Designer proteins that competitively inhibit Gαq by targeting its effector site

Going Rogue: Mechanisms, Regulation, and Roles of Mutationally Activated Gα in Human Cancer

G protein-coupled receptors (GPCRs) couple to heterotrimeric G proteins, comprised of α and βγ subunits, to convert extracellular signals into activation of intracellular signaling pathways. Canonically, GPCR-mediated activation results in the exchange of GDP for GTP on G protein α subunits (Gα) and the dissociation of Gα-GTP and G protein βγ subunits (Gβγ), both of which can regulate a variety of signaling pathways. Hydrolysis of bound GTP by Gα returns the protein to Gα-GDP and allows reassociation with Gβγ to reform the inactive heterotrimer. Naturally occurring mutations in Gα have been found at conserved glutamine and arginine amino acids that disrupt the canonical G protein cycle by inhibiting GTP hydrolysis, rendering these mutants constitutively active. Interestingly, these dysregulated Gα mutants are found in many different cancers due to their ability to sustain aberrant signaling without a need for activation by GPCRs. This review will highlight an increased recognition of the prevalence of such constitutively activating Gα mutations in cancers and the signaling pathways activated. In addition, we will discuss new knowledge regarding how these constitutively active Gα are regulated, how different mutations are biochemically distinct, and how mutationally activated Gα are unique compared with GPCR-activated Gα Lastly, we will discuss recent progress in developing inhibitors directly targeting constitutively active Gα mutants. SIGNIFICANCE STATEMENT: Constitutively activating mutations in G protein α subunits (Gα) widely occur in and contribute to the development of many human cancers. To develop ways to inhibit dysregulated, oncogenic signaling by these mutant Gα, it is crucial to better understand mechanisms that lead to constitutive Gα activation and unique mechanisms that regulate mutationally activated Gα in cells. The prevalence of activating mutations in Gα in various cancers makes Gα proteins compelling targets for the development of therapeutics.

Recent Advances in Molecular and Genetic Research on Uveal Melanoma

Uveal melanoma (UM), a distinct subtype of melanoma, presents unique challenges in its clinical management due to its complex molecular landscape and tendency for liver metastasis. This review highlights recent advancements in understanding the molecular pathogenesis, genetic alterations, and immune microenvironment of UM, with a focus on pivotal genes, such as GNAQ/11, BAP1, and CYSLTR2, and delves into the distinctive genetic and chromosomal classifications of UM, emphasizing the role of mutations and chromosomal rearrangements in disease progression and metastatic risk. Novel diagnostic biomarkers, including circulating tumor cells, DNA and extracellular vesicles, are discussed, offering potential non-invasive approaches for early detection and monitoring. It also explores emerging prognostic markers and their implications for patient stratification and personalized treatment strategies. Therapeutic approaches, including histone deacetylase inhibitors, MAPK pathway inhibitors, and emerging trends and concepts like CAR T-cell therapy, are evaluated for their efficacy in UM treatment. This review identifies challenges in UM research, such as the limited treatment options for metastatic UM and the need for improved prognostic tools, and suggests future directions, including the discovery of novel therapeutic targets, immunotherapeutic strategies, and advanced drug delivery systems. The review concludes by emphasizing the importance of continued research and innovation in addressing the unique challenges of UM to improve patient outcomes and develop more effective treatment strategies.

De novo design of stable proteins that efficaciously inhibit oncogenic G proteins

Many protein therapeutics are competitive inhibitors that function by binding to endogenous proteins and preventing them from interacting with native partners. One effective strategy for engineering competitive inhibitors is to graft structural motifs from a native partner into a host protein. Here, we develop and experimentally test a computational protocol for embedding binding motifs in de novo designed proteins. The protocol uses an "inside-out" approach: Starting with a structural model of the binding motif docked against the target protein, the de novo protein is built by growing new structural elements off the termini of the binding motif. During backbone assembly, a score function favors backbones that introduce new tertiary contacts within the designed protein and do not introduce clashes with the target binding partner. Final sequences are designed and optimized using the molecular modeling program Rosetta. To test our protocol, we designed small helical proteins to inhibit the interaction between Gαq and its effector PLC-β isozymes. Several of the designed proteins remain folded above 90°C and bind to Gαq with equilibrium dissociation constants tighter than 80 nM. In cellular assays with oncogenic variants of Gαq , the designed proteins inhibit activation of PLC-β isozymes and Dbl-family RhoGEFs. Our results demonstrate that computational protein design, in combination with motif grafting, can be used to directly generate potent inhibitors without further optimization via high throughput screening or selection.

Designer installation of a substrate recruitment domain to tailor enzyme specificity

Promiscuous enzymes that modify peptides and proteins are powerful tools for labeling biomolecules; however, directing these modifications to desired substrates can be challenging. Here, we use computational interface design to install a substrate recognition domain adjacent to the active site of a promiscuous enzyme, catechol O-methyltransferase. This design approach effectively decouples substrate recognition from the site of catalysis and promotes modification of peptides recognized by the recruitment domain. We determined the crystal structure of this novel multidomain enzyme, SH3-588, which shows that it closely matches our design. SH3-588 methylates directed peptides with catalytic efficiencies exceeding the wild-type enzyme by over 1,000-fold, whereas peptides lacking the directing recognition sequence do not display enhanced efficiencies. In competition experiments, the designer enzyme preferentially modifies directed substrates over undirected substrates, suggesting that we can use designed recruitment domains to direct post-translational modifications to specific sequence motifs on target proteins in complex multisubstrate environments.

De novo design of stable proteins that efficaciously inhibit oncogenic G proteins

Many protein therapeutics are competitive inhibitors that function by binding to endogenous proteins and preventing them from interacting with native partners. One effective strategy for engineering competitive inhibitors is to graft structural motifs from a native partner into a host protein. Here, we develop and experimentally test a computational protocol for embedding binding motifs in de novo designed proteins. The protocol uses an "inside-out" approach: Starting with a structural model of the binding motif docked against the target protein, the de novo protein is built by growing new structural elements off the termini of the binding motif. During backbone assembly, a score function favors backbones that introduce new tertiary contacts within the designed protein and do not introduce clashes with the target binding partner. Final sequences are designed and optimized using the molecular modeling program Rosetta. To test our protocol, we designed small helical proteins to inhibit the interaction between Gα q and its effector PLC-β isozymes. Several of the designed proteins remain folded above 90°C and bind to Gα q with equilibrium dissociation constants tighter than 80 nM. In cellular assays with oncogenic variants of Gα q , the designed proteins inhibit activation of PLC-β isozymes and Dbl-family RhoGEFs. Our results demonstrate that computational protein design, in combination with motif grafting, can be used to directly generate potent inhibitors without further optimization via high throughput screening or selection.

statement for broader audience

Engineered proteins that bind to specific target proteins are useful as research reagents, diagnostics, and therapeutics. We used computational protein design to engineer de novo proteins that bind and competitively inhibit the G protein, Gα q , which is an oncogene for uveal melanomas. This computational method is a general approach that should be useful for designing competitive inhibitors against other proteins of interest.

A novel nucleic acid-binding protein, Gp49, from mycobacteriophage with mycobactericidal activity has the potential to be a therapeutic agent

The mycobacteriophages encode unique proteins that are potent to be therapeutic agents. We screened several clones with mycobactericidal properties from a genomic library of mycobacteriophages. Here we report the properties of one such clone coding the gene product, Gp49, of the phage Che12. Gp49 is a 16 kD dimeric protein having an HTH motif at its C-terminal and is highly conserved among mycobacteriophages and likely to be part of phage DNA replication machinery. Alphafold predicts it to be an α-helical protein. However, its CD spectrum showed it to be predominantly β-sheeted. It is a high-affinity heparin-binding protein having similarities with the macrophage protein Azurocidin. Its β-sheeted apo-structure gets transformed into α-helix upon binding to heparin. It binds to linear dsDNA as well as ssDNA and RNA cooperatively in a sequence non-specific manner. This DNA binding property enables it to inhibit both in vitro and in vivo transcription. The c-terminal HTH motif is responsible for binding to both heparin and nucleic acids. Its in vivo localization on DNA could cause displacements of many DNA-binding proteins from the bacterial chromosome. We surmised that the bactericidal activity of Gp49 arises from its non-specific DNA binding leading to the inhibition of many host-DNA-dependent processes. Its heparin-binding ability could have therapeutic/diagnostic usages in bacterial sepsis treatment.

AlphaFold accurately predicts distinct conformations based on the oligomeric state of a de novo designed protein

Using the molecular modeling program Rosetta, we designed a de novo protein, called SEWN0.1, which binds the heterotrimeric G protein Gαq. The design is helical, well-folded, and primarily monomeric in solution at a concentration of 10 μM. However, when we solved the crystal structure of SEWN0.1 at 1.9 Å, we observed a dimer in a conformation incompatible with binding Gαq . Unintentionally, we had designed a protein that adopts alternate conformations depending on its oligomeric state. Recently, there has been tremendous progress in the field of protein structure prediction as new methods in artificial intelligence have been used to predict structures with high accuracy. We were curious if the structure prediction method AlphaFold could predict the structure of SEWN0.1 and if the prediction depended on oligomeric state. When AlphaFold was used to predict the structure of monomeric SEWN0.1, it produced a model that resembles the Rosetta design model and is compatible with binding Gαq , but when used to predict the structure of a dimer, it predicted a conformation that closely resembles the SEWN0.1 crystal structure. AlphaFold's ability to predict multiple conformations for a single protein sequence should be useful for engineering protein switches.