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@article{173094,
author = {Barla Karuna Devi and Chinnolla Lokesh and Kodi Ajay},
title = {In silico ADME, Toxicity Prediction, Pass Analysis, and Molecular Docking of Curcumin derivatives},
journal = {International Journal of Innovative Research in Technology},
year = {2025},
volume = {11},
number = {9},
pages = {2101-2108},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=173094},
abstract = {Curcumin, a bioactive polyphenol from Curcuma longa, has a wide range of pharmacological activities such as antioxidant, anti-inflammatory, anticancer, and antimicrobial activities. Though curcumin has therapeutic benefits, it is hindered by poor bioavailability, fast metabolism, and poor aqueous solubility. To overcome these drawbacks, curcumin derivatives with enhanced pharmacokinetic and pharmacodynamic profiles have been designed. Computational methods, especially in silico tools, have played an important role in the optimization of these derivatives for drug development. Molecular docking analyses, such as CB-Dock, assist in the identification of binding interactions among curcumin derivatives and the target proteins. ADMET prediction assists in analyzing drug-like attributes, while toxicity evaluation by using ProTox analysis and Osiris Property Explorer gives an understanding of possible safety issues. All these in silico approaches streamline the process of screening curcumin derivatives as therapeutic agents. In the current research very few curcumin derivatives were chosen and their ADME, Toxicity parameters, Pass analysis and Molecular docking studies were forecasted by using several in silico tools like Molinspiration, Protox-II, Osiris property explorer, Pass analysis and CB-Dock. The prime objective is to highlight the role of computational tools in improving their pharmacological potential and speeding up drug discovery.},
keywords = {Curcumin, in silico analysis, toxicity, docking.},
month = {February},
}
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