Aug 2026· Journal of the American Chemical Society· Vol 148 34, pp.
36392-36413
· 1 citation· 101 references
Medicine
TL;DR
This work investigates how protein folding landscapes are altered inside condensates, using the protein α-helix as a model folded domain and develops a chemically specific, residue-resolution model for quantification of α-helical folding and applies it to characterize diverse helices within condensates of varying physicochemical properties.
Abstract
Protein structure is exquisitely sensitive to the surrounding chemical environment, and many proteins encounter complex environments within cells. Importantly, numerous proteins organize into biomolecular condensates─dense macromolecular assemblies with distinct physicochemical properties. This raises a fundamental question: how do condensates reshape protein structure and dynamics? Here, we investigate how protein folding landscapes are altered inside condensates, using the protein α-helix as a model folded domain. Atomistic simulations suggest the helix-coil transition within condensates differs markedly from its behavior in dilute solution or in the presence of inert crowders. We then use Bayesian optimization to develop a chemically specific, residue-resolution model for quantification of α-helical folding and apply it to characterize diverse helices, including α-helical domains from the disease-associated proteins TDP-43, Annexin A11, and Androgen Receptor, within condensates of varying physicochemical properties. Our results support a framework in which multivalent interactions drive unfolding while crowding promotes folding, and α-helix conformational ensembles inside condensates emerge from this balance. Additionally, we show that helix folding transitions are kinetically frustrated inside condensates because they are coupled to the time scale of contact rearrangement with co-condensate proteins. As such, α-helix folding landscapes within condensates are dually sequence-dependent, informed by both the sequence of the α-helical domain and co-condensate proteins. Together, our work has implications for understanding condensate-mediated proteinopathies, targeting aberrant condensates, and designing condensates to program protein function across scales.
Biomolecular condensates represent unique microenvironments that organize intracellular biology and promote biochemical reactions. However, the biomolecular interactions driving condensate phase separation are often weak, transient, and heterogeneous. Investigating the structural biology and chemical properties of cond...
Ethan A. Perets, Jacob A. Spies, Justin H. Cheong et al.· Biophysical Journal· 0 citations
The current literature is summarized and biomolecular condensates are described as key regulators of protein misfolding and aggregation and the importance of the local milieu in determining aggregation outcomes is highlighted.
Emre Pekbilir, Dorothee Dormann· Current Opinion in Structura...· 0 citations
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It is found that Trp-cage folds primarily (80% of the paths) via a pathway forming the tertiary contacts and the salt-bridge, before helix formation, which is in contrast to previous predictions employing an implicit solvent.
The discovery of biomolecular condensates, driven by liquid–liquid phase separation of intrinsically disordered proteins has significant impacts on both fundamental and applied science and engineering. Although most studies on biomolecular condensates focus on intrinsically disordered structures, research on the role o...
Debdatta Das, Jenny N Nguyen, Navneet Sahoo et al.· Small· 0 citations
Protein folding is the process by which a polypeptide chain organizes into its three-dimensional structure through a balance of stabilizing and destabilizing interactions encoded by the sequence. A central question in protein biophysics is how thermodynamic factors guide a polypeptide toward its native folded state des...
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.