Биоинформатика Исследование терапевтического потенциала составов семян лотоса в многоразовом склерозе: сетевой анализ с-Джун Пути.
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Rushendran Rapuru, Singh S Ankul, Begum Rukaiah Fatma, Chitra Vellapandian, Ali Nemat, Prajapati Bhupendra G
Аннотация
Оригинал публикации
Bioinformatics Exploration of the Therapeutic Potential of Lotus Seed Compounds in Multiple Sclerosis: A Network Analysis of c-Jun Pathway.
The central nervous system is affected by multiple sclerosis (MS), a chronic autoimmune illness characterized by axonal destruction, demyelination, and inflammation. This article summarizes the state of the field, highlighting its complexity and significant influence on people's quality of life. The research employs a network pharmacological approach, integrating systems biology, bioinformatics, and pharmacology to identify biomarkers associated with MS. Utilizing Nelumbo Nucifera (Lotus) seeds, the study involves toxicity assessments, biomolecule screening, and target prediction. Advanced computational methodologies are employed, including molecular docking and dynamic simulations, to assess potential therapeutic interactions. Biomolecule screening identifies eight active compounds from Lotus seeds, including Anonaine and Liriodenine. Target prediction reveals 264 common targets with MS-related genes. Protein-protein interaction analysis establishes a complex network, identifying central targets like SRC and AKT1. Bioinformatics enrichment analysis uncovers potential therapeutic candidates and pathways. A Biomolecule-Target-Pathway network diagram visualizes interactions, with Anonaine and Liriodenine exhibiting strong binding affinities in molecular docking studies. Molecular dynamics simulations provide insights into dynamic interactions. In conclusion, through advanced computational techniques, it unveils molecular interactions, potential therapies, and pathways, bridging predictions with practical applications. Anonaine and Liriodenine show promise in curbing MS biomarkers.