Integrative computational and experimental approaches to Hydnocarpus wightianus phytochemicals: Targeting breast Cancer through systems biology, molecular dynamics simulations, and in vitro validation in MDA-MB-231 cells.
2/5 보강
TL;DR
The combination of network pharmacology, molecular dynamics, and DFT-based electronic analysis, along with experimental validation, ranks H. wightianus bioactive compounds as promising therapeutic candidates for future preclinical and clinical trials in the fight against breast cancer.
OpenAlex 토픽 ·
Computational Drug Discovery Methods
Phytochemicals and Medicinal Plants
Traditional and Medicinal Uses of Annonaceae
ℹ️ 이 논문은 무료 전문이 아직 없습니다. 코퍼스 전체의 43.8%는 무료 가능 (통계 →) · 🏥 기관 EZproxy로 시도
The combination of network pharmacology, molecular dynamics, and DFT-based electronic analysis, along with experimental validation, ranks H.
APA
Nachammai Kathiresan, Prajisha Jayaprakash, et al. (2026). Integrative computational and experimental approaches to Hydnocarpus wightianus phytochemicals: Targeting breast Cancer through systems biology, molecular dynamics simulations, and in vitro validation in MDA-MB-231 cells.. Bioorganic chemistry, 172, 109621. https://doi.org/10.1016/j.bioorg.2026.109621
MLA
Nachammai Kathiresan, et al.. "Integrative computational and experimental approaches to Hydnocarpus wightianus phytochemicals: Targeting breast Cancer through systems biology, molecular dynamics simulations, and in vitro validation in MDA-MB-231 cells.." Bioorganic chemistry, vol. 172, 2026, pp. 109621.
PMID
41666623 ↗
Abstract 한글 요약
Breast cancer causes a huge burden on healthcare systems, and it is crucial to identify new drugs from nature sources with better efficacy and safety profile. By employing an integrated computational and experimental strategy, the current study focuses on discovering phytochemicals from Hydnocarpus wightianus as anti-breast cancer agents, with the major concern of mechanistic understanding and molecular stability. Initially, H. wightianus phytochemicals were subjected to drug-likeness screening and their possible molecular targets were predicted using SwissTargetPrediction. Breast cancer associated genes were collected from GeneCards and OMIM databases. Compound-target and protein-protein interaction networks were constructed and analyzed using Cytoscape, CytoHubba, and MCODE to find out the important hub genes and functional modules. Further, Gene Ontology and KEGG pathway enrichment analyses were performed to confirm the biological relevance. Identified potential genes were docked and top leads were analyzed using ADMET profiling, and molecular dynamics simulations. Molecular Electrostatic Potential mapping and Density Functional Theory calculations were employed to reveal the electronic distribution and chemical reactivity of the predominant H. wightianus compound. MDA-MB-231 breast cancer cells were used for experimental validation. In vitro studies showed that cell death caused by the drug increased in relation to its concentration, mitochondria lost their potential, and cells were undergoing apoptotic ones as confirmed by Rhodamine 123, Hoechst, and AO/EtBr staining. The combination of network pharmacology, molecular dynamics, and DFT-based electronic analysis, along with experimental validation, ranks H. wightianus bioactive compounds as promising therapeutic candidates for future preclinical and clinical trials in the fight against breast cancer.
🏷️ 키워드 / MeSH 📖 같은 키워드 OA만
- Humans
- Breast Neoplasms
- Phytochemicals
- Antineoplastic Agents
- Phytogenic
- Molecular Dynamics Simulation
- Drug Screening Assays
- Antitumor
- Dose-Response Relationship
- Drug
- Cell Proliferation
- Molecular Structure
- Systems Biology
- Cell Line
- Tumor
- Female
- Structure-Activity Relationship
- Apoptosis
- MDA-MB-231 Cells
- ADMET profiling
- Breast cancer
- Density functional theory
- Hydnocarpus wightianus
- MDA-MB-231 cells
… 외 4개
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