Stem cell (SC)-based replacement therapy is emerging as a promising cure for diabetes. However, the population-wide applicability of this approach remains constrained by the limited efficiency of current protocols in controlling the state of pluripotency and/or patient-specific propensity of SC lines to respond to morphogens and inductive factors, thereby yielding heterogenous islet cell preparations containing variable proportions of endocrine and immature cell types. In this RC2 project, we integrate knowledge from a team of Investigators with complementary expertise to exploit the power of Artificial Intelligence (AI)-designed mini-proteins (EpiBinders) in controlling SC's ability to more efficiently differentiate into functional islet cells. This approach is based on our recent work demonstrating that EpiBinders can erase repressive histone methylation marks and activate select genes of interest, thus fostering the activation of downstream developmental programs. Building on this preliminary work, we hypothesize that the newly discovered regulatory function of AI-designed EpiBinders on gene expression can be harnessed to drive a more efficient differentiation of multiple SC lines into functional islet tissue. For one year of support, our collaborative project will focus on the following specific aims: Aim 1: Develop and in-cell validate a toolbox of Al-designed mini-proteins, with a focus on targeting epigenetic regulators of DNA methylation in SC lines. Aim 2: Apply and optimize the use of select EpiBinders to regulate islet cell development at specific stages of SC differentiation. Aim 3: Characterize the state of differentiation and functional maturation of epigenetically manipulated SC-derived islet cells, in vitro and in vivo, in non-diabetic transplantation models. We anticipate that our interdisciplinary efforts will produce new knowledge and resources that will be readily shared with the scientific community and that will advance collective efforts to broaden the future therapeutic potential of SC-based treatments by developing a radically new approach to enhancing the efficiency of islet tissue derivation from SC.