Stoichiometry and geometry of the CXC chemokine receptor 4 complex with CXC ligand 12: molecular modeling and experimental validation.

Chemokines and their receptors regulate cell migration during development, immune system function, and in inflammatory diseases, making them important therapeutic targets. Nevertheless, the structural basis of receptor:chemokine interaction is poorly understood. Adding to the complexity of the problem is the persistently dimeric behavior of receptors observed in cell-based studies, which in combination with structural and mutagenesis data, suggest several possibilities for receptor:chemokine complex stoichiometry. In this study, a combination of computational, functional, and biophysical approaches was used to elucidate the stoichiometry and geometry of the interaction between the CXC-type chemokine receptor 4 (CXCR4) and its ligand CXCL12. First, relevance and feasibility of a 2:1 stoichiometry hypothesis was probed using functional complementation experiments with multiple pairs of complementary nonfunctional CXCR4 mutants. Next, the importance of dimers of WT CXCR4 was explored using the strategy of dimer dilution, where WT receptor dimerization is disrupted by increasing expression of nonfunctional CXCR4 mutants. The results of these experiments were supportive of a 1:1 stoichiometry, although the latter could not simultaneously reconcile existing structural and mutagenesis data. To resolve the contradiction, cysteine trapping experiments were used to derive residue proximity constraints that enabled construction of a validated 1:1 receptor:chemokine model, consistent with the paradigmatic two-site hypothesis of receptor activation. The observation of a 1:1 stoichiometry is in line with accumulating evidence supporting monomers as minimal functional units of G protein-coupled receptors, and suggests transmission of conformational changes across the dimer interface as the most probable mechanism of altered signaling by receptor heterodimers.

Covalent trapping of methyllycaconitine at the α4-α4 interface of the α4ß2 nicotinic acetylcholine receptor: antagonist binding site and mode of receptor inhibition revealed.

The α4ß2 nicotinic acetylcholine receptors (nAChRs) are widely expressed in the brain and are implicated in a variety of physiological processes. There are two stoichiometries of the α4ß2 nAChR, (α4)2(ß2)3 and (α4)3(ß2)2, with different sensitivities to acetylcholine (ACh), but their pharmacological profiles are not fully understood. Methyllycaconitine (MLA) is known to be an antagonist of nAChRs. Using the two-electrode voltage clamp technique and α4ß2 nAChRs in the Xenopus oocyte expression system, we demonstrate that inhibition by MLA occurs via two different mechanisms; that is, a direct competitive antagonism and an apparently insurmountable mechanism that only occurs after preincubation with MLA. We hypothesized an additional MLA binding site in the α4-α4 interface that is unique to this stoichiometry. To prove this, we covalently trapped a cysteine-reactive MLA analog at an α4ß2 receptor containing an α4(D204C) mutation predicted by homology modeling to be within reach of the reactive probe. We demonstrate that covalent trapping results in irreversible reduction of ACh-elicited currents in the (α4)3(ß2)2 stoichiometry, indicating that MLA binds to the α4-α4 interface of the (α4)3(ß2)2 and providing direct evidence of ligand binding to the α4-α4 interface. Consistent with other studies, we propose that the α4-α4 interface is a structural target for potential therapeutics that modulate (α4)3(ß2)2 nAChRs.

Development of a Novel In Silico Classification Model to Assess Reactive Metabolite Formation in the Cysteine Trapping Assay and Investigation of Important Substructures.

Predicting whether a compound can cause drug-induced liver injury (DILI) is difficult due to the complexity of drug mechanism. The cysteine trapping assay is a method for detecting reactive metabolites that bind to microsomes covalently. However, it is cumbersome to use 35S isotope-labeled cysteine for this assay. Therefore, we constructed an in silico classification model for predicting a positive/negative outcome in the cysteine trapping assay. We collected 475 compounds (436 in-house compounds and 39 publicly available drugs) based on experimental data performed in this study, and the composition of the results showed 248 positives and 227 negatives. Using a Message Passing Neural Network (MPNN) and Random Forest (RF) with extended connectivity fingerprint (ECFP) 4, we built machine learning models to predict the covalent binding risk of compounds. In the time-split dataset, AUC-ROC of MPNN and RF were 0.625 and 0.559 in the hold-out test, restrictively. This result suggests that the MPNN model has a higher predictivity than RF in the time-split dataset. Hence, we conclude that the in silico MPNN classification model for the cysteine trapping assay has a better predictive power. Furthermore, most of the substructures that contributed positively to the cysteine trapping assay were consistent with previous results.

Lights and shadows of electrophile signaling: focus on the Nrf2-Keap1 pathway.

Targeted covalent modification is assuming consolidated importance in drug discovery. In this context, the electrophilic tuning of redox-dependent cell signaling is attracting major interest, as it opens prospect for treating numerous pathologic conditions. Herein, we discuss the rationale and the issues of electrophile-based approaches, focusing on the transcriptional Nrf2-Keap1 pathway as a test case. We also highlight relevant medicinal chemistry strategies researchers have devised to meet the ambitious goal, dwelling on the investigational and therapeutic potential of modulating redox-signaling networks through regulatory cysteine switches.

Disulfide Trapping for Modeling and Structure Determination of Receptor: Chemokine Complexes.

Despite the recent breakthrough advances in GPCR crystallography, structure determination of protein-protein complexes involving chemokine receptors and their endogenous chemokine ligands remains challenging. Here, we describe disulfide trapping, a methodology for generating irreversible covalent binary protein complexes from unbound protein partners by introducing two cysteine residues, one per interaction partner, at selected positions within their interaction interface. Disulfide trapping can serve at least two distinct purposes: (i) stabilization of the complex to assist structural studies and/or (ii) determination of pairwise residue proximities to guide molecular modeling. Methods for characterization of disulfide-trapped complexes are described and evaluated in terms of throughput, sensitivity, and specificity toward the most energetically favorable crosslinks. Due to abundance of native disulfide bonds at receptor:chemokine interfaces, disulfide trapping of their complexes can be associated with intramolecular disulfide shuffling and result in misfolding of the component proteins; because of this, evidence from several experiments is typically needed to firmly establish a positive disulfide crosslink. An optimal pipeline that maximizes throughput and minimizes time and costs by early triage of unsuccessful candidate constructs is proposed.