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Computational analysis of phytocompounds in Centella asiatica for its antifibrotic and drug-likeness properties - Herb to drug study.
Gayathri, K; Abhinand, P A; Gayathri, V; Prasanna Lakshmi, V; Chamundeeswari, D; Jiang, Li; Tian, Zhen; Malathi, N.
Afiliação
  • Gayathri K; Faculty of Biomedical Sciences, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, 600116, India.
  • Abhinand PA; Department of Oral Pathology and Microbiology, Sri Ramachandra Dental College, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, 600116, India.
  • Gayathri V; Department of Bioinformatics, Faculty of Engineering and Technology, Sri Ramachandra Institute of Higher Education & Research, Porur, Chennai, 600116, India.
  • Prasanna Lakshmi V; Centre for Toxicology and Developmental Research, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, 600116, India.
  • Chamundeeswari D; Department of Bioinformatics, Faculty of Engineering and Technology, Sri Ramachandra Institute of Higher Education & Research, Porur, Chennai, 600116, India.
  • Jiang L; Faculty of Pharmacy, Meenakshi Academy of Higher Education and Research, Chennai, India.
  • Tian Z; Department of Oral Pathology, The Ninth People's Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Malathi N; Department of Oral Pathology, The Ninth People's Hospital, Shanghai Jiao Tong University, Shanghai, China.
Heliyon ; 10(13): e33762, 2024 Jul 15.
Article em En | MEDLINE | ID: mdl-39027607
ABSTRACT
Oral submucous fibrosis (OSMF) is a potentially malignant disorder with no permanent cure that affects the quality of life due to trismus. Computational pharmacology has accelerated the discovery of drug candidates for the treatment of incurable diseases. The present study aimed to screen the compounds of the miracle herb Centella asiatica with drug-likeness properties based on the absorption, distribution, metabolism, and excretion (ADME) properties. The pharmacological actions of these screened compounds against OSMF were identified by network pharmacology, gene ontology, pathway enrichment analysis, molecular docking, and simulation. Fifteen drug-like ligands were identified after virtual screening viz; asiatic acid, kaempferol, quercetin, luteolin, apigenin, bayogenin, gallic acid, isothankunic acid, madecassic acid, madasiatic acid, arjunolic acid, terminolic acid, catechin, epicatechin, and nobiletin. 850 potential targets were predicted for the ligands, which were analyzed against 354 proteins associated with OSMF. Compound pathway analysis and disease pathway analysis identified 53 common proteins. The GO enrichment analysis identified 472 biological process terms, 76 molecular function terms, and 44 cellular component terms. Pathway enrichment analysis predicted 142 KEGG pathways, 35 Biocarta pathways, and 236 Reactome pathways for the target proteins. The analysis revealed that the herb targets crucial events of fibrosis such as inflammation, oxidative stress, apoptosis, collagen deposition, and epithelial-mesenchymal transition. The common 53 proteins were used for protein-protein interaction (PPI) network analysis, which revealed 4 key proteins interacting with the phytocompounds viz; transforming growth factor-ß1 (TGF-ß1), mothers against decapentaplegic-3 (SMAD-3), mitogen-activated protein kinase-1 (MAPK-1) and proto-oncogene tyrosine-protein kinase (SRC). Molecular docking revealed that all ligands had a good binding affinity to the target proteins. Bayogenin had the highest binding affinity towards MAPK-1 (-9.7 kcal/mol), followed by isothankunic acid towards SRC protein (-9.3 kcal/mol). Madasiatic acid had the highest binding affinity to SMAD-3 (-7.6 kcal/mol) and TGF-ß1 (-7.1 kcal/mol). Molecular dynamics simulation demonstrated stable ligand protein interactions of bayogenin and MAPK complex, isothankunic acid and SRC complex. This in silico study is the first to identify potential phytochemicals present in Centella asiatica and their target molecules, which might be responsible for reversing OSMF.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article