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Akki AJ, Patil SA, Hungund S, Sahana R, Patil MM, Kulkarni RV, Raghava Reddy K, Zameer F, Raghu AV. Advances in Parkinson's disease research - A computational network pharmacological approach. Int Immunopharmacol 2024; 139:112758. [PMID: 39067399 DOI: 10.1016/j.intimp.2024.112758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 07/22/2024] [Accepted: 07/22/2024] [Indexed: 07/30/2024]
Abstract
Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, is projected to see a significant rise in incidence over the next three decades. The precise treatment of PD remains a formidable challenge, prompting ongoing research into early diagnostic methodologies. Network pharmacology, a burgeoning field grounded in systems biology, examines the intricate networks of biological systems to identify critical signal nodes, facilitating the development of multi-target therapeutic molecules. This approach systematically maps the components of Parkinson's disease, thereby reducing its complexity. In this review, we explore the application of network pharmacology workflows in PD, discuss the techniques employed in this field, and evaluate the current advancements and status of network pharmacology in the context of Parkinson's disease. The comprehensive insights will pave newer paths to explore early disease biomarkers and to develop diagnosis with a holistic in silico, in vitro, in vivo and clinical studies.
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Affiliation(s)
- Ali Jawad Akki
- Faculty of Science and Technology, BLDE (Deemed-to-be University), Vijayapura 586 103, India
| | - Shruti A Patil
- Faculty of Science and Technology, BLDE (Deemed-to-be University), Vijayapura 586 103, India
| | - Sphoorty Hungund
- Faculty of Science and Technology, BLDE (Deemed-to-be University), Vijayapura 586 103, India
| | - R Sahana
- Department of Computer Science and Engineering, RV Institute of Technology and Management, 560 076 Bengaluru, India
| | - Malini M Patil
- Department of Computer Science and Engineering, RV Institute of Technology and Management, 560 076 Bengaluru, India.
| | - Raghavendra V Kulkarni
- Faculty of Science and Technology, BLDE (Deemed-to-be University), Vijayapura 586 103, India
| | - K Raghava Reddy
- School of Chemical and Biomolecular Engineering, The University of Sydney, Sydney, NSW 12 2006, Australia
| | - Farhan Zameer
- Department of Dravyaguna (Ayurveda Pharmacology), Alva's Ayurveda Medical College, and PathoGutOmics Laboratory, ATMA Research Centre, Dakshina Kannada 574 227, India.
| | - Anjanapura V Raghu
- Department of Basic Sciences, Faculty of Engineering and Technology, CMR University, 562149 Bangalore, India.
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Ding X, Ma X, Meng P, Yue J, Li L, Xu L. Potential Effects of Traditional Chinese Medicine in Anti-Aging and Aging-Related Diseases: Current Evidence and Perspectives. Clin Interv Aging 2024; 19:681-693. [PMID: 38706635 PMCID: PMC11070163 DOI: 10.2147/cia.s447514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 04/17/2024] [Indexed: 05/07/2024] Open
Abstract
Aging and aging-related diseases present a global public health problem. Therefore, the development of efficient anti-aging drugs has become an important area of research. Traditional Chinese medicine is an important complementary and alternative branch of aging-related diseases therapy. Recently, a growing number of studies have revealed that traditional Chinese medicine has a certain delaying effect on the progression of aging and aging-related diseases. Here, we review the progress in research into using traditional Chinese medicine for aging and aging-related diseases (including neurodegenerative diseases, cardiovascular diseases, diabetes, and cancer). Furthermore, we summarize the potential mechanisms of action of traditional Chinese medicine and provide references for further studies on aging and aging-related diseases.
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Affiliation(s)
- Xue Ding
- Department of Medical, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China
| | - Xiuxia Ma
- Department of AIDS Clinical Research Center, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China
| | - Pengfei Meng
- Department of the First Clinical Medical College, Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China
| | - Jingyu Yue
- Department of AIDS Clinical Research Center, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China
| | - Liangping Li
- Department of Graduate, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China
| | - Liran Xu
- Department of the First Clinical Medical College, Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China
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Sasikumar DSN, Thiruselvam P, Sundararajan V, Ravindran R, Gunasekaran S, Madathil D, Kaliamurthi S, Peslherbe GH, Selvaraj G, Sudhakaran SL. Insights into dietary phytochemicals targeting Parkinson's disease key genes and pathways: A network pharmacology approach. Comput Biol Med 2024; 172:108195. [PMID: 38460310 DOI: 10.1016/j.compbiomed.2024.108195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 01/26/2024] [Accepted: 02/18/2024] [Indexed: 03/11/2024]
Abstract
Parkinson's disease (PD) is a complex neurological disease associated with the degeneration of dopaminergic neurons. Oxidative stress is a key player in instigating apoptosis in dopaminergic neurons. To improve the survival of neurons many dietary phytochemicals have gathered significant attention recently. Thus, the present study implements a comprehensive network pharmacology approach to unravel the mechanisms of action of dietary phytochemicals that benefit disease management. A literature search was performed to identify ligands (i.e., comprising dietary phytochemicals and Food and Drug Administration pre-approved PD drugs) in the PubMed database. Targets associated with selected ligands were extracted from the search tool for interactions of chemicals (STITCH) database. Then, the construction of a gene-gene interaction (GGI) network, analysis of hub-gene, functional and pathway enrichment, associated transcription factors, miRNAs, ligand-target interaction network, docking were performed using various bioinformatics tools together with molecular dynamics (MD) simulations. The database search resulted in 69 ligands and 144 unique targets. GGI and subsequent topological measures indicate histone acetyltransferase p300 (EP300), mitogen-activated protein kinase 1 (MAPK1) or extracellular signal-regulated kinase (ERK)2, and CREB-binding protein (CREBBP) as hub genes. Neurodegeneration, MAPK signaling, apoptosis, and zinc binding are key pathways and gene ontology terms. hsa-miR-5692a and SCNA gene-associated transcription factors interact with all the 3 hub genes. Ligand-target interaction (LTI) network analysis suggest rasagiline and baicalein as candidate ligands targeting MAPK1. Rasagiline and baicalein form stable complexes with the Y205, K330, and V173 residues of MAPK1. Computational molecular insights suggest that baicalein and rasagiline are promising preclinical candidates for PD management.
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Affiliation(s)
- Devi Soorya Narayana Sasikumar
- Integrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, TN, 632014, India
| | - Premkumar Thiruselvam
- Integrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, TN, 632014, India
| | - Vino Sundararajan
- Integrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, TN, 632014, India
| | - Radhika Ravindran
- Department of Biotechnology, Indian Institute of Technology (Madras), Chennai, TN, 600036, India
| | - Shoba Gunasekaran
- Department of Biotechnology, Dwaraka Doss Goverdhan Doss Vaishnav College, Chennai, TN, 600106, India
| | - Deepa Madathil
- Jindal Institute of Behavioral Sciences, O.P Jindal Global University, Sonipat, Haryana, 131001, India
| | - Satyavani Kaliamurthi
- Centre for Research in Molecular Modeling (CERMM), Department of Chemistry and Biochemistry, Concordia University, Loyola Campus, Montreal, QC, H4B 1R6, Canada
| | - Gilles H Peslherbe
- Centre for Research in Molecular Modeling (CERMM), Department of Chemistry and Biochemistry, Concordia University, Loyola Campus, Montreal, QC, H4B 1R6, Canada
| | - Gurudeeban Selvaraj
- Centre for Research in Molecular Modeling (CERMM), Department of Chemistry and Biochemistry, Concordia University, Loyola Campus, Montreal, QC, H4B 1R6, Canada; Bioinformatics Unit, Department of Biomaterials, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS) University, Chennai, TN, 600077, India.
| | - Sajitha Lulu Sudhakaran
- Integrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, TN, 632014, India.
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Wang Y, Chen X, Wang Y, Zhong H, Liu L, Ye Y. Network pharmacology integrated with molecular docking technology to reveal the potential mechanism of Shuganfang against drug-induced liver injury. Medicine (Baltimore) 2023; 102:e36349. [PMID: 38050247 PMCID: PMC10695566 DOI: 10.1097/md.0000000000036349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 11/07/2023] [Indexed: 12/06/2023] Open
Abstract
This study aimed to investigate the active composition and mechanism of the Shuganfang (SGF) in treating drug-induced liver injury (DILI) using network pharmacology and molecular docking. The potential active ingredients and targets of SGF were obtained from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) database. DILI-related targets were queried from various databases including GEO, GeneCards, OMIM, NCBI, and DisGeNET. The STRING database was used to establish a protein-protein interaction (PPI) network. DAVID was utilized for conducting gene ontology (GO) function enrichment and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses. The data visualization and analysis of herb-ingredient-target and disease-pathway-target-ingredient networks were conducted using Cytoscape software (version 3.7.2). PyMoL and AutoDock software was used to select the best binding target for molecular docking. A total of 177 active ingredients,126 targets and 10112 disease targets were obtained, including 122 intersection targets. The identified potential active ingredients consisted of quercetin, kaempferol, luteolin, tanshinone IIa, nobiletin, isorhamnetin, beta-sitosterol and naringenin. The core targets implicated in the study were IL6, estrogen receptor 1 (ESR1), hypoxia-inducible factor alpha subunit 1 (HIF1A), MYC and vascular endothelial growth factor A (VEGFA). KEGG analysis revealed that the treatment of DILI with SGF mainly acted through apoptosis, the PI3K-Akt signaling pathway, and the tumor necrosis factor (TNF) signaling pathway. Furthermore, the binding affinities between the potential ingredients and the core targets were subsequently confirmed through molecular docking experiments. The findings indicated that the docking outcomes remained consistent and demonstrated a favorable capacity for binding. SGF exerts a therapeutic effect on DILI through multiple active ingredients, multiple targets and multiple pathways. Our findings contribute to a positive investigation and establish a theoretical basis for further extensive exploration of SGF as a potential treatment for DILI in future research.
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Affiliation(s)
- Ying Wang
- Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine, Hangzhou, China
| | - Xueying Chen
- The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yan Wang
- Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine, Hangzhou, China
| | - Hong Zhong
- Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine, Hangzhou, China
| | - Liqin Liu
- Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine, Hangzhou, China
| | - Yang Ye
- Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine, Hangzhou, China
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Altê GA, Rodrigues ALS. Exploring the Molecular Targets for the Antidepressant and Antisuicidal Effects of Ketamine Enantiomers by Using Network Pharmacology and Molecular Docking. Pharmaceuticals (Basel) 2023; 16:1013. [PMID: 37513925 PMCID: PMC10383558 DOI: 10.3390/ph16071013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 06/29/2023] [Accepted: 07/03/2023] [Indexed: 07/30/2023] Open
Abstract
Ketamine, a racemic mixture of esketamine (S-ketamine) and arketamine (R-ketamine), has received particular attention for its rapid antidepressant and antisuicidal effects. NMDA receptor inhibition has been indicated as one of the main mechanisms of action of the racemic mixture, but other pharmacological targets have also been proposed. This study aimed to explore the possible multiple targets of ketamine enantiomers related to their antidepressant and antisuicidal effects. To this end, targets were predicted using Swiss Target Prediction software for each ketamine enantiomer. Targets related to depression and suicide were collected by the Gene Cards database. The intersections of targets were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Network pharmacology analysis was performed using Gene Mania and Cytoscape software. Molecular docking was used to predict the main targets of the network. The results indicated that esketamine and arketamine share some biological targets, particularly NMDA receptor and phosphodiesterases 3A, 7A, and 5A but have specific molecular targets. While esketamine is predicted to interact with the GABAergic system, arketamine may interact with macrophage migration inhibitory factor (MIF). Both ketamine enantiomers activate neuroplasticity-related signaling pathways and show addiction potential. Our results identified novel, poorly explored molecular targets that may be related to the beneficial effects of esketamine and arketamine against depression and suicide.
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Affiliation(s)
- Glorister A Altê
- Department of Biochemistry, Center of Biological Sciences, Federal University of Santa Catarina, Florianópolis 88037-000, SC, Brazil
| | - Ana Lúcia S Rodrigues
- Department of Biochemistry, Center of Biological Sciences, Federal University of Santa Catarina, Florianópolis 88037-000, SC, Brazil
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