AI-guided design and ex vivo validation of nanobodies targeting aggregation motifs of intrinsically disordered protein tau
Rajbanshi, B.; Guruacharya, A.
Show abstract
Intrinsically disordered proteins (IDPs) represent major yet challenging therapeutic targets in neurodegenerative disease due to their conformational heterogeneity and aggregation-prone behavior. Tau protein is a prototypical IDP that forms pathological aggregates in Alzheimers disease and related tauopathies. Despite extensive clinical efforts, tau-directed monoclonal antibodies have demonstrated limited efficacy. Concurrently, single-domain antibodies (nanobodies) have been gaining importance because of their small size and membrane penetrating capabilities. New design paradigms are therefore required for nanobodies to enable precise targeting of disease-relevant conformations. Here, we describe a biophysical modelling and AI-guided nanobody discovery targeting the VQIVYK motif of tau, which constitutes the structural core of neurofibrillary tangles in Alzheimers Disease. Biophysical modelling-based target analysis identified low-energy conformational states of VQIVYK. These conformational insights were used to guide AI-driven nanobody design of CDR3 loops. Starting from a nanobody scaffold, we generated 145 candidate nanobodies through systematic backbone sampling and neural network-guided sequence design, followed by multi-dimensional computational prioritization. Two candidates demonstrated robust binding to synthetic full tau protein in ELISA binding assays, achieving binding indices of 148.9% and 140%, relative to reference controls. Notably, one candidate also exhibited strong reactivity in post-mortem Alzheimers disease human brain tissue, with a binding index of 236.1%, exceeding that of the positive control (222.9%). Structural analysis indicates that our nanobodies engineered CDR3 engages VQIVYK through optimized aromatic and hydrophobic interactions. Together, these findings establish a proof-of-concept for biophysics-guided, AI-guided nanobody engineering against IDPs and identifies them as a promising lead for tau-targeted single domain antibody development.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.