AlphaFold models of host-pathogen interactions elucidate the prevalence and structural modes of molecular mimicry
Baptista, D.; Gomez-Lucas, L.; Jänes, J.; Krogan, N. J.; Joao Amorim, M.; Ivarsson, Y.; Beltrao, P.
Show abstract
Pathogens exploit host cellular machinery through protein-protein interactions (PPIs), often using molecular mimicry to hijack host cellular processes. While there have been thousands of host-pathogen PPIs determined to date, the lack of structural information for these impedes the study of the prevalence of molecular mimicry and convergent evolution of protein interaction interfaces. To address this, we benchmarked AlphaFold2 and 3 for prediction of structures of host-pathogen interactions observing that accurate models can be retrieved when ranking by modelling confidence, despite an overall low performance. We predicted structures for 6,782 pathogen-human PPIs yielding 803 models of higher confidence. Most pathogen proteins interacting with a common human protein are predicted to do so via the same interface, suggesting a high degree of convergent evolution of protein interaction interfaces. When comparing structural models from host-pathogen and host-host interactions, we observe that a majority of pathogen proteins are predicted to target existing human PPI interfaces. We categorized instances of mimicry into different modes, occurring at different frequencies: 1) via the same domain family (least common); 2) via a similar structural motif; and 3) via a similar linear motif (most common). We selected examples of linear motif interactions for binding assay testing, confirming 8 out of 12 predicted interfaces, including 3 viral linear motif interactions. This validates AlphaFolds ability to model some host-pathogen interactions and the mechanisms underlying molecular mimicry. This work showcases the value of large-scale structural modelling to study convergent evolution of host-pathogen interactions and how molecular mimicry may contribute to infection or host defense.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A common binding motif in the ET domain of BRD3 forms polymorphic structural interfaces with host and viral proteins 95%
- Assessing PDB Macromolecular Crystal Structure Confidence at the Individual Amino Acid Residue Level 94%
- Nucleotide binding, evolutionary insights and interaction partners of the pseudokinase Unc-51-like kinase 4 94%
Similar papers in this journal
- The molecular architecture of the desmosomal outer dense plaque by integrative structural modeling 95%
- AlphaFold2 captures the conformational landscape of the HAMP signaling domain 95%
- Structure of the Disulfide-rich Modules of a Striking Tandem Repeat Protein, Avian Cysteine-Rich Eggshell Membrane Protein 95%
Similar papers in this journal
- Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses 97%
- Getting to know each other: PPIMem, a novel approach for predicting transmembrane protein-protein complexes 95%
- Evolutionary and Structural Bioinformatics Reveal GPR89 as a Conserved Solute Carrier Transporter 93%
Similar papers in this journal
- A graph-based approach identifies dynamic H-bond communication networks in spike protein S of SARS-CoV-2 96%
- Building alternative splicing and evolution-aware sequence-structure maps for protein repeats 95%
- A set of common movements within GPCR-G-protein complexes from variability analysis of cryo-EM datasets 94%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.