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

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.

scholarly journals Uncovering the mechanism of Ge-Gen-Qin-Lian decoction for treating ulcerative colitis based on network pharmacology and molecular docking verification

2021 ◽  
Vol 41 (2) ◽  
Author(s):  
Lin Xu ◽  
Jiaqi Zhang ◽  
Yifan Wang ◽  
Zedan Zhang ◽  
Fengyun Wang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Molecular Docking ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Potential Candidate ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Pharmacological Mechanism ◽  
Th17 Cell Differentiation ◽  
The Relationship

Abstract Background: Ge-Gen-Qin-Lian Decoction (GGQLD), a traditional Chinese medicine (TCM) formula, has been widely used for ulcerative colitis (UC) in China, but the pharmacological mechanisms remain unclear. This research was designed to clarify the underlying pharmacological mechanism of GGQLD against UC. Method: In this research, a GGQLD-compound-target-UC network was constructed based on public databases to clarify the relationship between active compounds in GGQLD and potential targets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were performed to investigate biological functions associated with potential targets. A protein–protein interaction network was constructed to screen and evaluate hub genes and key active ingredients. Molecular docking was used to verify the activities of binding between hub targets and ingredients. Results: Finally, 83 potential therapeutic targets and 118 corresponding active ingredients were obtained by network pharmacology. Quercetin, kaempferol, wogonin, baicalein, and naringenin were identified as potential candidate ingredients. GO and KEGG enrichment analyses revealed that GGQLD had anti-inflammatory, antioxidative, and immunomodulatory effects. The effect of GGQLD on UC might be achieved by regulating the balance of cytokines (e.g., IL-6, TNF, IL-1β, CXCL8, CCL2) in the immune system and inflammation-related pathways, such as the IL-17 pathway and the Th17 cell differentiation pathway. In addition, molecular docking results demonstrated that the main active ingredient, quercetin, exhibited good affinity to hub targets. Conclusion: This research fully reflects the multicomponent and multitarget characteristics of GGQLD in the treatment of UC. Furthermore, the present study provided new insight into the mechanisms of GGQLD against UC.

Exploration of  the mechanism of Ziyin Tongluo Formula on preventing and treating postmenopausal osteoporosis based on the network pharmacology

2020 ◽  
Author(s):  
Rong-Bin Chen ◽  
Ying-Dong Yang ◽  
Kai Sun ◽  
Shan Liu ◽  
Wei Guo ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Postmenopausal Osteoporosis ◽  
Target Genes ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Regulation Of Transcription ◽  
Active Ingredients ◽  
Active Components ◽  
Kegg Pathways ◽  
Key Genes

Abstract Background Postmenopausal osteoporosis (PMOP) is a global chronic and metabolic bone disease that poses huge challenges to individuals and society. Previous studies have confirmed that Ziyin Tongluo Formula (ZYTLF) has a good clinical effect in the treatment of PMOP. However, the material basis and mechanism of ZYLTF against PMOP has not been thoroughly explained. Methods TCMSP, TCMID, and BATMAN-TCM databases were used to identify the active ingredients and their putative targets. Genes associated with PMOP were mined from GeneCards, OMIM, DisGeNET databases, and then mapped with the putative targets to obtain overlapping target genes. A network model of "herb-active ingredient-overlapping target genes" was constructed and a protein-protein interaction network of overlapping target genes was built and the key genes were selected based on the MCC algorithm. The key genes were imported to the DAVID database to performs GO and KEGG pathway enrichment analyses. Results Ninety-two active components of ZYTLF corresponded to 243 targets, with 129 target genes interacting with PMOP, and 50 key genes were selected. GO analysis results showed that biological process mainly included positive regulation of transcription, negative regulation of apoptosis, and cell components were mainly nucleus, cytoplasm, and molecular functions mainly included enzyme binding, protein binding and transcription factor binding. There were two main types of significant KEGG pathways in PMOP, hormone-related signaling pathways (estrogen, prolactin, thyroid hormone) and inflammation-related pathways (TNF, PI3K-Akt, MAPK ). Conclusions The underlying therapeutic mechanisms of ZYTLF action on PMOP maybe is that, the active ingredients such as quercetin, kaempferol, luteolin act on ESR1, TNF, IL6, MAPK8 and other key genes, which mainly enrich in estrogen, TNF, PI3K-Akt, MAPK and other signaling pathways.

scholarly journals Based on Network Pharmacology and Molecular Docking to Explore the Underlying Mechanism of Huangqi Gegen Decoction for Treating Diabetic Nephropathy

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Shanshan Ding ◽  
Weihao Wang ◽  
Xujiao Song ◽  
Hao Ma
Keyword(s):  
Diabetic Nephropathy ◽  
Molecular Docking ◽  
Target Genes ◽  
Chinese Herb ◽  
Underlying Mechanism ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Core Components

Background. Huangqi Gegen decoction (HGD), a Chinese herb formula, has been widely used to treat diabetic nephropathy in China, while the pharmacological mechanisms are still unclear. Therefore, the present study aims to explore the underlying mechanism of HGD for treating diabetic nephropathy (DN). Materials and Methods. Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), UniProt, and SwissTargetPrediction databases were used to search the active ingredients and potential targets of HGD. In addition, multiple disease-related databases were used to collect DN-related targets. Common targets of the protein-protein interaction (PPI) network were established using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. At last, AutoDockVina was used to conduct molecular docking verification for the core components and targets. Results. A total of 27 active ingredients and 354 putative identified target genes were screened from HGD, of which 99 overlapped with the targets of DN and were considered potential therapeutic targets. Further analysis showed that the HGD activity of quercetin, formononetin, kaempferol, isorhamnetin, and beta-sitosterol ingredients is possible through VEGFA, IL6, TNF, AKT1, and TP53 targets involved in TNF, toll-like receptors, and MAPK-related pathways, which have anti-inflammatory, antiapoptosis, antioxidation, and autophagy effects, relieve renal fibrosis and renal cortex injury, and improve renal function, thus delaying the development of DN. The molecular docking results showed that quercetin, formononetin, kaempferol, isorhamnetin, beta-sitosterol had a good binding activity with VEGFA, IL6, TNF, AKT1, and TP53. Conclusion. This study demonstrated that HGD might take part in the treatment of DN through multicomponent, multitarget, and multichannel combined action.

scholarly journals Network pharmacology and molecular docking study on the mechanism of colorectal cancer treatment using Xiao-Chai-Hu-Tang

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252508
Author(s):  
Jingyun Jin ◽  
Bin Chen ◽  
Xiangyang Zhan ◽  
Zhiyi Zhou ◽  
Hui Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Target Genes ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Active Ingredients ◽  
Molecular Docking Study

Background and objective We aimed to predict the targets and signal pathways of Xiao-Chai-Hu-Tang (XCHT) in the treatment of colorectal cancer (CRC) based on network pharmacology, just as well as to further analyze its anti-CRC material basis and mechanism of action. Methods We adopted Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and Traditional Chinese Medicine Integrated Database (TCMID) databases to screen the active ingredients and potential targets of XCHT. CRC-related targets were retrieved by analyzing published microarray data (accession number GSE110224) from the Gene Expression Omnibus (GEO) database. The common targets were used to construct the “herb-active ingredient-target” network using the Cytoscape 3.8.0 software. Next, we constructed and analyzed protein-to-protein interaction (PPI) using BisoGenet and CytoNCA plug-in in Cytoscape. We then performed Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses of target genes using the R package of clusterProfiler. Furthermore, we used the AutoDock Tools software to conduct molecular docking studies on the active ingredients and key targets to verify the network pharmacological analysis results. Results We identified a total of 71 active XCHT ingredients and 20 potential anti-CRC targets. The network analysis revealed quercetin, stigmasterol, kaempferol, baicalein, and acacetin as potential key compounds, and PTGS2, NR3C2, CA2, and MMP1 as potential key targets. The active ingredients of XCHT interacted with most CRC disease targets. We showed that XCHT’s therapeutic effect was attributed to its synergistic action (multi-compound, multi-target, and multi-pathway). Our GO enrichment analysis showed 46 GO entries, including 20 biological processes, 6 cellular components, and 20 molecular functions. We identified 11 KEGG signaling pathways, including the IL-17, TNF, Toll-like receptor, and NF-kappa B signaling pathways. Our results showed that XCHT could play a role in CRC treatment by regulating different signaling pathways. The molecular docking experiment confirmed the correlation between five core compounds (quercetin, stigmasterol, kaempferol, baicalein, and acacetin) just as well as PTGS2, NR3C2, CA2, and MMP1. Conclusion In this study, we described the potential active ingredients, possible targets, and key biological pathways responsible for the efficacy of XCHT in CRC treatment, providing a theoretical basis for further research.

scholarly journals Investigation of Anti-SARS, MERS, and COVID-19 Effect of Jinhua Qinggan Granules Based on a Network Pharmacology and Molecular Docking Approach

2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110206
Author(s):  
Ying Zhang ◽  
Yunfeng Yao ◽  
Yanfang Yang ◽  
Hezhen Wu
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Interaction Network ◽  
Antiviral Effect ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Discovery Studio ◽  
Pathway Network ◽  
Protein Protein Interaction ◽  
The Common

Objective Jinhua Qinggan Granules (JQGs) have achieved certain results in the prevention and treatment of COVID-19 in China during this coronavirus storm. In this study, we aimed to analyze the common mechanisms of JQG in the treatment of coronavirus-induced diseases, such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19 via network pharmacology and molecular docking. Methods The active compounds of JQG were collected through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The common targets associated with these 3 diseases were screened from GeneCards database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of JQG’s core targets were analyzed using The Database for Annotation, Visualization, and Integrated Discovery and KOBAS 3.0 system. Further, the protein-protein interaction network was built using STRING database. The compound-target- signaling pathway network was constructed using Cytoscape 3.7.2. The core components of JQG were docked with core targets, COVID-19 coronavirus 3 Cl hydrolase, and angiotensin-converting enzyme 2 (ACE2) via Discovery Studio 2016 software. Results A total of 139 active compounds, 50 core targets, and 122 signaling pathways were screened out. The results of molecular docking showed that arctiin and linarin had a higher docking score with 3 Cl, ACE2, and core targets of JQH for antiviral effect. Conclusion The potential mechanism of action of JHQ in the treatment of MERS, SARS, and COVID-19 may be associated with the regulation of genes co-expressed with ACE2 and immune- related signaling pathways.

Discussion on the Mechanism of Lithospermum erythrorhizon in the Treatment of Cervical Cancer Based on Network Pharmacology and Molecular Docking Technology

2021 ◽  
Vol 7 (5) ◽  
pp. 3927-3933
Author(s):  
Qiong Yan ◽  
Fangwu Ye
Keyword(s):  
Cervical Cancer ◽  
Molecular Docking ◽  
Drug Targets ◽  
Target Genes ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Drug Candidate ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Stable Conformation

Objective To explore the “multi-component, multi-target, multi-pathway” mechanism of Lithospermum erythrorhizonagairtst cervical cancer. Methods The active ingredients and corresponding targets were screened through TCMSP, PubChem and SwissTargetPrediction databases. The GeneCarts platform was used to collect cervical cancer-related genes, and the intersection of drug targets and cervical cancer targets was analyzed. Use STRING to analyze protein interaction network, use Cytoscape software to construct component-target and core target interaction network, perform KEGG pathway enrichment analysis on core target genes, and conduct molecular docking verification.Results After screening, 12 main active ingredients of comfrey (including Shikonin A, 1-methoxyacetylshikonin, Shikonin B, etc.) and 35 key targets related to comfrey and cervical cancer were obtained (including ESR1, SRC, MMP9, PTGS2, etc.). And these genes were mainly enriched in 39 signaling pathways such as PI3K-Akt and estrogen. Molecular docking reminder that Lithospermum A has a higher affinity with ESR1, and Lithospermum B can form a stable conformation with SRC, MMP9, and PTGS2. Conclusion Lithospermum erythrorhizon is a potential drug candidate for the treatment of cervical cancer. It can treat cervical cancer through multi-component, multi-target, and multi-channel action.

Study on the Mechanism of Bushen Jianpi Decoction in the Treatment of T2DM Based on Network Pharmacology

2021 ◽  
Author(s):  
Dongqiang Luo ◽  
Ying Shao ◽  
Yong Sun ◽  
Shuntang Du ◽  
Feng Liu
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Genes ◽  
Fluid Shear Stress ◽  
Interaction Network ◽  
Binding Potential ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Protein Protein Interaction ◽  
Target Disease

Abstract Through the preliminary clinical observation, we had found that Bushen Jianpi decoction (BJD) combined with had better efficacy and less side effects, but its mechanism was not clear. The purpose of this study was to determine its molecular targets and mechanism in T2DM therapy by means of network pharmacology and molecular docking.Results: A total of 144 candidate compounds and 1103 differentially expressed genes were screened, and 43 common targets related to T2DM in BJD were identified. The "TCM-compound-target-disease" network suggested that quercetin, luteolin and kaempferol were the top three compounds. Through protein-protein interaction network, 45 core target genes were identified, including ITGA4, TP53, MYC and so on. GO enrichment showed that genes were significantly enriched in biological processes such as response to oxidative stress, response to lipopolysaccharide, response to molecule of bacterial origin and response to reactive oxygen species. KEGG enrichment showed that there was significant gene enrichment in Fluid shear stress and atherosclerosis, TNF signaling pathway, P13K-Akt signaling pathway, IL-17 signaling pathway and AGE-RAGE signaling pathway in diabetic complications signal pathways. The results of molecular docking showed that the key components of BJD had good binding potential with target genes. Conclusions: BJD may play a role in the treatment of T2DM through anti-inflammation, antioxidation and regulating metabolism, but it still needs to be further confirmed by experiments.Keywords: Network pharmacology, GEO database, Molecular docking, Bushen Jianpi decoction; T2DM

Network Pharmacology and Molecular Docking Study of Jinwei Decoction for Enhancement of Glucocorticoid Anti-Inflammatory Effect in COPD through miR-21

2021 ◽  
Author(s):  
jianjun wu ◽  
Ping-an Zhang ◽  
Ming-zhe Chen ◽  
Yi-xuan Li ◽  
Ying-xue Zhang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Ppi Networks ◽  
Core Proteins ◽  
Anti Inflammatory ◽  
Inflammatory Effect

Abstract PurposeJinwei decoction can enhance the anti-inflammatory effect of glucocorticoid (GC) on chronic obstructive pulmonary disease (COPD) by restoring the activity of HDAC2. But the upstream mechanism of Jinwei decoction on HDAC2 expression is not clear. ObjectiveTo explore whether Jinwei decoction can enhance the anti-inflammatory effect of GC on COPD through microRNA21 (miR-21) by network pharmacology. MethodsThe TCMSP database was used to screen active ingredients and target genes of Jinwei decoction, and miRWalk2.0 was used to predict downstream target genes of miR-21. COPD-related genes were identified by searching GeneCards and OMIM databases; Venny 2.1 was used to screen intersection genes; Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of intersection genes were analyzed by R software. Protein-protein interactions (PPIs) were analyzed by Cytoscape 3.7.2 software to identify core genes. Finally, interactions between main compounds and potential targets were verified by molecular docking. ResultsTwo hundred ninety-two active ingredients, 316 Jinwei drug targets, 10170 miR-21 target genes, 6617 COPD target genes, and 184 intersection gene were identified. Eleven core proteins of PPI networks may be involved. GO enrichment analysis showed that oxidative stress, regulation of inflammatory response, hormone transport, and histone modification were involved; KEGG pathway enrichment analysis concentrated in the PI3K-Akt, mitogen-activated protein kinase (MAPK), HIF-1, neutrophil extracellular bactericidal network, and other signaling pathways. ConclusionJinwei decoction can regulate histone deacetylase-2 activity and enhance the anti-inflammatory effect of GC on COPD by modulating miR-21. Its mechanism of action may be related to its effect on the PI3K Akt, MAPK, and TNF signaling pathways and neutrophil extracellular trap formation through miR-21.

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

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.

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

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.

Sign in / Sign up

Export Citation Format

Share Document