AlphaFold2-multimer guided high-accuracy prediction of typical and atypical ATG8-binding motifs

Abstract

Macroautophagy/autophagy is an intracellular degradation process central to cellular homeostasis and defense against pathogens in eukaryotic cells. Regulation of autophagy relies on hierarchical binding of autophagy cargo receptors and adaptors to ATG8/LC3 protein family members. Interactions with ATG8/LC3 are typically facilitated by a conserved, short linear sequence, referred to as the ATG8/LC3 interacting motif/region (AIM/LIR), present in autophagy adaptors and receptors as well as pathogen virulence factors targeting host autophagy machinery. Since the canonical AIM/LIR sequence can be found in many proteins, identifying functional AIM/LIR motifs has proven challenging. Here, we show that protein modelling using Alphafold-Multimer (AF2-multimer) identifies both canonical and atypical AIM/LIR motifs with a high level of accuracy. AF2-multimer can be modified to detect additional functional AIM/LIR motifs by using protein sequences with mutations in primary AIM/LIR residues. By combining protein modelling data from AF2-multimer with phylogenetic analysis of protein sequences and protein–protein interaction assays, we demonstrate that AF2-multimer predicts the physiologically relevant AIM motif in the ATG8-interacting protein 2 (ATI-2) as well as the previously uncharacterized noncanonical AIM motif in ATG3 from potato (Solanum tuberosum). AF2-multimer also identified the AIM/LIR motifs in pathogen-encoded virulence factors that target ATG8 members in their plant and human hosts, revealing that cross-kingdom ATG8-LIR/AIM associations can also be predicted by AF2-multimer. We conclude that the AF2-guided discovery of autophagy adaptors/receptors will substantially accelerate our understanding of the molecular basis of autophagy in all biological kingdoms.

Semisynthetic LC3 Probes for Autophagy Pathways Reveal a Noncanonical LC3 Interacting Region Motif Crucial for the Enzymatic Activity of Human ATG3

“…Recent improvements have enabled researchers to model protein–protein interactions, and we employed an open-source modeling tool, ColabFold, to model the protein–protein interaction between ATG3 and GABARAP (Figure c, Figures S4–S5). Intriguingly, ColabFold modeled a complex of ATG3 and GABARAP that resembled the canonical closed-conformation observed in E2-Ub thioester complexes. , Additionally, a section of the flexible region of ATG3, L94-Y111, folded into a short β-sheet that was bound to a groove formed by helices α2 and α3. The interaction site on GABARAP was equivalent to the canonical binding region of LIR motifs.…”

“…28 Intriguingly, ColabFold modeled a complex of ATG3 and GABARAP that resembled the canonical closed-conformation observed in E2-Ub thioester complexes. 29,30 Additionally, a section of the flexible region of ATG3, L94-Y111, folded into a short β-sheet that was bound to a groove formed by helices α2 and α3. The interaction site on GABARAP was equivalent to the canonical binding region of LIR motifs.…”

A genomic and structural bioinformatic pipeline identifies candidate type VI secretion antibacterial effector-immunity pairs

“…The huge progress in scientists' ability to predict protein structure from sequence biology due to AlphaFold2 and RoseTTAFold opens new doors for investigation of biology, specifically of protein-protein interactions 49,82,83 . AlphaFold-Multimer, which we use in this paper, has been used to model and predict protein-protein interactions in eukaryotes 84,85 as well as in microbes 86,87 . We have seen that certain proteins have areas of poor folding that are many times modeled as "linkers" between N-terminal T6SS core domains and C-terminal effector domains.…”

AlphaFold-multimer predicts ATG8 protein binding motifs crucial for autophagy research

“…This is done in an iterative manner. In this issue of PLOS Biology , Ibrahim and colleagues demonstrate how AlphaFold2 (AF2)-multimer can be used as an important and powerful new tool to successfully predict so-called LC3 interacting region (LIR) motifs (see below) in proteins involved in autophagy processes [ 2 ].…”

“…The recent AlphaFold-Multimer (AF2-multimer) now predicts interaction surfaces between two proteins [ 9 ]. In this issue of PLOS Biology , Ibrahim and colleagues demonstrate how AF2-multimer can be used to successfully predict LIR motifs of both known and unknown LIR-containing proteins and also to identify noncanonical LIR motifs ( Fig 1 ) [ 2 ]. This is a large step forward that the autophagy research community will benefit from.…”