Mapping of Biomolecular Transitions: ELViM as a Scalable Tool for Disordered and Aggregating Protein Landscapes

Navigating the complex energy landscapes of intrinsically disordered proteins and their aggregation pathways is often hindered by the biases inherent in traditional reaction coordinates. The Energy Landscape Visualization Method (ELViM) overcomes these constraints by utilizing a distance-based similarity metric paired with force projection embedding to transform high-dimensional conformational data into low-dimensional, easily interpretable spaces without a priori assumptions. Here, we demonstrate the versatility and predictive power of ELViM across three distinct protein systems illustrating different structural phenomena. In the intrinsically disordered C-terminal tail of the Sodium/Hydrogen Exchanger 1, ELViM resolved the precise local structural shifts driven by S785 phosphorylation, revealing how electrostatic interactions anchor and stabilize transient helical domains. Extending the framework to multi-chain assemblies, an enhanced implementation of ELViM was applied to the Tau protein to simultaneously map monomeric and oligomeric states; this approach successfully decoupled intra-chain folding from inter-chain interactions and showed how the pathogenic P301L mutation shifts the ensemble toward pre-organized, aggregation-prone conformations. Finally, ELViM was applied to coarse-grained simulations of amyloid-beta (Aβ40 and Aβ42) oligomerization from monomers to tetramers, mapping variant-specific pathways and confirming that Aβ40 relies on a distinct prefibrillar intermediate to progress to fibers, whereas Aβ42 bypasses this state entirely. Collectively, these applications establish ELViM as a robust, scalable methodology that provides deep thermodynamic and kinetic clarity across a wide spectrum of functional and pathological protein behaviors.