Energetic and topological features of coarse-grained chromosome models

High-resolution techniques capable of manipulating structures from single molecules to millions of cells are increasingly combined with three-dimensional modeling and simulations to investigate specific aspects of chromosome organization. From a theoretical perspective, the energy landscape theory of protein folding has inspired the development of minimal chromatin models for Hi-C data (MiChroM) and image-based experiments (AMI). Applying MiChroM to linear human chromosomes, we show that the type-to-type and ideal chromosome energy terms drive a competition between loci compartmentalization and motor-driven activity, respectively. Increased motorization enhances territory formation in multi-chromosome simulations, while reduced type interactions decrease contact formation, bringing the model closer to experimental Hi-C data. Regarding the topological aspects of circular DNA, super-resolution microscopy data from the Salmonella genome guided the simulation of a homopolymer using the Associative Memories for Imaging (AMI) Hamiltonian. These studies represent a significant step toward integrating 2D and 3D chromatin experimental big data with simplified 3D polymer models, addressing a critical gap in our understanding of chromatin architecture and its role in regulating nuclear functions.