Molecular crowding and amyloidogenic self-assembly: Emergent perspectives from modern computations

Macromolecular crowding defines the cellular interior, where high biomolecule concentrations reshape protein folding landscapes and intermolecular interactions. Excluded-volume effects, quinary interactions, and spatial confinement collectively modulate amyloidogenic self-assembly, a process central to both functional organization and protein misfolding diseases. This review emphasizes the context-dependent role of crowding in balancing native protein stability against aggregation propensity, highlighting how heterogeneous intracellular environments govern the emergence of functional assemblies or pathological amyloids. Recent computational advances provide key mechanistic insights across scales. Atomistic simulations resolve detailed conformations and interactions, while coarse-grained and implicit condensate models enable exploration of larger systems, longer timescales, phase behavior, and collective assembly. Together, these multiscale approaches underscore the need to move beyond dilute approximations. Integrative frameworks that incorporate enhanced sampling and artificial intelligence are essential to capture cellular complexity and enable predictive understanding of protein self-assembly and amyloidogenesis under crowded conditions.