Shen, J.; Zhou, S.; Che, X.

This paper discloses technical details of an early approach we explored for molecular glue induced ternary complex structure prediction using Feynman-Kac (FK) steering in the diffusion modules of AlphaFold3-type models. While we recently reported the successful results of our YDS-GlueFold model in predicting 8 novel molecular glue induced ternary structures validated by experimental data, here we share insights from our earlier FK steering experiments which were conducted prior to developing YDS-GlueFold. Notably, the unmodified AlphaFold3-type baseline failed to predict any of the eight complexes, underscoring the difficulty of sampling ternary conformations. By contrast, our FK-steered diffusion approach-FKSFold-successfully predicted 3 of the 8 cases in these early trials. We detail how we leveraged FK formalism to modify the diffusion process, using interface predicted TM-score (ipTM) as a reward function to guide sampling toward high-quality protein-protein interfaces in ternary complexes. This strategy of using ipTM as a reward function aligns well with the mechanism of action (MOA) of molecular glues, which function by inducing or stabilizing protein-protein interfaces. By implementing stochastic control theory within the diffusion module, our approach attempted to steer the reverse diffusion process toward conformations with superior interface quality in ternary protein-protein-small molecule complexes. In these early trials, FK steering successfully predicted 3 out of the 8 cases that were later all correctly predicted by YDS-GlueFold. This work provides insights into the evolution of our technical approaches toward molecular glue-induced complex prediction, documenting an important step in the development pathway that eventually led to YDS-GlueFold. Code is available at https://github.com/YDS-Pharmatech/FKSFold.