Structural assembly of the bacterial essential interactome

Abstract
Data availability
Article and author information
Metrics

Abstract

The study of protein interactions in living organisms is fundamental for understanding biological processes and central metabolic pathways. Yet, our knowledge of the bacterial interactome remains limited. Here, we combined gene deletion mutant analysis with deep learning protein folding using Alphafold2 to predict the core bacterial essential interactome. We predicted and modeled 1402 interactions between essential proteins in bacteria and generated 146 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. Our work provides a framework for predicting the essential interactomes of bacteria and highlight the potential of deep learning algorithms in advancing our understanding of the complex biology of living organisms. Also, the results presented here offer a promising approach to identify novel antibiotic targets.

Data availability

All models described in this paper are available on ModelArchive (https://modelarchive.org) with accession codes in Table 1. The scores of selected and random binary PPIs and the annotations of the essential proteins are provided in Source data 1.

Article and author information

Author details

Jordi Gomez Borrego

Department of Biochemistry and Molecular Biology, Autonomous University of Barcelona, Cerdanyola del Valles, Spain

Competing interests
The authors declare that no competing interests exist.
Marc Torrent

Department of Biochemistry and Molecular Biology, Autonomous University of Barcelona, Cerdanyola del Valles, Spain

For correspondence
marc.torrent@uab.cat

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-6567-3474

Funding

Ministerio de Ciencia e Innovación (PDC2021-121544-I00)

Marc Torrent

Ministerio de Ciencia e Innovación (PDC2021-121544-I00)

Marc Torrent

European Society of Clinical Microbiology and Infectious Diseases (ESCMID2022)

Marc Torrent

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.