Abstract Body: Introduction: Direct cardiac reprogramming—the conversion of fibroblasts into cardiomyocyte-like cells— offers a promising solution to the issue of the heart’s limited regenerative capacity. Traditionally achieved using a three-factor cocktail of MEF2C, GATA4, and TBX5 (MGT), recent advancements have shown that a more minimal cocktail consisting of proneural basic helix loop helix (bHLH) factor ASCL1 (A) and MEF2C (M) can more robustly drive cardiac reprogramming. Notably, while cardiac bHLH factor HAND2 is incapable of driving cardiac reprogramming when paired with MEF2C, A+M outperforms MGT. Despite this, A+M still induces residual neuronal reprogramming, indicating the need for further development.

This study aims to integrate computational tools into the optimization of A+M by (1) characterizing the domains of ASCL1 important for cardiac reprogramming, and (2) engineering hybrid constructs through systematic domain swapping between ASCL1 and HAND2 to reduce neuronal reprogramming.

Hypothesis: We hypothesize that certain domains of ASCL1 contribute to its residual neuronal reprogramming, and that interchanging these regions with that of HAND2 can enhance cardiac reprogramming.

Methods: To assess this, we engineered ASCL1 mutants with domain-specific deletions and ASCL1-HAND2 hybrids using protein structural prediction tool AlphaFold. We subsequently studied the predicted behavior of these proteins through protein docking simulations using molecular dynamics tool Schrödinger, evaluating their predicted DNA- and protein-binding affinities.

Results: Deletion of ASCL1’s basic domain was observed to impair its predicted binding affinity to both neural and cardiac targets, while swapping the basic domain of ASCL1 with that of HAND2 was observed to preserve strong cardiac DNA-binding behavior in hybrid constructs.

Conclusion: These results demonstrate how domain swapping may be a suitable approach to modulate ASCL1’s binding behavior to promote affinity for targets relevant to cardiac reprogramming. We also demonstrate how docking simulations can be used to streamline the optimization process, as the results of these analyses will be used to guide in vitro studies to design hybrid factors for an optimized cardiac reprogramming cocktail.