AutophagyBioinformaticsPeer-reviewed journal article
AlphaFold2 SLiM screen for LC3-LIR interactions in autophagy
Abstract
In selective autophagy, cargo recruitment is mediated by LC3-interacting regions (LIRs) / Atg8-interacting motifs (AIMs) in the cargo or cargo receptor proteins. The binding of these motifs to LC3/Atg8 proteins at the phagophore membrane is often modulated by post-translational modifications, especially phosphorylation. As a challenge for computational LIR predictions, sequences may contain the short canonical (W/F/Y)XX(L/I/V) motif without being functional. Conversely, LIRs may be formed by non-canonical but functional sequence motifs. AlphaFold2 has proven to be useful for LIR predictions, even if some LIRs are missed and proteins with thousands of residues reach the limits of computational feasibility. We present a fragment-based approach to address these limitations. We find that fragment length and phosphomimetic mutations modulate the interactions predicted by AlphaFold2. Systematic fragment screening for a range of target proteins yields structural models for interactions that AlphaFold2 and AlphaFold3 fail to predict for full-length targets. We provide guidance on fragment choice, sequence tuning, and LC3 isoform effects for optimal LIR screens. Finally, we also test the transferability of this general framework to SUMO-SIM interactions, another type of protein-protein interaction involving short linear motifs (SLiMs).
- assay: protein sequence
- research focus: protein structure prediction
- research focus: benchmarking
- approach: deep learning
- approach: experimental assay
- Citations
- 8
- FWCI
- 5.51
- Field percentile
- top 4%
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