Title : In silico structural mapping of endothelial LRP1 cluster II variants: Quantifying the biophysical mechanisms of impaired amyloid-beta efflux at the blood-brain barrier
Abstract:
This study aims to characterize how specific, clinically unannotated human missense mutations within the ligand-binding Cluster II domain of Low-Density Lipoprotein Receptor-Related Protein 1 (LRP1) alter its 3D structural conformation and binding affinity for Amyloid-Beta (Aβ1-42), a critical step in preserving blood-brain barrier efflux mechanisms. The wild-type (WT) sequence of LRP1 Cluster II (residues 804–1164) and three targeted variants exhibiting distinct chemical disruptions, specifically D1016A (charge switch), G932R (backbone flexibility disruption), and Y872C (aromatic stacking loss), were structurally modeled using AlphaFold3. Rigorous protein-protein docking simulations were executed via the HADDOCK 2.4 server against the solution NMR structure of monomeric Aβ1-42 (PDB ID: 1IYT). Interfacial binding kinetics, free energy of binding (ΔG), electrostatic surface potentials, and hydrogen/salt-bridge topologies were quantified using UCSF ChimeraX. Computational analysis revealed that the wild-type LRP1-Aβ complex stabilizes via extensive electrostatic coordination between negatively charged aspartate residues and the basic Lys16/Lys28 cluster of Aβ1-42. The D1016A mutation directly collapsed this local calcium-coordinating loop, resulting in a 34% reduction in interface binding energy (ΔG). The G932R mutation introduced severe steric clashes and a highly positive local surface charge that drove a structural rotation of the binding loop, completely displacing Aβ from its native pocket. Conversely, the Y872C mutation maintained baseline electrostatic affinity but significantly lowered the structural stability score due to the loss of aromatic π-stacking interactions. These in silico findings demonstrate that non-synonymous single nucleotide polymorphisms within LRP1 Cluster II can structurally incapacitate the receptor's capacity to bind amyloid-beta through distinct biophysical pathways, namely electrostatic collapse and steric hindrance. This study successfully establishes a structural screening framework to identify high-risk genetic variants that impair blood-brain barrier clearance, highlighting specific molecular targets for compensatory drug design.
