Narutoshi Kamiya

<jats:title>Abstract</jats:title> <jats:p>DNA-targeting drugs exploit structural features of DNA, including base stacking, grooves, and noncanonical structures, to bind and modulate DNA function. Similarly, DNA aptamers leverage unique physicochemical environments created by diverse DNA conformations to achieve high-affinity recognition of small molecules, making them critical for biosensing applications. Despite their therapeutic and sensing potential, accurately predicting binding configurations within these dynamic structures remains a significant computational challenge requiring advanced molecular dynamics (MD) simulations powered by modern force fields. To evaluate modern AMBER-based parametrizations across diverse structural motifs, including aptamers, duplexes, and quadruplex–duplex hybrids, we performed dynamic docking simulations of five DNA-ligand pairs using multicanonical MD, a generalized-ensemble method, across five distinct force fields (OL15, OL21, OL24, bsc1, and tumuc1). Analysis of 750 μs of trajectory data revealed significant variations in conformational ensembles. OL24 exhibited the highest accuracy in reproducing experimental structures based on our R-value analysis, which quantifies the ligand-DNA native contacts, while OL15, OL21, and bsc1 also demonstrated robust performance across all systems. In contrast, tumuc1 displayed a persistent bias toward distorted or misoriented conformations with low native-state populations, compromising structural reliability regardless of the system type. These findings provide critical insights for developing next-generation DNA force fields capable of accurately modeling non-native structures and enabling balanced sampling essential for predicting ligand binding in diverse biological contexts.</jats:p>