryseriol, norlobelanine, lobelanine, 2-[(2R,6S)-6-[(2R)-2-hydroxy-2-phenylethyl]-1-methylpiperidin-2-yl]-1-phenylethanone, hydroxygenkwanin, lobelanidine, quercetin, and diosmetin regulates 31 targets within multiple signaling pathways. The nitric oxide synthase, brain (NOS1), androgen receptor (ANDR), sodium- and chloride-dependent GABA transporter 1 (SC6A1), apoptosis regulator Bcl-2 (BCL2), RAC-alpha serine/threonine-protein kinase (AKT1), cellular tumor antigen p53, apoptosis regulator BAX, and tumor necrosis factor (TNFA) were identified as the majorly regulated genes. A majority of these target proteins act via several cancer-related pathways proven to have cross-talks with the pathogenesis of neurodegenerative diseases.ConclusionsThis study explains how the active ingredients of the Lobelia species exhibit their neuroprotective actions and provide a reference basis to investigate their pharmacological effects in detail.

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