髓系白血病
天然产物
酪氨酸激酶抑制剂
酪氨酸激酶
化学
癌症研究
计算生物学
药物发现
药理学
生物
对接(动物)
药品
疾病
酪氨酸
激酶
生物化学
受体酪氨酸激酶
生物信息学
小分子
髓样
分子力学
IC50型
机制(生物学)
作者
Joe Anthony Manzano,Reign Au Ruhamma Ammi D. Parico,Patric Joshua R. Fabrique,Adrienne Nicole Maldupana,Jovilyn C. Arevalo,Jay Carl M. Agbay,Mark Tristan J. Quimque,Allan Patrick G. Macabeo
出处
期刊:Journal of computational biophysics and chemistry
[World Scientific]
日期:2025-11-20
卷期号:25 (11): 2743-2758
被引量:1
标识
DOI:10.1142/s273741652650033x
摘要
Chronic myeloid leukemia (CML) remains among the most prevalent hematologic malignancies in many developing countries. The disease accounts for 15% of all newly diagnosed adult leukemias in the world. Although tyrosine kinase inhibitors offer effective disease control, therapeutic accessibility and long-term efficacy remain major challenges in local clinical settings. Moringa oleifera, a widely consumed vegetable, is known for its rich profile of phytochemicals with reported cytotoxic, antioxidant and anticancer properties. This study applied integrative computational modeling approaches to predict the inhibitory potential of 91 secondary metabolites from M. oleifera against key regulatory proteins implicated in CML progression: breakpoint cluster region-Abelson tyrosine kinase (BCR-ABL1), c-Src kinase, and fms-like tyrosine kinase 3 (FLT3). Using docking simulations, lycopene (16) exhibited strong predicted affinity for BCR-ABL1 (binding energy or BE [Formula: see text] –9.9 kcal/mol), while [Formula: see text]-carotene (6) showed the highest binding potential to c-Src (BE [Formula: see text] –11.0 kcal/mol) and FLT3 (BE [Formula: see text] –11.7 kcal/mol). Subsequent molecular dynamics simulations affirmed the thermodynamic stability of these ligand–target complexes, suggesting sustained interaction under physiological conditions. The majority of top-binding ligands were also predicted to have favorable drug-likeness, and pharmacokinetic and toxicity profiles. These findings underscore the potential of M. oleifera as a valuable source of lead compounds for CML drug discovery and exemplify the utility of integrative computational approaches in identifying functionally relevant natural products, especially in resource-limited settings.
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