Open Access

Lisa M. Pietrek, Lukas S. Stelzl, Gerhard Hummer

• Highlights • Sampling the large conformational space of disordered proteins requires extensive molecular dynamics (MD) simulations. • Fragment assembly complements MD simulations to produce extensive ensembles of disordered proteins with atomic detail. • Hierarchical chain growth (HCG) ensembles capture key experimental descriptors “out of the box”. • HCG has revealed local structural characteristics associated with protein dysfunction in neurodegeneration. Abstract Disordered proteins and nucleic acids play key roles in cellular function and disease. Here, we review recent advances in the computational exploration of the conformational dynamics of flexible biomolecules. While atomistic molecular dynamics (MD) simulation has seen a lot of improvement in recent years, large-scale computing resources and careful validation are required to simulate full-length disordered biopolymers in solution. As a computationally efficient alternative, hierarchical chain growth (HCG) combines pre-sampled chain fragments in a statistically reproducible manner into ensembles of full-length atomically detailed biomolecular structures. Experimental data can be integrated during and after chain assembly. Applications to the neurodegeneration-linked proteins α-synuclein, tau, and TDP-43, including as condensate, illustrate the use of HCG. We conclude by highlighting the emerging connections to AI-based structural modeling including AlphaFold2.