Rendering Antibody Light Chains Amyloidogenic: Insight into Systemic Amyloidosis from Molecular Dynamics Simulations

• Applicant: Professorin Nadine Schwierz, Ph.D.
• Subject Area: Biophysics ; Statistical Physics, Nonlinear Dynamics, Complex Systems, Soft and Fluid Matter, Biological Physics
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 529538247

Amyloid light chain amyloidosis, short AL amyloidosis, is a rare but often fatal disease. The disease is caused by misfolding of free antibody light chains into amyloid fibrils which deposit in organs and eventually cause their damage and failure. Despite the importance, no pharmacological treatment to prevent fibril formation exists to date and the factors that render the light chains amyloidogenic remain elusive. Therefore, a detailed understanding at the molecular level is required to advance early diagnosis and treatment. To gain molecular insights, molecular dynamics simulations offer promising perspectives by resolving the pathways of misfolding with atomistic resolution and by identifying the interactions that render antibody light chains amyloidogenic. However, up to now no systematic computational approach exists to resolve the factors that trigger misfolding and the onset of the fatal disease. To fill this gap, we aim to identify and apply promising approaches from state-of-the-art computer simulations. The computational models build on a recently collected, comprehensive dataset for patient-derived amyloidogenic light chains from cryo-electron microscopy, nuclear magnetic resonance and fibril assay experiments performed by our collaboration partners. Using in-silico protein design, we develop atomistic models of the misfolded fibril state and the native state based on the patient-derived amyloidogenic protein structures. In each model, we systematically introduce point mutations and posttranslational modifications, such that more than 40 different, potentially disease-causing modifications can be tested. Subsequently, we quantify the contribution of each modification to the fibril forming capability, nano-mechanical stability and growth kinetics by applying all-atom molecular dynamics simulations in combination with enhanced sampling techniques and efficient free energy calculations. The proposed work enables us to connect molecular insights from atomistic simulations with the pathological course of AL amyloidosis. We expect that the proposed systematic computational methodology allows us to identify the key interactions and to resolve the molecular principles of misfolding. The insights at the molecular level can then serve as foundation for improved diagnostics and novel treatment approaches.

• DFG Programme: Research Grants