Curcumin’s molecular mechanism of action and targets in the treatment of rheumatoid arthritis: A network analysis and molecular docking study

Curcumin’s molecular mechanism of action and targets in the treatment of rheumatoid arthritis: A network analysis and molecular docking study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Curcumin’s molecular mechanism of action and targets in the treatment of rheumatoid arthritis: A network analysis and molecular docking study Frank Kalungi, Pradeep Kumar, Ivan Ricardo Vega Valdez, Godwin Anywar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3685735/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction : Rheumatoid Arthritis (RA) is an autoimmune disorder that majorly affects the joints leading to pain, swelling, and stiffness and inflammation. Curcumin is a chemical compound from Curcuma longa (Tumeric). The aim of this study was to investigate the molecular mechanisms underlying the treatment of RA using curcumin. Methods: Curcumin associated targets were retrieved from SwissTargetPrediction, PharmMapper and DrugBank. The RA associated targets were retrieved from OMIM, GeneCards, NCBI gene databases. GeneVenn was used to determine overlapping genes (RA-curcumin associated targets). The targets were used to construct a compound-disease target network. Gene Ontology enrichment analysis was done to identify the molecular function, cellular components and biological processes associated with the targets. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses was performed to identify top pathways with p < 0.05. A disease target-pathway network (D-P) was constructed and then merged with the C-D network to produce a compound-disease target-pathway network (C-D-P). Results: We obtained 190 RA-curcumin associated targets.Gene ontology analysis revealed response to peptide, protein kinase complex and non-membrane spanning protein kinase activity as the major biological processes, cellular componentsand molecular functionterms respectively. Network analysis revealed SRC, AKT1 and AKT2 as the hub targets. Molecular docking showed that curcumin can bind stably to the hub targets. Conclusion: Curcumin can interact with various proteins involved in the treatment of RA which can guide further its clinical application. Rheumatoid arthritis curcumin network pharmacology inflammation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Rheumatoid arthritis (RA) is an autoimmune disorder that majorly affects the joints leading to pain, swelling, and stiffness. It occurs when the immune system mistakenly attacks the body’s own tissues leading to inflammation (Ding et al., 2023 ). This inflammation occurs mainly in the synovial tissue and is identified by the buildup of inflammatory cells, synovial fibroblasts, macrophages, inflammatory cytokines like TNF-⍺, IL-1β, and IL-6 (Amalraj et al., 2017 ). Rheumatoid arthritis can also affect other parts of the body such as skin, eyes and lungs and the symptoms vary from person to person (Bullock et al., 2019 ; Yan et al., 2020 ). Rheumatoid arthritis has a negative long-term outlook with up to 80% of patients experiencing disability after 20 years and a corresponding reduction in life expectancy by an average of 3 to 18 years. Without treatment, 20 to 30% of patients may become permanently work-disabled within two to three years of diagnosis (Chandran & Goel, 2012 ; Papakonstantinou, 2021 ). The exact cause of RA is uncertain but research suggests that a combination of genetic and environmental factors contribute to the development of the disease and related pathological processes (Pourhabibi-Zarandi et al., 2021 ). Many drugs have been developed for the treatment of RA such non-steroidal anti-inflammatory drugs (NSAIDS). However they are associated with various side effects (Laev & Salakhutdinov, 2015 ). Curcumin is a bright yellow compound from Curcuma longa L (Tumeric), family Zingiberaceae (Ali et al., 2021 ), but is also found in other Curcuma species. Curcumin is a polyphenolic compound with a chemical formula of C 21 H 20 O 6 , molecular weight of 368.38 g/mol (Porro & Panaro, 2023 ). Its structure consists of two aromatic rings connected by a seven-carbon linker with various functional groups, including methoxy and hydroxy groups and is relatively insoluble in water but soluble in organic solvents like ethanol and acetone as shown in Fig. 1 (Oglah et al., 2020 ; Slika & Patra, 2020 ). Curcumin has been extensively studied for its potential health benefits such as anti-inflammatory, antioxidant, anti-cancer and antidepressant effects (Rathore et al., 2020 ). Curcumin interacts with multiple molecular targets and pathways. For instance, it alleviated rheumatoid arthritis-induced inflammation and synovial hyperplasia by targeting the mTOR pathway and inhibiting proinflammatory cytokines such as IL-1β and TNF-α in rats (Dai et al., 2018 ). Network pharmacology is a rapidly developing field that utilizes computational methods to gain insights into the mechanisms of drug action across multiple levels of complexity ranging from individual drug targets to interactions between multiple targets (Belenahalli Shekarappa et al., 2019 ). By analyzing large-scale biological datasets and networks, network pharmacology seeks to uncover new drug targets and potential drug combinations that can be used to treat complex diseases. Ultimately, it aims to improve our understanding of how drugs interact with biological systems and pave the way for more personalized and effective drug therapies (Ayar et al., 2023 ; Kalungi et al., 2023 ). In recent years, molecular docking has become an essential tool for modern drug discovery. It involves the use of algorithms and software programs to simulate the interaction between the drug molecule and the target protein, and to predict the most favorable binding mode and energy (Anywar & Namukobe, 2020 ; Kalungi et al., 2023 ). Therefore, in this study, network pharmacology was used to explore the molecular mechanisms and targets involved in the treatment of RA with curcumin and the core targets were validated by molecular docking. Materials and Methods Identification of therapeutic targets associated with curcumin The therapeutic targets of curcumin were downloaded from DrugBank ( https://go.drugbank.com/),PharmMapper(http://lilabecust.cn/pharmmapper/index.html ) and SwissTargetPrediction ( http://swisstargetprediction.ch/ ) with all searches specific to Homo sapiens. The Swiss Target Prediction server predicts macromolecular targets of small bioactive molecules basing on a similarity principle through reverse screening (Daina et al., 2019 ). PharmMapper uses a pharmacophore mapping approach to predict potential targets for small molecules (Wang et al., 2017 ). DrugBank is a database containing information on drugs, their mechanisms, interactions and targets (Wishart et al., 2018 ). Identification of potential pathological targets related to rheumatoid arthritis RA-curcumin associated targets were retrieved from NCBI gene ( https://www.ncbi.nlm.nih.gov/gene ), GeneCards ( https://www.genecards.org/ ) and OMIM ( https://www.omim.org/ ) databases with all searches specific to Homo sapiens. The NCBI gene contains information such as reference sequences (RefSeq), maps, pathways, variations and phenotypes among others. GeneCards is a database of all annotated and predicted human genes. The OMIM database contains human genes and genetic phenotypes. Construction of a compound-disease target network Overlapping genes (RA-curcumin associated targets) between curcumin and rheumatoid arthritis were obtained using Gene List Venn Diagram ( https://www.bioinformatics.org/gvenn/ ) and they were used to construct a network using Cytoscape software (v 3.9.1). Cytoscape is tool for analyzing and visualization of biomolecular interaction networks (Shannon et al., 2003 ). Gene ontology (GO) enrichment analysis RA-curcumin associated targets were subjected to GO enrichment analysis i.e. biological process, cellular component and molecular function using ShinyGo ( http://bioinformatics.sdstate.edu/go/ ) and the False Discovery Rate (FDR) cut off was set at 0.05. ShinyGO is an interactive tool for gene set enrichment analysis for both animals and plants (Ge et al., 2020 ). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis The analysis was accomplished by The Database for Annotation, Visualization and Integrated Discovery (DAVID) using RA-curcumin associated targets as input. DAVID ( https://david.ncifcrf.gov/ ) is a web server for functional enrichment analyses and annotation of gene lists (Sherman et al., 2022 ). The bubble chart for KEGG pathway enrichment analysis was drawn using a bioinformatics web server ( http://www.bioinformatics.com.cn/ ). Construction of compound-disease-target-pathway (C-D-P) network Disease_target-pathway network was constructed and then merged with the compound-disease-target network using Cytoscape (v 3.9.1) to produce the C-D-P network. Pathways whose p < 0.05 were used in this network. Construction of Protein-Protein interaction network. RA-curcumin associated targets were inputted into STRING ( https://string-db.org/ ) to obtain a PPI network. To obtain a clear network a confidence score < 0.900 was used. The network was built specific to Homo sapiens. Molecular docking simulation The top targets with good interaction with the curcumin, other genes and pathways were subjected for molecular docking. Their structures were downloaded from the Protein Data Bank ( https://www.rcsb.org/ ) and then prepared for molecular docking using Autodock tools (ADT). Curcumin’s structure was obtained from PubChem ( https://pubchem.ncbi.nlm.nih.gov/ ) and then converted into PDB format using Open Babel (O'Boyle et al., 2011 ). The simulation was performed by using Autodock 4.2 (Download AutoDock4 – AutoDock (scripps.edu)) using Larmackian Genetic algorithm and ADT was used to visualize the docking results. Pymol software was used to visualize the protein ligand complexes and their interactions (DeLano, 2002 ). Results Therapeutic targets associated with curcumin, rheumatoid arthritis and Compound-disease_target construction Overall, 385 targets related to curcumin were retrieved from DrugBank, PharmMapper and SwissTargetPrediction. In addition, 5,351 targets associated with RA were retrieved from OMIM, GeneCards and NCBI gene. One hundred and ninety overlapping targets between curcumin and RA were obtained as shown in Fig. 2 . Rheumatoid Arthritis_curcumin associated targets were then used to construct a compound-disease-target network as shown in Fig. 3 Gene ontology analysis (GO) The most significant GO categories that pass the cut off criterion of FDR = 0.05 were obtained. RA-curcumin associated targets were associated with biological processes such as response to peptide, response to hormone, inflammatory response, cellular response to oxygen-containing compound, response to organonitrogen, negative regulation of cell death, regulation of response to external stimulus etc as shown in Fig. 4 a. In addition, the targets were associated with cellular components such as protein kinase complex, vesicle lumen, membrane raft, membrane microdomain, secretory granule lumen, cytoplasmic vesicle lumen, focal adhesion, cell-substrate junction etc as shown in Fig. 4 b. Finally, the targets were associated with molecular functions such as non-membrane spanning protein tyrosine kinase activity, nuclear receptor activity, ligand-activated transcription factor activity, transmembrane receptor protein tyrosine kinase activity, protein phosphatase binding etc as shown in Fig. 4 c. KEGG pathway enrichment analysis. One hundred and ninety RA-curcumin associated targets were uploaded into DAVID and top 19 enriched pathways with p < 0.05 and based on gene counts were selected. Figure 5 shows a bubble chart showing KEGG pathway enrichment analysis of 190 RA-curcumin associated targets. The targets were mainly enriched with 5 infections (hepatitis B, hepatitis C, human cytomegalovirus infection, toxoplasmosis, Helicobacter pylori infection) and signaling pathways related to cell function and regulation (MAPK signaling pathway, Ras signaling pathway, T cell receptor signaling pathway, FoxO signaling pathway, and PI3K-Akt signaling pathway). In addition, the targets were enriched with atherosclerosis and lipid-related pathways (lipid and atherosclerosis, fluid shear stress and atherosclerosis) and cancer-related pathways and diseases (pathways in cancer, prostate cancer, EGFR tyrosine kinase inhibitor resistance, proteoglycans in cancer, pancreatic cancer, PD-L1 expression and PD-1 checkpoint pathway in cancer, and acute myeloid leukemia). Compound-disease target-pathway network The D-P network was merged with C-D network to give C-D-P network with 209 nodes and 621 edges as shown in Fig. 6 . In the network, nodes represent curcumin, pathways and targets whereas the edges represent the multiple interactions among the nodes. The number of edges that a node has with other nodes in the network is referred to as the degree. AKT2 and AKT1 showed the highest degree among the target nodes and thus representing hub genes that may be play an important role in the structure and function of the network. PPI network analysis One hundred and ninety RA-curcumin associated targets were inputted into STRING to produce a PPI network. The network was downloaded and then analyzed using cytoscape and it contained 140 nodes and 422 edges. The top targets with the highest degree that is AKT1 and SRC were identified. Figure 7 shows the PPI network of 190 RA-curcumin associated targets. Molecular Docking The C-D-P and PPI network analysis revealed AKT1, AKT2 and SRC as the top three targets and were subjected to molecular docking with curcumin. Analysis of the docking results for the protein-ligand complexes was done using ADT. The binding affinity of curcumin and the targets were − 7.51 kj/mol, -6.85 kj/mol and − 8.52 kj/mol respectively. Figure 8 shows curcumin-target complexes visualized using pymol. Discussion Over the past years, there has been advancement in cheminformatics and establishment of large scale structure-activity-relationship databases and thus leading to development of in silico methods for multitarget drug (Ramsay et al., 2018 ). Understanding the specific binding of a drug to two or more targets and its effects on biological networks and phenotype is essential not only for improving its efficacy but also for understanding its toxicity (Brogi et al., 2020 ; Hopkins, 2008 ). In this study, a holistic systems biology approach integrating target identification, network construction and analysis, gene ontology analysis, KEGG pathway enrichment analysis, protein-protein interaction analysis and molecular docking was employed to evaluate the molecular mechanism and targets of curcumin against rheumatoid arthritis. From database mining, 190 RA-curcumin associated targets were retrieved and KEGG pathway enrichment analysis revealed that they were significantly enriched in various pathways related to infectious diseases, signaling pathways associated with cell function and regulation, atherosclerosis and lipid metabolism as well as cancer-related pathways and diseases. Gene ontology analysis demonstrated BP terms such response to peptide, response to hormone, inflammatory response, cellular response to oxygen containing compound etc. were revealed. A fibrinogen-derived 21-amino-acid-long citrullinated peptide was found to be a reliable biomarker for early rheumatoid arthritis diagnosis and flare prediction, which is valuable for managing patients who respond poorly to treatment (Khatri et al., 2020 ). Joint inflammation was found to recur in the same joints during the progression of RA (Heckert et al., 2022 ). In addition, CC terms such as protein kinase complex, vesicle lumen, membrane raft etc. were also revealed. Furthermore, MF terms revealed included non-membrane spanning protein tyrosine kinase activity, nuclear receptor activity, ligand-activated transcription factor activity etc. Analysis of the kinome in CD4 + T cells from rheumatoid arthritis (RA) patients unveiled substantial changes in the post-translational phosphorylation of proteins associated with kinases, notably G-protein-signaling modulator 2 (GPSM2), protein tyrosine kinase 6 (PTK6), and the precursor of vitronectin (VTNC) (Meyer et al., 2021 ). The removal of G protein-coupled receptor kinase 5 (GRK5) inhibits synovial inflammation in a mouse model of collagen antibody-induced arthritis (Toya et al., 2021 ). Network analysis revealed that AKT1, AKT2 and SRC were the three main targets among 190 RA-curcumin associated targets and were identified as hub genes. The targets were further validated by molecular docking simulation with curcumin and SRC showing the strongest binding affinity of -8.52 kj/mol followed by AKT1 (-7.51kj.mol) and AKT2 (-6.85 kj/mol). SRC is a proto-oncogene that encodes a tyrosine protein kinase which has been found to play central role in the activation and proper functioning of macrophages which are critical components of the immune system involved in the initial defense against pathogens and the regulation of inflammatory responses (Byeon et al., 2012 ). A recent study showed that nanospheres loaded with curcumin induced c-SRC activation which supports our findings (Kim et al., 2020 ). In order to understand the treatment of inflammatory and angiogenic diseases such as RA by targeting vascular cell adhesion molecule (VCAM)-1 signaling mechanisms, researchers showed that interleukin-18 exhibits direct and swift activation of SRC which suggested that SRC activation serves as an initial event shared by the PI3-kinase/AKT and ERK1/2 pathways (Morel et al., 2002 ). Furthermore, sphingosine-1-phosphate increased osteoblastic vascular endothelial growth factor expression and thus promoting endothelial progenitor cell angiogenesis by inhibiting miR-16-5p synthesis through c-SRC/FAK signaling and thus providing a valuable approach in developing of treatment strategies for RA (Huang et al., 2021 ). Moreover curcumin was found to inhibit the kinase activity of v-SRC leading to a decrease in tyrosyl substrate phosphorylation of Shc, cortactin, and FAK and thus demonstrating that it can retard cellular growth and migration (Leu et al., 2003 ). In addition, curcumin was found to inhibit NF-κB and Src Protein Kinase Signaling Pathways (Shakibaei et al., 2013 ). AKT is a type of serine/threonine protein kinase that plays a crucial role in numerous signaling pathways within cells. It acts as a significant mediator of signals downstream of activated phosphoinositide 3-kinase (PI3K), a key enzyme involved in cell growth and survival and it exists in three isoforms in mammals that is PKB-α (AKT1), PKB-β (AKT2), and PKBγ (AKT3) (Dummler & Hemmings, 2007 ). Curcumin inhibits collagen-induced arthritis AKT1 indicating that it may alleviate RA-induced inflammation and synovial hyperplasia (Dai et al., 2018 ). Curcumin was also found to inhibit P13K/AKT signaling in LPS activated microglia (Cianciulli et al., 2016 ). In addition, RA pathogenesis has been associated with reactive oxygen species (Veselinovic et al., 2014 ). The intracellular content of reactive oxygen species was found to be dependent on AKT1 and AKT2 (Juntilla et al., 2010 ). AKT2 enhances cell survival on exposure to hydrogen peroxide (Zhang et al., 2011 ). Curcumin was also found to inhibit P13/AKT signaling in SKOV3 by retarding their growth which is line with our results (Yu et al., 2016 ). Therefore, these findings highlight the multifaceted nature of curcumin and its potential implications in managing comorbidities observed in rheumatoid arthritis patients. Conclusion In this study, a new approach was taken to investigate the molecular targets and potential mechanisms underlying the treatment effects of curcumin on RA. Curcumin, a natural compound found in turmeric exerts its effects against RA through multiple targets, pathways, and biological processes. Molecular docking analysis revealed that curcumin can form stable interactions with key proteins involved in RA, including SRC, AKT1 and AKT2. These findings suggest that curcumin has the potential to interfere with the activity of these proteins and potentially inhibit the growth and progression of RA. However, further research is needed to validate the clinical effectiveness of curcumin and to understand the precise mechanisms by which it exerts its anti-RA effects. Declarations Acknowledgments We acknowledge the support from National Agricultural Research Laboratories, Kawanda, Dr. Miriam Nakabuye from Novo Nordisk Foundation Center for Basic Metabolic Research and the staff at the Department of Plant Sciences, Microbiology and Biotechnology, Makerere University. Author contributions FK designed and conducted the study under the guidance and supervision of GA. PK and IRVVconducted and verified some of the experiments. FK wrote the first draft of the manuscript under the guidance of and GA. All authors have read and approved the manuscript. Funding This study did not receive funding from anybody or organization Data availability The data that support the findings of this study are available from the corresponding authors upon request. Conflicts of Interest The authors declare no conflicts of interest regarding this work. References Ali A, Ali A, Tahir A, Bakht MA, Salahuddin, Ahsan MJ (2021). Molecular engineering of curcumin, an active constituent of Curcuma longa L.(Turmeric) of the family Zingiberaceae with improved antiproliferative activity. Plants, 10(8), 1559. Amalraj A, Varma K, Jacob J, Divya C, Kunnumakkara AB, Stohs SJ, Gopi S (2017). A novel highly bioavailable curcumin formulation improves symptoms and diagnostic indicators in rheumatoid arthritis patients: a randomized, double-blind, placebo-controlled, two-dose, three-arm, and parallel-group study. Journal of medicinal food, 20 (10), 1022-1030. Anywar G, Namukobe J (2020). Factors affecting the choice for plant-based products in drug discoveries Phytochemicals as Lead Compounds for New Drug Discovery (pp. 15-24): Elsevier. Ayar ES, Dadmand S, Tuncbag N (2023). Network Medicine: From Conceptual Frameworks to Applications and Future Trends. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. Belenahalli Shekarappa S, Kandagalla S, Hanumanthappa M (2019). A network pharmacology approach to investigate the pharmacological effect of curcumin and capsaicin targets in cancer angiogenesis by module-based PPI network analysis. Journal of Proteins and Proteomics, 10, 109-120. Brogi S, Ramalho TC, Kuca K, Medina-Franco JL, Valko M (2020) In silico methods for drug design and discovery (Vol. 8, pp. 612): Frontiers Media SA. Bullock J, Rizvi SA, Saleh AM, Ahmed SS, Do DP, Ansari RA, Ahmed J (2019) Rheumatoid arthritis: a brief overview of the treatment. Medical Principles and Practice, 27(6), 501-507. Byeon SE, Yi Y-S, Oh J, Yoo BC, Hong S, Cho JY (2012) The role of Src kinase in macrophage-mediated inflammatory responses. Mediators of inflammation, 2012. Chandran, B., & Goel, A. (2012). A randomized, pilot study to assess the efficacy and safety of curcumin in patients with active rheumatoid arthritis. Phytotherapy research, 26 (11), 1719-1725. Cianciulli, A., Calvello, R., Porro, C., Trotta, T., Salvatore, R., & Panaro, M. A. (2016). PI3k/Akt signalling pathway plays a crucial role in the anti-inflammatory effects of curcumin in LPS-activated microglia. International immunopharmacology, 36 , 282-290. Dai, Q., Zhou, D., Xu, L., & Song, X. (2018). Curcumin alleviates rheumatoid arthritis-induced inflammation and synovial hyperplasia by targeting mTOR pathway in rats. Drug design, development and therapy , 4095-4105. Daina, A., Michielin, O., & Zoete, V. (2019). SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules. Nucleic acids research, 47 (W1), W357-W364. DeLano, W. L. (2002). Pymol: An open-source molecular graphics tool. CCP4 Newsl. Protein Crystallogr, 40 (1), 82-92. Ding, Q., Hu, W., Wang, R., Yang, Q., Zhu, M., Li, M., . . . Zhu, Y. Z. (2023). Signaling pathways in rheumatoid arthritis: implications for targeted therapy. Signal Transduction and Targeted Therapy, 8 (1), 68. Dummler, B., & Hemmings, B. (2007). Physiological roles of PKB/Akt isoforms in development and disease: Portland Press Ltd. Ge, S. X., Jung, D., & Yao, R. (2020). ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinformatics, 36 (8), 2628-2629. Heckert, S. L., Bergstra, S. A., Matthijssen, X. M., Goekoop-Ruiterman, Y. P., Fodili, F., Ten Wolde, S., . . . Huizinga, T. W. (2022). Joint inflammation tends to recur in the same joints during the rheumatoid arthritis disease course. Annals of the Rheumatic Diseases, 81 (2), 169-174. Hopkins, A. L. (2008). Network pharmacology: the next paradigm in drug discovery. Nature chemical biology, 4 (11), 682-690. Huang, C.-C., Tseng, T.-T., Liu, S.-C., Lin, Y.-Y., Law, Y.-Y., Hu, S.-L., . . . Tang, C.-H. (2021). S1p increases vegf production in osteoblasts and facilitates endothelial progenitor cell angiogenesis by inhibiting mir-16-5p expression via the c-src/fak signaling pathway in rheumatoid arthritis. Cells, 10 (8), 2168. Juntilla, M. M., Patil, V. D., Calamito, M., Joshi, R. P., Birnbaum, M. J., & Koretzky, G. A. (2010). AKT1 and AKT2 maintain hematopoietic stem cell function by regulating reactive oxygen species. Blood, The Journal of the American Society of Hematology, 115 (20), 4030-4038. Kalungi, F., Nsubuga, A., & Anywar, G. (2023). Network analysis and molecular docking studies of quercetin as a potential treatment for prostate cancer. In Silico Pharmacology, 11 (1), 24. Khatri, S., Hansen, J., & Astakhova, K. (2020). Antibodies to synthetic citrullinated peptide epitope correlate with disease activity and flares in rheumatoid arthritis. PloS one, 15 (4), e0232010. Kim, D.-W., Choi, C.-H., Park, J. P., & Lee, S.-J. (2020). Nanospheres loaded with curcumin improve the bioactivity of umbilical cord BLOOD-mesenchymal stem cells via c-Src activation during the skin wound healing process. Cells, 9 (6), 1467. Laev, S. S., & Salakhutdinov, N. F. (2015). Anti-arthritic agents: progress and potential. Bioorganic & medicinal chemistry, 23 (13), 3059-3080. Leu, T.-H., Su, S. L., Chuang, Y.-C., & Maa, M.-C. (2003). Direct inhibitory effect of curcumin on Src and focal adhesion kinase activity. Biochemical pharmacology, 66 (12), 2323-2331. Meyer, A., Yan, S., Golumba-Nagy, V., Esser, R. L., Barbarino, V., Blakemore, S. J., . . . Gruell, H. (2021). Kinase activity profiling reveals contribution of G-protein signaling modulator 2 deficiency to impaired regulatory T cell migration in rheumatoid arthritis. Journal of Autoimmunity, 124 , 102726. Morel, J. C., Park, C. C., Zhu, K., Kumar, P., Ruth, J. H., & Koch, A. E. (2002). Signal transduction pathways involved in rheumatoid arthritis synovial fibroblast interleukin-18-induced vascular cell adhesion molecule-1 expression. Journal of Biological Chemistry, 277 (38), 34679-34691. O'Boyle, N. M., Banck, M., James, C. A., Morley, C., Vandermeersch, T., & Hutchison, G. R. (2011). Open Babel: An open chemical toolbox. Journal of cheminformatics, 3 (1), 1-14. Oglah, M. K., Mustafa, Y. F., Bashir, M. K., Jasim, M. H., & Mustafa, Y. F. (2020). Curcumin and its derivatives: A review of their biological activities. Syst. Rev. Pharm, 11 (3), 472-481. Papakonstantinou, D. (2021). Work disability and rheumatoid arthritis: Predictive factors. Work, 69 (4), 1293-1304. Porro, C., & Panaro, M. A. (2023). Recent Progress in Understanding the Health Benefits of Curcumin. Molecules, 28 (5), 2418. Pourhabibi‐Zarandi, F., Shojaei‐Zarghani, S., & Rafraf, M. (2021). Curcumin and rheumatoid arthritis: A systematic review of literature. International Journal of Clinical Practice, 75 (10), e14280. Shakibaei, M., Mobasheri, A., Lueders, C., Busch, F., Shayan, P., & Goel, A. (2013). Curcumin enhances the effect of chemotherapy against colorectal cancer cells by inhibition of NF-κB and Src protein kinase signaling pathways. PloS one, 8 (2), e57218. Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., . . . Ideker, T. (2003). Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome research, 13 (11), 2498-2504. Sherman, B. T., Hao, M., Qiu, J., Jiao, X., Baseler, M. W., Lane, H. C., . . . Chang, W. (2022). DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic acids research, 50 (W1), W216-W221. Slika, L., & Patra, D. (2020). A short review on chemical properties, stability and nano-technological advances for curcumin delivery. Expert opinion on drug delivery, 17 (1), 61-75. Toya, M., Akasaki, Y., Sueishi, T., Kurakazu, I., Kuwahara, M., Uchida, T., . . . Lotz, M. K. (2021). G protein-coupled receptor kinase 5 deletion suppresses synovial inflammation in a murine model of collagen antibody-induced arthritis. Scientific reports, 11 (1), 10481. Veselinovic, M., Barudzic, N., Vuletic, M., Zivkovic, V., Tomic-Lucic, A., Djuric, D., & Jakovljevic, V. (2014). Oxidative stress in rheumatoid arthritis patients: relationship to diseases activity. Molecular and cellular biochemistry, 391 , 225-232. Wang, X., Shen, Y., Wang, S., Li, S., Zhang, W., Liu, X., . . . Li, H. (2017). PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database. Nucleic acids research, 45 (W1), W356-W360. Wishart, D. S., Feunang, Y. D., Guo, A. C., Lo, E. J., Marcu, A., Grant, J. R., . . . Sayeeda, Z. (2018). DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic acids research, 46 (D1), D1074-D1082. Yan, M., Su, J., & Li, Y. (2020). Rheumatoid arthritis-associated bone erosions: evolving insights and promising therapeutic strategies. BioScience Trends, 14 (5), 342-348. Yu, Z., Wan, Y., Liu, Y., Yang, J., Li, L., & Zhang, W. (2016). Curcumin induced apoptosis via PI3K/Akt-signalling pathways in SKOV3 cells. Pharmaceutical biology, 54 (10), 2026-2032. Zhang, L., Sun, S., Zhou, J., Liu, J., Lv, J.-H., Yu, X.-Q., . . . Deng, M. (2011). Knockdown of Akt1 promotes Akt2 upregulation and resistance to oxidative-stress-induced apoptosis through control of multiple signaling pathways. Antioxidants & redox signaling, 15 (1), 1-17. Ramsay, R. R., Popovic-Nikolic, M. R., Nikolic, K., Uliassi, E., & Bolognesi, M. L. (2018). A perspective on multi-target drug discovery and design for complex diseases. Clinical and translational medicine, 7 (1), 1-14. Rathore, S., Mukim, M., Sharma, P., Devi, S., Nagar, J. C., & Khalid, M. (2020). Curcumin: A review for health benefits. Int. J. Res. Rev, 7 (1), 273-290. Sharifi-Rad, J., Cruz-Martins, N., López-Jornet, P., Lopez, E. P.-F., Harun, N., Yeskaliyeva, B., . . . Sharopov, F. (2021). Natural coumarins: exploring the pharmacological complexity and underlying molecular mechanisms. Oxidative Medicine and Cellular Longevity, 2021 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3685735","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":254773639,"identity":"9c3bee41-648f-4bc3-91b4-bc1d44c4f355","order_by":0,"name":"Frank Kalungi","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Frank","middleName":"","lastName":"Kalungi","suffix":""},{"id":254773640,"identity":"e920773f-dadc-4744-bd78-670d6e4c06dd","order_by":1,"name":"Pradeep Kumar","email":"","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":false,"prefix":"","firstName":"Pradeep","middleName":"","lastName":"Kumar","suffix":""},{"id":254773641,"identity":"4ce714ee-f680-4461-ad4a-86c0da07f719","order_by":2,"name":"Ivan Ricardo Vega Valdez","email":"","orcid":"","institution":"Laboratorio de Biotecnologíay Bioinformática Genómica, Instituto Politécnico Nacional, Mexico","correspondingAuthor":false,"prefix":"","firstName":"Ivan","middleName":"Ricardo Vega","lastName":"Valdez","suffix":""},{"id":254773642,"identity":"717d9ca1-49f0-4102-8403-bc6bf3f63c5a","order_by":3,"name":"Godwin Anywar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYHACA4YEGPMDELOxk6KFcQZICzMxWmCAmQdMElAv7968TeLhDrs8gxvJzz7b/Nomz8fMwPjhYw5uLYZnjpVJJJ5JLja4kWY8O7fvtmEbMwOz5MxteLTMyDG7kdjGnLjhdoIxc27PbUagFjZmXsJa6oFa0j8zW/bctieoRV4CrOUwUEuOMTPDj9uJBLUY8Bwr/5HYdjxx5v03xYy9DbeT25gZm/H6Rb69ebPhz7bqxL4zxzcz/Phz23Z+e/PBDx/x2XIAylAAMRjbQEzGBtzqQbY0oDD+4FU8CkbBKBgFIxQAAEiBVhs8MXLnAAAAAElFTkSuQmCC","orcid":"","institution":"Makerere University","correspondingAuthor":true,"prefix":"","firstName":"Godwin","middleName":"","lastName":"Anywar","suffix":""}],"badges":[],"createdAt":"2023-11-30 08:44:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3685735/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3685735/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":47576219,"identity":"3402fb08-040a-4bf3-b53d-79b09be8291c","added_by":"auto","created_at":"2023-12-04 17:54:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54663,"visible":true,"origin":"","legend":"\u003cp\u003eChemical structure of Tumeric. Adapted from (\u003ca href=\"https://www.researchsquare.com/article/rs-3685735/admin/draft#_ENREF_3\" title=\"Sharifi-Rad, 2021 #85\"\u003eSharifi-Rad et al., 2021\u003c/a\u003e) .\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3685735/v1/c00854b07d2eebe370eea1be.png"},{"id":47576217,"identity":"5f11c11d-5b14-4e63-83bb-f617c6c8a8e9","added_by":"auto","created_at":"2023-12-04 17:54:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":70163,"visible":true,"origin":"","legend":"\u003cp\u003eOverlapping targets between curcumin and rheumatoid arthritis\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3685735/v1/545a1b25e79c3e79bbbe20d6.png"},{"id":47576222,"identity":"45ccfc01-5d4e-4fea-8835-3c4cfeddcc3b","added_by":"auto","created_at":"2023-12-04 17:54:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1011691,"visible":true,"origin":"","legend":"\u003cp\u003eCompound-disease_target network\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3685735/v1/1aa83a41b13e4a7d0b5f9177.png"},{"id":47576218,"identity":"017560b1-10fa-4742-b53a-4ad96086718c","added_by":"auto","created_at":"2023-12-04 17:54:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":175294,"visible":true,"origin":"","legend":"\u003cp\u003ea: Biological processes enriched with the RA-curcumin associated targets\u003c/p\u003e\n\u003cp\u003eb: Cellular components enriched with RA-curcumin associated targets\u003c/p\u003e\n\u003cp\u003ec: Molecular functions associated with RA-curcumin associated targets\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3685735/v1/6b482618e356a413053276ef.png"},{"id":47577671,"identity":"210dfba3-a026-4b90-af88-1eadda03e0ed","added_by":"auto","created_at":"2023-12-04 18:02:22","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":147347,"visible":true,"origin":"","legend":"\u003cp\u003eBubble chart showing KEGG pathway enrichment analysis of 190 targets RA-curcumin associated targets\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3685735/v1/0931d7a5aa79a77be2cfdded.png"},{"id":47577670,"identity":"9e1dd0ed-3f10-4346-90e5-1c487f3a8fa1","added_by":"auto","created_at":"2023-12-04 18:02:22","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1311760,"visible":true,"origin":"","legend":"\u003cp\u003eCompound-disease target-pathway network\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3685735/v1/499f9aa87ed8a41b22fbaf39.png"},{"id":47576225,"identity":"13ab4e70-e426-49ef-8724-62d8b05f9aab","added_by":"auto","created_at":"2023-12-04 17:54:23","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1299717,"visible":true,"origin":"","legend":"\u003cp\u003eProtein to Protein interaction network of 190 targets visualized using cytoscape (v 3.9.1)\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3685735/v1/42700019876f307c680d7c90.png"},{"id":47576221,"identity":"97e6ab96-23ef-40b5-b18f-3977e6c0eff8","added_by":"auto","created_at":"2023-12-04 17:54:22","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":477015,"visible":true,"origin":"","legend":"\u003cp\u003eCurcumin-target complexes visualized using Pymol.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-3685735/v1/ef1f7b4d269f6fd7e2413a96.png"},{"id":54631949,"identity":"20f5acbd-40ee-4817-a216-6e3c648d7e16","added_by":"auto","created_at":"2024-04-13 18:24:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4643009,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3685735/v1/3c97e454-d089-4cb6-9c31-e8408664266f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Curcumin’s molecular mechanism of action and targets in the treatment of rheumatoid arthritis: A network analysis and molecular docking study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRheumatoid arthritis (RA) is an autoimmune disorder that majorly affects the joints leading to pain, swelling, and stiffness. It occurs when the immune system mistakenly attacks the body\u0026rsquo;s own tissues leading to inflammation (Ding et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This inflammation occurs mainly in the synovial tissue and is identified by the buildup of inflammatory cells, synovial fibroblasts, macrophages, inflammatory cytokines like TNF-⍺, IL-1β, and IL-6 (Amalraj et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Rheumatoid arthritis can also affect other parts of the body such as skin, eyes and lungs and the symptoms vary from person to person (Bullock et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yan et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRheumatoid arthritis has a negative long-term outlook with up to 80% of patients experiencing disability after 20 years and a corresponding reduction in life expectancy by an average of 3 to 18 years. Without treatment, 20 to 30% of patients may become permanently work-disabled within two to three years of diagnosis (Chandran \u0026amp; Goel, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Papakonstantinou, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The exact cause of RA is uncertain but research suggests that a combination of genetic and environmental factors contribute to the development of the disease and related pathological processes (Pourhabibi-Zarandi et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Many drugs have been developed for the treatment of RA such non-steroidal anti-inflammatory drugs (NSAIDS). However they are associated with various side effects (Laev \u0026amp; Salakhutdinov, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCurcumin is a bright yellow compound from \u003cem\u003eCurcuma longa\u003c/em\u003e L (Tumeric), family \u003cem\u003eZingiberaceae\u003c/em\u003e (Ali et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), but is also found in other \u003cem\u003eCurcuma\u003c/em\u003e species. Curcumin is a polyphenolic compound with a chemical formula of C\u003csub\u003e21\u003c/sub\u003eH\u003csub\u003e20\u003c/sub\u003eO\u003csub\u003e6 ,\u003c/sub\u003e molecular weight of 368.38 g/mol (Porro \u0026amp; Panaro, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Its structure consists of two aromatic rings connected by a seven-carbon linker with various functional groups, including methoxy and hydroxy groups and is relatively insoluble in water but soluble in organic solvents like ethanol and acetone as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (Oglah et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Slika \u0026amp; Patra, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCurcumin has been extensively studied for its potential health benefits such as anti-inflammatory, antioxidant, anti-cancer and antidepressant effects (Rathore et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Curcumin interacts with multiple molecular targets and pathways. For instance, it alleviated rheumatoid arthritis-induced inflammation and synovial hyperplasia by targeting the mTOR pathway and inhibiting proinflammatory cytokines such as IL-1β and TNF-α in rats (Dai et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNetwork pharmacology is a rapidly developing field that utilizes computational methods to gain insights into the mechanisms of drug action across multiple levels of complexity ranging from individual drug targets to interactions between multiple targets (Belenahalli Shekarappa et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). By analyzing large-scale biological datasets and networks, network pharmacology seeks to uncover new drug targets and potential drug combinations that can be used to treat complex diseases. Ultimately, it aims to improve our understanding of how drugs interact with biological systems and pave the way for more personalized and effective drug therapies (Ayar et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kalungi et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn recent years, molecular docking has become an essential tool for modern drug discovery. It involves the use of algorithms and software programs to simulate the interaction between the drug molecule and the target protein, and to predict the most favorable binding mode and energy (Anywar \u0026amp; Namukobe, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kalungi et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, in this study, network pharmacology was used to explore the molecular mechanisms and targets involved in the treatment of RA with curcumin and the core targets were validated by molecular docking.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of therapeutic targets associated with curcumin\u003c/h2\u003e \u003cp\u003eThe therapeutic targets of curcumin were downloaded from DrugBank ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://go.drugbank.com/),PharmMapper(http://lilabecust.cn/pharmmapper/index.html\u003c/span\u003e\u003cspan address=\"https://go.drugbank.com/),PharmMapper(http://lilabecust.cn/pharmmapper/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) and SwissTargetPrediction ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://swisstargetprediction.ch/\u003c/span\u003e\u003cspan address=\"http://swisstargetprediction.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) with all searches specific to \u003cem\u003eHomo sapiens.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eThe Swiss Target Prediction server predicts macromolecular targets of small bioactive molecules basing on a similarity principle through reverse screening (Daina et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). PharmMapper uses a pharmacophore mapping approach to predict potential targets for small molecules (Wang et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). DrugBank is a database containing information on drugs, their mechanisms, interactions and targets (Wishart et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of potential pathological targets related to rheumatoid arthritis\u003c/h2\u003e \u003cp\u003eRA-curcumin associated targets were retrieved from NCBI gene ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/gene\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/gene\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ), GeneCards ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) and OMIM ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.omim.org/\u003c/span\u003e\u003cspan address=\"https://www.omim.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) databases with all searches specific to \u003cem\u003eHomo sapiens.\u003c/em\u003e The NCBI gene contains information such as reference sequences (RefSeq), maps, pathways, variations and phenotypes among others. GeneCards is a database of all annotated and predicted human genes. The OMIM database contains human genes and genetic phenotypes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of a compound-disease target network\u003c/h2\u003e \u003cp\u003eOverlapping genes (RA-curcumin associated targets) between curcumin and rheumatoid arthritis were obtained using Gene List Venn Diagram ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.org/gvenn/\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.org/gvenn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) and they were used to construct a network using Cytoscape software (v 3.9.1). Cytoscape is tool for analyzing and visualization of biomolecular interaction networks (Shannon et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eGene ontology (GO) enrichment analysis\u003c/h2\u003e \u003cp\u003eRA-curcumin associated targets were subjected to GO enrichment analysis i.e. biological process, cellular component and molecular function using ShinyGo (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bioinformatics.sdstate.edu/go/\u003c/span\u003e\u003cspan address=\"http://bioinformatics.sdstate.edu/go/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) and the False Discovery Rate (FDR) cut off was set at 0.05. ShinyGO is an interactive tool for gene set enrichment analysis for both animals and plants (Ge et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eKyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis\u003c/h2\u003e \u003cp\u003eThe analysis was accomplished by The Database for Annotation, Visualization and Integrated Discovery (DAVID) using RA-curcumin associated targets as input. DAVID ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://david.ncifcrf.gov/\u003c/span\u003e\u003cspan address=\"https://david.ncifcrf.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) is a web server for functional enrichment analyses and annotation of gene lists (Sherman et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The bubble chart for KEGG pathway enrichment analysis was drawn using a bioinformatics web server ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.bioinformatics.com.cn/\u003c/span\u003e\u003cspan address=\"http://www.bioinformatics.com.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of compound-disease-target-pathway (C-D-P) network\u003c/h2\u003e \u003cp\u003eDisease_target-pathway network was constructed and then merged with the compound-disease-target network using Cytoscape (v 3.9.1) to produce the C-D-P network. Pathways whose p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were used in this network.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConstruction of Protein-Protein interaction network.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eRA-curcumin associated targets were inputted into STRING ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003cspan address=\"https://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) to obtain a PPI network. To obtain a clear network a confidence score\u0026thinsp;\u0026lt;\u0026thinsp;0.900 was used. The network was built specific to \u003cem\u003eHomo sapiens.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMolecular docking simulation\u003c/h2\u003e \u003cp\u003eThe top targets with good interaction with the curcumin, other genes and pathways were subjected for molecular docking. Their structures were downloaded from the Protein Data Bank ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcsb.org/\u003c/span\u003e\u003cspan address=\"https://www.rcsb.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) and then prepared for molecular docking using Autodock tools (ADT). Curcumin\u0026rsquo;s structure was obtained from PubChem ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) and then converted into PDB format using Open Babel (O'Boyle et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe simulation was performed by using Autodock 4.2 (Download AutoDock4 \u0026ndash; AutoDock (scripps.edu)) using Larmackian Genetic algorithm and ADT was used to visualize the docking results. Pymol software was used to visualize the protein ligand complexes and their interactions (DeLano, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eTherapeutic targets associated with curcumin, rheumatoid arthritis and Compound-disease_target construction\u003c/h2\u003e\n \u003cp\u003eOverall, 385 targets related to curcumin were retrieved from DrugBank, PharmMapper and SwissTargetPrediction. In addition, 5,351 targets associated with RA were retrieved from OMIM, GeneCards and NCBI gene. One hundred and ninety overlapping targets between curcumin and RA were obtained as shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eRheumatoid Arthritis_curcumin associated targets were then used to construct a compound-disease-target network as shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eGene ontology analysis (GO)\u003c/h2\u003e\n \u003cp\u003eThe most significant GO categories that pass the cut off criterion of FDR\u0026thinsp;=\u0026thinsp;0.05 were obtained. RA-curcumin associated targets were associated with biological processes such as response to peptide, response to hormone, inflammatory response, cellular response to oxygen-containing compound, response to organonitrogen, negative regulation of cell death, regulation of response to external stimulus etc as shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea.\u003c/p\u003e\n \u003cp\u003eIn addition, the targets were associated with cellular components such as protein kinase complex, vesicle lumen, membrane raft, membrane microdomain, secretory granule lumen, cytoplasmic vesicle lumen, focal adhesion, cell-substrate junction etc as shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb. Finally, the targets were associated with molecular functions such as non-membrane spanning protein tyrosine kinase activity, nuclear receptor activity, ligand-activated transcription factor activity, transmembrane receptor protein tyrosine kinase activity, protein phosphatase binding etc as shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ec.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eKEGG pathway enrichment analysis.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eOne hundred and ninety RA-curcumin associated targets were uploaded into DAVID and top 19 enriched pathways with \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and based on gene counts were selected. Figure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e shows a bubble chart showing KEGG pathway enrichment analysis of 190 RA-curcumin associated targets. The targets were mainly enriched with 5 infections (hepatitis B, hepatitis C, human cytomegalovirus infection, toxoplasmosis, \u003cem\u003eHelicobacter pylori\u003c/em\u003e infection) and signaling pathways related to cell function and regulation (MAPK signaling pathway, Ras signaling pathway, T cell receptor signaling pathway, FoxO signaling pathway, and PI3K-Akt signaling pathway).\u003c/p\u003e\n \u003cp\u003eIn addition, the targets were enriched with atherosclerosis and lipid-related pathways (lipid and atherosclerosis, fluid shear stress and atherosclerosis) and cancer-related pathways and diseases (pathways in cancer, prostate cancer, EGFR tyrosine kinase inhibitor resistance, proteoglycans in cancer, pancreatic cancer, PD-L1 expression and PD-1 checkpoint pathway in cancer, and acute myeloid leukemia).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eCompound-disease target-pathway network\u003c/h2\u003e\n \u003cp\u003eThe D-P network was merged with C-D network to give C-D-P network with 209 nodes and 621 edges as shown in Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e. In the network, nodes represent curcumin, pathways and targets whereas the edges represent the multiple interactions among the nodes. The number of edges that a node has with other nodes in the network is referred to as the degree.\u003c/p\u003e\n \u003cp\u003eAKT2 and AKT1 showed the highest degree among the target nodes and thus representing hub genes that may be play an important role in the structure and function of the network.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003ePPI network analysis\u003c/h2\u003e\n \u003cp\u003eOne hundred and ninety RA-curcumin associated targets were inputted into STRING to produce a PPI network. The network was downloaded and then analyzed using cytoscape and it contained 140 nodes and 422 edges. The top targets with the highest degree that is AKT1 and SRC were identified. Figure \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e shows the PPI network of 190 RA-curcumin associated targets.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eMolecular Docking\u003c/h2\u003e\n \u003cp\u003eThe C-D-P and PPI network analysis revealed AKT1, AKT2 and SRC as the top three targets and were subjected to molecular docking with curcumin. Analysis of the docking results for the protein-ligand complexes was done using ADT. The binding affinity of curcumin and the targets were \u0026minus;\u0026thinsp;7.51 kj/mol, -6.85 kj/mol and \u0026minus;\u0026thinsp;8.52 kj/mol respectively. Figure \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e shows curcumin-target complexes visualized using pymol.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOver the past years, there has been advancement in cheminformatics and establishment of large scale structure-activity-relationship databases and thus leading to development of \u003cem\u003ein silico\u003c/em\u003e methods for multitarget drug (Ramsay et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Understanding the specific binding of a drug to two or more targets and its effects on biological networks and phenotype is essential not only for improving its efficacy but also for understanding its toxicity (Brogi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hopkins, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, a holistic systems biology approach integrating target identification, network construction and analysis, gene ontology analysis, KEGG pathway enrichment analysis, protein-protein interaction analysis and molecular docking was employed to evaluate the molecular mechanism and targets of curcumin against rheumatoid arthritis. From database mining, 190 RA-curcumin associated targets were retrieved and KEGG pathway enrichment analysis revealed that they were significantly enriched in various pathways related to infectious diseases, signaling pathways associated with cell function and regulation, atherosclerosis and lipid metabolism as well as cancer-related pathways and diseases.\u003c/p\u003e \u003cp\u003eGene ontology analysis demonstrated BP terms such response to peptide, response to hormone, inflammatory response, cellular response to oxygen containing compound etc. were revealed. A fibrinogen-derived 21-amino-acid-long citrullinated peptide was found to be a reliable biomarker for early rheumatoid arthritis diagnosis and flare prediction, which is valuable for managing patients who respond poorly to treatment (Khatri et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Joint inflammation was found to recur in the same joints during the progression of RA (Heckert et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition, CC terms such as protein kinase complex, vesicle lumen, membrane raft etc. were also revealed. Furthermore, MF terms revealed included non-membrane spanning protein tyrosine kinase activity, nuclear receptor activity, ligand-activated transcription factor activity etc. Analysis of the kinome in CD4\u0026thinsp;+\u0026thinsp;T cells from rheumatoid arthritis (RA) patients unveiled substantial changes in the post-translational phosphorylation of proteins associated with kinases, notably G-protein-signaling modulator 2 (GPSM2), protein tyrosine kinase 6 (PTK6), and the precursor of vitronectin (VTNC) (Meyer et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The removal of G protein-coupled receptor kinase 5 (GRK5) inhibits synovial inflammation in a mouse model of collagen antibody-induced arthritis (Toya et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNetwork analysis revealed that AKT1, AKT2 and SRC were the three main targets among 190 RA-curcumin associated targets and were identified as hub genes. The targets were further validated by molecular docking simulation with curcumin and SRC showing the strongest binding affinity of -8.52 kj/mol followed by AKT1 (-7.51kj.mol) and AKT2 (-6.85 kj/mol). SRC is a proto-oncogene that encodes a tyrosine protein kinase which has been found to play central role in the activation and proper functioning of macrophages which are critical components of the immune system involved in the initial defense against pathogens and the regulation of inflammatory responses (Byeon et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). A recent study showed that nanospheres loaded with curcumin induced c-SRC activation which supports our findings (Kim et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn order to understand the treatment of inflammatory and angiogenic diseases such as RA by targeting vascular cell adhesion molecule (VCAM)-1 signaling mechanisms, researchers showed that interleukin-18 exhibits direct and swift activation of SRC which suggested that SRC activation serves as an initial event shared by the PI3-kinase/AKT and ERK1/2 pathways (Morel et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, sphingosine-1-phosphate increased osteoblastic vascular endothelial growth factor expression and thus promoting endothelial progenitor cell angiogenesis by inhibiting miR-16-5p synthesis through c-SRC/FAK signaling and thus providing a valuable approach in developing of treatment strategies for RA (Huang et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Moreover curcumin was found to inhibit the kinase activity of v-SRC leading to a decrease in tyrosyl substrate phosphorylation of Shc, cortactin, and FAK and thus demonstrating that it can retard cellular growth and migration (Leu et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). In addition, curcumin was found to inhibit NF-κB and Src Protein Kinase Signaling Pathways (Shakibaei et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAKT is a type of serine/threonine protein kinase that plays a crucial role in numerous signaling pathways within cells. It acts as a significant mediator of signals downstream of activated phosphoinositide 3-kinase (PI3K), a key enzyme involved in cell growth and survival and it exists in three isoforms in mammals that is PKB-α (AKT1), PKB-β (AKT2), and PKBγ (AKT3) (Dummler \u0026amp; Hemmings, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Curcumin inhibits collagen-induced arthritis AKT1 indicating that it may alleviate RA-induced inflammation and synovial hyperplasia (Dai et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Curcumin was also found to inhibit P13K/AKT signaling in LPS activated microglia (Cianciulli et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition, RA pathogenesis has been associated with reactive oxygen species (Veselinovic et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The intracellular content of reactive oxygen species was found to be dependent on AKT1 and AKT2 (Juntilla et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). AKT2 enhances cell survival on exposure to hydrogen peroxide (Zhang et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Curcumin was also found to inhibit P13/AKT signaling in SKOV3 by retarding their growth which is line with our results (Yu et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Therefore, these findings highlight the multifaceted nature of curcumin and its potential implications in managing comorbidities observed in rheumatoid arthritis patients.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, a new approach was taken to investigate the molecular targets and potential mechanisms underlying the treatment effects of curcumin on RA. Curcumin, a natural compound found in turmeric exerts its effects against RA through multiple targets, pathways, and biological processes. Molecular docking analysis revealed that curcumin can form stable interactions with key proteins involved in RA, including SRC, AKT1 and AKT2. These findings suggest that curcumin has the potential to interfere with the activity of these proteins and potentially inhibit the growth and progression of RA. However, further research is needed to validate the clinical effectiveness of curcumin and to understand the precise mechanisms by which it exerts its anti-RA effects.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the support from National Agricultural Research Laboratories, Kawanda, Dr. Miriam Nakabuye from Novo Nordisk Foundation Center for Basic Metabolic Research and the staff at the Department of Plant Sciences, Microbiology and Biotechnology, Makerere University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFK designed and conducted the study under the guidance and supervision of GA. PK and IRVVconducted and verified some of the experiments. FK wrote the first draft of the manuscript under the guidance of and GA. All authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive funding from anybody or organization\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding authors upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest regarding this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAli A, Ali A, Tahir A, Bakht MA, Salahuddin, Ahsan MJ (2021). Molecular engineering of curcumin, an active constituent of Curcuma longa L.(Turmeric) of the family Zingiberaceae with improved antiproliferative activity. Plants, 10(8), 1559. \u003c/li\u003e\n\u003cli\u003eAmalraj A, Varma K, Jacob J, Divya C, Kunnumakkara AB, Stohs SJ, Gopi S (2017). A novel highly bioavailable curcumin formulation improves symptoms and diagnostic indicators in rheumatoid arthritis patients: a randomized, double-blind, placebo-controlled, two-dose, three-arm, and parallel-group study. \u003cem\u003eJournal of medicinal food, 20\u003c/em\u003e(10), 1022-1030. \u003c/li\u003e\n\u003cli\u003eAnywar G, Namukobe J (2020). Factors affecting the choice for plant-based products in drug discoveries \u003cem\u003ePhytochemicals as Lead Compounds for New Drug Discovery\u003c/em\u003e (pp. 15-24): Elsevier.\u003c/li\u003e\n\u003cli\u003eAyar ES, Dadmand S, Tuncbag N (2023). Network Medicine: From Conceptual Frameworks to Applications and Future Trends. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. \u003c/li\u003e\n\u003cli\u003eBelenahalli Shekarappa S, Kandagalla S, Hanumanthappa M (2019). A network pharmacology approach to investigate the pharmacological effect of curcumin and capsaicin targets in cancer angiogenesis by module-based PPI network analysis. Journal of Proteins and Proteomics, 10, 109-120. \u003c/li\u003e\n\u003cli\u003eBrogi S, Ramalho TC, Kuca K, Medina-Franco JL, Valko M (2020) In silico methods for drug design and discovery (Vol. 8, pp. 612): Frontiers Media SA.\u003c/li\u003e\n\u003cli\u003eBullock J, Rizvi SA, Saleh AM, Ahmed SS, Do DP, Ansari RA, Ahmed J (2019) Rheumatoid arthritis: a brief overview of the treatment. Medical Principles and Practice, 27(6), 501-507. \u003c/li\u003e\n\u003cli\u003eByeon SE, Yi Y-S, Oh J, Yoo BC, Hong S, Cho JY (2012) The role of Src kinase in macrophage-mediated inflammatory responses. Mediators of inflammation, 2012. \u003c/li\u003e\n\u003cli\u003eChandran, B., \u0026amp; Goel, A. (2012). A randomized, pilot study to assess the efficacy and safety of curcumin in patients with active rheumatoid arthritis. \u003cem\u003ePhytotherapy research, 26\u003c/em\u003e(11), 1719-1725. \u003c/li\u003e\n\u003cli\u003eCianciulli, A., Calvello, R., Porro, C., Trotta, T., Salvatore, R., \u0026amp; Panaro, M. A. (2016). PI3k/Akt signalling pathway plays a crucial role in the anti-inflammatory effects of curcumin in LPS-activated microglia. \u003cem\u003eInternational immunopharmacology, 36\u003c/em\u003e, 282-290. \u003c/li\u003e\n\u003cli\u003eDai, Q., Zhou, D., Xu, L., \u0026amp; Song, X. (2018). Curcumin alleviates rheumatoid arthritis-induced inflammation and synovial hyperplasia by targeting mTOR pathway in rats. \u003cem\u003eDrug design, development and therapy\u003c/em\u003e, 4095-4105. \u003c/li\u003e\n\u003cli\u003eDaina, A., Michielin, O., \u0026amp; Zoete, V. (2019). SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules. \u003cem\u003eNucleic acids research, 47\u003c/em\u003e(W1), W357-W364. \u003c/li\u003e\n\u003cli\u003eDeLano, W. L. (2002). Pymol: An open-source molecular graphics tool. \u003cem\u003eCCP4 Newsl. Protein Crystallogr, 40\u003c/em\u003e(1), 82-92. \u003c/li\u003e\n\u003cli\u003eDing, Q., Hu, W., Wang, R., Yang, Q., Zhu, M., Li, M., . . . Zhu, Y. Z. (2023). Signaling pathways in rheumatoid arthritis: implications for targeted therapy. \u003cem\u003eSignal Transduction and Targeted Therapy, 8\u003c/em\u003e(1), 68. \u003c/li\u003e\n\u003cli\u003eDummler, B., \u0026amp; Hemmings, B. (2007). Physiological roles of PKB/Akt isoforms in development and disease: Portland Press Ltd.\u003c/li\u003e\n\u003cli\u003eGe, S. X., Jung, D., \u0026amp; Yao, R. (2020). ShinyGO: a graphical gene-set enrichment tool for animals and plants. \u003cem\u003eBioinformatics, 36\u003c/em\u003e(8), 2628-2629. \u003c/li\u003e\n\u003cli\u003eHeckert, S. L., Bergstra, S. A., Matthijssen, X. M., Goekoop-Ruiterman, Y. P., Fodili, F., Ten Wolde, S., . . . Huizinga, T. W. (2022). Joint inflammation tends to recur in the same joints during the rheumatoid arthritis disease course. \u003cem\u003eAnnals of the Rheumatic Diseases, 81\u003c/em\u003e(2), 169-174. \u003c/li\u003e\n\u003cli\u003eHopkins, A. L. (2008). Network pharmacology: the next paradigm in drug discovery. \u003cem\u003eNature chemical biology, 4\u003c/em\u003e(11), 682-690. \u003c/li\u003e\n\u003cli\u003eHuang, C.-C., Tseng, T.-T., Liu, S.-C., Lin, Y.-Y., Law, Y.-Y., Hu, S.-L., . . . Tang, C.-H. (2021). S1p increases vegf production in osteoblasts and facilitates endothelial progenitor cell angiogenesis by inhibiting mir-16-5p expression via the c-src/fak signaling pathway in rheumatoid arthritis. \u003cem\u003eCells, 10\u003c/em\u003e(8), 2168. \u003c/li\u003e\n\u003cli\u003eJuntilla, M. M., Patil, V. D., Calamito, M., Joshi, R. P., Birnbaum, M. J., \u0026amp; Koretzky, G. A. (2010). AKT1 and AKT2 maintain hematopoietic stem cell function by regulating reactive oxygen species. \u003cem\u003eBlood, The Journal of the American Society of Hematology, 115\u003c/em\u003e(20), 4030-4038. \u003c/li\u003e\n\u003cli\u003eKalungi, F., Nsubuga, A., \u0026amp; Anywar, G. (2023). Network analysis and molecular docking studies of quercetin as a potential treatment for prostate cancer. \u003cem\u003eIn Silico Pharmacology, 11\u003c/em\u003e(1), 24. \u003c/li\u003e\n\u003cli\u003eKhatri, S., Hansen, J., \u0026amp; Astakhova, K. (2020). Antibodies to synthetic citrullinated peptide epitope correlate with disease activity and flares in rheumatoid arthritis. \u003cem\u003ePloS one, 15\u003c/em\u003e(4), e0232010. \u003c/li\u003e\n\u003cli\u003eKim, D.-W., Choi, C.-H., Park, J. P., \u0026amp; Lee, S.-J. (2020). Nanospheres loaded with curcumin improve the bioactivity of umbilical cord BLOOD-mesenchymal stem cells via c-Src activation during the skin wound healing process. \u003cem\u003eCells, 9\u003c/em\u003e(6), 1467. \u003c/li\u003e\n\u003cli\u003eLaev, S. S., \u0026amp; Salakhutdinov, N. F. (2015). Anti-arthritic agents: progress and potential. \u003cem\u003eBioorganic \u0026amp; medicinal chemistry, 23\u003c/em\u003e(13), 3059-3080. \u003c/li\u003e\n\u003cli\u003eLeu, T.-H., Su, S. L., Chuang, Y.-C., \u0026amp; Maa, M.-C. (2003). Direct inhibitory effect of curcumin on Src and focal adhesion kinase activity. \u003cem\u003eBiochemical pharmacology, 66\u003c/em\u003e(12), 2323-2331. \u003c/li\u003e\n\u003cli\u003eMeyer, A., Yan, S., Golumba-Nagy, V., Esser, R. L., Barbarino, V., Blakemore, S. J., . . . Gruell, H. (2021). Kinase activity profiling reveals contribution of G-protein signaling modulator 2 deficiency to impaired regulatory T cell migration in rheumatoid arthritis. \u003cem\u003eJournal of Autoimmunity, 124\u003c/em\u003e, 102726. \u003c/li\u003e\n\u003cli\u003eMorel, J. C., Park, C. C., Zhu, K., Kumar, P., Ruth, J. H., \u0026amp; Koch, A. E. (2002). Signal transduction pathways involved in rheumatoid arthritis synovial fibroblast interleukin-18-induced vascular cell adhesion molecule-1 expression. \u003cem\u003eJournal of Biological Chemistry, 277\u003c/em\u003e(38), 34679-34691. \u003c/li\u003e\n\u003cli\u003eO\u0026apos;Boyle, N. M., Banck, M., James, C. A., Morley, C., Vandermeersch, T., \u0026amp; Hutchison, G. R. (2011). Open Babel: An open chemical toolbox. \u003cem\u003eJournal of cheminformatics, 3\u003c/em\u003e(1), 1-14. \u003c/li\u003e\n\u003cli\u003eOglah, M. K., Mustafa, Y. F., Bashir, M. K., Jasim, M. H., \u0026amp; Mustafa, Y. F. (2020). Curcumin and its derivatives: A review of their biological activities. \u003cem\u003eSyst. Rev. Pharm, 11\u003c/em\u003e(3), 472-481. \u003c/li\u003e\n\u003cli\u003ePapakonstantinou, D. (2021). Work disability and rheumatoid arthritis: Predictive factors. \u003cem\u003eWork, 69\u003c/em\u003e(4), 1293-1304. \u003c/li\u003e\n\u003cli\u003ePorro, C., \u0026amp; Panaro, M. A. (2023). Recent Progress in Understanding the Health Benefits of Curcumin. \u003cem\u003eMolecules, 28\u003c/em\u003e(5), 2418. \u003c/li\u003e\n\u003cli\u003ePourhabibi‐Zarandi, F., Shojaei‐Zarghani, S., \u0026amp; Rafraf, M. (2021). Curcumin and rheumatoid arthritis: A systematic review of literature. \u003cem\u003eInternational Journal of Clinical Practice, 75\u003c/em\u003e(10), e14280. \u003c/li\u003e\n\u003cli\u003eShakibaei, M., Mobasheri, A., Lueders, C., Busch, F., Shayan, P., \u0026amp; Goel, A. (2013). Curcumin enhances the effect of chemotherapy against colorectal cancer cells by inhibition of NF-\u0026kappa;B and Src protein kinase signaling pathways. \u003cem\u003ePloS one, 8\u003c/em\u003e(2), e57218. \u003c/li\u003e\n\u003cli\u003eShannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., . . . Ideker, T. (2003). Cytoscape: a software environment for integrated models of biomolecular interaction networks. \u003cem\u003eGenome research, 13\u003c/em\u003e(11), 2498-2504. \u003c/li\u003e\n\u003cli\u003eSherman, B. T., Hao, M., Qiu, J., Jiao, X., Baseler, M. W., Lane, H. C., . . . Chang, W. (2022). DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). \u003cem\u003eNucleic acids research, 50\u003c/em\u003e(W1), W216-W221. \u003c/li\u003e\n\u003cli\u003eSlika, L., \u0026amp; Patra, D. (2020). A short review on chemical properties, stability and nano-technological advances for curcumin delivery. \u003cem\u003eExpert opinion on drug delivery, 17\u003c/em\u003e(1), 61-75. \u003c/li\u003e\n\u003cli\u003eToya, M., Akasaki, Y., Sueishi, T., Kurakazu, I., Kuwahara, M., Uchida, T., . . . Lotz, M. K. (2021). G protein-coupled receptor kinase 5 deletion suppresses synovial inflammation in a murine model of collagen antibody-induced arthritis. \u003cem\u003eScientific reports, 11\u003c/em\u003e(1), 10481. \u003c/li\u003e\n\u003cli\u003eVeselinovic, M., Barudzic, N., Vuletic, M., Zivkovic, V., Tomic-Lucic, A., Djuric, D., \u0026amp; Jakovljevic, V. (2014). Oxidative stress in rheumatoid arthritis patients: relationship to diseases activity. \u003cem\u003eMolecular and cellular biochemistry, 391\u003c/em\u003e, 225-232. \u003c/li\u003e\n\u003cli\u003eWang, X., Shen, Y., Wang, S., Li, S., Zhang, W., Liu, X., . . . Li, H. (2017). PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database. \u003cem\u003eNucleic acids research, 45\u003c/em\u003e(W1), W356-W360. \u003c/li\u003e\n\u003cli\u003eWishart, D. S., Feunang, Y. D., Guo, A. C., Lo, E. J., Marcu, A., Grant, J. R., . . . Sayeeda, Z. (2018). DrugBank 5.0: a major update to the DrugBank database for 2018. \u003cem\u003eNucleic acids research, 46\u003c/em\u003e(D1), D1074-D1082. \u003c/li\u003e\n\u003cli\u003eYan, M., Su, J., \u0026amp; Li, Y. (2020). Rheumatoid arthritis-associated bone erosions: evolving insights and promising therapeutic strategies. \u003cem\u003eBioScience Trends, 14\u003c/em\u003e(5), 342-348. \u003c/li\u003e\n\u003cli\u003eYu, Z., Wan, Y., Liu, Y., Yang, J., Li, L., \u0026amp; Zhang, W. (2016). Curcumin induced apoptosis via PI3K/Akt-signalling pathways in SKOV3 cells. \u003cem\u003ePharmaceutical biology, 54\u003c/em\u003e(10), 2026-2032. \u003c/li\u003e\n\u003cli\u003eZhang, L., Sun, S., Zhou, J., Liu, J., Lv, J.-H., Yu, X.-Q., . . . Deng, M. (2011). Knockdown of Akt1 promotes Akt2 upregulation and resistance to oxidative-stress-induced apoptosis through control of multiple signaling pathways. \u003cem\u003eAntioxidants \u0026amp; redox signaling, 15\u003c/em\u003e(1), 1-17. \u003c/li\u003e\n\u003cli\u003eRamsay, R. R., Popovic-Nikolic, M. R., Nikolic, K., Uliassi, E., \u0026amp; Bolognesi, M. L. (2018). A perspective on multi-target drug discovery and design for complex diseases. \u003cem\u003eClinical and translational medicine, 7\u003c/em\u003e(1), 1-14.\u003c/li\u003e\n\u003cli\u003eRathore, S., Mukim, M., Sharma, P., Devi, S., Nagar, J. C., \u0026amp; Khalid, M. (2020). Curcumin: A review for health benefits. \u003cem\u003eInt. J. Res. Rev, 7\u003c/em\u003e(1), 273-290.\u003c/li\u003e\n\u003cli\u003eSharifi-Rad, J., Cruz-Martins, N., L\u0026oacute;pez-Jornet, P., Lopez, E. P.-F., Harun, N., Yeskaliyeva, B., . . . Sharopov, F. (2021). Natural coumarins: exploring the pharmacological complexity and underlying molecular mechanisms. \u003cem\u003eOxidative Medicine and Cellular Longevity, 2021\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rheumatoid arthritis, curcumin, network pharmacology, inflammation","lastPublishedDoi":"10.21203/rs.3.rs-3685735/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3685735/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e: Rheumatoid Arthritis (RA) is an autoimmune disorder that majorly affects the joints leading to pain, swelling, and stiffness and inflammation. Curcumin is a chemical compound from \u003cem\u003eCurcuma longa\u003c/em\u003e(Tumeric). The aim of this study was to investigate the molecular mechanisms underlying the treatment of RA using curcumin.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Curcumin associated targets were retrieved from SwissTargetPrediction, PharmMapper and DrugBank. The RA associated targets were retrieved from OMIM, GeneCards, NCBI gene databases.\u003cem\u003e \u003c/em\u003eGeneVenn was used to determine overlapping genes (RA-curcumin associated targets).\u003cem\u003e \u003c/em\u003eThe targets were used to construct a compound-disease target network. Gene Ontology enrichment analysis was done to identify the molecular function, cellular components and biological processes associated with the targets. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses was performed to identify top pathways with \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05. A disease target-pathway network (D-P) was constructed and then merged with the C-D network to produce a compound-disease target-pathway network (C-D-P).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eWe obtained 190\u003cstrong\u003e \u003c/strong\u003eRA-curcumin associated targets.Gene ontology analysis revealed response to peptide, protein kinase complex and non-membrane spanning protein kinase activity as the major biological processes, cellular componentsand molecular functionterms respectively. Network analysis revealed SRC, AKT1 and AKT2 as the hub targets. Molecular docking showed that curcumin can bind stably to the hub targets.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eCurcumin can interact with various proteins involved in the treatment of RA which can guide further its clinical application.\u003c/p\u003e","manuscriptTitle":"Curcumin’s molecular mechanism of action and targets in the treatment of rheumatoid arthritis: A network analysis and molecular docking study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-12-04 17:54:18","doi":"10.21203/rs.3.rs-3685735/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a8aeabc5-4d19-44d6-bb3f-7add970f3fe2","owner":[],"postedDate":"December 4th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-13T18:16:32+00:00","versionOfRecord":[],"versionCreatedAt":"2023-12-04 17:54:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3685735","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3685735","identity":"rs-3685735","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}