Molecular basis of AMPA receptor labeling by ligand-directed acyl imidazole chemistry in living neurons
Guzman-Ocampo, D. C.; De Sancho, D.; Lopez, X.
Show abstract
Rational design of covalent protein-labeling reagents in complex biological environments requires a molecular-level understanding of how the protein microenvironment governs chemical reactivity; yet, such mechanistic details remain inaccessible to experimental methods alone. In living neurons, Ligand-Directed Acyl Imidazole (LDAI) chemistry has been used to label AMPA receptors as a traceless, affinity-based protein labeling method. Although LDAI labeling reagents have been optimized in the lab, the atomic details of their interactions with the protein and the underlying mechanism remain elusive. In this work, we combined Quantum Mechanical (QM) calculations and molecular dynamics (MD) simulations to propose a detailed reaction mechanism for AMPAR labeling by LDAI reagents and to clarify how the protein microenvironment governs reactivity. Although Lys residues are usually protonated at physiological pH and therefore less nucleophilic in water, our QM results show that Lys labeling is energetically more favorable than competing reactions with Ser or water. MD simulations reveal that PFQX ---the LDAI reagent precursor--- binds dynamically to the GluA2 AMPAR as an antagonist, inducing conformational changes that reshape the local environment of the acyl imidazole (AI) warhead, underscoring that ligand identity strongly affects labeling outcomes. We also identified intra and intermolecular hydrogen bond networks that may contribute to further immobilize and pre-organize the LDAI reagent. Moreover, the probe's chemical nature shapes its interactions with the Ligand Binding Domain (LBD), offering a plausible rationale for the previously experimentally observed ligand-dependent fluorescent response. Taken together, our results establish design principles for exploiting the reagent geometry and binding pocket hydrogen-bonding networks for the rational design of LDAI reagents.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A Global Ligandability Map of Tryptoline Butynamide Stereoprobes Identifies Covalent Inhibitors of the Actin Maturation Protease ACTMAP 95%
- TRPM8 protein dynamics correlates with ligand structure and cellular function 95%
- De novo design of proteins that bind naphthalenediimides, powerful photooxidants with tunable photophysical properties 94%
Similar papers in this journal
- Residue-Specific Modulation of Aggregation-Associated Interactions bySpermine in Tau, α-Synuclein, and Aβ40 94%
- Catalytic Redundancies and Conformational Plasticity Drives Selectivity and Promiscuity in Quorum Quenching Lactonases 93%
- Identifying Selectivity Filters in Protein Biosensor for Ligand Screening 93%
Similar papers in this journal
- Analogs of the Dopamine Metabolite 5,6-Dihydroxyindole Bind Directly to and Activate the Nuclear Receptor Nurr1 (NR4A2) 95%
- Development of Second-Generation Acyl Silane Photoaffinity Probes for Cellular Chemoproteomic Profiling 94%
- Conditional covalent lethality driven by oncometabolite accumulation 93%
Similar papers in this journal
- Describing Inhibitor Specificity for the Amino Acid Transporter LAT1 from Metainference Simulations 93%
- Simulations support the interaction of the SARS-CoV-2 spike protein with nicotinic acetylcholine receptors 92%
- Effect of Histidine Covalent Modification on Strigolactone Receptor Activation and Selectivity 92%
"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.