Application of Density Functional Theory in Modeling Radiation–Biomolecule Interactions

Abstract

Ionizing radiation induces complex physicochemical interactions in biological systems through ultrafast ionization, excitation, and radical-generation processes that damage cellular biomolecules. Density Functional Theory (DFT) and Time-Dependent Density Functional Theory (TD-DFT) have emerged as important computational approaches for investigating these radiation-induced mechanisms at the molecular level. This review analyzes published studies from 2015–2025 involving DFT-based simulations of radiation interactions with water, DNA, proteins, and lipids, with emphasis on computational predictions validated against experimental spectroscopy and radiochemical data. Literature was selected from major scientific databases including Scopus, Web of Science, and PubMed using keywords related to radiation chemistry, biomolecular damage, and quantum chemical modeling. Comparative findings show that DFT effectively predicts bond dissociation energies, charge-transfer mechanisms, radical formation pathways, and oxidative damage processes associated with water radiolysis, DNA strand breaks, protein oxidation, and lipid peroxidation. The review also highlights recent advances such as hybrid QM/MM techniques, fragment-based DFT, and machine-learning-assisted simulations that improve the modeling of large biomolecular systems. However, limitations including high computational cost, restricted system size, and challenges in accurately reproducing dynamic cellular environments remain significant. Overall, DFT-based approaches continue to enhance mechanistic understanding in radiation biology and support applications in radiotherapy optimization, radioprotection, and predictive health-risk assessment.