In an alarming context of resistance to antibiotics, Mfd bacterial protein was identified as an innovative target for the development of new drugs. Mfd is a nanomachine of 1200 amino acid residues grouped in 8 structural domains that assembled into five functional modules that reshape severely to interact timely and functionaly with its cognate partners (RNAP, UvrA, DNA etc). We aim to dissect the molecular drivers that takes over Mfd reshaping in order to design small molecules that could inhibit Mfd structure/function cycle. By using a new in silico approach that combine connected component analysis (CCA) and Dynamical Perturbation Contact Networks (DPCN), we aim to capture the propagation of the allosteric signal within protein graph (Gheerart et al., 2023 J. Phys. Chem. B 2023, 127, 7571−7580). Recent advances in computational power have render possible to perform classical molecular dynamics (MD) simulations on systems of significantly larger size and over extended timescales. Still, extracting meaningful insights into system dynamics is challenging, especially for large molecules. Dynamical network analysis has emerged as a powerful computational strategy to investigate structural reorganization within proteins and to explore allosteric systems. The DPCN/CCA approach involves analyzing atomic contacts between amino acid residues across experimental structures an has proven promising to uncover the mechanisms underlying allosteric signaling and to measure the impact of effector binding on proteins. The 3D coordinates Mfd of E. coli have been solved by cryo-EM in several conformational states that describe an entire reshaping of Mfd (Kang et al., Elife. 2021 Jan 22;10:e62117). These data will serve as accurate basis for MD simulations mandatory for DPCN/CCA analysis so to build the protein graph and identify the correlated motion features. This work will identify the amino acid residues that are responsible for the largest perturbations. Accprdingly, we will test how to freeze these correlated motions through steric inhibition by small ligands. We recently set up an in-house pipeline dedicated for medium-to-intensive in silico screenings of chemical libraries. In fine, for in vitro validation, the effectors will be tested at PIMS on Mfd wild type and variants.