Piéger une enzyme pour cartographier son réseau d’influence dans la cellule

Hypothèse formelle

If a cell-permeable, covalent activity-based probe (ABP) targeting a specific enzyme family is applied at a concentration that achieves ≥90% target occupancy within 15 minutes, then the resulting multi-omics perturbation response (transcriptomics, proteomics, metabolomics) will enable the inference of causal edges in the target’s signaling network with a precision-recall AUC ≥ 0.75, because the ABP’s activity-dependent, irreversible binding creates a temporally precise and specific node inhibition that allows for the deconvolution of direct from indirect regulatory effects via differential equation modeling of the time-resolved omics data.

Titre donné par l’affûteur : Activity-Based Probes as Causal Perturbagens for Dynamic Inference of Enzyme Network Topology in Live Cells

Contre-preuves

1. A supposedly specific covalent inhibitor (K777 analogue) was found to have an off-target (TcCYP51) that was actually responsible for its primary activity. This highlights the risk of off-target effects with covalent probes, which could confound causal inference in the proposed platform.

   Gravité sérieuseChemical–biological characterization of a cruzain inhibitor reveals a second target and a mammalian off-target (2013)

2. The study observed stochasticity in network remodeling upon chronic inhibition, suggesting that even with specific perturbations, the system’s response can be variable and not deterministic. This could complicate causal inference from single perturbation experiments.

   Gravité surmontableEmpirical inference of circuitry and plasticity in a kinase signaling network (2015)

Inconnues et conditions de validité

Inconnues identifiées

• We do not know whether the off-target profile of a given ABP (e.g., IMP-1710) will be sufficiently clean in a non-human cell line (e.g., HEK293T) to avoid confounding signals.
• We do not know the optimal number of time points or the sampling frequency required to capture the fastest post-translational modification events (e.g., phosphorylation within 1-2 minutes).
• We do not know whether the inferred causal edges will be stable across different cell types or if they are highly context-dependent.

Conditions de validité

• ABP concentration must be ≤10 µM to avoid non-specific thiol reactivity.Justification : Above 10 µM, many covalent warheads (e.g., acrylamides) begin to react with off-target cysteines, violating the specificity assumption.
• Cell viability must remain >90% (by MTT assay) throughout the 120-minute experiment.Justification : If cell death exceeds 10%, the omics signal will be dominated by apoptosis/necrosis pathways rather than the specific network perturbation.
• The target enzyme must have a known, validated fluorogenic or activity-based substrate for the in-cell activity assay.Justification : Without a direct activity readout, target engagement cannot be confirmed, and the causal chain from probe binding to network perturbation is unverifiable.
• The experiment must be performed in a cell line with a sequenced genome and well-annotated proteome (e.g., HEK293T, HeLa).Justification : Accurate protein identification and quantification in the omics pipeline requires a high-quality reference database.

Mécanisme proposé

Chaîne causale

1. Step 1: ABP (e.g., IMP-1710 for UCHL1) is added to live cells at a concentration (e.g., 1 µM) that saturates the active site of the target enzyme within 15 minutes, forming a covalent adduct and reducing its catalytic activity by ≥95%.
2. Step 2: The acute loss of target enzyme function disrupts its immediate downstream substrates (e.g., ubiquitin chain processing for UCHL1), causing a rapid accumulation of specific substrate species within 5-10 minutes.
3. Step 3: The accumulated substrates trigger compensatory or feed-forward signaling through parallel pathways, leading to a cascade of post-translational modifications (e.g., phosphorylation) and transcriptional changes measurable by phosphoproteomics and RNA-seq at 30-120 minutes.
4. Step 4: Time-resolved multi-omics data (e.g., 8 time points over 0-120 min) are used to fit a dynamic Bayesian network or ordinary differential equation model, where the known time of ABP addition serves as a forced intervention node, allowing the algorithm to distinguish causal edges from correlations.

Postulats clés

• Assumption 1: The ABP is cell-permeable and reaches an intracellular concentration sufficient for target occupancy without significant efflux or metabolism within the experimental window.
• Assumption 2: The ABP has no measurable off-target activity against any other enzyme in the proteome at the working concentration (selectivity >100-fold over the next closest target).
• Assumption 3: The target enzyme’s activity is the rate-limiting step for its immediate downstream reactions, such that its inhibition produces a detectable accumulation of substrate within 10 minutes.
• Assumption 4: The biological network is at steady-state prior to perturbation, and the observed omics changes are solely due to the ABP-induced node inhibition, not to cellular stress responses from the vehicle (e.g., DMSO ≤0.1% v/v).

Cadre théorique

Causal inference in biological networks via interventional perturbation-omics

Variables

Prédictions falsifiables

1. 1

   Application of 1 µM IMP-1710 to HEK293T cells will reduce UCHL1 activity by ≥95% within 15 minutes, as measured by a fluorogenic substrate assay.

   Borne quantitative

   Residual UCHL1 activity ≤5% of DMSO control at t=15 min.

   Méthode de mesure

   In-cell activity assay using Ub-AMC substrate (ex/em 380/460 nm) on cell lysates.Test statistique One-tailed t-test, α=0.01, n=3 biological replicates.

   Hypothèse nulle

   H0: Mean residual UCHL1 activity at 15 min is not significantly different from DMSO control (≥90% of control).

2. 2

   The number of differentially expressed proteins (DEPs, fold-change >2, FDR <0.05) at 60 minutes post-IMP-1710 treatment will be at least 50, as measured by TMT-based quantitative proteomics.

   Borne quantitative

   ≥50 DEPs identified at 60 min vs. DMSO control.

   Méthode de mesure

   TMT10-plex quantitative proteomics on a Q-Exactive HF-X mass spectrometer.Test statistique Permutation test (10,000 permutations) on the number of proteins with q<0.05, α=0.05.

   Hypothèse nulle

   H0: The number of DEPs at 60 min does not exceed the number expected by chance (≤5 DEPs).

3. 3

   Causal network inference using the time-resolved phosphoproteomics data (8 time points, 0-120 min) will achieve a precision-recall AUC ≥0.75 when validated against a known gold-standard network for UCHL1 signaling derived from literature-curated interactions.

   Borne quantitative

   PR-AUC ≥0.75 for the inferred network.

   Méthode de mesure

   Dynamic Bayesian network inference (e.g., using the “CausalBench” framework) on phosphopeptide intensity time series.Test statistique One-sided Wilcoxon signed-rank test comparing PR-AUC from 10 independent DBN runs vs. 10 runs on permuted data, α=0.05.

   Hypothèse nulle

   H0: The PR-AUC of the inferred network is not significantly greater than that of a network inferred from randomly permuted time labels (PR-AUC ≤0.50).

Protocole expérimental

Références

8 références, toutes issues de Semantic Scholar. Une référence vérifiée est un article qui existe et qui est indexé par Semantic Scholar. Cela ne veut pas dire qu’il confirme l’idée.

1. 1
   Nattawadee Panyain, A. Godinat, Thomas Lanyon-Hogg et al. (2019). Discovery of a Potent and Selective Covalent Inhibitor and Activity-Based Probe for the Deubiquitylating Enzyme UCHL1, with Antifibrotic Activity.appui direct · 68 citations · doi:10.1021/jacs.0c04527Ce qu’en retient le documentaliste IMP-1710 is a potent and selective covalent inhibitor/ABP for UCHL1 that labels the catalytic cysteine at low nanomolar concentrations in intact cells.Pertinence Directly demonstrates the design and application of an activity-based probe (ABP) that covalently and selectively binds to the active form of a specific enzyme (UCHL1). This is the core chemical biology tool the hypothesis relies on.
2. 2
   G. Kennedy, David E Holt, F. Azari et al. (2022). A cathepsin targeted quenched activity-based probe facilitates enhanced detection of human tumors during resection.appui direct · 30 citations · doi:10.1158/1078-0432.CCR-22-1215Ce qu’en retient le documentaliste VGT-309, a cathepsin-targeted quenched ABP, safely and specifically labels human pulmonary tumors during resection, demonstrating in vivo utility.Pertinence Shows clinical translation of an ABP (VGT-309) that targets cathepsins, demonstrating that ABPs can be used in vivo for specific, activity-dependent labeling. Supports the feasibility of using ABPs as perturbations in living systems.
3. 3
   Michael Mayers, Clara Moon, Gregory S. Stupp et al. (2017). Quantitative metaproteomics and activity-based probe enrichment reveals significant alterations in protein expression from a mouse model of inflammatory bowel disease.appui indirect · 59 citations · doi:10.1021/acs.jproteome.6b00938Ce qu’en retient le documentaliste ABPs can enrich and analyze both host and microbial proteins with specificity in a complex in vivo system (mouse model of IBD).Pertinence Combines ABPs with quantitative proteomics (metaproteomics) to study a biological system. This is methodologically similar to the proposed “chemically triggered perturbation-omics” platform, though the focus is on enrichment/detection rather than perturbation for causal inference.
4. 4
   L. T. Henneberg, Jaspal Singh, David M. Duda et al. (2023). Activity-based profiling of cullin–RING E3 networks by conformation-specific probes.appui indirect · 21 citations · doi:10.1038/s41589-023-01392-5Ce qu’en retient le documentaliste Conformation-specific antibodies (probes) were developed to profile activated cullin-RING E3 ligase networks in response to stimuli and drugs.Pertinence Develops probes that specifically recognize the active conformation of CRL complexes. This is an advanced form of activity-based probing that could be adapted for perturbation experiments to map network topology.
5. 5
   E. Wilkes, Camille Terfve, J. Gribben et al. (2015). Empirical inference of circuitry and plasticity in a kinase signaling network.appui indirect · 72 citations · doi:10.1073/pnas.1423344112Ce qu’en retient le documentaliste Kinase signaling network topology can be inferred de novo from MS-based phosphoproteomics data following pharmacological perturbations.Pertinence Demonstrates the systems biology goal of inferring network topology from perturbation experiments (using kinase inhibitors). Supports the feasibility of the overall approach, though the perturbations used are not ABPs.
6. 6
   Mathieu Chevalley, Yusuf H. Roohani, Arash Mehrjou et al. (2025). A large-scale benchmark for network inference from single-cell perturbation data.appui indirect · 35 citations · doi:10.1038/s42003-025-07764-yCe qu’en retient le documentaliste CausalBench provides a standardized framework for evaluating network inference methods using real-world perturbation data.Pertinence Provides a benchmark for causal network inference from perturbation data, validating the systems biology methodology that the hypothesis aims to enhance with ABPs.
7. 7
   Amanda M. Tallon, Yingrong Xu, Graham M. West et al. (2023). Thiomethyltetrazines are Reversible Covalent Cysteine Warheads whose Dynamic Behavior can be “Switched Off” via Bioorthogonal Chemistry Inside Live Cells.appui indirect · 21 citations · doi:10.1021/jacs.3c04444Ce qu’en retient le documentaliste Thiomethyltetrazines act as reversible covalent warheads that can be “locked” via bioorthogonal Diels-Alder chemistry inside live cells.Pertinence Introduces a bioorthogonal “switch” to lock in covalent modifications. This provides a chemical tool that could be used to create temporally controlled perturbations (e.g., turn on/off inhibition), which is a key aspect of the hypothesis.
8. 8
   Samuel L. Scinto, Oshini Ekanayake, Uthpala I. Seneviratne et al. (2019). Dual-Reactivity trans-Cyclooctenol Probes for Sulfenylation in Live Cells Enable Temporal Control via Bioorthogonal Quenching.appui indirect · 37 citations · doi:10.1021/jacs.9b01164Ce qu’en retient le documentaliste SAM-TCO probes enable temporal control of sulfenic acid labeling via bioorthogonal quenching in live cells.Pertinence Demonstrates temporal control of probe reactivity via bioorthogonal quenching. This supports the hypothesis’s claim that ABPs can provide time-controlled perturbations.

Nouveauté

Score de nouveauté : 0,85 sur 1 · Verdict : jugée nouvelle

Ce score est attribué par un agent à partir des travaux trouvés. C’est une estimation, pas une mesure. Comment ce score est produit

Travaux les plus proches

• Empirical inference of circuitry and plasticity in a kinase signaling network (2015)Différence avec l’idée : This paper uses pharmacological inhibitors (kinase inhibitors) as perturbations to infer network topology, but does not use activity-based probes (ABPs) that covalently bind only the active form of enzymes. The hypothesis proposes ABPs as a more specific, activity-dependent perturbation tool, which is a methodological refinement not demonstrated here.
• A large-scale benchmark for network inference from single-cell perturbation data (2025)Différence avec l’idée : This paper uses genetic perturbations (CRISPR) for causal network inference, not chemical perturbations. The hypothesis specifically proposes chemical biology probes as a complementary approach with different advantages (temporal control, reversibility, activity-dependence), which is not addressed here.
• Concurrent TMS-fMRI for causal network perturbation and proof of target engagement (2021)Différence avec l’idée : This paper uses neurostimulation (TMS) for causal perturbation in neuroscience, which is conceptually analogous but in a different domain (neuroscience vs. molecular/cellular biology). The hypothesis applies the same logic to chemical biology probes in molecular networks.

Lacunes et données

Lacunes identifiées

• The counter_evidence from paper 835de5f009e82d7344540cdf8c62db91426db64f reveals a critical gap: the potential for off-target effects of ABPs to confound causal inference. The hypothesis must address how to validate target specificity in the proposed platform.
• The counter_evidence from paper 0aca68b2f5922b5c02d4d4fe138430fde9a05499 reveals a gap in understanding how stochasticity in network remodeling might affect the reproducibility and interpretability of causal inference from single ABP perturbations.

Données disponibles

• Paper b43e97cba1389b70ae218b1608117524f15ef7e8 provides a benchmark dataset (CausalBench) for evaluating network inference methods from perturbation data.
• Paper 0aca68b2f5922b5c02d4d4fe138430fde9a05499 provides a dataset of phosphoproteomic responses to kinase inhibitor perturbations.

Synthèse du panel

Note de consensus : 5,86/10 Moyenne des cinq notes, pondérée par la confiance que chaque relecteur déclare.

Verdict du méta-relecteur : publier

Points d’accord

• The use of ABPs as temporally precise causal perturbagens is conceptually elegant and addresses a genuine methodological need in network inference.
• The explicit formulation of quantitative predictions (≥90% occupancy, PR-AUC ≥0.75, ≥50 DEPs) and GO/NO-GO criteria is a methodological strength that renders the hypothesis falsifiable.
• ABP selectivity is unanimously identified as the critical Achilles heel: the near-inevitable off-target effects of covalent probes directly threaten the validity of causal inference.
• The current temporal design (8 time points over 120 min) is judged by several reviewers to be insufficient for capturing the rapid causal dynamics of signalling events.

Points de désaccord

• The Contrarian (score 2.5, confidence 0.9) judges the hypothesis to be untestable and rejects it outright, whereas the other reviewers (scores 6.5–7.2) see significant potential despite major reservations.
• Disagreement is noted regarding the feasibility of achieving PR-AUC ≥0.75: the Contrarian and the Domain Expert consider this threshold unrealistic (<0.5–0.6 in real networks), while the Methodologist and the Funding Strategist regard it as an ambitious but defensible target.
• The Domain Expert and the Industrialist judge the market to be too narrow for a standalone product, whereas the Funding Strategist sees potential for ERC/ANR funding for an exploratory project.
• Disagreement is noted regarding the strength of the expected omic signal: the Contrarian predicts a signal too weak in HEK293T (UCHL1 being poorly expressed), whereas the Domain Expert and the Funding Strategist consider the UCHL1 interactome to be sufficient.

Chemin critique

The absolute prerequisite, without which the entire hypothesis collapses, is the irrefutable experimental demonstration of the selectivity of the ABP IMP-1710 (or an alternative ABP) through large-scale competition proteomics in the chosen cellular system, coupled with a validation that the inhibition of UCHL1 produces a robust and reproducible omic signal (≥100 significant phosphopeptides at early time points <15 min).

Recommandation finale

The hypothesis is judged intellectually promising but immature. The panel recommends major revision before resubmission. The authors are required to: (1) provide competitive proteomics data demonstrating ABP selectivity in the target cellular system; (2) increase the temporal resolution to 12–15 points, including time points <5 min; (3) demonstrate a robust early omic signal in a well-characterised model; (4) integrate controls for compensatory pathways (e.g., proteasome inhibitor). Without these prerequisites, the hypothesis remains speculative and cannot be published in a leading journal.