This project aims to explore the regulatory role of allosteric sites in integrating metabolic information and modifying enzyme activity and gene expression. The study will be conducted using the yeast S. cerevisiae. The objectives are to identify proteome-wide putative allosteric sites, perform high-throughput genetic perturbation, measure fitness consequences in diverse environments, and validate the functionality of the novel allosteric sites identified. In the first step, we will combine experimental and computational approaches, utilizing data from LIP-MS and computationally predicted protein-metabolite interactions. The second step involves conducting genome-wide perturbation using CRISPR-Cas9, introducing tens of thousands of mutations in S. cerevisiae. The third step includes exploring fitness differences across strains under various growth conditions, such as different carbon sources or oxidatives stress. Once the phenotypic landscape of allosteric sites is mapped, I will focus on sites with clear and reproducible phenotypes, curating putative allosteric sites based on 3D protein structures and genetic conservation. Finally, I will validate and characterize the novel allosteric sites generating individual mutant strains, assessing their fitness, and exploring their impact on metabolism and gene expression. This disruptive project will provide the first proteome-wide map of allosteric site functionality, potentially revolutionizing our understanding of metabolic regulation and gene expression crosstalk. The knowledge gained could have significant implications for the swift adaptation of cells to changing environments, coordinating multiple cellular processes. Furthermore, insights from this yeast-focused study could be translated to target homologous proteins in humans, facilitating the development of novel drugs targeting tumour cell metabolism to inhibit their proliferation.