Modeling-guided optimization of chitosan-bioactive glass composites for cancer diagnostics

This study presents computational modeling and optimization of chitosan-bioactive glass composite designed for sensitive detection of carcinoembryonic antigen (CEA), a key cancer biomarker. Density functional theory (DFT) and molecular docking were employed to optimize binding affinity and electronic performance. DFT analysis revealed enhanced electronic polarization and charge-transfer capability with increasing chitosan content, evidenced by a marked reduction in the HOMO-LUMO molecular orbital energy gap from 5.55 eV (Si₃O₆) and 5.09 eV (P₄O₁₀) to 0.32 eV in the chitosan (Cs) -rich P₄O₁₀/Si₃O₆/CaO/Cs with three Cs units (3 U Cs) composite. The total dipole moment increased substantially to 22.02 D, indicating improved signal transduction potential. Molecular docking demonstrated strong CEA binding, with the Cs 3 U system achieving the highest affinity (-9.9 kcal/mol) through hydrogen bonding and electrostatic interactions. These findings computationally demonstrate that the chitosan-bioactive glass composite is a promising candidate for further experimental investigation as a biosensor recognition element for cancer biomarker detection. This work provides a rational computational screening framework that may guide and reduce trial-and-error in experimental biosensor development.