Review papers with raw data transparency

E2V recovery per RBR E3 (phage selections)

Data: phage screen outputs reported in Du et al., PNAS 2026; 23 E2Vs total targeting ARIH1, ARIH2, ANKIB1, CUL9, RNF14, HOIL1, HOIP, and LUBAC Du et al., counts and methods

Representative affinity improvements (ITC) — schematic summary

Notes: affinities measured by ITC for selected E2Vs showed up to ~10–30 fold improvements for many targets and orders-of-magnitude enrichment for ARIH2 when profiled by ABP-MS; exact Kd numbers and E2V~Ub mimics are provided in the paper and SI (ITC/BLI datasets) Du et al., ITC and kinetics

Key strengths (evidence-linked)

• Well‑executed, multi-modal validation: selections → pulldown/ITC → activity assays → cryo‑EM → ABP‑MS (datasets deposited; Addgene plasmids available) Du et al., methods and datasets
• Enables structural capture of previously intractable complex: E2V permitted 2.97–3.06 Å cryo‑EM maps of ARIH2 bound to neddylated CUL5-CRL with substrate — a major technical advance for RBR structural biology Du et al., cryo-EM structures
• Cellular activity-based profiling: E2V‑ABPs capture distinct E3 cohorts and show stimulus-dependent enrichment (TNFα → LUBAC), demonstrating utility beyond purified systems Du et al., ABP proteomics

Key weaknesses, limitations, and blindspots

• Incomplete specificity — cross‑reactivity persists: despite stringent negative selection, many E2Vs still bind closely related RBR family members (not absolute single‑E3 specificity). This is acknowledged by the authors and visible in pulldowns and ABP profiles Du et al., specificity limitations
• Affinity ≠ catalysis for noncognate pairs: high-affinity E2V–E3 binding did not always translate into efficient Ub transfer (e.g., UBE2L3‑derived E2Vs bound RNF14 but failed to restore catalysis), implying structural/catalytic incompatibilities beyond simple binding thermodynamics Du et al., binding vs catalysis
• Phage library coverage and sequence space: though theoretical diversities were large, selections sampled finite space — absolute specificity might require alternate scaffold engineering or computational design to access rarer sequences (authors discuss this) Du et al., library design and limits
• Cellular ABP caveats — abundance/accessibility bias: ABP enrichment depends on target abundance, accessibility of catalytic Cys, and probe delivery; low abundance E3s may be missed, and off-target capture via the Ub warhead is possible — authors note this and deposit raw MS for reanalysis Du et al., ABP caveats

How this fits into existing E2/E3 knowledge

Two prior themes are essential context: (1) RBR E3s use RING1 to recruit E2 and RING2 (Rcat) to form an E3~Ub thioester (hybrid RING‑HECT mechanism), and (2) E2 surfaces are evolutionarily constrained for multi‑partner recognition, producing promiscuity that complicates selective probing. Du et al. move the field forward by experimentally altering E2 surfaces to bias partner selection while retaining activity in many cases — consistent with mechanistic variability previously reported for RBR–E2 recognition modes Martino et al., Sci Rep 2018

Practical takeaways for users/experimentalists

1. Use E2Vs as selective enrichment tools (ABPs) or structural chaperones to trap complexes — they are powerful for cryo‑EM and AP‑MS (use data deposits: PDB 9SDX/9SDY, PRIDE PXD068594) Du et al., data deposits
2. Expect cross‑reactivity: include orthogonal readouts (activity assays, rescue experiments, catalytically dead competitors) to confirm functional specificity.
3. For structural trapping, prefer E2V~Ub mimics and crosslinking strategies as in the paper — these aided visualization of RING2 and active-site geometry at high resolution Du et al., cryo-EM trapping strategy
4. When using E2V ABPs in cells, control for abundance/accessibility and include nonreactive probe controls; reprocess PRIDE data if needed for alternative thresholds (data available) Du et al., PRIDE dataset

Reproducibility checklist (what to look for in SI/data)

• Oligonucleotide design for phage libraries and coverage statistics (Dataset S1) — verify degeneracy and observed sequence diversity.
• Full ITC/BLI raw curves (Dataset S3) — check model fits and stoichiometry.
• Uncropped gels and replicate numbers for activity assays (Dataset S1) — look for biological as well as technical replicates; many assays reported n=2 technical replicates.
• PRIDE raw MS files to confirm enrichment and fold-change calculations (PXD068594) Du et al., PRIDE and Addgene

Concise conclusions and confidence

Du et al. deliver a compelling, well‑documented toolkit (23 E2Vs) that meaningfully extends the proteomic and structural toolbox for RBR E3 biology: E2Vs can (i) bias E2–E3 pairing to enable cryo‑EM of otherwise fleeting complexes, (ii) separate activities of E3s inside multi‑E3 complexes (e.g., HOIP vs HOIL1 in LUBAC), and (iii) increase sensitivity of ABP‑based profiling to detect stimulus‑responsive E3s. The approach is generalizable in principle but will often produce partial rather than absolute specificity and sometimes binding without catalysis; users should pair binding data with activity readouts and consider additional library/computational design to reach single‑E3 specificity.

Caveat: claims are well supported by deposited data (PDB/EMDB/PRIDE/Addgene); remaining uncertainties concern in‑cell specificity, generalizability across all E3 families, and whether engineered E2Vs fully recapitulate catalytic positioning for all partner E3s (authors acknowledge these limitations and outline future library strategies) Du et al., limitations and future directions

Open: Author reviews (click to request an Author Review via BGPT)