The Conformational Landscape of <scp>AlphaFold2</scp>‐Predicted Amyloidogenic Light Chains and Their Correlation With <scp>VL</scp> Domain Mutations and Aggregation Propensity

Systemic light-chain amyloidosis (AL) is caused by the misfolding and aggregation of immunoglobulin light chains (LCs), which natively form homodimers comprising variable (VL) and constant (CL) domains in each monomer. High sequence variability, particularly within the VL domain, results in varied structural changes and aggregation propensities, making it challenging to develop broadly effective native protein stabilizers/aggregation inhibitors, as each AL patient carries a unique light chain. Using artificial intelligence (AI)-based AlphaFold2, known for its accuracy in modeling folded proteins, we generated an extensive repertoire of structural models of full-length LCs from four amyloidogenic germlines: IGLV1(λ1), IGLV3(λ3), IGLV6(λ6), and IGKV1(κ1), over-represented in AL patients to identify germline-specific structural features. The resulting models cover multiple structural folds, benchmarked against the Protein Data Bank (PDB) deposited structures. We identified clear germline-specific structural patterns: λ6 and λ1 LCs frequently adopt open dimers, with two VL domains far apart, in 86% and 72% of predicted structures, respectively. The open structures are under-represented in the PDB due to the limited availability of structural data for each amyloidogenic germline. In contrast, λ3 shows 48% open dimers, while κ1 consistently forms closed dimers. These trends mirror clinical prevalence and aggregation propensity with an order of λ6 > λ1 > λ3 > κ1 in AL patients. Moreover, adopting open conformations, but not the number of mutations, correlates with a higher aggregation propensity in amyloidogenic germlines. This study identifies germline-specific structural features as broadly applicable therapeutic targets, potentially reducing the cost and complexity of personalized treatments for polymorphic disease, AL amyloidosis.