In Silico Structure-Guided Design of Peptide Candidates Targeting γ-Secretase Subunit Assembly

Abstract

The gamma-secretase complex is a membrane-embedded protease essential for intramembrane cleavage of substrates such as Notch receptors and the amyloid precursor protein (APP), processes central to cancer progression and Alzheimer's disease (AD) pathology. However, catalytic inhibition of gamma-secretase disrupts multiple signaling pathways, resulting in dose-limiting toxicities. In this study, we report a structure-guided approach to generate peptides with binding and stability profiles that disrupt the assembly of gamma-secretase by targeting the interactions of Presenilin-1 and Nicastrin with APH1. First, molecular docking was performed for 36 248 peptides of varying lengths to assess their affinity scores to the PS1 and NCT interaction regions of APH1. Peptides filtered based on their affinity scores and physicochemical properties were then subjected to global molecular docking. 50-nanosecond molecular dynamics simulations and MM/PBSA analyses were performed on the top 10 potential candidates, identifying those with high dynamic interaction potential. Thus, seven gamma-secretase inhibitor candidates with favorable affinity scores capable of providing stable interactions and thereby having the potential to disrupt the APH1:PS1 assembly were identified. This approach, which overcomes the challenges of targeting the transmembrane catalytic domain, is based on the inhibition of subunit assembly and presents promising candidates for future experimental studies.