Structural assembly of the bacterial essential interactome

Abstract

The study of protein interactions in living organisms is fundamental to understanding biological processes and central metabolic pathways. However, our understanding of the bacterial interactome remains limited, hindering the identification of new drug targets and the development of new therapeutic strategies. Here, we predict the assembly of the essential proteins in bacteria using the deep learning protein folding algorithm Alphafold2. We modeled 1089 interactions between essential proteins in bacteria and generated 115 high-accuracy models. Our analysis reveals previously unknown details about the assembly mechanisms of these complexes, highlighting the importance of specific structural features in their stability and function. Furthermore, we identify several novel protein-protein interactions that provide new targets for drug development. Our work provides a framework for predicting the interactome of other bacteria and highlights the potential of deep learning algorithms in advancing our understanding of the complex biology of living organisms.