AI-assisted identification of innovative phytochemicals from Aizoon canariense aimed at brachyury protein in chordoma: a computational strategy
Year: 2025
Type: article
Abstract: Chordoma is an unique and aggressive bone malignancy along with limited therapeutic options, largely due to the undruggable nature of the TBXT oncoprotein. In this study, we employed an AI-assisted drug discovery approach to optimize β-sitosterol from Aizoon canariense against TBXT. Among the generated analogs, Artificial Intelligence Ligand 2 demonstrated strong inhibitory potential, showing a stable binding free energy of - 81.09 kcal/mol and maintaining conformational stability during a 500 ns molecular dynamics simulation. Key pharmacokinetic parameters revealed blood-brain barrier permeability, high gastrointestinal absorption as well as compliance with Lipinski's rules, while toxicity evaluation predicted moderate acute toxicity (LD₅₀ = 800 mg/kg, Class IV) with no major systemic risks. Density Functional Theory analysis confirmed molecular stability and reactivity suitable for biological interactions. Overall, these results highlight AI-Ligand 2 as a promising phytochemical derivative for targeting TBXT in chordoma, providing a foundation for future experimental validation and preclinical studies.
Source: Scientific Reports
Author: Shifaa O. Alshammari
Institution: University of Hafr Al-Batin
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
Funder: University of Hafr Al Batin
OpenAlex ID: W4417535259