用精确的理论方法破译姜黄素、胡椒碱和乳蛋白之间的协同相互作用

IF 3.1 4区 生物学 Q2 BIOLOGY
Madhesh Palanisamy , Gayathri Krishnamoorthy , Vidya Ravindran
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引用次数: 0

摘要

这项工作的重点是研究在姜黄和辣椒中发现的活性生物分子与关键牛奶蛋白之间的相互作用,这是印度传统医学体系之一Siddha普遍采用的一种治疗感冒和喉咙相关疾病的方法。姜黄素和胡椒碱分别是姜黄和辣椒中的活性生物分子。因此,我们分析了它们与牛血清白蛋白(BSA)、乳球蛋白和乳白蛋白等关键乳蛋白的相互作用。利用基于密度泛函理论(DFT)和分子对接模拟的精确第一性原理计算,对这些相互作用进行了计算研究,以阐明上述配方功效背后的潜在机制。使用计算技术评估了姜黄素-胡椒碱(CP)复合物的形成及其与乳蛋白的结合。我们预测了牛奶蛋白的变构位点,并研究了姜黄素和胡椒碱对这些蛋白的变构调节作用。结果揭示了药物复合物的形成和生物活性的增加,从而为观察到的传统配方的增效作用提供了分子基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deciphering synergistic interactions between Curcumin, Piperine, and milk proteins using accurate theoretical methods
This work focuses on studying the interaction between the active biomolecules found in turmeric and pepper with key milk proteins, which is a popularly adopted in the Siddha, one of the Indian Traditional Medicinal Systems, to treat cold and throat-related illnesses. Curcumin and Piperine are the active biomolecules in turmeric and pepper, respectively. Hence, we have analyzed their interaction with key milk proteins such as Bovine Serum Albumin (BSA), Lactaglobulin, and Lactalbumin. The interactions were computationally investigated to elucidate the underlying mechanism behind the efficacy of the aforementioned formulation using accurate first-principle calculations based on Density Functional Theory (DFT) and Molecular Docking simulations. The formation of the Curcumin-Piperine (CP) complex, as well as its binding with milk proteins, was evaluated using computational techniques. We have predicted the allosteric sites of the milk proteins and investigated the allosteric regulation effect in these proteins by Curcumin and Piperine. The results revealed the formation and increased bioactivity of the drug complex, thereby providing a molecular basis for the observed synergistic efficacy of this traditional formulation.
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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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