Bayesian network models identify cooperative GPCR:G protein interactions that contribute to G protein coupling.

Cooperative interactions in protein-protein interfaces demonstrate the interdependency or the linked network-like behavior and their effect on the coupling of proteins. Cooperative interactions also could cause ripple or allosteric effects at a distance in protein-protein interfaces. Although they are critically important in protein-protein interfaces, it is challenging to determine which amino acid pair interactions are cooperative. In this work, we have used Bayesian network modeling, an interpretable machine learning method, combined with molecular dynamics trajectories to identify the residue pairs that show high cooperativity and their allosteric effect in the interface of G protein-coupled receptor (GPCR) complexes with Gα subunits. Our results reveal six GPCR:Gα contacts that are common to the different Gα subtypes and show strong cooperativity in the formation of interface. Both the C terminus helix5 and the core of the G protein are codependent entities and play an important role in GPCR coupling. We show that a promiscuous GPCR coupling to different Gα subtypes, makes all the GPCR:Gα contacts that are specific to each Gα subtype (Gαs, Gαi, and Gαq). This work underscores the potential of data-driven Bayesian network modeling in elucidating the intricate dependencies and selectivity determinants in GPCR:G protein complexes, offering valuable insights into the dynamic nature of these essential cellular signaling components.

Stabilization of interdomain interactions in G protein α subunits as a determinant of Gαi subtype signaling specificity.

Highly homologous members of the Gαi family, Gαi1-3, have distinct tissue distributions and physiological functions, yet their biochemical and functional properties are very similar. We recently identified PDZ-RhoGEF (PRG) as a novel Gαi1 effector that is poorly activated by Gαi2. In a proteomic proximity labeling screen we observed a strong preference for Gαi1 relative to Gαi2 with respect to engagement of a broad range of potential targets. We investigated the mechanistic basis for this selectivity using PRG as a representative target. Substitution of either the helical domain (HD) from Gαi1 into Gαi2 or substitution of a single amino acid, A230 in Gαi2 with the corresponding D in Gαi1, largely rescues PRG activation and interactions with other potential Gαi targets. Molecular dynamics simulations combined with Bayesian network models revealed that in the GTP bound state, separation at the HD-Ras-like domain (RLD) interface is more pronounced in Gαi2 than Gαi1. Mutation of A230 to D in Gαi2 stabilizes HD-RLD interactions via ionic interactions with R145 in the HD which in turn modify the conformation of Switch III. These data support a model where D229 in Gαi1 interacts with R144 and stabilizes a network of interactions between HD and RLD to promote protein target recognition. The corresponding A230 in Gαi2 is unable to stabilize this network leading to an overall lower efficacy with respect to target interactions. This study reveals distinct mechanistic properties that could underly differential biological and physiological consequences of activation of Gαi1 or Gαi2 by G protein-coupled receptors.

Cellular lipids regulate the conformational ensembles of the disordered intracellular loop 3 in ß2-adrenergic receptor.

The intracellular loops of G protein-coupled receptors (GPCRs) have been shown to play a key role in G protein coupling and selectivity. We recently showed that the intrinsically disordered third intracellular loop (ICL3) of ß2-adrenergic receptor is dynamic and equilibrates between open and closed conformations to regulate the G protein coupling. In this study, using the extensive molecular dynamics simulations in multi-lipid bilayer models, we show that the lipid phosphatidylinositol 4,5-bisphosphate (PIP2) stabilizes the active state of ß2-adrenergic receptor by keeping ICL3 in an open conformation. This stabilization results in a tilt of the receptor within the membrane. Additionally, the ganglioside lipid, GM3 interacts with extracellular loops, impacting the ligand binding site allosterically. This demonstrates the active role of the chemistry of lipids in stabilizing specific GPCR conformations.

Oligo-PROTAC strategy for cell-selective and targeted degradation of activated STAT3.

Decoy oligodeoxynucleotides (ODNs) allow targeting undruggable transcription factors, such as STAT3, but their limited potency and lack of delivery methods hampered translation. To overcome these challenges, we conjugated a STAT3-specific decoy to thalidomide, a ligand to cereblon in E3 ubiquitin ligase complex, to generate a proteolysis-targeting chimera (STAT3DPROTAC). STAT3DPROTAC downregulated STAT3 in target cells, but not STAT1 or STAT5. Computational modeling of the STAT3DPROTAC ternary complex predicted two surface lysines, K601 and K626, in STAT3 as potential ubiquitination sites. Accordingly, K601/K626 point mutations in STAT3, as well as proteasome inhibition or cereblon deletion, alleviated STAT3DPROTAC effect. Next, we conjugated STAT3DPROTAC to a CpG oligonucleotide targeting Toll-like receptor 9 (TLR9) to generate myeloid/B cell-selective C-STAT3DPROTAC. Naked C-STAT3DPROTAC was spontaneously internalized by TLR9+ myeloid cells, B cells, and human and mouse lymphoma cells but not by T cells. C-STAT3DPROTAC effectively decreased STAT3 protein levels and also STAT3-regulated target genes critical for lymphoma cell proliferation and/or survival (BCL2L1, CCND2, and MYC). Finally, local C-STAT3DPROTAC administration to human Ly3 lymphoma-bearing mice triggered tumor regression, while control C-STAT3D and C-SCR treatments had limited effects. Our results underscore the feasibility of using a PROTAC strategy for cell-selective, decoy oligonucleotide-based STAT3 targeting of and potentially other tumorigenic transcription factors for cancer therapy.

A novel class of inhibitors that disrupts the stability of integrin heterodimers identified by CRISPR-tiling-instructed genetic screens.

The plasma membrane is enriched for receptors and signaling proteins that are accessible from the extracellular space for pharmacological intervention. Here we conducted a series of CRISPR screens using human cell surface proteome and integrin family libraries in multiple cancer models. Our results identified ITGAV (integrin αV) and its heterodimer partner ITGB5 (integrin ß5) as the essential integrin α/ß pair for cancer cell expansion. High-density CRISPR gene tiling further pinpointed the integral pocket within the ß-propeller domain of ITGAV for integrin αVß5 dimerization. Combined with in silico compound docking, we developed a CRISPR-Tiling-Instructed Computer-Aided (CRISPR-TICA) pipeline for drug discovery and identified Cpd_AV2 as a lead inhibitor targeting the ß-propeller central pocket of ITGAV. Cpd_AV2 treatment led to rapid uncoupling of integrin αVß5 and cellular apoptosis, providing a unique class of therapeutic action that eliminates the integrin signaling via heterodimer dissociation. We also foresee the CRISPR-TICA approach to be an accessible method for future drug discovery studies.

Therapeutic targeting Tudor domains in leukemia via CRISPR-Scan Assisted Drug Discovery.

Epigenetic dysregulation has been reported in multiple cancers including leukemias. Nonetheless, the roles of the epigenetic reader Tudor domains in leukemia progression and therapy remain unexplored. Here, we conducted a Tudor domain-focused CRISPR screen and identified SGF29, a component of SAGA/ATAC acetyltransferase complexes, as a crucial factor for H3K9 acetylation, ribosomal gene expression, and leukemogenesis. To facilitate drug development, we integrated the CRISPR tiling scan with compound docking and molecular dynamics simulation, presenting a generally applicable strategy called CRISPR-Scan Assisted Drug Discovery (CRISPR-SADD). Using this approach, we identified a lead inhibitor that selectively targets SGF29's Tudor domain and demonstrates efficacy against leukemia. Furthermore, we propose that the structural genetics approach used in our study can be widely applied to diverse fields for de novo drug discovery.

A neurodevelopmental disorder mutation locks G proteins in the transitory pre-activated state.

Many neurotransmitter receptors activate G proteins through exchange of GDP for GTP. The intermediate nucleotide-free state has eluded characterization, due largely to its inherent instability. Here we characterize a G protein variant associated with a rare neurological disorder in humans. GαoK46E has a charge reversal that clashes with the phosphate groups of GDP and GTP. As anticipated, the purified protein binds poorly to guanine nucleotides yet retains wild-type affinity for G protein ßγ subunits. In cells with physiological concentrations of nucleotide, GαoK46E forms a stable complex with receptors and Gßγ, impeding effector activation. Further, we demonstrate that the mutant can be easily purified in complex with dopamine-bound D2 receptors, and use cryo-electron microscopy to determine the structure, including both domains of Gαo, without nucleotide or stabilizing nanobodies. These findings reveal the molecular basis for the first committed step of G protein activation, establish a mechanistic basis for a neurological disorder, provide a simplified strategy to determine receptor-G protein structures, and a method to detect high affinity agonist binding in cells.